Compare commits

..

1 Commits

Author SHA1 Message Date
Shroominic
4974a22d0f reproducible cursor problems 2025-12-26 17:27:49 +01:00
401 changed files with 38741 additions and 61345 deletions

View File

@@ -2,9 +2,6 @@
UPSTREAM_BASE_URL=https://api.openai.com/v1
UPSTREAM_API_KEY=your-upstream-api-key
# Tinfoil (confidential inference enclaves, EHBP)
# TINFOIL_API_KEY=your-tinfoil-api-key
# ADMIN_PASSWORD=secure-admin-password
# Database
@@ -17,7 +14,6 @@ UPSTREAM_API_KEY=your-upstream-api-key
# HTTP_URL=https://api.mynode.com
# ONION_URL=http://mynode.onion (auto fetched from compose)
# RELAYS="wss://relay.damus.io,wss://relay.nostr.band,wss://eden.nostr.land,wss://relay.routstr.com"
# ENABLE_ANALYTICS_SHARING=true
# CASHU_MINTS="https://mint.minibits.cash/Bitcoin,https://mint.cubabitcoin.org,https://ecashmint.otrta.me"
# RECEIVE_LN_ADDRESS=

View File

@@ -14,14 +14,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v3
with:
fetch-depth: 0
- name: Resolve git metadata
id: gitmeta
run: |
echo "sha=$(git rev-parse --short=7 HEAD)" >> "$GITHUB_OUTPUT"
echo "tag=$(git describe --tags --exact-match HEAD 2>/dev/null || true)" >> "$GITHUB_OUTPUT"
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
@@ -37,11 +29,7 @@ jobs:
uses: docker/build-push-action@v4
with:
context: .
file: Dockerfile.full
push: true
build-args: |
GIT_COMMIT=${{ steps.gitmeta.outputs.sha }}
GIT_TAG=${{ steps.gitmeta.outputs.tag }}
tags: |
ghcr.io/routstr/proxy:latest
ghcr.io/routstr/core:latest

View File

@@ -59,30 +59,25 @@ jobs:
- name: Checkout code
uses: actions/checkout@v4
- name: Setup pnpm
uses: pnpm/action-setup@v4
with:
version: 10
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: "20"
cache: "pnpm"
cache-dependency-path: ui/pnpm-lock.yaml
node-version: "18"
cache: "npm"
cache-dependency-path: ui/package-lock.json
- name: Install UI dependencies
working-directory: ./ui
run: pnpm install --frozen-lockfile
run: npm ci
- name: Run UI format check
working-directory: ./ui
run: pnpm run format-check
run: npm run format-check
- name: Run UI linting
working-directory: ./ui
run: pnpm run lint
run: npm run lint
- name: Run UI build
working-directory: ./ui
run: pnpm run build
run: npm run build

4
.gitignore vendored
View File

@@ -16,9 +16,6 @@ dist/
*.db-shm
*.db-wal
.*wallet.sqlite3
.wallet/
AGENTS.md
TEST_SUITE_OVERVIEW.md
*models.json
.cashu
.relay
@@ -41,4 +38,3 @@ proof_backups
*.todo
ui_out
.worktrees

View File

@@ -1,29 +1,26 @@
FROM ghcr.io/astral-sh/uv:python3.11-bookworm-slim
FROM ghcr.io/astral-sh/uv:python3.11-alpine
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
git \
build-essential \
pkg-config \
libsecp256k1-dev \
autoconf \
automake \
libtool \
&& rm -rf /var/lib/apt/lists/*
# Install system dependencies required for secp256k1
RUN apk add --no-cache \
pkgconf \
build-base \
automake \
autoconf \
libtool \
m4 \
perl
RUN apk add git
COPY uv.lock pyproject.toml ./
RUN mkdir -p /routstr
RUN uv sync --frozen --no-dev --no-install-project
RUN uv add git+https://github.com/saschanaz/secp256k1-py.git#branch=upgrade060
# RUN uv sync
WORKDIR /app
COPY . .
ARG GIT_COMMIT=""
ARG GIT_TAG=""
ENV GIT_COMMIT=${GIT_COMMIT}
ENV GIT_TAG=${GIT_TAG}
ENV PORT=8000
ENV PYTHONUNBUFFERED=1

View File

@@ -1,53 +0,0 @@
# Multi-stage Dockerfile for Routstr (includes UI build)
# Stage 1: Build the UI
FROM node:23-alpine AS ui-builder
WORKDIR /app/ui
# Install pnpm
RUN corepack enable pnpm && corepack prepare pnpm@10.15.0 --activate
# Copy UI source
COPY ui/package.json ui/pnpm-lock.yaml* ui/pnpm-workspace.yaml* ./
RUN pnpm install --frozen-lockfile
COPY ui/ ./
ENV NEXT_TELEMETRY_DISABLED=1
# Next.js build produces a static export in 'out' directory
RUN pnpm run build
# Stage 2: Build the Routstr Node
FROM ghcr.io/astral-sh/uv:python3.11-bookworm-slim AS runner
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
git \
build-essential \
pkg-config \
libsecp256k1-dev \
autoconf \
automake \
libtool \
&& rm -rf /var/lib/apt/lists/*
COPY uv.lock pyproject.toml ./
RUN uv sync --no-dev --no-install-project
WORKDIR /app
COPY . .
# Copy the built UI from the ui-builder stage
COPY --from=ui-builder /app/ui/out ./ui_out
ARG GIT_COMMIT=""
ARG GIT_TAG=""
ENV GIT_COMMIT=${GIT_COMMIT}
ENV GIT_TAG=${GIT_TAG}
ENV PORT=8000
ENV PYTHONUNBUFFERED=1
EXPOSE 8000
# Run the application
CMD ["/.venv/bin/fastapi", "run", "routstr", "--host", "0.0.0.0"]

View File

@@ -98,7 +98,7 @@ docker-down:
lint:
@echo "🔍 Running linting checks..."
$(RUFF) check .
$(MYPY) .
$(MYPY) routstr/ --ignore-missing-imports
format:
@echo "✨ Formatting code..."
@@ -107,7 +107,7 @@ format:
type-check:
@echo "🔎 Running type checks..."
$(MYPY) .
$(MYPY) routstr/ --ignore-missing-imports
# Development setup
dev-setup:
@@ -234,7 +234,7 @@ ci-test:
ci-lint:
@echo "🤖 Running CI linting..."
$(RUFF) check . --exit-non-zero-on-fix
$(MYPY) . --no-error-summary
$(MYPY) routstr/ --ignore-missing-imports --no-error-summary
# Debug helpers
test-debug:

299
README.md
View File

@@ -1,81 +1,256 @@
# Routstr Payment Proxy
[![License](https://img.shields.io/github/license/routstr/routstr-core?style=flat-square)](LICENSE)
[![Stars](https://img.shields.io/github/stars/routstr/routstr-core?style=flat-square)](https://github.com/routstr/routstr-core/stargazers)
[![Issues](https://img.shields.io/github/issues/routstr/routstr-core?style=flat-square)](https://github.com/routstr/routstr-core/issues)
[![Release](https://img.shields.io/github/v/release/routstr/routstr-core?style=flat-square)](https://github.com/routstr/routstr-core/releases)
Routstr is a FastAPI-based reverse proxy that sits in front of any OpenAI-compatible API. It handles pay-per-request billing using the [Cashu](https://cashu.space/) eCash protocol on Bitcoin and tracks usage in a local SQL database.
Routstr is a decentralized protocol for permissionless, private, and censorship-resistant AI inference. It combines Nostr for discovery and Cashu for private Bitcoin micropayments.
The server exposes the same endpoints as the upstream API and deducts sats from user accounts for each call. Pricing can be static or model-specific by loading `models.json` (falls back to `models.example.json`).
This repo contains Routstr Core: a FastAPI-based reverse proxy that sits in front of OpenAI-compatible APIs and handles pay-per-request billing.
## How It Works
## Start Here
The proxy implements a seamless eCash payment flow that maintains compatibility with existing OpenAI clients while enabling Bitcoin micropayments:
- **Overview**: <https://docs.routstr.com/overview/>
- **Provider Guide**: <https://docs.routstr.com/provider/quickstart/>
- **User Guide**: <https://docs.routstr.com/user-guide/introduction/>
```mermaid
sequenceDiagram
participant Client
participant Proxy as Routstr Proxy
participant DB as Database
participant Upstream as OpenAI API
participant Wallet as Cashu Wallet
## Basic Usage
If you are a user/developer, you just point an OpenAI-compatible SDK at a Routstr node and pay with a Cashu token.
### OpenAI SDK
```python
from openai import OpenAI
client = OpenAI(
base_url="https://api.routstr.com/v1",
api_key="cashuBo2FteCJodHRwczovL21...",
)
response = client.chat.completions.create(
model="gpt-5-nano",
messages=[{"role": "user", "content": "hello"}],
)
print(response.choices[0].message.content)
Client->>Proxy: API Request + eCash Token
Proxy->>Wallet: Validate & Redeem Token
Wallet-->>Proxy: Token Value (sats)
Proxy->>DB: Store/Update Balance
Proxy->>Upstream: Forward API Request
Upstream-->>Proxy: API Response + Usage Data
Proxy->>DB: Deduct Actual Request Cost
Proxy->>DB: Update Final Balance
Proxy-->>Client: API Response
```
### cURL
## Features
- **Cashu Wallet Integration** Accept Lightning payments and redeem eCash tokens before forwarding requests
- **API Key Management** Hashed keys stored in SQLite with balance tracking and optional expiry/refund address
- **Model-Based Pricing** Convert USD prices in `models.json` to sats using live BTC/USD rates
- **Admin Dashboard** Simple HTML interface at `/admin/` to view balances and API keys
- **Discovery** Fetch available providers from Nostr relays using NIP-91 protocol
- **NIP-91 Auto-Announcement** Automatically announce this provider to Nostr relays when NSEC is provided
- **Docker Support** Provided `Dockerfile` and `compose.yml` for running with an optional Tor hidden service
## Getting Started
### Running the proxy using Docker
```bash
curl https://api.routstr.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "x-cashu: cashuBo2FteCJodHRwczovL21..." \
-d '{
"model": "gpt-5-nano",
"messages": [{"role": "user", "content": "hello"}]
}'
docker run -d \
--name routstr-proxy \
-p 8000:8000 \
-e UPSTREAM_BASE_URL=https://api.openai.com/v1 \
-e UPSTREAM_API_KEY=your-openai-api-key \
ghcr.io/routstr/proxy:latest
```
## Quick Start (Docker)
### Development Requirements
If you are a node runner, start a Routstr Core instance using Docker Compose:
- Python 3.11+
- [uv](https://github.com/astral-sh/uv) package manager (used in development)
1. **Prepare your `.env`**:
```bash
ADMIN_PASSWORD=mysecretpassword
NAME="My AI Node"
DESCRIPTION="Fast access to models"
NSEC=yournsec
RECEIVE_LN_ADDRESS=yourname@wallet.com
```
2. **Start the services**:
```bash
docker compose up -d
```
3. **Configure**:
Open [http://localhost:8000/admin/](http://localhost:8000/admin/) to connect your AI providers and set pricing.
For full instructions, see the **[Provider Quick Start Guide](https://docs.routstr.com/provider/quickstart/)**.
## Development
### Installation
```bash
uv sync # install dependencies
```
Create a `.env` file based on `.env.example` and fill in the required values:
```bash
make setup
cp .env.example .env
fastapi run routstr
```
### Running Locally
```bash
fastapi run routstr --host 0.0.0.0 --port 8000
```
The service forwards requests to `UPSTREAM_BASE_URL`. Supply the upstream API key via the `UPSTREAM_API_KEY` environment variable if required.
### Docker
```bash
docker compose up --build
```
This builds the image and also starts a Tor container exposing the API as a hidden service.
## Environment Variables
The most common settings are shown below. See `.env.example` for the full list.
### Core Settings
- `UPSTREAM_BASE_URL` URL of the OpenAI-compatible service
- `UPSTREAM_API_KEY` API key for the upstream service (optional)
- `FIXED_PRICING` Set to `true` to use a fixed per-request price; `false` (default) uses model pricing from `models.json`
- `ADMIN_PASSWORD` Password for the `/admin/` dashboard
- `CASHU_MINTS` Comma-separated list of Cashu mint URLs
- `NAME` Name of the proxy
- `DESCRIPTION` Description of the proxy
- `NPUB` Nostr public key of the proxy
- `HTTP_URL` Public-facing URL of the proxy
- `ONION_URL` Tor hidden service URL of the proxy
- `NEXT_PUBLIC_API_URL` - UI Configuration for Next.js frontend (proxy URL, default: 'http://127.0.0.1:8000' )
## Database Migrations
The application uses Alembic for database schema management and **automatically runs migrations on startup**. This ensures your database is always up-to-date when deploying new versions.
### Automatic Migrations in Production
When the FastAPI application starts, it automatically:
1. Runs all pending database migrations
2. Updates the schema to the latest version
3. Logs the migration status
This means you don't need to manually run migrations when deploying - just restart the application and migrations will be applied automatically.
### Manual Migration Commands
For development or troubleshooting, you can use these Makefile commands:
```bash
make db-upgrade # Apply all pending migrations
make db-downgrade # Downgrade one migration
make db-current # Show current migration revision
make db-history # Show migration history
make db-migrate # Auto-generate new migration from model changes
make db-revision # Create empty migration file
make db-heads # Show current migration heads
make db-clean # Clean migration cache files
```
### Creating New Migrations
When you modify SQLModel models:
```bash
# Auto-generate a migration from model changes
make db-migrate
# Enter a descriptive message when prompted
# Review the generated migration file in migrations/versions/
# Edit if needed, then test with:
make db-upgrade
```
## Admin UI
Routstr includes a modern Next.js admin dashboard that's served directly from the Python backend as static files - no separate Node.js server required.
### Building the UI
```bash
make ui-build
```
This compiles the Next.js application into static HTML, CSS, and JavaScript files in `ui/out/`.
### Accessing the Dashboard
Once built, the UI is automatically served by the FastAPI backend:
- **Dashboard**: `http://localhost:8000/`
- **Login**: `http://localhost:8000/login`
- **Models Management**: `http://localhost:8000/model`
- **Providers Management**: `http://localhost:8000/providers`
- **Settings**: `http://localhost:8000/settings`
The dashboard provides:
- Real-time wallet balance monitoring
- Model pricing configuration
- Upstream provider management
- Transaction history
- System settings
**Authentication**: Use the `ADMIN_PASSWORD` environment variable to access the dashboard.
## Withdrawing Balance
Go to the admin dashboard at `http://localhost:8000/` and login with your `ADMIN_PASSWORD` to withdraw your balance as a Cashu token.
## Example Client
`example.py` shows how to use the proxy with the official OpenAI client:
```bash
CASHU_TOKEN=<redeemable token> python example.py
```
The script sends streaming chat completions and pays for each request using the provided token.
## Running Tests
```bash
uv run pytest
```
The tests create a temporary SQLite database and mock the Cashu wallet. See `tests/README.md` for more details.
## Future Features
### Nut-24 Header Support (Coming Soon)
We're implementing support for the Cashu Nut-24 specification, which will enable per-request token exchange with automatic change handling:
```mermaid
graph TD
A["Client Request<br/>x-cashu: token"] --> B[Proxy Validates Token]
B --> C{Token ≥ Minimum Amount?}
C -->|No| F[Return 402 Payment Required]
C -->|Yes| D[Calculate Request Cost]
D --> E[Process Request]
E --> G[Forward to Upstream API]
G --> H[Receive API Response]
H --> I[Calculate Change]
I --> J["Return Response<br/>x-cashu: change_token"]
F --> K[End]
J --> K
```
**Key Benefits:**
- **Per-Request Payments** Send exact tokens for each API call
- **Automatic Change** Receive change tokens in response headers
- **No Pre-funding** No need to maintain account balances
- **Precise Billing** Pay only for actual usage with msat-level precision
- **Minimum Amount Protection** Proxy enforces minimum token value to prevent dust attacks
**Header Format:**
- **Request**: `x-cashu: <ecash_token>` Token to spend for this request (must meet minimum amount)
- **Response**: `x-cashu: <change_token>` Change token if payment exceeds cost
**Implementation Note:**
The proxy should implement either a dedicated endpoint to communicate minimum eCash requirements per request, or extend the existing `models.json` to include minimum token amounts per model. This allows clients to autonomously determine the appropriate token amount to send with each request.
**Compatible Clients:**
To use this feature, you'll need a client that handles both OpenAI API calls and eCash header management. The following clients provide seamless integration:
- **[routstr-chat](https://github.com/routstr/routstr-chat)** chat app for the routstr network
- **[otrta-client](https://github.com/routstr/otrta-client)** rust web app for the routstr network
clients automatically:
- **Handle eCash Headers** Add `x-cashu` tokens to requests and process change tokens
- **Manage Wallets** Maintain your Cashu wallet
- **Configure Proxy** Set Routstr proxy endpoints
- **Top-up Balances** Automatically request ecash when tokens run low and redeem ecash tokens
This approach eliminates the need for account management while maintaining the security and privacy benefits of eCash payments.
## License
This project is licensed under the terms of the GPLv3. See the `LICENSE` file for the full license text.

View File

@@ -6,11 +6,10 @@ services:
context: ./ui
dockerfile: Dockerfile.build
args:
# NEXT_PUBLIC_API_URL: ${NEXT_PUBLIC_API_URL:-http://127.0.0.1:8000}
NEXT_PUBLIC_API_URL: ${NEXT_PUBLIC_API_URL:-http://127.0.0.1:8000}
NEXT_PUBLIC_ADMIN_API_KEY: ${NEXT_PUBLIC_ADMIN_API_KEY:-}
user: root
volumes:
- ./ui_out:/output:z
- ./ui_out:/output
command:
["sh", "-c", "mkdir -p /output && cp -r /app/built/. /output/ && echo 'UI build copied to mounted volume' && ls -la /output/ && echo 'UI built and ready' && tail -f /dev/null"]
@@ -19,10 +18,10 @@ services:
depends_on:
- ui
volumes:
- .:/app:z
- ./logs:/app/logs:z
- .:/app
- ./logs:/app/logs
- tor-data:/var/lib/tor:ro
- ./ui_out:/app/ui_out:ro,z
- ./ui_out:/app/ui_out:ro
env_file:
- .env
environment:

View File

@@ -0,0 +1,44 @@
# Reproducing Cursor Problems
Each subdirectory contains a `request.json` (the request body) and `response.json` (the error response received).
## Using curl to reproduce
From the `routstr-core/` directory:
```bash
# OpenAI model error
curl -X POST https://staging.routstr.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $API_KEY" \
-d @cursor-problems/openai-model-error/request.json
# Anthropic internal error
curl -X POST https://staging.routstr.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $API_KEY" \
-d @cursor-problems/anthropic-internal-error/request.json
# Model not found error
curl -X POST https://staging.routstr.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $API_KEY" \
-d @cursor-problems/model-not-found-error/request.json
# Upstream rate limit error
curl -X POST https://staging.routstr.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $API_KEY" \
-d @cursor-problems/upstream-rate-limit-error/request.json
```
## Generic pattern
```bash
curl -X POST <API_ENDPOINT> \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $API_KEY" \
-d @cursor-problems/<directory>/request.json
```
The `-d @filename` syntax tells curl to read the request body from a file.

File diff suppressed because one or more lines are too long

View File

@@ -0,0 +1,8 @@
{
"error": {
"message": "Internal Server Error",
"type": "upstream_error",
"code": 502
},
"request_id": "4a04e4f8-4a31-45f1-8189-455c86fc4e89"
}

File diff suppressed because one or more lines are too long

View File

@@ -0,0 +1,8 @@
{
"error": {
"message": "Model 'claude-4.5-sonnet-thinking' not found",
"type": "invalid_model",
"code": 400
},
"request_id": "d410f512-3221-4047-a4ee-9be6e3fabe38"
}

File diff suppressed because one or more lines are too long

View File

@@ -0,0 +1,8 @@
{
"error": {
"message": "Input required: specify \"prompt\" or \"messages\"",
"type": "invalid_request_error",
"code": 400
},
"request_id": "586e0aec-351f-413a-8641-ddda4a0cbadf"
}

File diff suppressed because one or more lines are too long

View File

@@ -0,0 +1,8 @@
{
"error": {
"message": "Upstream request failed",
"type": "rate_limit_exceeded",
"code": 429
},
"request_id": "80657fc6-4bca-4cb1-945d-ea65ec8a53c4"
}

View File

@@ -0,0 +1,567 @@
# Custom Pricing
This guide covers advanced pricing strategies and customization options for Routstr Core.
## Pricing Models Overview
Routstr supports three pricing models:
1. **Fixed Pricing** - Simple per-request fee
2. **Token-Based Pricing** - Charge per input/output token
3. **Model-Based Pricing** - Dynamic pricing from models.json
## Model-Based Pricing
### Configuration
Enable model-based pricing (default behavior):
```bash
# .env
FIXED_PRICING=false
MODELS_PATH=/app/config/models.json
EXCHANGE_FEE=1.005 # 0.5% exchange fee
UPSTREAM_PROVIDER_FEE=1.05 # 5% provider margin
```
### Custom Models File
Create a `models.json` with your pricing:
```json
{
"models": [
{
"id": "gpt-4",
"name": "GPT-4",
"description": "Advanced reasoning model",
"context_length": 8192,
"pricing": {
"prompt": "0.03", // USD per 1K tokens
"completion": "0.06", // USD per 1K tokens
"request": "0.0001", // Fixed per-request fee
"image": "0", // For multimodal models
"web_search": "0.005", // Additional features
"internal_reasoning": "0.01"
},
"supported_features": [
"function_calling",
"vision",
"json_mode"
],
"deprecation_date": null,
"replacement_model": null
},
{
"id": "custom-model",
"name": "Custom Fine-tuned Model",
"pricing": {
"prompt": "0.001",
"completion": "0.002",
"request": "0.00005"
},
"minimum_charge": "0.0001" // Minimum charge per request
}
],
"default_pricing": {
"prompt": "0.002",
"completion": "0.002",
"request": "0"
}
}
```
### Dynamic Price Updates
Automatically fetch prices from providers:
```python
# scripts/update_prices.py
import asyncio
import httpx
import json
async def fetch_openrouter_models():
"""Fetch current model pricing from OpenRouter."""
async with httpx.AsyncClient() as client:
response = await client.get(
"https://openrouter.ai/api/v1/models"
)
return response.json()
async def update_models_json():
"""Update local models.json with latest prices."""
data = await fetch_openrouter_models()
models = []
for model in data['data']:
models.append({
"id": model['id'],
"name": model['name'],
"pricing": {
"prompt": model['pricing']['prompt'],
"completion": model['pricing']['completion'],
"request": model['pricing'].get('request', '0')
},
"context_length": model.get('context_length', 4096)
})
with open('models.json', 'w') as f:
json.dump({"models": models}, f, indent=2)
# Run periodically
if __name__ == "__main__":
asyncio.run(update_models_json())
```
## Token-Based Pricing
### Configuration
Set up token-based pricing overrides:
```bash
# .env
FIXED_PRICING=false # use model pricing
FIXED_COST_PER_REQUEST=1 # optional base fee
FIXED_PER_1K_INPUT_TOKENS=5 # optional override
FIXED_PER_1K_OUTPUT_TOKENS=15 # optional override
```
### Custom Token Counting
Override default token counting:
```python
from tiktoken import encoding_for_model
class CustomTokenCounter:
def __init__(self):
self.encodings = {}
def count_tokens(
self,
text: str,
model: str
) -> int:
"""Custom token counting logic."""
# Cache encodings
if model not in self.encodings:
try:
self.encodings[model] = encoding_for_model(model)
except:
# Fallback encoding
self.encodings[model] = encoding_for_model("gpt-3.5-turbo")
encoding = self.encodings[model]
# Special handling for certain content
if text.startswith("```"):
# Code blocks might need special handling
tokens = encoding.encode(text)
return len(tokens) * 1.1 # 10% markup for code
return len(encoding.encode(text))
```
## Advanced Pricing Strategies
### Time-Based Pricing
Implement peak/off-peak pricing:
```python
from datetime import datetime
import pytz
class TimeBased PricingStrategy:
def __init__(self):
self.timezone = pytz.timezone('US/Eastern')
self.peak_hours = [(9, 17)] # 9 AM - 5 PM
self.peak_multiplier = 1.5
self.weekend_discount = 0.8
def get_price_multiplier(self) -> float:
"""Calculate price multiplier based on time."""
now = datetime.now(self.timezone)
# Weekend discount
if now.weekday() >= 5: # Saturday or Sunday
return self.weekend_discount
# Peak hours surcharge
hour = now.hour
for start, end in self.peak_hours:
if start <= hour < end:
return self.peak_multiplier
# Off-peak standard pricing
return 1.0
def apply_to_cost(self, base_cost: int) -> int:
"""Apply time-based pricing to cost."""
multiplier = self.get_price_multiplier()
return int(base_cost * multiplier)
```
### Model-Specific Surcharges
Add custom fees for specific models:
```python
class ModelSurchargeStrategy:
def __init__(self):
self.surcharges = {
"gpt-4-turbo": 1.1, # 10% premium
"claude-3-opus": 1.15, # 15% premium
"dall-e-3-hd": 1.25, # 25% premium for HD
}
self.discounts = {
"gpt-3.5-turbo": 0.95, # 5% discount
"deprecated-model": 0.8, # 20% discount
}
def get_model_multiplier(self, model: str) -> float:
"""Get price multiplier for model."""
if model in self.surcharges:
return self.surcharges[model]
elif model in self.discounts:
return self.discounts[model]
return 1.0
```
### Geographic Pricing
Adjust pricing based on client location:
```python
import geoip2.database
class GeographicPricingStrategy:
def __init__(self):
self.reader = geoip2.database.Reader('GeoLite2-Country.mmdb')
self.country_multipliers = {
'US': 1.0,
'GB': 1.0,
'DE': 1.0,
'IN': 0.7, # 30% discount
'BR': 0.8, # 20% discount
'NG': 0.6, # 40% discount
}
self.default_multiplier = 0.9
def get_country_multiplier(self, ip_address: str) -> float:
"""Get price multiplier based on country."""
try:
response = self.reader.country(ip_address)
country_code = response.country.iso_code
return self.country_multipliers.get(
country_code,
self.default_multiplier
)
except:
return 1.0 # Default pricing if lookup fails
```
## Cost Calculation Pipeline
### Implementing Custom Calculator
```python
from abc import ABC, abstractmethod
class CostCalculator(ABC):
@abstractmethod
async def calculate(
self,
request_data: dict,
usage_data: dict,
context: dict
) -> CostResult:
pass
class CompositeCostCalculator(CostCalculator):
"""Combine multiple pricing strategies."""
def __init__(self):
self.strategies = [
BaseCostCalculator(),
TimeBasedPricingStrategy(),
ModelSurchargeStrategy(),
GeographicPricingStrategy()
]
async def calculate(
self,
request_data: dict,
usage_data: dict,
context: dict
) -> CostResult:
# Start with base cost
base_cost = await self.strategies[0].calculate(
request_data, usage_data, context
)
# Apply each strategy
final_cost = base_cost.total_msats
breakdown = {"base": base_cost.total_msats}
for strategy in self.strategies[1:]:
multiplier = await strategy.get_multiplier(context)
adjustment = final_cost * (multiplier - 1)
final_cost += adjustment
breakdown[strategy.__class__.__name__] = adjustment
return CostResult(
total_msats=int(final_cost),
breakdown=breakdown
)
```
### Integration with Routstr
```python
# In routstr/payment/cost_calculation.py
async def calculate_request_cost(
model: str,
prompt_tokens: int,
completion_tokens: int,
request_type: str,
context: dict
) -> CostData:
"""Enhanced cost calculation with custom strategies."""
# Use custom calculator if configured
if os.getenv("USE_CUSTOM_PRICING", "false").lower() == "true":
calculator = CompositeCostCalculator()
result = await calculator.calculate(
request_data={
"model": model,
"type": request_type
},
usage_data={
"prompt_tokens": prompt_tokens,
"completion_tokens": completion_tokens
},
context=context
)
return result
# Fall back to standard calculation
return standard_calculate_cost(...)
```
## Monitoring Pricing
### Price Analytics
Track pricing effectiveness:
```python
class PricingAnalytics:
async def analyze_pricing(
self,
start_date: datetime,
end_date: datetime
):
"""Analyze pricing performance."""
# Average cost per request by model
model_costs = await self.get_average_costs_by_model(
start_date, end_date
)
# Revenue by pricing strategy
strategy_revenue = await self.get_revenue_by_strategy(
start_date, end_date
)
# Price elasticity
elasticity = await self.calculate_price_elasticity()
return {
"model_costs": model_costs,
"strategy_revenue": strategy_revenue,
"price_elasticity": elasticity,
"recommendations": self.generate_recommendations(
model_costs, elasticity
)
}
```
### A/B Testing Prices
Test different pricing strategies:
```python
class PricingExperiment:
def __init__(self):
self.experiments = {
"exp_001": {
"name": "10% discount test",
"group_a": {"multiplier": 1.0},
"group_b": {"multiplier": 0.9},
"allocation": 0.5 # 50/50 split
}
}
def assign_group(self, api_key_id: int) -> str:
"""Assign API key to experiment group."""
# Consistent assignment based on key ID
import hashlib
hash_value = int(hashlib.md5(
str(api_key_id).encode()
).hexdigest()[:8], 16)
return "group_b" if (hash_value % 100) < 50 else "group_a"
def get_experiment_multiplier(
self,
api_key_id: int,
experiment_id: str
) -> float:
"""Get price multiplier for experiment."""
experiment = self.experiments.get(experiment_id)
if not experiment:
return 1.0
group = self.assign_group(api_key_id)
return experiment[group]["multiplier"]
```
## Configuration Examples
### Enterprise Pricing
```json
{
"models": [
{
"id": "gpt-4-enterprise",
"name": "GPT-4 Enterprise",
"pricing": {
"prompt": "0.02",
"completion": "0.04"
},
"minimum_commitment": "1000", // $1000/month minimum
"sla": {
"uptime": "99.9%",
"support_response": "1 hour",
"dedicated_capacity": true
}
}
],
"enterprise_features": {
"priority_queue": true,
"custom_models": true,
"audit_logs": true,
"sso": true
}
}
```
### Budget-Friendly Options
```json
{
"models": [
{
"id": "gpt-3.5-turbo-budget",
"name": "GPT-3.5 Turbo Budget",
"pricing": {
"prompt": "0.0005",
"completion": "0.001"
},
"restrictions": {
"max_tokens_per_request": 1000,
"requests_per_minute": 10,
"peak_hours_blocked": true
}
}
],
"prepaid_packages": [
{
"name": "Starter Pack",
"price_usd": 10,
"tokens_included": 10000000,
"expires_days": 30
}
]
}
```
## Troubleshooting
### Price Calculation Issues
```python
# Debug pricing
async def debug_price_calculation(
model: str,
tokens: dict,
api_key_id: int
):
"""Debug price calculation step by step."""
print(f"Model: {model}")
print(f"Tokens: {tokens}")
# Base price
base_price = get_model_price(model)
print(f"Base price: {base_price}")
# Token cost
token_cost = calculate_token_cost(base_price, tokens)
print(f"Token cost: {token_cost}")
# Strategies
strategies = get_active_strategies()
for strategy in strategies:
multiplier = await strategy.get_multiplier(api_key_id)
print(f"{strategy.name}: {multiplier}x")
# Final cost
final_cost = apply_all_strategies(token_cost, api_key_id)
print(f"Final cost: {final_cost} msats")
return final_cost
```
### Common Issues
1. **Prices Not Updating**
- Check `MODELS_PATH` is correct
- Verify file permissions
- Check background task logs
2. **Wrong Currency Conversion**
- Verify BTC/USD rate source
- Check `EXCHANGE_FEE` setting
- Monitor rate update frequency
3. **Discounts Not Applied**
- Verify strategy configuration
- Check API key metadata
- Review transaction history
## Best Practices
1. **Transparent Pricing**
- Publish pricing clearly
- Show cost breakdowns
- Notify of price changes
2. **Fair Pricing**
- Regular competitive analysis
- Consider user feedback
- Offer budget options
3. **Performance**
- Cache price calculations
- Optimize database queries
- Monitor calculation time
## Next Steps
- [Migrations](migrations.md) - Database migration guide
- [API Endpoints](../api/endpoints.md) - Pricing endpoints
- [Monitoring](../user-guide/admin-dashboard.md) - Track pricing metrics

646
docs/advanced/migrations.md Normal file
View File

@@ -0,0 +1,646 @@
# Database Migrations
This guide covers database schema management using Alembic migrations in Routstr Core.
## Overview
Routstr uses Alembic for database migrations with these features:
- **Automatic migrations** on startup
- **Version control** for schema changes
- **Rollback capability** for safety
- **Support for multiple databases** (SQLite, PostgreSQL)
## Automatic Migrations
### Startup Behavior
Migrations run automatically when Routstr starts:
```python
# In routstr/core/main.py
@asynccontextmanager
async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
logger.info("Running database migrations")
run_migrations() # Automatic migration
await init_db() # Initialize connection pool
# ... rest of startup
```
This ensures:
- ✅ Database is always up-to-date
- ✅ No manual migration steps in production
- ✅ Zero-downtime deployments
- ✅ Backwards compatibility
### Migration Safety
Migrations are designed to be safe:
- Idempotent (can run multiple times)
- Non-destructive by default
- Tested before release
- Reversible when possible
## Creating Migrations
### Auto-generating from Models
After modifying SQLModel classes:
```bash
# Generate migration from model changes
make db-migrate
# You'll be prompted for a description
Enter migration message: Add user preferences table
# Review generated file
cat migrations/versions/xxxx_add_user_preferences_table.py
```
### Manual Migrations
For complex changes, create manually:
```bash
# Create empty migration
alembic revision -m "Complex data transformation"
# Edit the generated file
vim migrations/versions/xxxx_complex_data_transformation.py
```
### Migration Template
```python
"""Add user preferences table
Revision ID: a1b2c3d4e5f6
Revises: f6e5d4c3b2a1
Create Date: 2024-01-15 10:30:00.123456
"""
from alembic import op
import sqlalchemy as sa
import sqlmodel
# revision identifiers
revision = 'a1b2c3d4e5f6'
down_revision = 'f6e5d4c3b2a1'
branch_labels = None
depends_on = None
def upgrade() -> None:
"""Apply migration."""
# Create new table
op.create_table(
'userpreferences',
sa.Column('id', sa.Integer(), nullable=False),
sa.Column('api_key_id', sa.Integer(), nullable=False),
sa.Column('theme', sa.String(), nullable=True),
sa.Column('notifications_enabled', sa.Boolean(), default=True),
sa.Column('created_at', sa.DateTime(), nullable=False),
sa.PrimaryKeyConstraint('id'),
sa.ForeignKeyConstraint(['api_key_id'], ['apikey.id'], )
)
# Create index
op.create_index(
'ix_userpreferences_api_key_id',
'userpreferences',
['api_key_id']
)
def downgrade() -> None:
"""Revert migration."""
op.drop_index('ix_userpreferences_api_key_id', table_name='userpreferences')
op.drop_table('userpreferences')
```
## Common Migration Patterns
### Adding Columns
Add column with default value:
```python
def upgrade():
# Add nullable column first
op.add_column(
'apikey',
sa.Column('last_rotation', sa.DateTime(), nullable=True)
)
# Populate existing rows
connection = op.get_bind()
connection.execute(
"UPDATE apikey SET last_rotation = created_at WHERE last_rotation IS NULL"
)
# Make non-nullable if needed
op.alter_column('apikey', 'last_rotation', nullable=False)
```
### Renaming Columns
Safe column rename:
```python
def upgrade():
# SQLite doesn't support ALTER COLUMN, so we need a workaround
with op.batch_alter_table('apikey') as batch_op:
batch_op.alter_column('old_name', new_column_name='new_name')
```
### Adding Indexes
Performance-improving indexes:
```python
def upgrade():
# Single column index
op.create_index(
'ix_transaction_timestamp',
'transaction',
['timestamp']
)
# Composite index
op.create_index(
'ix_transaction_key_time',
'transaction',
['api_key_id', 'timestamp']
)
# Partial index (PostgreSQL only)
op.create_index(
'ix_apikey_active',
'apikey',
['balance'],
postgresql_where='balance > 0'
)
```
### Data Migrations
Transform existing data:
```python
def upgrade():
# Add new column
op.add_column(
'apikey',
sa.Column('key_type', sa.String(), nullable=True)
)
# Migrate data
connection = op.get_bind()
result = connection.execute('SELECT id, metadata FROM apikey')
for row in result:
key_type = 'premium' if row.metadata.get('premium') else 'standard'
connection.execute(
f"UPDATE apikey SET key_type = '{key_type}' WHERE id = {row.id}"
)
# Make column non-nullable
op.alter_column('apikey', 'key_type', nullable=False)
```
### Enum Types
Add enum column:
```python
from enum import Enum
class KeyStatus(str, Enum):
ACTIVE = "active"
SUSPENDED = "suspended"
EXPIRED = "expired"
def upgrade():
# Create enum type (PostgreSQL)
key_status_enum = sa.Enum(KeyStatus, name='keystatus')
key_status_enum.create(op.get_bind(), checkfirst=True)
# Add column
op.add_column(
'apikey',
sa.Column(
'status',
key_status_enum,
nullable=False,
server_default='active'
)
)
```
## Database-Specific Considerations
### SQLite Limitations
SQLite has limitations requiring workarounds:
```python
def upgrade():
# SQLite doesn't support ALTER COLUMN directly
# Use batch_alter_table for compatibility
with op.batch_alter_table('apikey') as batch_op:
batch_op.alter_column(
'balance',
type_=sa.BigInteger(), # Change from Integer
existing_type=sa.Integer()
)
```
### PostgreSQL Features
Leverage PostgreSQL-specific features:
```python
def upgrade():
# Use JSONB for better performance
op.add_column(
'apikey',
sa.Column('metadata', sa.JSON().with_variant(
sa.dialects.postgresql.JSONB(), 'postgresql'
))
)
# Add GIN index for JSONB queries
op.create_index(
'ix_apikey_metadata',
'apikey',
['metadata'],
postgresql_using='gin'
)
# Add check constraint
op.create_check_constraint(
'ck_apikey_balance_positive',
'apikey',
'balance >= 0'
)
```
## Migration Commands
### Running Migrations
```bash
# Apply all pending migrations
make db-upgrade
# Upgrade to specific revision
alembic upgrade a1b2c3d4e5f6
# Upgrade one revision
alembic upgrade +1
```
### Checking Status
```bash
# Show current revision
make db-current
# Output: a1b2c3d4e5f6 (head)
# Show migration history
make db-history
# Output:
# a1b2c3d4e5f6 -> b2c3d4e5f6a7 (head), Add user preferences
# f6e5d4c3b2a1 -> a1b2c3d4e5f6, Add indexes
# e5d4c3b2a1f6 -> f6e5d4c3b2a1, Initial schema
```
### Rolling Back
```bash
# Rollback one migration
make db-downgrade
# Rollback to specific revision
alembic downgrade f6e5d4c3b2a1
# Rollback all (dangerous!)
alembic downgrade base
```
## Testing Migrations
### Unit Testing
Test migrations in isolation:
```python
import pytest
from alembic import command
from alembic.config import Config
from sqlalchemy import create_engine, inspect
def test_migration_add_user_preferences():
"""Test user preferences migration."""
# Create test database
engine = create_engine("sqlite:///:memory:")
# Run migrations up to previous version
alembic_cfg = Config("alembic.ini")
alembic_cfg.set_main_option("sqlalchemy.url", str(engine.url))
command.upgrade(alembic_cfg, "f6e5d4c3b2a1")
# Verify state before migration
inspector = inspect(engine)
tables = inspector.get_table_names()
assert "userpreferences" not in tables
# Run target migration
command.upgrade(alembic_cfg, "a1b2c3d4e5f6")
# Verify state after migration
inspector = inspect(engine)
tables = inspector.get_table_names()
assert "userpreferences" in tables
# Check columns
columns = {col['name'] for col in inspector.get_columns('userpreferences')}
assert columns == {'id', 'api_key_id', 'theme', 'notifications_enabled', 'created_at'}
# Test downgrade
command.downgrade(alembic_cfg, "f6e5d4c3b2a1")
inspector = inspect(engine)
tables = inspector.get_table_names()
assert "userpreferences" not in tables
```
### Integration Testing
Test with real data:
```python
async def test_migration_with_data():
"""Test migration preserves existing data."""
# Setup test database with data
async with test_engine.begin() as conn:
# Insert test data
await conn.execute(
"INSERT INTO apikey (key_hash, balance) VALUES ('test', 1000)"
)
# Run migration
run_migrations()
# Verify data integrity
async with test_engine.connect() as conn:
result = await conn.execute("SELECT * FROM apikey WHERE key_hash = 'test'")
row = result.first()
assert row.balance == 1000
assert row.key_type == 'standard' # New column with default
```
## Production Deployment
### Zero-Downtime Migrations
Strategy for seamless updates:
1. **Make migrations backwards compatible**
```python
# Good: Add nullable column
op.add_column('apikey', sa.Column('new_field', sa.String(), nullable=True))
# Bad: Drop column immediately
# op.drop_column('apikey', 'old_field')
```
2. **Deploy in phases**
```bash
# Phase 1: Deploy code that works with both schemas
# Phase 2: Run migration
# Phase 3: Deploy code that requires new schema
# Phase 4: Clean up deprecated columns
```
3. **Use feature flags**
```python
if feature_enabled('use_new_schema'):
# Use new column
query = select(APIKey.new_field)
else:
# Use old column
query = select(APIKey.old_field)
```
### Migration Monitoring
Track migration execution:
```python
# Add to migration
def upgrade():
start_time = time.time()
logger.info(f"Starting migration {revision}")
try:
# Migration logic here
op.create_table(...)
duration = time.time() - start_time
logger.info(f"Migration {revision} completed in {duration:.2f}s")
except Exception as e:
logger.error(f"Migration {revision} failed: {e}")
raise
```
### Backup Before Migration
Always backup before major changes:
```bash
#!/bin/bash
# backup_before_migration.sh
# Backup database
if [[ "$DATABASE_URL" == *"sqlite"* ]]; then
cp database.db "backup_$(date +%Y%m%d_%H%M%S).db"
else
pg_dump $DATABASE_URL > "backup_$(date +%Y%m%d_%H%M%S).sql"
fi
# Run migration
alembic upgrade head
# Verify
alembic current
```
## Troubleshooting
### Common Issues
**Migration Conflicts**
```bash
# Multiple heads detected
alembic heads
# a1b2c3d4e5f6 (head)
# b2c3d4e5f6a7 (head)
# Merge heads
alembic merge -m "Merge migrations" a1b2c3 b2c3d4
```
**Failed Migration**
```python
# Add rollback logic
def upgrade():
try:
op.create_table(...)
except Exception as e:
# Clean up partial changes
op.drop_table('partial_table', checkfirst=True)
raise
def downgrade():
# Ensure clean rollback
op.drop_table('new_table', checkfirst=True)
```
**Lock Timeout**
```python
# Add timeout handling
def upgrade():
connection = op.get_bind()
# Set timeout (PostgreSQL)
connection.execute("SET lock_timeout = '10s'")
try:
op.add_column(...)
except OperationalError as e:
if 'lock timeout' in str(e):
logger.error("Migration failed due to lock timeout")
raise
```
### Recovery Procedures
If migration fails in production:
1. **Check current state**
```bash
alembic current
alembic history
```
2. **Manual rollback if needed**
```sql
-- Check migration table
SELECT * FROM alembic_version;
-- Force version if necessary
UPDATE alembic_version SET version_num = 'previous_version';
```
3. **Fix and retry**
```bash
# Fix migration file
vim migrations/versions/problematic_migration.py
# Retry
alembic upgrade head
```
## Best Practices
### Migration Guidelines
1. **Keep migrations small and focused**
- One logical change per migration
- Easier to review and rollback
2. **Test migrations thoroughly**
- Test upgrade and downgrade
- Test with production-like data
- Test database-specific features
3. **Document breaking changes**
```python
"""BREAKING: Change balance column type
This migration requires application update.
Deploy order:
1. Update application to handle both int and bigint
2. Run this migration
3. Update application to use only bigint
"""
```
4. **Make migrations idempotent**
```python
def upgrade():
# Check if column exists
inspector = inspect(op.get_bind())
columns = [col['name'] for col in inspector.get_columns('apikey')]
if 'new_column' not in columns:
op.add_column(
'apikey',
sa.Column('new_column', sa.String())
)
```
### Performance Considerations
1. **Add indexes concurrently (PostgreSQL)**
```python
def upgrade():
# Create index without locking table
op.create_index(
'ix_large_table_column',
'large_table',
['column'],
postgresql_concurrently=True
)
```
2. **Batch large updates**
```python
def upgrade():
connection = op.get_bind()
# Process in batches
batch_size = 1000
offset = 0
while True:
result = connection.execute(
f"UPDATE apikey SET processed = true "
f"WHERE id IN (SELECT id FROM apikey WHERE processed = false LIMIT {batch_size})"
)
if result.rowcount == 0:
break
offset += batch_size
time.sleep(0.1) # Prevent overload
```
## Next Steps
- [Testing Guide](../contributing/testing.md) - Testing migrations
- [Deployment](../getting-started/docker.md) - Production deployment

598
docs/advanced/nostr.md Normal file
View File

@@ -0,0 +1,598 @@
# Nostr Discovery
Routstr Core integrates with Nostr (Notes and Other Stuff Transmitted by Relays) for decentralized provider discovery. This enables users to find Routstr nodes without relying on centralized directories.
## Overview
Nostr integration provides:
- **Decentralized Discovery**: Find providers through relay network
- **Cryptographic Identity**: Providers identified by public keys
- **Real-time Updates**: Live provider status and pricing
- **Censorship Resistance**: No central point of control
## How It Works
```mermaid
graph LR
A[Routstr Node] --> B[Nostr Relay]
B --> C[Nostr Relay]
B --> D[Nostr Relay]
E[User Client] --> B
E --> C
E --> D
B --> F[Provider List]
C --> F
D --> F
```
Providers announce themselves by publishing signed events to Nostr relays. Clients can query these relays to discover available providers.
## Provider Configuration
### Setting Up Nostr Identity
1. **Generate Nostr Keys**
```bash
# Using nostril or similar tool
nostril --generate-keypair
# Output:
# Private key (nsec): nsec1abc...
# Public key (npub): npub1xyz...
```
2. **Configure Environment**
```bash
# .env
NPUB=npub1xyz... # Your public key
NSEC=nsec1abc... # Your private key (keep secret!)
NAME=Lightning AI Gateway
DESCRIPTION=Fast and reliable AI API with Bitcoin payments
HTTP_URL=https://api.lightning-ai.com
ONION_URL=http://lightningai.onion
```
### Publishing to Nostr
Routstr automatically publishes provider information to configured relays:
```python
# Published event structure (NIP-89)
{
"kind": 31990, # Application handler event
"pubkey": "your_public_key",
"content": {
"name": "Lightning AI Gateway",
"description": "Fast and reliable AI API",
"endpoints": {
"http": "https://api.lightning-ai.com",
"onion": "http://lightningai.onion"
},
"models": ["gpt-3.5-turbo", "gpt-4", "claude-3"],
"pricing": {
"gpt-3.5-turbo": {
"prompt_sats_per_1k": 3,
"completion_sats_per_1k": 4
}
},
"cashu_mints": [
"https://mint.minibits.cash/Bitcoin"
]
},
"tags": [
["d", "routstr"],
["t", "ai-api"],
["t", "bitcoin"],
["p", "payment-proxy"]
]
}
```
### Relay Configuration
Configure which relays to publish to:
```python
# Default relays
DEFAULT_RELAYS = [
"wss://relay.damus.io",
"wss://relay.nostr.band",
"wss://relay.routstr.com",
"wss://nos.lol"
]
# Custom relay configuration
RELAYS=wss://relay1.com,wss://relay2.com
```
## Client Discovery
### Using the Discovery Endpoint
Find providers through the API:
```bash
GET /v1/providers
Response:
{
"providers": [
{
"name": "Lightning AI Gateway",
"npub": "npub1xyz...",
"description": "Fast and reliable AI API",
"endpoints": {
"http": "https://api.lightning-ai.com",
"onion": "http://lightningai.onion"
},
"models": ["gpt-3.5-turbo", "gpt-4"],
"pricing": {
"gpt-3.5-turbo": {
"prompt_sats_per_1k": 3,
"completion_sats_per_1k": 4
}
},
"last_seen": "2024-01-01T12:00:00Z",
"reliability_score": 0.99
}
]
}
```
### Direct Nostr Queries
Query Nostr relays directly:
```python
import json
import websocket
def discover_providers(relay_url: str):
"""Discover Routstr providers from Nostr relay."""
ws = websocket.create_connection(relay_url)
# Subscribe to provider events
subscription = {
"kinds": [31990],
"tags": {
"d": ["routstr"]
}
}
ws.send(json.dumps(["REQ", "sub1", subscription]))
providers = []
while True:
response = json.loads(ws.recv())
if response[0] == "EVENT":
event = response[2]
providers.append(parse_provider_event(event))
elif response[0] == "EOSE": # End of stored events
break
ws.close()
return providers
```
### JavaScript/TypeScript
```typescript
import { SimplePool } from 'nostr-tools';
async function discoverProviders(): Promise<Provider[]> {
const pool = new SimplePool();
const relays = [
'wss://relay.damus.io',
'wss://relay.nostr.band'
];
const filter = {
kinds: [31990],
'#d': ['routstr']
};
const events = await pool.list(relays, [filter]);
return events.map(event => ({
name: event.content.name,
npub: nip19.npubEncode(event.pubkey),
url: event.content.endpoints.http,
models: event.content.models,
pricing: event.content.pricing
}));
}
```
## Provider Ranking
### Reliability Scoring
Providers are ranked based on:
```python
class ProviderScore:
def calculate(self, provider: Provider) -> float:
score = 1.0
# Uptime (based on recent checks)
uptime_ratio = provider.successful_pings / provider.total_pings
score *= uptime_ratio
# Response time
if provider.avg_response_time < 500: # ms
score *= 1.0
elif provider.avg_response_time < 1000:
score *= 0.9
else:
score *= 0.7
# Model availability
model_score = len(provider.models) / 10 # Max 10 models
score *= min(1.0, 0.5 + model_score * 0.5)
# Price competitiveness
if provider.is_cheapest_for_any_model():
score *= 1.1
return min(1.0, score)
```
### Provider Selection
Choose optimal provider:
```python
def select_provider(
providers: list[Provider],
model: str,
requirements: dict
) -> Provider:
"""Select best provider for requirements."""
# Filter by model availability
candidates = [p for p in providers if model in p.models]
# Filter by requirements
if requirements.get('tor_required'):
candidates = [p for p in candidates if p.onion_url]
if requirements.get('max_price_per_1k'):
max_price = requirements['max_price_per_1k']
candidates = [
p for p in candidates
if p.pricing[model]['prompt_sats_per_1k'] <= max_price
]
# Sort by score
candidates.sort(key=lambda p: p.reliability_score, reverse=True)
return candidates[0] if candidates else None
```
## Publishing Updates
### Automatic Updates
Routstr publishes updates when:
- Node starts up
- Configuration changes
- Models are added/removed
- Pricing updates
### Manual Publishing
Force publish current state:
```python
async def publish_provider_info():
"""Manually publish provider information."""
event = create_provider_event(
name=os.getenv("NAME"),
description=os.getenv("DESCRIPTION"),
models=get_available_models(),
pricing=get_current_pricing()
)
await publish_to_relays(event, RELAYS)
```
### Event Lifecycle
```python
# Publish every 6 hours
@periodic_task(hours=6)
async def update_nostr_presence():
"""Keep provider information fresh."""
try:
await publish_provider_info()
logger.info("Updated Nostr presence")
except Exception as e:
logger.error(f"Failed to update Nostr: {e}")
# Delete on shutdown
async def remove_nostr_presence():
"""Remove provider from discovery."""
deletion_event = create_deletion_event()
await publish_to_relays(deletion_event, RELAYS)
```
## Security Considerations
### Key Management
1. **Secure Storage**
```python
# Never log private keys
SENSITIVE_VARS = ['NSEC', 'ADMIN_PASSWORD']
def sanitize_env(env_dict: dict) -> dict:
return {
k: '***' if k in SENSITIVE_VARS else v
for k, v in env_dict.items()
}
```
2. **Key Rotation**
```bash
# Generate new keys
nostril --generate-keypair
# Update configuration
# Publish transition event
# Update all references
```
### Event Validation
Verify provider events:
```python
def validate_provider_event(event: dict) -> bool:
"""Validate provider announcement."""
# Check signature
if not verify_signature(event):
return False
# Check required fields
required = ['name', 'endpoints', 'models', 'pricing']
content = json.loads(event['content'])
if not all(field in content for field in required):
return False
# Verify endpoints are reachable
if not await check_endpoints(content['endpoints']):
return False
return True
```
### Relay Security
Choose relays carefully:
```python
TRUSTED_RELAYS = {
'wss://relay.damus.io': {
'operator': 'Damus',
'reputation': 'high',
'filters_spam': True
},
'wss://relay.nostr.band': {
'operator': 'Nostr.Band',
'reputation': 'high',
'paid_tier': True
}
}
```
## Advanced Features
### Multi-Relay Broadcasting
Ensure wide distribution:
```python
async def broadcast_to_relays(event: dict, relays: list[str]):
"""Broadcast event to multiple relays."""
tasks = []
for relay in relays:
task = asyncio.create_task(
publish_to_relay(event, relay)
)
tasks.append(task)
results = await asyncio.gather(*tasks, return_exceptions=True)
successful = sum(1 for r in results if not isinstance(r, Exception))
logger.info(f"Published to {successful}/{len(relays)} relays")
```
### Provider Metadata
Extended metadata in events:
```json
{
"kind": 31990,
"content": {
"name": "Lightning AI",
"description": "Enterprise AI API",
"metadata": {
"established": "2024-01-01",
"total_requests": 1000000,
"average_response_ms": 250,
"supported_features": [
"streaming",
"function_calling",
"vision",
"embeddings"
],
"certifications": ["SOC2", "GDPR"],
"contact": {
"nostr": "npub1contact...",
"email": "support@lightning-ai.com"
}
}
}
}
```
### Discovery Filters
Advanced filtering options:
```python
# Find providers with specific features
GET /v1/providers?features=streaming,vision&max_price=5&min_reliability=0.95
# Response includes filtered results
{
"providers": [...],
"filters_applied": {
"features": ["streaming", "vision"],
"max_price_sats_per_1k": 5,
"min_reliability": 0.95
},
"total_providers": 50,
"matching_providers": 12
}
```
## Monitoring
### Discovery Metrics
Track discovery performance:
```python
class DiscoveryMetrics:
def __init__(self):
self.relay_health = {}
self.provider_count = 0
self.query_latency = []
async def check_relay_health(self, relay_url: str):
"""Monitor relay connectivity."""
start = time.time()
try:
await connect_to_relay(relay_url)
latency = time.time() - start
self.relay_health[relay_url] = {
'status': 'healthy',
'latency_ms': latency * 1000
}
except Exception as e:
self.relay_health[relay_url] = {
'status': 'unhealthy',
'error': str(e)
}
```
### Provider Monitoring
```python
@periodic_task(minutes=5)
async def monitor_providers():
"""Check provider health."""
providers = await discover_providers()
for provider in providers:
try:
# Test endpoint
response = await test_provider_endpoint(provider.http_url)
# Update metrics
await update_provider_metrics(
provider.npub,
success=response.status_code == 200,
response_time=response.elapsed
)
except Exception as e:
logger.warning(f"Provider {provider.name} check failed: {e}")
```
## Troubleshooting
### No Providers Found
```python
# Debug discovery issues
async def debug_discovery():
"""Diagnose discovery problems."""
issues = []
# Check relay connectivity
for relay in RELAYS:
if not await can_connect_to_relay(relay):
issues.append(f"Cannot connect to {relay}")
# Check event publishing
if not await verify_own_events_visible():
issues.append("Own events not visible on relays")
# Check filters
if len(await get_all_provider_events()) == 0:
issues.append("No provider events on any relay")
return issues
```
### Relay Connection Issues
```bash
# Test relay connection
wscat -c wss://relay.damus.io
# Send subscription
["REQ","test",{"kinds":[31990],"#d":["routstr"]}]
```
## Best Practices
### For Providers
1. **Consistent Identity**
- Use same npub across services
- Maintain profile metadata
- Verify identity on multiple platforms
2. **Regular Updates**
- Publish status every few hours
- Update pricing promptly
- Remove stale information
3. **Relay Diversity**
- Publish to 5+ relays
- Include regional relays
- Monitor relay health
### For Clients
1. **Verify Providers**
- Check multiple relays
- Verify endpoints work
- Monitor reliability over time
2. **Cache Discovery**
- Cache provider list
- Refresh periodically
- Handle stale data gracefully
3. **Fallback Options**
- Keep backup providers
- Handle discovery failures
- Support manual configuration
## Next Steps
- [Tor Support](tor.md) - Anonymous provider access
- [Custom Pricing](custom-pricing.md) - Dynamic pricing strategies
- [API Reference](../api/endpoints.md) - Discovery API details

530
docs/advanced/tor.md Normal file
View File

@@ -0,0 +1,530 @@
# Tor Support
Routstr Core includes built-in support for Tor hidden services, enabling anonymous access to your API and enhanced privacy for users.
## Overview
Tor support provides:
- **Anonymous Access**: Hidden service (.onion) address
- **Enhanced Privacy**: No IP address logging
- **Censorship Resistance**: Accessible from restricted networks
- **Optional Usage**: Regular HTTP/HTTPS access remains available
## Docker Setup
### Using Docker Compose
The included `compose.yml` automatically sets up Tor:
```yaml
version: '3.8'
services:
routstr:
build: .
environment:
- TOR_PROXY_URL=socks5://tor:9050
ports:
- 8000:8000
tor:
image: ghcr.io/hundehausen/tor-hidden-service:latest
volumes:
- tor-data:/var/lib/tor
environment:
- HS_ROUTER=routstr:8000:80
depends_on:
- routstr
volumes:
tor-data:
```
Start with:
```bash
docker compose up -d
```
### Getting Your Onion Address
After starting, retrieve your hidden service address:
```bash
# View Tor logs
docker compose logs tor
# Or directly from the hostname file
docker exec tor cat /var/lib/tor/hidden_service/hostname
```
Your onion address will look like:
```
roustrjfsdgfiueghsklchg.onion
```
## Manual Tor Setup
### Install Tor
```bash
# Ubuntu/Debian
sudo apt-get install tor
# macOS
brew install tor
# Start Tor
sudo systemctl start tor
```
### Configure Hidden Service
Edit `/etc/tor/torrc`:
```bash
# Hidden service configuration
HiddenServiceDir /var/lib/tor/routstr/
HiddenServicePort 80 127.0.0.1:8000
# Optional: Restrict to v3 addresses
HiddenServiceVersion 3
```
Restart Tor:
```bash
sudo systemctl restart tor
```
Get onion address:
```bash
sudo cat /var/lib/tor/routstr/hostname
```
## Client Configuration
### Using Tor with Python
```python
import httpx
from openai import OpenAI
# Configure SOCKS proxy
proxies = {
"http://": "socks5://127.0.0.1:9050",
"https://": "socks5://127.0.0.1:9050"
}
# Create client with Tor
http_client = httpx.Client(proxies=proxies)
client = OpenAI(
api_key="sk-...",
base_url="http://roustrjfsdgfiueghsklchg.onion/v1",
http_client=http_client
)
# Use normally
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "Hello via Tor!"}]
)
```
### Using Tor with cURL
```bash
# Install torify
sudo apt-get install torsocks
# Make request through Tor
torify curl http://roustrjfsdgfiueghsklchg.onion/v1/models
# Or with explicit proxy
curl --socks5 127.0.0.1:9050 http://roustrjfsdgfiueghsklchg.onion/v1/models
```
### JavaScript/Node.js
```javascript
import { SocksProxyAgent } from 'socks-proxy-agent';
import OpenAI from 'openai';
// Create SOCKS agent
const agent = new SocksProxyAgent('socks5://127.0.0.1:9050');
// Configure OpenAI client
const openai = new OpenAI({
apiKey: 'sk-...',
baseURL: 'http://roustrjfsdgfiueghsklchg.onion/v1',
httpAgent: agent
});
// Use normally
const response = await openai.chat.completions.create({
model: 'gpt-3.5-turbo',
messages: [{ role: 'user', content: 'Hello via Tor!' }]
});
```
## Configuration
### Environment Variables
Configure Tor proxy for outgoing connections:
```bash
# .env
TOR_PROXY_URL=socks5://tor:9050 # Docker
# or
TOR_PROXY_URL=socks5://127.0.0.1:9050 # Local
```
### Publishing Onion Address
Make your onion address discoverable:
```bash
# .env
ONION_URL=http://roustrjfsdgfiueghsklchg.onion
```
This will be included in:
- `/v1/info` endpoint
- Nostr announcements
- Admin dashboard
## Security Considerations
### Hidden Service Security
1. **Keep Private Key Secure**
```bash
# Backup hidden service keys
sudo tar -czf tor-keys-backup.tar.gz /var/lib/tor/routstr/
# Restore to maintain same address
sudo tar -xzf tor-keys-backup.tar.gz -C /
```
2. **Access Control**
```bash
# Restrict to authenticated clients
HiddenServiceAuthorizeClient stealth client1,client2
```
3. **Rate Limiting**
```bash
# In torrc
HiddenServiceMaxStreams 100
HiddenServiceMaxStreamsCloseCircuit 1
```
### Operational Security
1. **Separate Tor Instance**
```yaml
# Use dedicated Tor container
tor:
image: ghcr.io/hundehausen/tor-hidden-service:latest
restart: always
networks:
- tor_network
```
2. **Monitor Tor Health**
```python
async def check_tor_connection():
"""Verify Tor connectivity."""
try:
async with httpx.AsyncClient(
proxies={"all://": TOR_PROXY_URL}
) as client:
response = await client.get(
"https://check.torproject.org/api/ip"
)
data = response.json()
return data.get("IsTor", False)
except Exception:
return False
```
3. **Logging Considerations**
```python
# Don't log .onion addresses with IPs
def sanitize_logs(message: str) -> str:
# Remove IP addresses when .onion is present
if ".onion" in message:
message = re.sub(r'\d+\.\d+\.\d+\.\d+', '[IP]', message)
return message
```
## Performance Optimization
### Connection Pooling
```python
# Reuse Tor circuits
class TorConnectionPool:
def __init__(self, proxy_url: str):
self.proxy_url = proxy_url
self._clients = []
async def get_client(self) -> httpx.AsyncClient:
if not self._clients:
client = httpx.AsyncClient(
proxies={"all://": self.proxy_url},
timeout=httpx.Timeout(30.0),
limits=httpx.Limits(
max_keepalive_connections=5,
max_connections=10
)
)
self._clients.append(client)
return self._clients[0]
```
### Circuit Management
```python
# Rotate Tor circuits periodically
async def rotate_tor_circuit():
"""Signal Tor to create new circuit."""
async with httpx.AsyncClient() as client:
# Tor control port (requires configuration)
response = await client.post(
"http://localhost:9051",
data="AUTHENTICATE\r\nSIGNAL NEWNYM\r\n"
)
```
### Caching Strategies
```python
# Cache responses for Tor users
@lru_cache(maxsize=1000)
def get_cached_response(
endpoint: str,
params_hash: str
) -> Optional[dict]:
"""Cache frequently accessed data."""
# Longer cache for Tor users due to latency
return cache.get(f"tor:{endpoint}:{params_hash}")
```
## Monitoring
### Tor Metrics
Track Tor-specific metrics:
```python
class TorMetrics:
def __init__(self):
self.tor_requests = 0
self.tor_errors = 0
self.circuit_builds = 0
self.average_latency = 0
async def record_request(
self,
duration: float,
success: bool
):
self.tor_requests += 1
if not success:
self.tor_errors += 1
# Update average latency
self.average_latency = (
(self.average_latency * (self.tor_requests - 1) + duration)
/ self.tor_requests
)
```
### Health Checks
```python
@router.get("/health/tor")
async def tor_health():
"""Check Tor service health."""
checks = {
"tor_proxy": await check_tor_proxy(),
"hidden_service": await check_hidden_service(),
"circuit_established": await check_circuit()
}
status = "healthy" if all(checks.values()) else "unhealthy"
return {
"status": status,
"checks": checks,
"metrics": {
"tor_requests_total": metrics.tor_requests,
"tor_error_rate": metrics.tor_errors / max(metrics.tor_requests, 1),
"average_latency_ms": metrics.average_latency * 1000
}
}
```
## Troubleshooting
### Common Issues
**Hidden Service Not Accessible**
```bash
# Check Tor logs
docker compose logs tor
# or
sudo journalctl -u tor
# Verify service is running
sudo systemctl status tor
# Test locally
curl --socks5 127.0.0.1:9050 http://your-onion.onion/v1/info
```
**Slow Connection**
- Tor adds 3+ hops of latency
- Use connection pooling
- Implement aggressive caching
- Consider increasing timeouts
**Connection Errors**
```python
# Implement Tor-specific retry logic
async def tor_retry(func, max_retries=5):
for attempt in range(max_retries):
try:
return await func()
except httpx.ProxyError:
if attempt < max_retries - 1:
# Exponential backoff for circuit building
await asyncio.sleep(2 ** attempt)
else:
raise
```
### Debugging
Enable Tor debug logging:
```bash
# In torrc
Log debug file /var/log/tor/debug.log
# Monitor in real-time
tail -f /var/log/tor/debug.log
```
## Best Practices
### For Operators
1. **Backup Hidden Service Keys**
- Store securely offline
- Enables service recovery
- Maintains same .onion address
2. **Monitor Tor Health**
- Check circuit establishment
- Track request latency
- Alert on failures
3. **Separate Concerns**
- Run Tor in separate container
- Isolate from main application
- Use internal networks
### For Users
1. **Verify Onion Addresses**
- Check against multiple sources
- Bookmark verified addresses
- Watch for phishing
2. **Handle Higher Latency**
- Increase client timeouts
- Implement retries
- Use connection pooling
3. **Enhance Privacy**
- Use Tor Browser for web access
- Avoid mixing Tor/clearnet
- Don't include identifying info
## Advanced Configuration
### Multi-Hop Onion Services
For extra security, chain multiple Tor instances:
```yaml
# compose.yml
services:
tor-entry:
image: tor:latest
command: tor -f /etc/tor/torrc.entry
tor-middle:
image: tor:latest
command: tor -f /etc/tor/torrc.middle
tor-exit:
image: tor:latest
command: tor -f /etc/tor/torrc.exit
```
### Onion Service Authentication
Require client authorization:
```bash
# Generate client auth
openssl rand -base64 32 > client_auth_key
# In torrc
HiddenServiceDir /var/lib/tor/routstr/
HiddenServicePort 80 127.0.0.1:8000
HiddenServiceAuthorizeClient stealth payments
```
### Load Balancing
Distribute load across multiple instances:
```nginx
# Onion service nginx config
upstream routstr_backends {
server routstr1:8000;
server routstr2:8000;
server routstr3:8000;
}
server {
listen 80;
location / {
proxy_pass http://routstr_backends;
}
}
```
## Next Steps
- [Nostr Discovery](nostr.md) - Announce your onion service
- [Docker Setup](../getting-started/docker.md) - Container configuration

View File

@@ -425,4 +425,4 @@ All API key usage is logged:
- [Endpoints](endpoints.md) - Complete endpoint reference
- [Errors](errors.md) - Error handling guide
- [Using the API](../client/integration.md) - Integration examples
- [Using the API](../user-guide/using-api.md) - Integration examples

View File

@@ -360,44 +360,6 @@ POST /v1/wallet/create
}
```
### Get Key Information
Get current balance, consumption data, and child keys for an API key.
```http
GET /v1/balance/info
Authorization: Bearer sk-...
```
**Response:**
```json
{
"api_key": "sk-abc...",
"balance": 8500000,
"reserved": 0,
"is_child": false,
"parent_key": null,
"total_requests": 42,
"total_spent": 1500000,
"balance_limit": null,
"balance_limit_reset": null,
"validity_date": null,
"child_keys": [
{
"api_key": "sk-child1...",
"total_requests": 10,
"total_spent": 500000,
"balance_limit": 1000000,
"balance_limit_reset": "daily",
"validity_date": 1738000000
}
]
}
```
`balance` is the spendable balance used by request admission.
### Check Balance
Get current wallet balance.
@@ -472,42 +434,6 @@ Authorization: Bearer sk-...
}
```
### Create Child Key
Creates one or more child API keys that share the parent's balance. Each child key creation costs a fixed amount (configurable).
```http
POST /v1/balance/child-key
Authorization: Bearer sk-...
```
**Request Body:**
```json
{
"count": 1
}
```
**Parameters:**
| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `count` | integer | Yes | - | Number of child keys to create (1-50) |
**Response:**
```json
{
"api_keys": ["sk-abc...", "sk-def..."],
"count": 2,
"cost_msats": 2000,
"cost_sats": 2,
"parent_balance": 98000,
"parent_balance_sats": 98
}
```
## Provider Discovery
## Admin Settings
@@ -601,4 +527,4 @@ Rate limit information is included in response headers.
- [Errors](errors.md) - Error handling reference
- [Authentication](authentication.md) - Auth details
- [Integration Guide](../client/integration.md) - Code examples
- [Examples](../user-guide/using-api.md) - Code examples

View File

@@ -113,109 +113,42 @@ All errors follow a consistent JSON structure:
**Status:** 402
**Resolution:** Top up API key balance
### Cashu Token Redemption Errors
These errors are returned when a Cashu token you pay with cannot be redeemed.
They apply to every endpoint that accepts a token:
- **Per-request payment** via the `X-Cashu` header (chat completions + Responses API).
- **API key top-up** via `POST /v1/wallet/topup`.
- **Minting an API key** from a token sent in `Authorization: Bearer <cashu-token>`.
All three share one classifier, so the same failure yields the same HTTP status
and sanitized message everywhere. Structured error envelopes (`X-Cashu` and
`Authorization: Bearer <cashu-token>`) also expose the same `type` and `code`
branch on `type` (or `code` for finer granularity). `POST /v1/wallet/topup`
keeps its existing plain-string `detail` envelope, so branch on status there.
| `type` | Status | `code` | Retryable | Meaning |
|--------|--------|--------|-----------|---------|
| `token_already_spent` | 400 | `cashu_token_already_spent` | No | The token was already redeemed. |
| `invalid_token` | 400 | `invalid_cashu_token` | No | The token is malformed or cannot be decoded. |
| `mint_error` | 422 | `cashu_token_swap_fees_exceed_amount` | No | Token value is too small to cover the mint's swap/melt fees. |
| `mint_error` | 422 | `cashu_foreign_mint_swap_failed` | No | Swapping the token from a foreign mint to the primary mint failed. |
| `mint_unreachable` | 503 | `cashu_mint_unreachable` | **Yes** | The mint could not be reached (DNS failure, refused/reset connection, timeout). The token is fine — retry once the mint recovers. |
| `cashu_error` | 400 | `cashu_token_redemption_failed` | No | The token could not be redeemed for another expected reason. |
| `cashu_error` | 400 | `cashu_token_zero_value` | No | The token redeemed to zero (empty/dust token, or value fully consumed by fees). |
| `token_consumed` | 500 | `cashu_token_consumed` | No | The token was **spent** (melted/redeemed) but crediting it then failed. Do not retry — the token is gone; contact support to reconcile. |
| `api_error` | 500 | `internal_error` | Maybe | Unexpected server-side fault during redemption. |
!!! important "Retry only `mint_unreachable`"
Only `mint_unreachable` (503) means the same token will work again later —
everything else is a permanent property of the token and must not be
blindly retried. Use exponential backoff for the 503. In particular, a
`token_consumed` 500 means the mint already spent the token, so a retry
would fail as `token_already_spent`.
#### Mint Unreachable (retryable)
#### Invalid Token
```json
{
"error": {
"type": "mint_unreachable",
"message": "Cashu mint is unreachable",
"code": "cashu_mint_unreachable"
"type": "payment_error",
"message": "Invalid Cashu token",
"code": "invalid_token",
"details": {
"reason": "Token already spent"
}
}
}
```
**Status:** 503
**Status:** 400
**Resolution:** Use a valid, unspent token
**Resolution:** The token is valid — the mint is temporarily down. Retry with
backoff, or pay with a token from a different mint.
#### Token Already Spent
#### Mint Unavailable
```json
{
"error": {
"type": "token_already_spent",
"message": "Cashu token already spent",
"code": "cashu_token_already_spent"
"type": "payment_error",
"message": "Cannot connect to Cashu mint",
"code": "mint_unavailable",
"details": {
"mint_url": "https://mint.example.com",
"retry_after": 60
}
}
}
```
**Status:** 400
**Resolution:** Use a fresh, unspent token. Do not retry with the same token.
#### Response envelope differs by endpoint
The `error` object above is identical everywhere, but the surrounding envelope
depends on how you paid:
- **`X-Cashu` header payments** (chat + Responses API) return the object at the
top level, alongside a `request_id`:
```json
{
"error": { "type": "mint_unreachable", "message": "Cashu mint is unreachable", "code": "cashu_mint_unreachable" },
"request_id": "req-abc123"
}
```
The original token is echoed back in the `X-Cashu` **response header only when
it is still spendable** (e.g. `mint_unreachable`, `invalid_cashu_token`, fee
errors) so you can recover/retry it. It is **not** echoed for spent/consumed
tokens (`cashu_token_already_spent`, `cashu_token_consumed`,
`cashu_token_zero_value`, `internal_error`) — retrying those can never succeed.
- **`Authorization: Bearer <cashu-token>`** (API key minting) wraps it in
FastAPI's `detail` field:
```json
{ "detail": { "error": { "type": "mint_unreachable", "message": "Cashu mint is unreachable", "code": "cashu_mint_unreachable" } } }
```
- **`POST /v1/wallet/topup`** returns a plain string message under `detail` —
it carries the shared HTTP **status** and **message** (e.g. `503` for an
unreachable mint) but not the structured `type`/`code`, so branch on the
status code here:
```json
{ "detail": "Cashu mint is unreachable" }
```
**Status:** 503
**Resolution:** Try again later or use different mint
### Validation Errors
@@ -414,7 +347,7 @@ class ErrorHandler:
'rate_limit',
'upstream_timeout',
'model_overloaded',
'cashu_mint_unreachable'
'mint_unavailable'
}
# Errors requiring user action
@@ -656,4 +589,4 @@ class ErrorMetrics:
- [Authentication](authentication.md) - Auth error details
- [Endpoints](endpoints.md) - Endpoint-specific errors
- [Integration Guide](../client/integration.md) - Error handling examples
- [Examples](../user-guide/using-api.md) - Error handling examples

View File

@@ -99,19 +99,19 @@ All errors follow a consistent format:
Standard OpenAI-compatible endpoints:
- **Models**: `/v1/models`
- **Responses**: `/v1/responses`
- **Chat Completions**: `/v1/chat/completions`
- **Embeddings**: `/v1/embeddings`
- **Completions**: `/v1/completions` *(planned)*
- **Images**: `/v1/images/generations` *(planned)*
- **Audio**: `/v1/audio/transcriptions` *(planned)*
- **Completions**: `/v1/completions` *(Coming soon)*
- **Embeddings**: `/v1/embeddings` *(Coming soon)*
- **Images**: `/v1/images/generations` *(Coming soon)*
- **Audio**: `/v1/audio/transcriptions` *(Coming soon)*
- **Models**: `/v1/models`
### Payment Endpoints
Routstr-specific payment management:
- **Balance**: `/v1/balance/*`
- **Wallet**: `/v1/wallet/*`
- **Balance**: `/v1/balance`
- **Node Info**: `/v1/info`
### Admin Endpoints
@@ -137,25 +137,9 @@ Protected administrative functions:
| Header | Description |
|--------|-------------|
| `X-Routstr-Version` | API version override |
| `X-Cashu` | eCash token for per-request payment |
#### X-Cashu: Stateless Per-Request Payment
Instead of using `Authorization: Bearer sk-...`, you can send a Cashu token directly in the `X-Cashu` header. The response will include an `X-Cashu-Refund` header with your change.
```bash
curl https://api.routstr.com/v1/chat/completions \
-H "X-Cashu: cashuA3s8jKx9..." \
-H "Content-Type: application/json" \
-d '{"model": "gpt-4o", "messages": [{"role": "user", "content": "Hello"}]}'
```
The response includes your change in the same header:
```
X-Cashu: cashuA7k2mNp4...
```
This is fully stateless—no session, no `/v1/balance/refund` call needed. However, **streaming does not work with `X-Cashu`** because the refund can only be calculated after the full response is generated. If you lose the `X-Cashu` response header before claiming your change, you can reclaim the refund via `POST /v1/wallet/refund` by supplying the original payment token in the `x-cashu` header.
| `X-Max-Cost` | Maximum acceptable cost in sats |
## Response Headers
@@ -165,8 +149,16 @@ This is fully stateless—no session, no `/v1/balance/refund` call needed. Howev
|--------|-------------|
| `Content-Type` | Response format |
| `Content-Length` | Response size |
| `X-Request-ID` | Unique request identifier |
| `X-Cashu` | Change token (when request used `X-Cashu` header) |
| `X-Routstr-Request-ID` | Unique request identifier |
| `X-Routstr-Version` | API version used |
### Cost Headers
| Header | Description |
|--------|-------------|
| `X-Routstr-Cost` | Request cost in sats |
| `X-Routstr-Balance` | Remaining balance |
| `X-Cashu` | Change token (if applicable) |
## Streaming Responses
@@ -253,6 +245,8 @@ X-Webhook-Signature: sha256=...
- Current version: `v1`
- Version in URL path: `/v1/endpoint`
- Override with header: `X-Routstr-Version: v2`
- Deprecation notices: 6 months
## Status Codes
@@ -290,23 +284,82 @@ Responses are compressed with gzip when:
- Response is larger than 1KB
- Content type is compressible
## Batch Requests *(planned)*
## Pagination
Process multiple operations in one request. Coming soon.
## Node Info
Get node metadata:
List endpoints support pagination:
```
GET /v1/info
GET /v1/transactions?limit=50&offset=100
```
Supported models and pricing are available at `/v1/models`.
Response includes pagination metadata:
```json
{
"data": [...],
"has_more": true,
"total": 500,
"limit": 50,
"offset": 100
}
```
## Field Filtering
Select specific fields in responses:
```
GET /v1/models?fields=id,name,pricing
```
## Batch Requests
Process multiple operations in one request:
```json
POST /v1/batch
{
"requests": [
{"method": "POST", "endpoint": "/chat/completions", "body": {...}},
{"method": "GET", "endpoint": "/models"},
{"method": "GET", "endpoint": "/balance"}
]
}
```
## Idempotency
Prevent duplicate operations:
```
Idempotency-Key: unique-request-id
```
Keys are stored for 24 hours.
## Health Check
Monitor service status:
```
GET /health
Response:
{
"status": "healthy",
"version": "0.2.0",
"timestamp": "2024-01-01T00:00:00Z",
"checks": {
"database": "ok",
"upstream": "ok",
"mint": "ok"
}
}
```
## Next Steps
- [Authentication](authentication.md) - Detailed auth guide
- [Endpoints](endpoints.md) - Complete endpoint reference
- [Errors](errors.md) - Error handling guide
- [Integration Guide](../client/integration.md) - Code examples
- [Examples](../user-guide/using-api.md) - Code examples

View File

@@ -1,143 +0,0 @@
# Using the API
Routstr is **OpenAI-compatible**. Almost any AI application, SDK, or tool that supports custom endpoints will work out of the box. Just change two things:
```
BASE_URL → https://api.routstr.com/v1
API_KEY → sk-... or cashuA...
```
**Both work as API keys:**
- `sk-7f8e9d...` — Session key (from Lightning invoice or Cashu import)
- `cashuA3s8j...` — Raw Cashu token (use directly from your wallet)
If the app lets you set a base URL and API key, you're good to go.
---
## Quick Setup Examples
### OpenAI SDK (Python/JS)
```python
client = OpenAI(base_url="https://api.routstr.com/v1", api_key="sk-...") # or any provider's URL
```
### Claude Code
```bash
export ANTHROPIC_BASE_URL=https://api.routstr.com/v1
export ANTHROPIC_AUTH_TOKEN=sk-...
```
### Any OpenAI-compatible app
Look for "Custom API endpoint", "Base URL", or "OpenAI-compatible" in settings. Paste the URL and key.
---
## Detailed Examples
### Python (Official SDK)
```python
from openai import OpenAI
# 1. Initialize with Routstr URL and your funded key
client = OpenAI(
base_url="https://api.routstr.com/v1",
api_key="sk-7f8e9d..."
)
# 2. Call the API normally
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello!"}],
stream=True
)
for chunk in response:
if chunk.choices[0].delta.content:
print(chunk.choices[0].delta.content, end="")
```
### Node.js
```javascript
import OpenAI from 'openai';
// You can use a session key OR a raw Cashu token directly
const openai = new OpenAI({
baseURL: 'https://api.routstr.com/v1',
apiKey: 'cashuA3s8jKx9...', // or 'sk-7f8e9d...'
});
async function main() {
const completion = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'gpt-3.5-turbo',
});
console.log(completion.choices[0]);
}
main();
```
### cURL
```bash
# Works with session key or raw Cashu token
curl https://api.routstr.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer cashuA3s8jKx9..." \
-d '{
"model": "gpt-4o-mini",
"messages": [{"role": "user", "content": "Hello!"}]
}'
```
---
## Error Handling
### Insufficient Balance (402 Payment Required)
If your session runs out of funds, the API will return a `402` error.
```json
{
"error": {
"message": "Insufficient balance. Current: 1000 msat, Required: 5000 msat",
"type": "insufficient_balance",
"code": 402
}
}
```
**Action**: Top up your key using the `/lightning/invoice` (topup purpose) or `/v1/balance/topup` endpoints.
### Rate Limiting
Routstr passes through rate limits from the upstream provider. Handle `429 Too Many Requests` with standard exponential backoff.
---
## Advanced: Tor Access
If the node is running as a hidden service, use a SOCKS5 proxy (like `127.0.0.1:9050`).
**Python:**
```python
import httpx
from openai import OpenAI
proxy_mounts = {
"http://": httpx.HTTPTransport(proxy="socks5://127.0.0.1:9050"),
"https://": httpx.HTTPTransport(proxy="socks5://127.0.0.1:9050"),
}
client = OpenAI(
base_url="http://verylongonionaddress.onion/v1",
api_key="sk-...",
http_client=httpx.Client(mounts=proxy_mounts),
)
```

View File

@@ -1,142 +0,0 @@
# Introduction to Routstr
Welcome to the Routstr Core User Guide. This guide will help you understand how to use Routstr to access AI APIs with Bitcoin micropayments.
## What You'll Learn
- How the payment system works (Cashu eCash)
- Creating and managing API keys (Ephemeral Sessions)
- Making API calls through Routstr
- Using the admin dashboard
## Prerequisites
### 💰 Wallet
Cashu ([cashu.me](https://cashu.me)) or Lightning ([Strike](https://strike.me), Cash App, etc.)
### 🌐 Provider
A Routstr node, e.g. `https://api.routstr.com`
### 🤖 Client
OpenAI SDK, Claude Code, Cursor, or any OpenAI-compatible tool
---
## How Routstr Works
Routstr is a **Payment Proxy**. It sits between your code and the AI provider.
### Traditional API vs Routstr
| Traditional | Routstr |
|---|---|
| Credit Card Required | Bitcoin / Lightning / eCash |
| Monthly Billing | Pay-per-request (Real-time) |
| KYC / Account | No Account / Private |
| Single Provider | Aggregated Providers |
### Key Concepts
#### 1. Cashu eCash
Digital bearer tokens backed by Bitcoin. They are instant, private, and have no fees for internal transfers. Routstr uses these tokens as the "credits" for API requests.
#### 2. Ephemeral Sessions (API Keys)
Instead of a permanent account, you create a **Session**.
- You fund a session with eCash or Lightning.
- Routstr gives you an `api_key` (`sk-...`) representing that session.
- You use the `api_key` until funds run out or you finish your task.
- You can **refund** the remaining balance back to your wallet at any time.
#### 3. Millisats (msats)
Everything is priced in **millisatoshis**.
- 1 Satoshi (sat) = 1,000 msats.
- This allows for extremely precise pricing (e.g., 0.05 sats per prompt).
---
## Workflow: Zero to Intelligence
### 1. Fund a Session
You need an `api_key` with a balance.
**Easiest: Use the Web UI**
Visit the node's root page (e.g., [api.routstr.com](https://api.routstr.com)) or [chat.routstr.com](https://chat.routstr.com) → Settings to create a key visually with Lightning.
**Option A: Lightning Invoice (CLI)**
Generate an invoice and pay it with any Lightning wallet.
```bash
curl -X POST https://api.routstr.com/lightning/invoice \
-d '{"amount_sats": 1000, "purpose": "create"}'
```
*Returns an invoice (`bolt11`) and an ID. Once paid, the status endpoint returns your `api_key`.*
**Option B: Cashu Token (Best for privacy & devs)**
If you have a Cashu wallet, you can copy a token string (`cashuA...`) and use it directly.
- **Direct Usage**: Use the token *as* your API key in the `Authorization` header.
- **Import**: Or exchange it for a standard `sk-...` key:
```bash
curl "https://api.routstr.com/v1/balance/create?initial_balance_token=cashuA..."
```
*Returns your `api_key` immediately.*
### 2. Configure Your Client
Use the standard OpenAI SDK, just changing the `base_url` and `api_key`.
```python
from openai import OpenAI
client = OpenAI(
base_url="https://api.routstr.com/v1",
api_key="sk-7f8e9d..." # The key from Step 1
)
```
### 3. Make Requests
```python
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Explain quantum computing."}]
)
```
### 4. Withdraw Change
When you are done, get your change back as a Cashu token.
```bash
curl -X POST https://api.routstr.com/v1/balance/refund \
-H "Authorization: Bearer sk-7f8e9d..."
```
*Returns a `token` that you can paste back into Nutstash or Minibits to reclaim your funds.*
---
## Supported Features
- **Responses**: `/v1/responses` (OpenAI Responses API)
- **Chat Completions**: `/v1/chat/completions` (Streaming supported)
- **Embeddings**: `/v1/embeddings`
- **Models**: `/v1/models` (List available models and prices)
## Next Steps
- **[Payment Flow](payments.md)**: Detailed breakdown of the funding lifecycle.
- **[Models & Pricing](../provider/pricing.md)**: How costs are calculated.
- **[Admin Dashboard](../provider/dashboard.md)**: Managing your node if you are the operator.

View File

@@ -1,99 +0,0 @@
# Payment Flow
Routstr uses a **Pre-paid, Ephemeral** payment model. Pay first, use the funds, withdraw the rest. No accounts, no credit cards, no trails.
```
💰 Deposit → 🤖 Use AI → 💸 Withdraw Change
```
## 1. Creating a Balance (Deposit)
To start making requests, you must create a "Balance" (represented by an API Key).
### Method A: Lightning Network (Bolt11)
**Ideal for**: Users connecting from a standard Lightning wallet (Strike, Cash App, WoS).
1. **Request Invoice**:
`POST /lightning/invoice` with `{"amount_sats": 5000, "purpose": "create"}`.
2. **Pay Invoice**: User scans and pays the QR code/bolt11 string.
3. **Receive Key**: Routstr detects the payment and issues a new API Key (`sk-...`) pre-loaded with 5,000 sats (5,000,000 msats).
### Method B: Cashu Token Import
**Ideal for**: Private, instant access or automated agents.
1. **Generate Token**: User creates a token in their local wallet (e.g., 1000 sats).
2. **Import**: `GET /v1/balance/create?initial_balance_token=cashuA...`
3. **Receive Key**: Routstr claims the token and issues an API Key (`sk-...`) with that balance.
---
## 2. Consuming Funds (Inference)
Every time you make a request to `/v1/chat/completions` (or others), the cost is deducted from your balance **in real-time**.
### Cost Calculation
`Cost = (Input_Tokens * Price_Input) + (Output_Tokens * Price_Output) + Request_Fee`
- Prices are defined per model (see `/v1/models`).
- If you stream the response, the balance is deducted incrementally or finalized at the end of the stream.
- If your balance hits 0 mid-stream, the connection is closed.
### Headers
Routstr checks the `Authorization: Bearer sk-...` header to identify which balance to charge.
---
## 3. Topping Up
If your balance runs low, you don't need a new key. You can top up the existing one.
### Via Lightning
`POST /lightning/invoice` with `Authorization: Bearer sk-...` header and body `{"amount_sats": 1000, "purpose": "topup"}`.
*Once paid, the funds are added to your existing key.*
> Legacy: the endpoint is also exposed at `/v1/balance/lightning/invoice`, and accepts an `api_key` field in the body as a fallback for older clients. New integrations should use the RIP-08 path with the `Authorization` header.
### Via Cashu
`POST /v1/balance/topup` with `{"cashu_token": "..."}` and `Authorization: Bearer sk-...`.
---
## 4. Refund (Withdrawal)
Don't leave large balances sitting on a node—it's a hot wallet. When you're done, get your sats back.
### Endpoint
`POST /v1/balance/refund`
**Headers**:
`Authorization: Bearer sk-...`
**Response**:
```json
{
"token": "cashuAeyJ0b2tlbiI6W3sibWludCI6...",
"msats": "450000"
}
```
You can verify the refund was successful by checking that the API Key is now invalid or has 0 balance. Copy the `token` string and paste it into your Cashu wallet to claim the Bitcoin.
---
## Summary
| Step | Action | Result |
|------|--------|--------|
| 💰 **Deposit** | Pay Lightning invoice or import Cashu | Get `sk-...` key |
| 🤖 **Use** | Make API requests | Balance decreases |
| 💸 **Refund** | Call `/v1/balance/refund` | Get Cashu token back |
That's it. No monthly bills, no surprise charges, no data harvesting.

View File

@@ -4,7 +4,7 @@ This document describes the high-level architecture of Routstr Core, helping con
## System Overview
Routstr Core is a FastAPI-based reverse proxy that adds Bitcoin micropayments to OpenAI-compatible APIs and can optionally announce providers via Nostr.
Routstr Core is a FastAPI-based reverse proxy that adds Bitcoin micropayments to OpenAI-compatible APIs.
```mermaid
graph TB
@@ -20,7 +20,7 @@ graph TB
Auth[Auth Module]
Payment[Payment Module]
Proxy[Proxy Module]
DB[(SQLModel DB)]
DB[(SQLite DB)]
API --> Auth
Auth --> Payment
@@ -40,87 +40,57 @@ graph TB
The main application is initialized in `routstr/core/main.py`:
- **Lifespan Management**: Runs migrations, initializes DB, refreshes pricing/models, starts background tasks
- **Middleware**: CORS and request logging
- **Routers**: Admin, pricing/models, balance/wallet, providers discovery, proxy
- **Background Tasks**: Price refresh, model map refresh, payouts, node announcements, provider discovery refresh
- **Lifespan Management**: Handles startup/shutdown tasks
- **Middleware**: CORS, logging, error handling
- **Routers**: Modular endpoint organization
- **Background Tasks**: Price updates, automatic payouts
### Authentication System
Located in `routstr/auth.py`, handles:
- **API Key Validation**: SHA-256 hashed key lookup and persistence
- **Balance Checking**: Ensures sufficient funds before requests
- **Token Redemption**: Converts Cashu tokens to balance
- **API Key Validation**: Hashed key storage and lookup
- **Balance Checking**: Ensures sufficient funds
- **Rate Limiting**: Optional request throttling
- **Token Redemption**: Converts eCash to balance
### Payment Processing
The `routstr/payment/` module manages:
- **Cost Calculation**: Token-based or fixed pricing
- **Model Pricing**: Derived from upstream providers and DB overrides
- **Currency Conversion**: BTC/USD price refresh and conversion
- **Fee Application**: Provider fee applied to upstream model pricing
- **Model Pricing**: Dynamic pricing from models.json
- **Currency Conversion**: BTC/USD rate management
- **Fee Application**: Exchange and provider fees
### Request Proxying
`routstr/proxy.py` handles:
- **Request Forwarding**: Forwards requests to selected upstream providers
- **Response Streaming**: Streaming and non-streaming paths
- **Usage Tracking**: Adjusts costs after upstream responses
- **Error Handling**: Maps upstream errors to consistent responses
- **Request Forwarding**: Preserves headers and body
- **Response Streaming**: Efficient memory usage
- **Usage Tracking**: Counts tokens and costs
- **Error Handling**: Graceful upstream failures
### Database Layer
Using SQLModel in `routstr/core/db.py`:
```python
# Core tables
ApiKey:
- hashed_key: Primary key (SHA-256 of key or Cashu token)
# Core models
APIKey:
- id: Primary key
- key_hash: Hashed API key
- balance: Current balance (msats)
- reserved_balance: Reserved balance (msats)
- refund_address: Optional LNURL for refunds
- key_expiry_time: Optional refund expiry timestamp
- total_spent: Total spent (msats)
- total_requests: Request count
- refund_mint_url: Mint URL for refunds
- refund_currency: Refund currency
- created_at: Timestamp
- metadata: JSON field
UpstreamProviderRow:
Transaction:
- id: Primary key
- provider_type: openai/anthropic/azure/openrouter/etc.
- base_url: Provider API base URL
- api_key: Provider API key
- api_version: Optional API version
- enabled: Provider enabled flag
- provider_fee: Provider fee multiplier
ModelRow:
- id: Model ID
- upstream_provider_id: Provider foreign key
- name: Model name
- architecture: JSON
- pricing: JSON
- sats_pricing: JSON
- per_request_limits: JSON
- top_provider: JSON
- canonical_slug: Canonical model slug
- alias_ids: Model aliases
- enabled: Model enabled flag
LightningInvoice:
- id: Primary key
- bolt11: Invoice
- amount_sats: Amount in sats
- payment_hash: Payment hash
- status: pending/paid/expired/cancelled
- api_key_hash: Optional associated API key
- purpose: create/topup
- created_at: Unix timestamp
- expires_at: Unix timestamp
- paid_at: Unix timestamp
- api_key_id: Foreign key
- amount: Transaction amount
- type: deposit/usage/withdrawal
- timestamp: When occurred
```
## Request Flow
@@ -137,10 +107,10 @@ sequenceDiagram
C->>R: API Request + Key
R->>D: Validate Key
D-->>R: Key Info + Balance
R->>R: Reserve Max Cost
R->>R: Check Balance
R->>P: Forward Request
P-->>R: AI Response
R->>D: Finalize Cost (adjust by usage)
R->>D: Deduct Cost
R-->>C: Return Response
```
@@ -154,20 +124,36 @@ sequenceDiagram
participant M as Cashu Mint
participant D as Database
C->>R: Request + Cashu Token
R->>W: Redeem Token
C->>R: Create Key Request + Token
R->>W: Validate Token
W->>M: Verify with Mint
M-->>W: Token Valid
W-->>R: Token Amount
R->>D: Create/Update Key + Balance
R-->>C: Continue Request
R->>D: Create Key + Balance
R-->>C: Return API Key
```
## Key Design Decisions
### 1. Async Architecture
The system is async end-to-end, with background tasks for pricing refresh, provider discovery, model map refresh, and payouts.
Everything is async for maximum performance:
```python
async def handle_request(request: Request) -> Response:
# Non-blocking database queries
api_key = await get_api_key(request.headers["Authorization"])
# Concurrent operations
balance_check, rate_limit = await asyncio.gather(
check_balance(api_key),
check_rate_limit(api_key)
)
# Stream response without blocking
async for chunk in proxy_request(request):
yield chunk
```
### 2. Modular Design
@@ -180,46 +166,82 @@ Components are loosely coupled:
### 3. Error Handling
Exceptions are handled by FastAPI exception handlers to return consistent JSON responses with a request ID.
Graceful degradation and clear error messages:
```python
class RoustrError(Exception):
"""Base exception with structured error response"""
status_code: int = 500
error_type: str = "internal_error"
class InsufficientBalanceError(RoustrError):
status_code = 402
error_type = "insufficient_balance"
```
### 4. Database Migrations
Alembic migrations are run on startup, and tables are created for any models not tracked by migrations.
Using Alembic for schema management:
- Auto-migrations on startup
- Version control for schema changes
- Rollback capability
- Zero-downtime updates
## Security Architecture
### API Key Security
- **Storage**: SHA-256 hashed keys
- **Generation**: Cryptographically secure random (when creating new keys)
- **Validation**: Hash lookup in DB
- **Expiry**: Optional refund flow via `key_expiry_time` and `refund_address`
- **Generation**: Cryptographically secure random
- **Validation**: Constant-time comparison
- **Rotation**: Support for key expiry
### Payment Security
- **Token Validation**: Cashu token redemption via mint
- **Balance Protection**: Atomic updates and reserved balance tracking
- **Audit Trail**: Structured logging of payments and adjustments
- **Token Validation**: Cryptographic verification
- **Double-Spend Prevention**: Mint verification
- **Balance Protection**: Atomic transactions
- **Audit Trail**: All transactions logged
### Network Security
- **HTTPS**: Enforced in production
- **CORS**: Configurable origins
- **Rate Limiting**: Per-key limits
- **Input Validation**: Pydantic models
## Performance Considerations
### Caching Strategy
Model and provider selections are cached in process memory and refreshed on a schedule.
```python
# Model pricing cache
@lru_cache(maxsize=100)
def get_model_price(model_id: str) -> ModelPrice:
return MODELS.get(model_id)
# Balance cache with TTL
balance_cache = TTLCache(maxsize=1000, ttl=60)
```
### Database Optimization
- **Connection Pooling**: Reuse connections
- **Indexed Queries**: Key lookups are O(1)
- **Batch Operations**: Group updates
- **Async I/O**: Non-blocking queries
- **Atomic Updates**: Balance reservation and finalization updates
### Streaming Responses
Streaming responses are forwarded from upstream providers with usage tracking hooks.
Efficient memory usage for large responses:
```python
async def stream_response(upstream_response):
async for chunk in upstream_response.aiter_bytes():
# Process chunk without loading full response
yield process_chunk(chunk)
```
## Extension Points
@@ -251,6 +273,8 @@ Streaming responses are forwarded from upstream providers with usage tracking ho
- Mock external dependencies
- Test business logic in isolation
- Fast execution (< 1 second per test)
- High coverage target (> 80%)
### Integration Tests
@@ -261,7 +285,10 @@ Streaming responses are forwarded from upstream providers with usage tracking ho
### Performance Tests
- Response time benchmarks (as needed)
- Load testing with locust
- Memory profiling
- Database query optimization
- Response time benchmarks
## Monitoring and Observability
@@ -281,17 +308,41 @@ logger.info("api_request", extra={
### Metrics Collection
Structured logs are emitted for requests, pricing, and payment events.
Key metrics tracked:
- Request rate by endpoint
- Token usage by model
- Balance changes
- Error rates
- Response times
### Health Checks
Use `/v1/info` for basic service metadata and configuration visibility.
```python
@app.get("/health")
async def health_check():
return {
"status": "healthy",
"version": __version__,
"database": await check_db(),
"upstream": await check_upstream(),
"mints": await check_mints()
}
```
## Deployment Architecture
### Container Structure
See `core/Dockerfile` for the current container build configuration.
```dockerfile
# Multi-stage build
FROM python:3.11-slim AS builder
# Install dependencies
FROM python:3.11-slim
# Copy only runtime needs
# Run as non-root user
```
### Environment Configuration
@@ -301,9 +352,10 @@ See `core/Dockerfile` for the current container build configuration.
### Scaling Considerations
- **Horizontal**: Multiple instances behind a load balancer
- **Horizontal**: Multiple instances behind load balancer
- **Vertical**: Async handles high concurrency
- **Database**: Configure `DATABASE_URL` for external databases
- **Database**: Consider PostgreSQL for scale
- **Caching**: Redis for distributed cache
## Future Architecture

View File

@@ -7,13 +7,10 @@ This guide provides a detailed overview of Routstr Core's codebase organization
```
routstr-core/
├── routstr/ # Main application package
│ ├── __init__.py # Package initialization, exports FastAPI app
│ ├── algorithm.py # Model selection/mapping logic
│ ├── auth.py # Bearer/Cashu auth and payment handling
│ ├── __init__.py # Package initialization, loads .env
│ ├── auth.py # Authentication and authorization
│ ├── balance.py # Balance management endpoints
│ ├── discovery.py # Nostr relay discovery
│ ├── lightning.py # Lightning invoice topups
│ ├── nip91.py # Node announcement logic
│ ├── proxy.py # Request proxying logic
│ ├── wallet.py # Cashu wallet operations
│ │
@@ -21,23 +18,19 @@ routstr-core/
│ │ ├── __init__.py
│ │ ├── admin.py # Admin dashboard and API
│ │ ├── db.py # Database models and connection
│ │ ├── exceptions.py # Exception handlers
│ │ ├── exceptions.py # Custom exception classes
│ │ ├── logging.py # Structured logging setup
│ │ ├── main.py # FastAPI app initialization
│ │ └── middleware.py # HTTP middleware components
│ │
── payment/ # Payment processing
├── __init__.py
├── cost_calculation.py # Usage cost calculation
├── helpers.py # Payment utilities
├── lnurl.py # Lightning URL support
├── models.py # Model pricing management
── price.py # BTC/USD price handling
│ └── upstream/ # Upstream provider integrations
│ ├── base.py # Base provider logic
│ ├── helpers.py # Provider init and model refresh
│ └── ... # Provider implementations
── payment/ # Payment processing
├── __init__.py
├── cost_calculation.py # Usage cost calculation
├── helpers.py # Payment utilities
├── lnurl.py # Lightning URL support
├── models.py # Model pricing management
── price.py # BTC/USD price handling
└── x_cashu.py # Cashu header protocol
├── tests/ # Test suite
│ ├── __init__.py
@@ -52,12 +45,7 @@ routstr-core/
│ └── versions/ # Migration files
├── scripts/ # Utility scripts
── models_meta.py # Fetch model pricing
│ └── ... # Build/update helpers
├── examples/ # Example clients
├── testing-clients/ # HTML test clients
├── ui/ # Next.js admin UI
── models_meta.py # Fetch model pricing
├── docs/ # Documentation
├── logs/ # Application logs (git ignored)
@@ -83,27 +71,30 @@ routstr-core/
#### `routstr/__init__.py`
```python
from .core.main import app as fastapi_app
# Loads environment variables
import dotenv
dotenv.load_dotenv()
__all__ = ["fastapi_app"]
# Exports FastAPI app
from .core.main import app as fastapi_app
```
#### `routstr/core/main.py`
```python
# FastAPI application setup
app = FastAPI(version=__version__, lifespan=lifespan)
app = FastAPI(
title="Routstr Node",
lifespan=lifespan, # Manages startup/shutdown
)
# Middleware registration
app.add_middleware(CORSMiddleware, ...)
app.add_middleware(LoggingMiddleware)
# Router inclusion
app.include_router(models_router)
app.include_router(admin_router)
app.include_router(balance_router)
app.include_router(deprecated_wallet_router)
app.include_router(providers_router)
app.include_router(proxy_router)
```
@@ -111,24 +102,29 @@ app.include_router(proxy_router)
#### `routstr/auth.py`
Handles bearer key validation and payment lifecycle (bearer or Cashu token):
Handles API key validation and authorization:
```python
async def validate_bearer_key(
bearer_key: str,
session: AsyncSession,
refund_address: Optional[str] = None,
key_expiry_time: Optional[int] = None,
) -> ApiKey:
"""Validate bearer API key or redeem Cashu token into a balance."""
class APIKeyAuth:
"""FastAPI dependency for API key authentication"""
async def __call__(self, request: Request) -> APIKey:
# Extract and validate API key
# Check balance
# Return authenticated key object
# Usage in routes:
@router.get("/protected")
async def protected_route(api_key: APIKey = Depends(APIKeyAuth())):
pass
```
Key functions:
- `validate_bearer_key()` - Validate API key or Cashu token
- `pay_for_request()` - Reserve max cost before upstream call
- `adjust_payment_for_tokens()` - Adjust final cost after response
- `revert_pay_for_request()` - Refund on upstream failure
- `create_api_key()` - Generate new API keys
- `validate_api_key()` - Verify and retrieve key
- `check_balance()` - Ensure sufficient funds
- `update_last_used()` - Track usage
### Payment Processing
@@ -137,30 +133,56 @@ Key functions:
Calculates request costs:
```python
async def calculate_cost(
response_data: dict, max_cost: int, session: AsyncSession
) -> CostData | MaxCostData | CostDataError:
"""Calculate cost in millisatoshis from response usage or model pricing."""
def calculate_request_cost(
model: str,
prompt_tokens: int,
completion_tokens: int,
**kwargs
) -> CostData:
"""Calculate cost in millisatoshis"""
# Model-based or fixed pricing
# Token counting
# Fee application
# Currency conversion
```
#### `routstr/payment/models.py`
Manages model pricing, database overrides, and pricing refresh:
Manages model pricing data:
```python
class Model(BaseModel):
class ModelPrice:
id: str
name: str
pricing: Pricing
sats_pricing: Pricing | None = None
pricing: dict[str, float] # USD prices
context_length: int
# Global model registry
MODELS: dict[str, ModelPrice] = load_models()
# Dynamic price updates
async def update_sats_pricing():
"""Periodic task to update sats pricing for providers and overrides."""
"""Background task to update BTC prices"""
```
#### `routstr/proxy.py` + `routstr/upstream/*`
#### `routstr/payment/x_cashu.py`
The `x-cashu` header is handled by the proxy route and delegated to upstream providers.
Implements Cashu payment protocol:
```python
class XCashuHandler:
"""Handle x-cashu header payments"""
async def process_request_payment(
self,
token: str,
estimated_cost: int
) -> PaymentResult:
# Validate token
# Check minimum amount
# Process payment
# Generate change
```
### Request Proxying
@@ -169,11 +191,17 @@ The `x-cashu` header is handled by the proxy route and delegated to upstream pro
Core proxy functionality:
```python
@proxy_router.api_route("/{path:path}", methods=["GET", "POST"], response_model=None)
async def proxy(
request: Request, path: str, session: AsyncSession = Depends(get_session)
) -> Response | StreamingResponse:
"""Forward requests to upstream provider and charge usage."""
@router.api_route("/{path:path}", methods=ALL_METHODS)
async def proxy_request(
request: Request,
path: str,
api_key: APIKey = Depends(APIKeyAuth())
) -> Response:
"""Forward requests to upstream provider"""
# Build upstream request
# Stream response
# Track usage
# Deduct costs
```
Key features:
@@ -187,29 +215,27 @@ Key features:
#### `routstr/core/db.py`
SQLModel definitions (selected):
SQLModel definitions:
```python
class ApiKey(SQLModel, table=True):
hashed_key: str = Field(primary_key=True)
balance: int
reserved_balance: int = 0
refund_address: str | None = None
key_expiry_time: int | None = None
class APIKey(SQLModel, table=True):
id: int | None = Field(primary_key=True)
key_hash: str = Field(index=True, unique=True)
balance: int # millisatoshis
total_deposited: int = 0
total_spent: int = 0
total_requests: int = 0
created_at: datetime
expires_at: datetime | None = None
metadata: dict = Field(default_factory=dict, sa_column=Column(JSON))
class LightningInvoice(SQLModel, table=True):
id: str = Field(primary_key=True)
bolt11: str
amount_sats: int
status: str
class UpstreamProviderRow(SQLModel, table=True):
id: int | None = Field(default=None, primary_key=True)
provider_type: str
base_url: str
api_key: str
class Transaction(SQLModel, table=True):
id: int | None = Field(primary_key=True)
api_key_id: int = Field(foreign_key="apikey.id")
amount: int # can be negative
balance_after: int
type: TransactionType
description: str
timestamp: datetime
```
### Admin Interface
@@ -219,17 +245,18 @@ class UpstreamProviderRow(SQLModel, table=True):
Web dashboard and admin API:
```python
@admin_router.get("/admin")
@admin_router.get("/admin/")
async def admin_dashboard(request: Request):
"""Render admin HTML interface"""
# Authentication check
# Load statistics
# Render template
@admin_router.post("/admin/withdraw")
@admin_router.post("/admin/api/withdraw")
async def withdraw_balance(
request: Request, withdraw_request: WithdrawRequest
) -> dict[str, str]:
api_key: str,
amount: int | None = None
) -> WithdrawalResponse:
"""Generate eCash token for withdrawal"""
```
@@ -244,14 +271,25 @@ Features:
#### `routstr/wallet.py`
Cashu wallet operations (function-based):
Cashu wallet operations:
```python
async def recieve_token(token: str) -> tuple[int, str, str]:
"""Redeem eCash token and return amount/unit/mint."""
async def send_token(amount: int, unit: str, mint_url: str | None = None) -> str:
"""Create eCash token for withdrawal."""
class WalletManager:
"""Manage Cashu wallet instances"""
async def redeem_token(
self,
token: str,
mint_url: str | None = None
) -> int:
"""Redeem eCash token and return value"""
async def create_token(
self,
amount: int,
mint_url: str
) -> str:
"""Create eCash token for withdrawal"""
```
### Utility Modules
@@ -263,9 +301,12 @@ Structured logging configuration:
```python
def setup_logging():
"""Configure JSON structured logging"""
class RequestIdFilter(logging.Filter):
"""Attach request ID to log records."""
# Set log level
# Configure formatters
# Add handlers
class RequestIdMiddleware:
"""Add request ID to all logs"""
```
#### `routstr/core/middleware.py`
@@ -275,18 +316,27 @@ HTTP middleware components:
```python
class LoggingMiddleware:
"""Log all HTTP requests/responses"""
class ErrorHandlingMiddleware:
"""Consistent error responses"""
```
#### `routstr/core/exceptions.py`
Exception handlers:
Custom exception hierarchy:
```python
async def http_exception_handler(request: Request, exc: Exception) -> JSONResponse:
"""HTTP exception handler with request ID"""
class RoustrError(Exception):
"""Base exception with error details"""
status_code: int
error_type: str
detail: str
async def general_exception_handler(request: Request, exc: Exception) -> JSONResponse:
"""Fallback exception handler with request ID"""
class PaymentError(RoustrError):
"""Payment-related errors"""
class UpstreamError(RoustrError):
"""Upstream API errors"""
```
## Configuration Files
@@ -298,7 +348,7 @@ Project metadata and dependencies:
```toml
[project]
name = "routstr"
version = "0.2.2"
version = "0.2.0"
dependencies = [
"fastapi[standard]>=0.115",
"sqlmodel>=0.0.24",
@@ -359,13 +409,13 @@ Using FastAPI's DI system:
```python
# Define dependency
async def get_session() -> AsyncGenerator[AsyncSession, None]:
async with AsyncSession(engine, expire_on_commit=False) as session:
async def get_db() -> AsyncSession:
async with async_session() as session:
yield session
# Use in routes
@router.get("/items")
async def get_items(db: AsyncSession = Depends(get_session)):
async def get_items(db: AsyncSession = Depends(get_db)):
result = await db.execute(select(Item))
return result.scalars().all()
```

View File

@@ -22,7 +22,22 @@ git clone https://github.com/YOUR_USERNAME/routstr-core.git
cd routstr-core
```
### 2. Set Up Environment
### 2. Install uv
We use [uv](https://github.com/astral-sh/uv) for fast, reliable Python package management:
```bash
# Using the installer script
curl -LsSf https://astral.sh/uv/install.sh | sh
# Or with pip
pip install uv
# Or with Homebrew (macOS)
brew install uv
```
### 3. Set Up Environment
Run the setup command:
@@ -32,13 +47,13 @@ make setup
This will:
- ✅ Install [uv](https://github.com/astral-sh/uv) if not present
- ✅ Install uv if not present
- ✅ Create a virtual environment
- ✅ Install all dependencies
- ✅ Install dev tools (mypy, ruff, pytest)
- ✅ Install project in editable mode
### 3. Configure Environment
### 4. Configure Environment
Create your environment file:
@@ -56,7 +71,7 @@ ADMIN_PASSWORD=development-password
DATABASE_URL=sqlite+aiosqlite:///dev.db
```
### 4. Verify Installation
### 5. Verify Installation
Run these commands to verify your setup:
@@ -153,92 +168,42 @@ Understanding the codebase:
```
routstr-core/
├── routstr/ # Main package
│ ├── __init__.py
│ ├── algorithm.py # Provider selection algorithms
│ ├── __init__.py # Package initialization
│ ├── auth.py # Authentication logic
│ ├── balance.py # Balance management API
│ ├── balance.py # Balance management
│ ├── discovery.py # Nostr discovery
│ ├── lightning.py # Lightning invoice handling
│ ├── nip91.py # Node announcement implementation
│ ├── proxy.py # Request proxying
│ ├── wallet.py # Cashu wallet integration
│ │
│ ├── core/ # Core modules
│ │ ├── admin.py # Admin dashboard API
│ │ ├── db.py # Database models (SQLModel)
│ │ ├── admin.py # Admin dashboard
│ │ ├── db.py # Database models
│ │ ├── exceptions.py # Custom exceptions
│ │ ├── log_manager.py # Log management
│ │ ├── logging.py # Logging setup
│ │ ├── main.py # FastAPI app entry
│ │ ── middleware.py # HTTP middleware
│ │ └── settings.py # Configuration
│ │ ├── main.py # FastAPI app
│ │ ── middleware.py # HTTP middleware
│ │
── payment/ # Payment processing
├── cost_calculation.py
├── helpers.py
├── lnurl.py # LNURL support
├── models.py # Model pricing
── price.py # BTC/USD rates
│ └── upstream/ # Upstream providers
│ ├── base.py # Base provider class
│ ├── helpers.py # Shared utilities
│ ├── openai.py # OpenAI
│ ├── anthropic.py # Anthropic
│ ├── gemini.py # Google Gemini
│ ├── openrouter.py # OpenRouter
│ └── ... # More providers
├── ui/ # Admin dashboard (Next.js)
│ ├── app/ # Next.js app router
│ │ ├── page.tsx # Landing page
│ │ ├── balances/ # Balance management
│ │ ├── logs/ # Request logs viewer
│ │ ├── model/ # Model configuration
│ │ ├── providers/ # Upstream providers
│ │ ├── settings/ # Node settings
│ │ └── transactions/ # Transaction history
│ ├── components/ # React components
│ │ ├── ui/ # shadcn/ui primitives
│ │ ├── landing/ # Landing page components
│ │ └── settings/ # Settings components
│ └── lib/ # Utilities & API client
│ ├── api/ # Backend API client
│ ├── auth/ # Auth context
│ └── hooks/ # React hooks
── payment/ # Payment processing
├── cost_calculation.py # Cost logic
├── helpers.py # Utilities
├── lnurl.py # Lightning URLs
├── models.py # Model pricing
── price.py # BTC pricing
└── x_cashu.py # Cashu headers
├── tests/ # Test suite
├── migrations/ # Alembic migrations
├── scripts/ # Utility scripts
├── docs/ # Documentation
├── examples/ # Usage examples
│ ├── unit/ # Unit tests
│ └── integration/ # Integration tests
├── Makefile # Dev commands
├── pyproject.toml # Project config
── compose.yml # Docker setup
├── migrations/ # Database migrations
├── scripts/ # Utility scripts
── docs/ # Documentation
├── Makefile # Dev commands
├── pyproject.toml # Project config
└── compose.yml # Docker setup
```
### Admin Dashboard (UI)
The admin dashboard is a Next.js app using:
- **Next.js 14** with App Router
- **shadcn/ui** for components
- **Tailwind CSS** for styling
- **pnpm** for package management
```bash
# Development
cd ui
pnpm install
pnpm dev # http://localhost:3000
# Build for production
pnpm build
```
The UI is served by the FastAPI backend at `/admin/` when built. Use `make build-ui` to build and copy to the backend.
## Common Tasks
### Adding a New Endpoint
@@ -418,7 +383,7 @@ rm -rf test_*.db
Now that you're set up:
1. Read the [Architecture Overview](architecture.md)
2. Check [open issues](https://github.com/routstr/routstr-core/issues)
3. Start with a small contribution
3. Check [open issues](https://github.com/routstr/routstr-core/issues)
4. Start with a small contribution
Happy coding! 🚀

View File

@@ -6,228 +6,576 @@ This guide covers testing practices, patterns, and tools used in Routstr Core de
We follow these principles:
- Test behavior, not implementation
- Fast feedback
- Reliable tests
- Clear failures
- **Test Behavior, Not Implementation** - Tests should survive refactoring
- **Fast Feedback** - Unit tests run in milliseconds
- **Reliable Tests** - No flaky tests allowed
- **Clear Failures** - Tests should clearly indicate what broke
## Test Structure
```
tests/
├── integration/
├── conftest.py
├── utils.py
│ ├── test_wallet_topup.py
│ ├── test_wallet_refund.py
│ ├── test_wallet_information.py
│ ├── test_proxy_get_endpoints.py
── test_proxy_post_endpoints.py
│ └── ... more integration tests
├── unit/
├── test_algorithm.py
├── test_fee_consistency.py
── test_image_tokens.py
│ ├── test_logging_securityfilter.py
│ ├── test_payment_helpers.py
│ ├── test_settings.py
│ ├── test_wallet.py
│ └── ... more unit tests
└── run_integration.py
├── __init__.py
├── conftest.py # Shared fixtures and configuration
├── unit/ # Fast, isolated unit tests
│ ├── test_auth.py
│ ├── test_balance.py
│ ├── test_cost_calculation.py
│ ├── test_models.py
── test_wallet.py
└── integration/ # Component integration tests
├── test_api_endpoints.py
├── test_payment_flow.py
├── test_proxy_streaming.py
── test_real_mint.py
```
## Running Tests
### Make Targets
```bash
# Run all tests (unit + integration with mocks)
make test
# Unit tests only
make test-unit
# Integration tests with mocks (fast)
make test-integration
# Integration tests with Docker services
make test-integration-docker
# Fast tests only (skip slow and Docker tests)
make test-fast
# Performance tests
make test-performance
# Coverage
make test-coverage
```
### Direct pytest Commands
### Quick Test Commands
```bash
# Run all tests
pytest
make test
# Run a specific test file
pytest tests/unit/test_wallet.py -v
# Run unit tests only (fast)
make test-unit
# Run a specific test
pytest tests/unit/test_wallet.py::test_get_balance -v
# Run integration tests
make test-integration
# Run tests matching a pattern
pytest -k "wallet" -v
# Run with coverage
make test-coverage
# Run specific test file
uv run pytest tests/unit/test_auth.py -v
# Run specific test
uv run pytest tests/unit/test_auth.py::test_create_api_key -v
# Run tests matching pattern
uv run pytest -k "balance" -v
```
## Test Modes (Integration)
### Test Markers
Integration tests support two execution modes:
Use markers to categorize tests:
- Mock mode (default): uses in-memory mocks, no Docker required
- Docker mode: uses real Docker services (Cashu mint, mock OpenAI, Nostr relay)
```python
@pytest.mark.slow
async def test_heavy_computation():
pass
Use the runner script for Docker mode:
@pytest.mark.requires_docker
async def test_real_services():
pass
```bash
./tests/run_integration.py
```
Or manually:
```bash
docker-compose -f compose.testing.yml up -d
USE_LOCAL_SERVICES=1 pytest tests/integration/ -v
docker-compose -f compose.testing.yml down -v
```
## Test Markers
Markers are defined in `pyproject.toml`:
- `integration`
- `unit`
- `slow`
- `requires_docker`
- `requires_real_mint`
- `performance`
- `asyncio`
Examples:
```bash
# Skip slow tests
pytest -m "not slow" -v
# Run without slow tests
pytest -m "not slow"
# Run only integration tests
pytest -m "integration" -v
# Run performance tests
pytest -m "performance" -v
pytest -m "integration"
```
## Fixtures and Utilities
### Core Integration Fixtures
Defined in `tests/integration/conftest.py`:
- `integration_client` - Async HTTP client for the FastAPI app
- `authenticated_client` - Client with a pre-created API key
- `testmint_wallet` - Test wallet for generating Cashu tokens
- `db_snapshot` - Database state snapshot/diff helper
- `create_api_key` - Helper to create API keys for tests
- `integration_engine`, `integration_session` - Async DB engine/session
- `background_tasks_controller` - Control background tasks in tests
- `mock_upstream_server` - Mock upstream API responses
### Integration Utilities
Defined in `tests/integration/utils.py`:
- `CashuTokenGenerator`
- `ResponseValidator`
- `PerformanceValidator`
- `ConcurrencyTester`
- `DatabaseStateValidator`
- `MockServiceBuilder`
- `TestDataBuilder`
## Writing Tests
### Unit Test Example
```python
from routstr.algorithm import calculate_model_cost_score
from routstr.payment.models import Architecture, Model, Pricing
# tests/unit/test_auth.py
import pytest
from routstr.auth import create_api_key, validate_api_key
def test_calculate_model_cost_score_basic() -> None:
model = Model(
id="test-model",
name="Test test-model",
created=1234567890,
description="Test model",
context_length=8192,
architecture=Architecture(
modality="text",
input_modalities=["text"],
output_modalities=["text"],
tokenizer="gpt",
instruct_type=None,
),
pricing=Pricing(
prompt=0.001,
completion=0.002,
request=0.0,
image=0.0,
web_search=0.0,
internal_reasoning=0.0,
),
)
assert calculate_model_cost_score(model) == 0.002
class TestAPIKeyAuth:
"""Test API key authentication functionality"""
async def test_create_api_key(self, test_db):
"""Test creating a new API key"""
# Arrange
initial_balance = 10000
# Act
api_key = await create_api_key(
balance=initial_balance,
name="Test Key"
)
# Assert
assert api_key.key.startswith("sk-")
assert len(api_key.key) == 32
assert api_key.balance == initial_balance
async def test_validate_invalid_key(self, test_db):
"""Test validation fails for invalid key"""
# Act & Assert
with pytest.raises(InvalidAPIKeyError):
await validate_api_key("invalid_key")
```
### Integration Test Example
```python
# tests/integration/test_payment_flow.py
import pytest
from httpx import AsyncClient
@pytest.mark.integration
@pytest.mark.asyncio
async def test_wallet_topup(
authenticated_client: AsyncClient,
testmint_wallet: object,
db_snapshot: object,
) -> None:
await db_snapshot.capture()
token = await testmint_wallet.mint_tokens(1000)
response = await authenticated_client.post(
"/v1/wallet/topup", params={"cashu_token": token}
)
assert response.status_code == 200
diff = await db_snapshot.diff()
assert len(diff["api_keys"]["modified"]) == 1
class TestPaymentFlow:
"""Test end-to-end payment flows"""
@pytest.mark.asyncio
async def test_token_redemption_flow(
self,
app_client: AsyncClient,
mock_cashu_wallet
):
"""Test complete token redemption and API usage"""
# Arrange
token = create_test_token(amount=5000)
mock_cashu_wallet.redeem.return_value = 5000
# Act - Create API key
response = await app_client.post(
"/v1/wallet/create",
json={"cashu_token": token}
)
# Assert - Key created
assert response.status_code == 200
api_key = response.json()["api_key"]
assert response.json()["balance"] == 5000
# Act - Use API key
response = await app_client.post(
"/v1/chat/completions",
headers={"Authorization": f"Bearer {api_key}"},
json={
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "Hi"}]
}
)
# Assert - Request successful
assert response.status_code == 200
assert "choices" in response.json()
```
## Debugging Tips
## Test Fixtures
### Common Fixtures
Located in `tests/conftest.py`:
```python
@pytest.fixture
async def test_db():
"""Provide a clean test database"""
# Create in-memory SQLite database
engine = create_async_engine("sqlite+aiosqlite:///:memory:")
async with engine.begin() as conn:
await conn.run_sync(SQLModel.metadata.create_all)
async_session = sessionmaker(engine, class_=AsyncSession)
async with async_session() as session:
yield session
await engine.dispose()
@pytest.fixture
async def app_client(test_db):
"""Provide test client with test database"""
app.dependency_overrides[get_db] = lambda: test_db
async with AsyncClient(app=app, base_url="http://test") as client:
yield client
app.dependency_overrides.clear()
@pytest.fixture
def mock_cashu_wallet(mocker):
"""Mock Cashu wallet for testing"""
mock = mocker.patch("routstr.wallet.Wallet")
mock.return_value.redeem.return_value = 1000
return mock
```
### Using Fixtures
```python
async def test_with_fixtures(
test_db, # Get test database
app_client, # Get test HTTP client
mock_cashu_wallet # Get mocked wallet
):
# Use fixtures in test
pass
```
## Mocking Strategies
### Mocking External Services
```python
# Mock upstream API
@pytest.fixture
def mock_openai(mocker):
mock_response = mocker.Mock()
mock_response.json.return_value = {
"choices": [{
"message": {"content": "Hello!"},
"finish_reason": "stop"
}],
"usage": {
"prompt_tokens": 10,
"completion_tokens": 20,
"total_tokens": 30
}
}
mocker.patch(
"httpx.AsyncClient.post",
return_value=mock_response
)
# Mock Cashu mint
@pytest.fixture
def mock_mint(mocker):
mint = mocker.patch("routstr.wallet.Mint")
mint.return_value.check_proof_state.return_value = True
return mint
```
### Mocking Time
```python
from freezegun import freeze_time
@freeze_time("2024-01-01 12:00:00")
async def test_time_dependent():
# Time is frozen during test
key = await create_api_key(expires_in_days=30)
assert key.expires_at == datetime(2024, 1, 31, 12, 0, 0)
```
## Test Patterns
### Testing Async Code
```python
# Always mark async tests
@pytest.mark.asyncio
async def test_async_function():
result = await async_operation()
assert result == expected
# Test async context managers
async def test_async_context():
async with create_resource() as resource:
assert resource.is_active
```
### Testing Exceptions
```python
# Test specific exception
async def test_raises_specific_error():
with pytest.raises(InsufficientBalanceError) as exc_info:
await deduct_balance(api_key, amount=999999)
assert "Insufficient balance" in str(exc_info.value)
assert exc_info.value.status_code == 402
# Test exception details
async def test_exception_details():
with pytest.raises(RoustrError) as exc_info:
await risky_operation()
error = exc_info.value
assert error.error_type == "validation_error"
assert error.detail == "Invalid input"
```
### Testing Streaming Responses
```python
async def test_streaming_response():
"""Test streaming chat completion"""
chunks = []
async with app_client.stream(
"POST",
"/v1/chat/completions",
json={"model": "gpt-3.5-turbo", "stream": True}
) as response:
async for line in response.aiter_lines():
if line.startswith("data: "):
chunks.append(json.loads(line[6:]))
# Verify chunks
assert len(chunks) > 0
assert chunks[-1] == "[DONE]"
```
### Database Testing
```python
async def test_database_transaction(test_db):
"""Test atomic transactions"""
async with test_db.begin():
# Create test data
api_key = APIKey(key_hash="test", balance=1000)
test_db.add(api_key)
await test_db.flush()
# Test rollback
try:
async with test_db.begin_nested():
api_key.balance = -100 # Invalid
await test_db.flush()
raise ValueError("Rollback")
except ValueError:
pass
# Verify rollback worked
await test_db.refresh(api_key)
assert api_key.balance == 1000
```
## Performance Testing
### Benchmark Tests
```python
@pytest.mark.benchmark
def test_performance(benchmark):
"""Benchmark critical functions"""
result = benchmark(expensive_function, arg1, arg2)
assert result == expected
# Run benchmarks
pytest --benchmark-only
```
### Load Testing
```python
# tests/integration/test_load.py
async def test_concurrent_requests(app_client):
"""Test handling multiple concurrent requests"""
async def make_request(i):
response = await app_client.get(f"/test/{i}")
return response.status_code
# Make 100 concurrent requests
tasks = [make_request(i) for i in range(100)]
results = await asyncio.gather(*tasks)
# All should succeed
assert all(status == 200 for status in results)
```
## Test Data
### Factories
```python
# tests/factories.py
from datetime import datetime, timedelta
def create_test_api_key(**kwargs):
"""Factory for test API keys"""
defaults = {
"key": f"sk-test-{uuid4().hex[:8]}",
"balance": 10000,
"created_at": datetime.utcnow(),
"expires_at": datetime.utcnow() + timedelta(days=30)
}
defaults.update(kwargs)
return APIKey(**defaults)
def create_test_token(amount: int = 1000, mint: str = None):
"""Factory for test Cashu tokens"""
# Create valid test token structure
return base64.encode(...)
```
### Test Constants
```python
# tests/constants.py
TEST_MODELS = {
"gpt-3.5-turbo": {
"prompt": 0.0015,
"completion": 0.002
},
"gpt-4": {
"prompt": 0.03,
"completion": 0.06
}
}
TEST_API_KEY = "sk-test-1234567890"
TEST_MINT_URL = "https://testmint.example.com"
```
## Coverage
### Running Coverage
```bash
# Show print output
pytest -s tests/unit/test_wallet.py
# Generate coverage report
make test-coverage
# View HTML report
open htmlcov/index.html
# Coverage with specific tests
pytest --cov=routstr --cov-report=html tests/unit/
```
### Coverage Configuration
In `pyproject.toml`:
```toml
[tool.coverage.run]
source = ["routstr"]
omit = ["tests/*", "*/migrations/*"]
[tool.coverage.report]
exclude_lines = [
"pragma: no cover",
"def __repr__",
"raise AssertionError",
"raise NotImplementedError",
"if TYPE_CHECKING:"
]
```
## Debugging Tests
### Print Debugging
```python
# Use -s flag to see print output
pytest -s tests/unit/test_auth.py
# In test
async def test_debug():
print(f"Value: {value}") # Will show with -s
assert value == expected
```
### Interactive Debugging
```python
# Drop into debugger on failure
pytest --pdb
# Set breakpoint in test
async def test_debug():
import pdb; pdb.set_trace()
# Execution stops here
```
### Logging in Tests
```python
# Enable debug logging in tests
import logging
logging.basicConfig(level=logging.DEBUG)
# Or use caplog fixture
async def test_logging(caplog):
with caplog.at_level(logging.INFO):
await function_that_logs()
assert "Expected message" in caplog.text
```
## CI/CD Integration
### GitHub Actions
Tests run automatically on:
- Pull requests
- Pushes to main
- Nightly schedules
See `.github/workflows/test.yml` for configuration.
### Pre-commit Hooks
Install pre-commit hooks:
```bash
pre-commit install
# Run manually
pre-commit run --all-files
```
## Best Practices
### Do's
1. ✅ Write tests first (TDD)
2. ✅ Keep tests simple and focused
3. ✅ Use descriptive test names
4. ✅ Test edge cases
5. ✅ Mock external dependencies
6. ✅ Use fixtures for setup
7. ✅ Assert specific values
### Don'ts
1. ❌ Don't test implementation details
2. ❌ Don't use production services
3. ❌ Don't rely on test order
4. ❌ Don't ignore flaky tests
5. ❌ Don't skip error cases
6. ❌ Don't use hard-coded waits
7. ❌ Don't commit commented tests
## Troubleshooting
- Docker mode failures: check `docker ps` and `docker-compose -f compose.testing.yml logs`
- Connection errors: make sure ports 3338, 3000, 8000, and 8088 are free
- Slow tests: use `pytest -m "not slow"` or `make test-fast`
### Common Issues
**Async Test Errors**
```python
# Wrong
def test_async(): # Missing async
await function()
# Right
async def test_async():
await function()
```
**Database State**
```python
# Ensure clean state
@pytest.fixture(autouse=True)
async def cleanup(test_db):
yield
# Cleanup after each test
await test_db.execute("DELETE FROM apikey")
await test_db.commit()
```
**Mock Not Working**
```python
# Check import path
mocker.patch("routstr.wallet.Wallet") # Full path
# Not just "Wallet"
```
## Next Steps
- See [Architecture](architecture.md)
- Read [Setup Guide](setup.md)
- See [Architecture](architecture.md) for system design
- Read [Setup Guide](setup.md) for environment setup

View File

@@ -1,150 +0,0 @@
# EHBP Proxy Support for Tinfoil Models
## Problem
The SDK's `SecureClient.fetch` encrypts request bodies with HPKE (EHBP protocol)
and sends them to the Routstr provider. The Routstr proxy had no EHBP handling:
1. It tried to `json.loads()` the binary HPKE-sealed body → failed with a 400
2. The upstream PPQ.AI public endpoint (`/v1/chat/completions`) doesn't speak
EHBP, so the response had no `Ehbp-Response-Nonce` header
3. `SecureClient` threw `Missing Ehbp-Response-Nonce header` because it expects
every response from an EHBP-configured `baseURL` to carry that header
## Root cause
PPQ.AI exposes EHBP-aware inference at `/private/`, separate from the public
`/v1/` endpoint. The Routstr proxy was forwarding to `/v1/` (the public
endpoint) instead of `/private/` (the enclave endpoint). The public endpoint
can't decrypt the body, returns a normal HTTP response, and the SDK can't
decrypt it because there's no nonce header.
The PPQ private-mode proxy (`ppq-private-mode-proxy/lib/proxy.ts`) shows the
correct pattern: `SecureClient` talks to `api.ppq.ai/private/v1/chat/completions`,
which decrypts inside the attested enclave and returns an EHBP-encrypted
response with the `Ehbp-Response-Nonce` header.
## What was changed
### `routstr/proxy.py`
Detects EHBP requests by checking for the `Ehbp-Encapsulated-Key` header (set
by the EHBP transport on every encrypted request). For EHBP requests:
- Skips JSON body parsing (the body is binary ciphertext, not JSON)
- Reads the model ID from the `X-Routstr-Model` header (set by the SDK) instead
of from `body.model`
- Routes through new `forward_ehbp_request` (bearer auth) and
`forward_ehbp_x_cashu_request` (x-cashu auth) methods
- Skips reactive 400 param correction (can't parse encrypted response body)
- Still charges the user via `pay_for_request` (uses `max_cost_for_model` from
the model registry, not the body)
### `routstr/upstream/base.py`
Keeps EHBP as an explicit opt-in provider capability instead of making every
upstream provider appear EHBP-capable:
- `supports_ehbp = False` by default
- `get_ehbp_forwarding_target(path, model_obj)` raises `NotImplementedError`
unless a provider opts in and returns a provider-specific EHBP target
The actual EHBP forwarding logic does **not** live in `base.py`.
### `routstr/upstream/ehbp.py`
Contains the shared opaque EHBP transport and billing helpers:
- `EHBPForwardingTarget` — provider-specific target URL plus extra headers
- `forward_ehbp_request()` — forwards the encrypted body, captures Tinfoil
usage from a response header or streaming HTTP trailer, and finalizes bearer
billing at actual cost (falling back to max cost when usage is unavailable)
- `forward_ehbp_x_cashu_request()` — redeems the Cashu token, refunds the full
token on upstream failure, and refunds the difference between the redeemed
amount and actual cost (or max cost when usage is unavailable)
### Provider support
EHBP is currently enabled only for `TinfoilUpstreamProvider`. It forwards to
Tinfoil's attested enclave and requests `X-Tinfoil-Usage-Metrics` for billing.
PPQ.AI retains its private-target implementation, but `supports_ehbp = False`
until it has a provider-specific trusted usage/model-binding strategy.
## Why it's done this way
The proxy is a **blind relay** for EHBP requests. It cannot decrypt the body
(only the attested enclave can), so it must:
1. Get the model ID from a header, not the body
2. Forward the raw bytes without parsing or transformation
3. Stream the response back without SSE/cost parsing
4. Pass through EHBP protocol headers (`Ehbp-Encapsulated-Key` on request,
`Ehbp-Response-Nonce` on response)
Cost tracking happens at the proxy level. Routstr reserves or redeems up to
`max_cost_for_model`, then Tinfoil's out-of-band usage header/trailer allows it
to finalize at actual token cost. If trusted usage is missing or invalid, the
proxy safely falls back to max-cost billing.
## End-to-end flow
```
SDK Routstr Proxy PPQ.AI /private/
│ │ │
│── X-Routstr-Model: tinfoil-kimi-k2-6 ─│ │
│── Ehbp-Encapsulated-Key: <hex> ───────│ │
│── Authorization: Bearer <cashu> ──────│ │
│── body = HPKE-encrypted(kimi-k2-6) ───│ │
│ │ │
│ detects Ehbp-Encapsulated-Key │
│ reads model from X-Routstr-Model │
│ does billing/routing │
│ │ │
│ adds X-Private-Model: private/kimi-k2-6
│ forwards raw body to /private/v1/... │
│ │──────────────────────────────▶│
│ │ enclave decrypts
│ │ runs inference
│ │◀── Ehbp-Response-Nonce ──────│
│ │◀── encrypted response ────────│
│ │ │
│ streams response back untouched │
│◀── encrypted response ────────────────│ │
│ │ │
SecureClient reads nonce, decrypts │ │
SDK SSE processing sees plaintext │ │
```
## Model ID mapping
Three parties see three different model IDs:
| Party | Header/Body | Value | Source |
|---|---|---|---|
| Routstr proxy | `X-Routstr-Model` header | `tinfoil-kimi-k2-6` | SDK sends full caller-facing id |
| Tinfoil usage metrics | `model` field | `kimi-k2-6` | Enclave reports the model actually served |
| Tinfoil enclave | `body.model` (encrypted) | `kimi-k2-6` | SDK strips `tinfoil-` prefix before encryption |
## Implementation status
A dedicated `TinfoilUpstreamProvider` (`routstr/upstream/tinfoil.py`) now
implements the direct blind-upstream pattern described above. The shared EHBP
helpers in `routstr/upstream/ehbp.py` were extended to:
- Request usage metrics via `X-Tinfoil-Request-Usage-Metrics: true`.
- Parse `X-Tinfoil-Usage-Metrics` from the response header (non-streaming) or
HTTP trailer (streaming).
- Override the forwarding URL with a validated `X-Tinfoil-Enclave-Url` when the
SDK sends it.
- Finalize bearer billing with the dedicated EHBP actual-cost finalizer.
- Compute X-Cashu refunds from actual cost instead of max cost.
See `docs/tinfoil-direct-integration.md` for the full implementation notes.
## Verification status
Unit coverage includes usage parsing, target validation, HTTP trailer capture,
response-size limits, and bearer payment finalization. End-to-end requests have
verified both non-streaming usage headers and streaming usage trailers against
Tinfoil. SDK behavior on proxy-generated non-2xx responses without an
`Ehbp-Response-Nonce` still merits explicit end-to-end coverage.

View File

@@ -0,0 +1,260 @@
# Configuration
Routstr Core is configured via a single settings row in the database. Environment variables are only used on first run to seed that row (with a few computed defaults like `ONION_URL`). After that, the database is the source of truth. You can update settings at runtime via the admin API. `DATABASE_URL` is always env-only.
## Environment Variables
### Core Settings
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `UPSTREAM_BASE_URL` | Base URL of the OpenAI-compatible API to proxy | - | ✅ |
| `UPSTREAM_API_KEY` | API key for the upstream service | - | ❌ |
| `ADMIN_PASSWORD` | Password for admin dashboard access | - | ⚠️ |
### Node Information
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `NAME` | Public name of your Routstr node | `ARoutstrNode` | ❌ |
| `DESCRIPTION` | Description of your node | `A Routstr Node` | ❌ |
| `NPUB` | Nostr public key for node identity | - | ❌ |
| `HTTP_URL` | Public HTTP URL of your node | - | ❌ |
| `ONION_URL` | Tor hidden service URL | - | ❌ |
### Cashu Configuration
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `CASHU_MINTS` | Comma-separated list of trusted Cashu mint URLs | `https://mint.minibits.cash/Bitcoin` | ❌ |
| `RECEIVE_LN_ADDRESS` | Lightning address for automatic payouts | - | ❌ |
### Pricing Configuration
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `FIXED_PRICING` | Force fixed per-request pricing (ignore model token pricing) | `false` | ❌ |
| `FIXED_COST_PER_REQUEST` | Fixed cost per API request in sats | `1` | ❌ |
| `FIXED_PER_1K_INPUT_TOKENS` | Optional override: sats per 1000 input tokens | `0` | ❌ |
| `FIXED_PER_1K_OUTPUT_TOKENS` | Optional override: sats per 1000 output tokens | `0` | ❌ |
| `EXCHANGE_FEE` | Exchange rate markup (1.005 = 0.5% fee) | `1.005` | ❌ |
| `UPSTREAM_PROVIDER_FEE` | Provider fee markup (1.05 = 5% fee) | `1.05` | ❌ |
### Network & Discovery
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `CORS_ORIGINS` | Comma-separated list of allowed CORS origins | `*` | ❌ |
| `TOR_PROXY_URL` | SOCKS5 proxy URL for Tor connections | `socks5://127.0.0.1:9050` | ❌ |
| `RELAYS` | Comma-separated nostr relays used for provider discovery | sane defaults | ❌ |
| `PROVIDERS_REFRESH_INTERVAL_SECONDS` | Provider cache refresh interval | `300` | ❌ |
### Logging Configuration
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `LOG_LEVEL` | Logging level (DEBUG, INFO, WARNING, ERROR) | `INFO` | ❌ |
| `ENABLE_CONSOLE_LOGGING` | Enable console log output | `true` | ❌ |
### Other
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `CHAT_COMPLETIONS_API_VERSION` | Append `api-version` to `/chat/completions` (Azure OpenAI) | - | ❌ |
| `DATABASE_URL` | SQLite database connection string | `sqlite+aiosqlite:///keys.db` | ❌ |
| `REFUND_CACHE_TTL_SECONDS` | Cache TTL for refund responses (seconds) | `3600` | ❌ |
## Configuration Examples
### Basic OpenAI Proxy
```bash
# .env
UPSTREAM_BASE_URL=https://api.openai.com/v1
UPSTREAM_API_KEY=sk-...
ADMIN_PASSWORD=my-secure-password
```
### Custom AI Provider
```bash
# .env
UPSTREAM_BASE_URL=https://api.anthropic.com/v1
UPSTREAM_API_KEY=your-anthropic-key
MODELS_PATH=/app/config/anthropic-models.json
```
### Azure OpenAI (optional)
```bash
# .env
UPSTREAM_BASE_URL=https://<resource>.openai.azure.com/openai/deployments/<deployment>
UPSTREAM_API_KEY=<azure_api_key>
CHAT_COMPLETIONS_API_VERSION=2024-05-01-preview
```
### High-Security Setup
```bash
# .env
UPSTREAM_BASE_URL=https://api.openai.com/v1
UPSTREAM_API_KEY=sk-...
ADMIN_PASSWORD=very-long-secure-password-here
CORS_ORIGINS=https://myapp.com,https://app.myapp.com
TOR_PROXY_URL=socks5://tor:9050
LOG_LEVEL=WARNING
```
### Public Node Configuration
```bash
# .env
NAME=Lightning AI Gateway
DESCRIPTION=Fast and reliable AI API access with Bitcoin payments
NPUB=npub1abcd...
HTTP_URL=https://api.lightning-ai.com
ONION_URL=http://lightningai.onion
CASHU_MINTS=https://mint1.com,https://mint2.com
```
## Pricing
- Default: pricing comes from your `models.json`.
- Force fixed per-request pricing: set `FIXED_PRICING=true` and `FIXED_COST_PER_REQUEST`.
- Optional token overrides when using model pricing: set
`FIXED_PER_1K_INPUT_TOKENS` and/or `FIXED_PER_1K_OUTPUT_TOKENS`.
- Legacy envs are still accepted and mapped automatically:
`MODEL_BASED_PRICING``!FIXED_PRICING`, `COST_PER_REQUEST``FIXED_COST_PER_REQUEST`,
`COST_PER_1K_*``FIXED_PER_1K_*`.
Example fixed pricing:
```bash
FIXED_PRICING=true
FIXED_COST_PER_REQUEST=10
```
## Custom Models Configuration
Create a `models.json` file:
```json
{
"models": [
{
"id": "gpt-4",
"name": "GPT-4",
"pricing": {
"prompt": "0.00003",
"completion": "0.00006",
"request": "0"
}
},
{
"id": "gpt-3.5-turbo",
"name": "GPT-3.5 Turbo",
"pricing": {
"prompt": "0.0000015",
"completion": "0.000002",
"request": "0"
}
}
]
}
```
## Security Best Practices
### Admin Password
Generate a strong password:
```bash
openssl rand -base64 32
```
### API Keys
- Rotate upstream API keys regularly
- Use read-only keys when possible
- Monitor key usage
### Network Security
- Restrict CORS origins in production
- Use HTTPS for public endpoints
- Enable Tor for anonymity
### Database Security
- Regular backups
- Encrypted storage volumes
- Restricted file permissions
## Troubleshooting
### Check Current Configuration
```bash
# View all environment variables
docker exec routstr env | sort
# Test configuration
curl http://localhost:8000/v1/info
```
### Common Issues
**Missing Upstream URL**
```
ERROR: UPSTREAM_BASE_URL not set
Solution: Set UPSTREAM_BASE_URL in .env
```
**Invalid Cashu Mint**
```
ERROR: Failed to connect to mint
Solution: Verify CASHU_MINTS URLs are accessible
```
**Database Errors**
```
ERROR: Database connection failed
Solution: Check DATABASE_URL and file permissions
```
## Advanced Configuration
### Multiple Mints
Configure fallback mints:
```bash
CASHU_MINTS=https://primary.mint,https://backup1.mint,https://backup2.mint
```
### Custom Database
Use PostgreSQL instead of SQLite:
```bash
DATABASE_URL=postgresql+asyncpg://user:pass@localhost/routstr
```
### Proxy Settings
For corporate environments:
```bash
HTTP_PROXY=http://proxy.company.com:8080
HTTPS_PROXY=http://proxy.company.com:8080
```
## Next Steps
- [User Guide](../user-guide/introduction.md) - Start using Routstr
- [Admin Dashboard](../user-guide/admin-dashboard.md) - Manage your node
- [Custom Pricing](../advanced/custom-pricing.md) - Advanced pricing strategies

View File

@@ -0,0 +1,337 @@
# Docker Setup
This guide covers deploying Routstr Core using Docker for production environments.
## Docker Images
Official images are available on GitHub Container Registry:
```bash
ghcr.io/routstr/proxy:latest
```
## Basic Docker Run
### Minimal Setup
```bash
docker run -d \
--name routstr \
-p 8000:8000 \
-e UPSTREAM_BASE_URL=https://api.openai.com/v1 \
-e UPSTREAM_API_KEY=sk-... \
-e ADMIN_PASSWORD=secure-password \
ghcr.io/routstr/proxy:latest
```
### With Persistent Storage
```bash
docker run -d \
--name routstr \
-p 8000:8000 \
-v routstr-data:/app/data \
-v routstr-logs:/app/logs \
-e UPSTREAM_BASE_URL=https://api.openai.com/v1 \
-e UPSTREAM_API_KEY=sk-... \
-e DATABASE_URL=sqlite+aiosqlite:///data/keys.db \
ghcr.io/routstr/proxy:latest
```
## Docker Compose Setup
### Basic Configuration
Create `compose.yml`:
```yaml
version: '3.8'
services:
routstr:
image: ghcr.io/routstr/proxy:latest
ports:
- "8000:8000"
volumes:
- ./data:/app/data
- ./logs:/app/logs
env_file:
- .env
restart: unless-stopped
```
### With Tor Hidden Service
The included `compose.yml` provides Tor support:
```yaml
version: '3.8'
services:
routstr:
build: . # Or use image: ghcr.io/routstr/proxy:latest
volumes:
- .:/app
- ./logs:/app/logs
env_file:
- .env
environment:
- TOR_PROXY_URL=socks5://tor:9050
ports:
- 8000:8000
extra_hosts:
- "host.docker.internal:host-gateway"
tor:
image: ghcr.io/hundehausen/tor-hidden-service:latest
volumes:
- tor-data:/var/lib/tor
environment:
- HS_ROUTER=routstr:8000:80
depends_on:
- routstr
volumes:
tor-data:
```
### Environment File
Create `.env` file:
```bash
# Required
UPSTREAM_BASE_URL=https://api.openai.com/v1
UPSTREAM_API_KEY=your-api-key
ADMIN_PASSWORD=secure-admin-password
# Cashu Configuration
CASHU_MINTS=https://mint.minibits.cash/Bitcoin
# Optional
NAME=My Routstr Node
DESCRIPTION=Pay-per-use AI API proxy
NPUB=npub1...
HTTP_URL=https://api.mynode.com
ONION_URL=http://mynode.onion
# Pricing (optional)
FIXED_PRICING=false
EXCHANGE_FEE=1.005
UPSTREAM_PROVIDER_FEE=1.05
```
## Building Custom Image
### Dockerfile Overview
The provided Dockerfile:
- Uses Alpine Linux for small size
- Installs required dependencies for secp256k1
- Runs as non-root user
- Exposes port 8000
### Build Locally
```bash
# Clone repository
git clone https://github.com/routstr/routstr-core.git
cd routstr-core
# Build image
docker build -t my-routstr:latest .
# Run custom image
docker run -d \
--name routstr \
-p 8000:8000 \
--env-file .env \
my-routstr:latest
```
## Deployment Considerations
### Resource Requirements
- **CPU**: 1-2 cores recommended
- **Memory**: 512MB-1GB
- **Storage**: 1GB + database growth
- **Network**: Low latency to upstream provider
### Health Checks
Add health check to compose.yml:
```yaml
services:
routstr:
# ... other config ...
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/v1/info"]
interval: 30s
timeout: 10s
retries: 3
start_period: 40s
```
### Reverse Proxy Setup
#### Nginx Example
```nginx
server {
listen 443 ssl http2;
server_name api.yournode.com;
ssl_certificate /path/to/cert.pem;
ssl_certificate_key /path/to/key.pem;
location / {
proxy_pass http://localhost:8000;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
# For streaming responses
proxy_buffering off;
proxy_cache off;
proxy_set_header Connection '';
proxy_http_version 1.1;
chunked_transfer_encoding off;
}
}
```
#### Caddy Example
```caddy
api.yournode.com {
reverse_proxy localhost:8000 {
flush_interval -1
}
}
```
## Monitoring
### Log Management
View logs:
```bash
# Docker
docker logs -f routstr
# Docker Compose
docker compose logs -f routstr
# Log files
tail -f ./logs/routstr.log
```
### Metrics
Monitor key metrics:
- Request count and latency
- Token validation success rate
- Upstream API errors
- Database size growth
## Backup and Recovery
### Database Backup
```bash
# Backup SQLite database
docker exec routstr sqlite3 /app/data/keys.db ".backup /app/data/backup.db"
# Copy backup locally
docker cp routstr:/app/data/backup.db ./backup-$(date +%Y%m%d).db
```
### Restore from Backup
```bash
# Stop service
docker compose down
# Restore database
docker cp ./backup.db routstr:/app/data/keys.db
# Restart service
docker compose up -d
```
## Security Considerations
### Environment Variables
- Never commit `.env` files
- Use Docker secrets for sensitive data
- Rotate API keys regularly
- Use strong admin passwords
### Network Security
- Use HTTPS/TLS termination
- Restrict admin interface access
- Enable firewall rules
- Monitor for suspicious activity
### Container Security
- Run as non-root user
- Use read-only filesystem where possible
- Limit container capabilities
- Keep base image updated
## Troubleshooting
### Container Won't Start
```bash
# Check logs
docker logs routstr
# Verify environment
docker exec routstr env | grep -E "(UPSTREAM|CASHU|ADMIN)"
# Test database connection
docker exec routstr sqlite3 /app/data/keys.db ".tables"
```
### Permission Issues
```bash
# Fix volume permissions
sudo chown -R 1000:1000 ./data ./logs
```
### Network Issues
```bash
# Test upstream connectivity
docker exec routstr curl -I https://api.openai.com
# Check DNS resolution
docker exec routstr nslookup api.openai.com
```
## Production Checklist
- [ ] Set strong `ADMIN_PASSWORD`
- [ ] Configure proper `UPSTREAM_BASE_URL` and `UPSTREAM_API_KEY`
- [ ] Set up persistent volumes for data and logs
- [ ] Configure reverse proxy with TLS
- [ ] Set up monitoring and alerting
- [ ] Implement backup strategy
- [ ] Test disaster recovery
- [ ] Document deployment process
## Next Steps
- [Configuration Guide](configuration.md) - All environment variables
- [Admin Dashboard](../user-guide/admin-dashboard.md) - Manage your node

View File

@@ -0,0 +1,156 @@
# Overview
Routstr Core is a powerful payment proxy that brings Bitcoin micropayments to AI APIs. This overview will help you understand the core concepts and architecture.
## Core Concepts
### Payment Proxy
Routstr acts as a transparent proxy between your application and OpenAI-compatible APIs. It:
- Intercepts API requests
- Validates payment tokens
- Forwards requests to the upstream provider
- Tracks usage and deducts costs
- Returns responses to the client
### Cashu eCash Protocol
[Cashu](https://cashu.space) is a Bitcoin eCash protocol that enables:
- **Privacy**: Payments are unlinkable and untraceable
- **Instant Settlement**: No waiting for blockchain confirmations
- **Micropayments**: Send fractions of a satoshi
- **Offline Capability**: Tokens can be transferred without internet
### Lightning Network Integration
Routstr connects to the Lightning Network through Cashu mints, enabling:
- Fast Bitcoin deposits and withdrawals
- Global payment reach
- Low transaction fees
- No minimum payment amounts
## Architecture
### System Components
```mermaid
graph TB
subgraph "Client Side"
A[AI Application]
B[OpenAI SDK]
C[eCash Wallet]
end
subgraph "Routstr Core"
D[FastAPI Server]
E[Auth Module]
F[Payment Module]
G[Proxy Module]
H[SQLite Database]
end
subgraph "External Services"
I[Upstream AI Provider]
J[Cashu Mint]
K[Bitcoin/Lightning]
end
A --> B
B --> D
C --> D
D --> E
E --> F
F --> J
D --> G
G --> I
D --> H
J --> K
```
### Key Modules
1. **Authentication** (`auth.py`)
- API key validation
- Balance checking
- Request authorization
2. **Payment Processing** (`payment/`)
- Token validation
- Cost calculation
- Balance updates
- Pricing models
3. **Proxy Handler** (`proxy.py`)
- Request forwarding
- Response streaming
- Usage tracking
- Error handling
4. **Wallet Management** (`wallet.py`)
- Cashu wallet integration
- Token redemption
- Balance management
- Automatic payouts
5. **Admin Interface** (`core/admin.py`)
- Web dashboard
- Balance viewing
- Key management
- Withdrawal interface
## Payment Flow
### Standard Flow (API Key)
1. User deposits eCash tokens to create an API key
2. Client sends requests with the API key
3. Routstr checks balance and forwards request
4. Cost is deducted based on actual usage
5. Response is returned to client
### Per-Request Flow (Coming Soon)
1. Client includes eCash token in request header
2. Routstr validates token meets minimum amount
3. Request is processed
4. Change is returned in response header
5. No account or balance needed
## Supported Features
### API Compatibility
- ✅ Chat completions (streaming and non-streaming)
- ✅ Text completions
- ✅ Embeddings
- ✅ Image generation
- ✅ Audio transcription/translation
- ✅ Model listing
- ✅ Custom endpoints
### Payment Features
- ✅ Multiple Cashu mint support
- ✅ Automatic balance tracking
- ✅ Model-based pricing
- ✅ USD to BTC conversion
- ✅ Configurable fees
- ✅ Balance withdrawals
### Operational Features
- ✅ Docker deployment
- ✅ Tor hidden service support
- ✅ Nostr relay discovery
- ✅ Database migrations
- ✅ Comprehensive logging
- ✅ Admin dashboard
## Next Steps
- [Quick Start](quickstart.md) - Get running in minutes
- [Docker Setup](docker.md) - Deploy with containers
- [Configuration](configuration.md) - Customize your instance

View File

@@ -0,0 +1,226 @@
# Quick Start
Get Routstr Core up and running in minutes with Docker or local development setup.
## Prerequisites
- Docker and Docker Compose (for production)
- Python 3.11+ (for development)
- A Cashu-compatible wallet (optional for testing)
## Option 1: Docker (Recommended)
### Quick Run
The fastest way to start Routstr Core:
```bash
docker run -d \
--name routstr-proxy \
-p 8000:8000 \
-e UPSTREAM_BASE_URL=https://api.openai.com/v1 \
-e UPSTREAM_API_KEY=your-openai-api-key \
ghcr.io/routstr/proxy:latest
```
### Docker Compose
For a full setup with Tor support:
1. Clone the repository:
```bash
git clone https://github.com/routstr/routstr-core.git
cd routstr-core
```
2. Create environment file:
```bash
cp .env.example .env
# Edit .env with your settings
```
3. Start the services:
```bash
docker compose up -d
```
This will start:
- Routstr proxy on port 8000
- Tor hidden service (optional)
- Automatic database migrations
### Verify Installation
Check that Routstr is running:
```bash
curl http://localhost:8000/v1/info
```
You should see:
```json
{
"name": "ARoutstrNode",
"description": "A Routstr Node",
"version": "0.2.0",
"npub": "",
"mints": ["https://mint.minibits.cash/Bitcoin"],
"models": {...}
}
```
## Option 2: Local Development
### Install Dependencies
1. Install [uv](https://github.com/astral-sh/uv) package manager:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
2. Clone and setup:
```bash
git clone https://github.com/routstr/routstr-core.git
cd routstr-core
uv sync
```
3. Configure environment:
```bash
cp .env.example .env
# Edit .env with your settings
```
### Run the Server
```bash
fastapi run routstr --host 0.0.0.0 --port 8000
```
## First API Call
### 1. Get an eCash Token
You'll need a Cashu token to pay for API calls. Options:
- Use a [Cashu wallet](https://cashu.space) to create tokens
- Get test tokens from a testnet mint
- Use the example token (for testing only)
### 2. Create an API Key
Send your eCash token to create an API key:
```bash
curl -X POST http://localhost:8000/v1/wallet/create \
-H "Content-Type: application/json" \
-d '{
"cashu_token": "cashuAeyJ0b2..."
}'
```
Response:
```json
{
"api_key": "rUvK7...",
"balance": 10000
}
```
### 3. Make an API Call
Use your API key like a normal OpenAI key:
```python
import openai
client = openai.OpenAI(
api_key="rUvK7...", # Your Routstr API key
base_url="http://localhost:8000/v1"
)
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
```
## Example Client
Run the included example:
```bash
CASHU_TOKEN="your-token" python example.py
```
This demonstrates:
- Creating an API key from a token
- Making streaming chat requests
- Automatic balance deduction
## Testing the Setup
### Check Available Models
```bash
curl http://localhost:8000/v1/models
```
### View Admin Dashboard
Open <http://localhost:8000/admin/> in your browser.
Default password is set in `ADMIN_PASSWORD` environment variable.
### Monitor Logs
Docker:
```bash
docker compose logs -f routstr
```
Local:
```bash
# Logs are in ./logs/ directory
tail -f logs/routstr.log
```
## Common Issues
### Connection Refused
- Ensure the service is running: `docker ps`
- Check firewall settings
- Verify port 8000 is not in use
### Invalid API Key
- Ensure you've created an API key with sufficient balance
- Check the token was valid and had value
- Verify the mint URL is accessible
### Upstream Errors
- Check `UPSTREAM_BASE_URL` is correct
- Verify `UPSTREAM_API_KEY` if required
- Test upstream service directly
## Next Steps
- [Configuration Guide](configuration.md) - Customize settings
- [Docker Setup](docker.md) - Production deployment
- [User Guide](../user-guide/introduction.md) - Detailed usage

View File

@@ -0,0 +1,53 @@
# UI Configuration
This guide explains how to configure the Routstr UI for different environments.
## Environment Variables
The UI uses Next.js environment variables to configure API endpoints and authentication.
### Centralized Configuration
This project uses a centralized configuration approach with a single `.env` file in the project root. This file contains both backend and frontend configuration variables.
Create or update your `.env` file in the project root:
```bash
# .env (in project root)
# UI Configuration (NEXT_PUBLIC_ variables are exposed to the browser)
NEXT_PUBLIC_API_URL=http://127.0.0.1:8000
```
### Development vs Production
The same `.env` file is used for both development and production. Simply change the values:
**Development:**
```bash
NEXT_PUBLIC_API_URL=http://127.0.0.1:8000
```
**Production:**
```bash
NEXT_PUBLIC_API_URL=https://api.yourroutstr.com
```
## Building the UI
The build process automatically reads configuration from the root `.env` file:
```bash
# From the project root
make ui-build
# or
./scripts/build-ui.sh
```
The build script will automatically:
- Load `NEXT_PUBLIC_*` variables from the root `.env` file
- Use them during the Next.js build process
- Display warnings if the `.env` file is missing

View File

@@ -1,44 +1,83 @@
# Routstr Core Documentation
**Routstr** is a decentralized protocol for permissionless AI inference. It enables an open marketplace where anyone can buy and sell compute using **Bitcoin eCash (Cashu)**.
Welcome to the official documentation for **Routstr Core** - a FastAPI-based reverse proxy that enables Bitcoin micropayments for OpenAI-compatible APIs using the Cashu eCash protocol.
---
## What is Routstr Core?
## 🐣 For Clients (Users & Builders)
Routstr Core is a payment proxy that sits between API clients and OpenAI-compatible services. It enables:
If you want to use AI models in your application without accounts or KYC.
- **Pay-per-request billing** using Bitcoin eCash tokens
- **Seamless integration** with existing OpenAI clients
- **Privacy-preserving payments** through the Cashu protocol
- **Flexible pricing models** with per-token or per-request billing
- **Multi-provider support** for various AI model providers
- **[Introduction](client/introduction.md)**: How the ecosystem works.
- **[Payment Flow](client/payments.md)**: Funding sessions, topping up, and refunds.
- **[Integration Guide](client/integration.md)**: Code examples for Python, JS, and cURL.
### Key Features
## 🦁 For Providers (Node Operators)
- 🪙 **Cashu Wallet Integration** - Accept Lightning payments and redeem eCash tokens
- 🔑 **API Key Management** - Secure key storage with balance tracking
- 💰 **Dynamic Pricing** - Model-based pricing with live BTC/USD conversion
- 🎛️ **Admin Dashboard** - Web interface for balance and key management
- 🌐 **Nostr Discovery** - Find providers through decentralized relay network
- 🐋 **Docker Support** - Easy deployment with optional Tor hidden service
-**Lightning Fast** - Minimal latency overhead for API requests
If you want to run a node, resell API access, or monetize hardware.
## How It Works
- **[Quick Start](provider/quickstart.md)**: Deploy a node in 5 minutes.
- **[Deployment](provider/deployment.md)**: Production Docker setup.
- **[Configuration](provider/configuration.md)**: Environment variables and settings.
- **[Dashboard](provider/dashboard.md)**: Managing your node visually.
- **[Pricing Strategy](provider/pricing.md)**: Setting margins and fees.
- **[Discovery](provider/discovery.md)**: Announcing your node on Nostr.
- **[Tor Support](provider/tor.md)**: Running an anonymous hidden service.
```mermaid
sequenceDiagram
participant Client
participant Routstr as Routstr Proxy
participant DB as Database
participant Upstream as AI Provider
participant Wallet as Cashu Wallet
---
Client->>Routstr: API Request + eCash Token
Routstr->>Wallet: Validate & Redeem Token
Wallet-->>Routstr: Token Value (sats)
Routstr->>DB: Store/Update Balance
Routstr->>Upstream: Forward API Request
Upstream-->>Routstr: API Response + Usage Data
Routstr->>DB: Deduct Actual Cost
Routstr-->>Client: API Response
```
## 🔌 API Reference
## Quick Links
- **[Overview](api/overview.md)**: Base URL, headers, and standards.
- **[Endpoints](api/endpoints.md)**: Full list of REST endpoints.
- **[Authentication](api/authentication.md)**: Handling API keys and tokens.
- **[Errors](api/errors.md)**: Status codes and debugging.
<div class="grid cards" markdown>
## 🛠️ Contributing
- :rocket: **[Quick Start](getting-started/quickstart.md)**
- **[Architecture](contributing/architecture.md)**: System design.
- **[Setup](contributing/setup.md)**: Development environment.
- **[Testing](contributing/testing.md)**: Running tests.
Get up and running with Docker in minutes
---
- :gear: **[Configuration](getting-started/configuration.md)**
*Powered by [Cashu](https://cashu.space) and [Nostr](https://nostr.com).*
Learn about environment variables and settings
- :book: **[User Guide](user-guide/introduction.md)**
Comprehensive guide for using Routstr
- :hammer: **[Contributing](contributing/setup.md)**
Help improve Routstr Core
</div>
## Use Cases
- **AI Application Developers** - Add Bitcoin payments to your AI apps without managing infrastructure
- **API Resellers** - Resell API access with custom pricing and profit margins
- **Privacy-Focused Users** - Access AI models without revealing personal information
- **Micropayment Experiments** - Test new business models with instant, small payments
## Getting Help
- 📖 Browse the [User Guide](user-guide/introduction.md) for detailed usage instructions
- 🐛 Report issues on [GitHub](https://github.com/routstr/routstr-core/issues)
- 💬 Join the community discussions
- 🔧 Check the [API Reference](api/overview.md) for technical details
## License
Routstr Core is open source software licensed under the GPLv3. See the [LICENSE](https://github.com/routstr/routstr-core/blob/main/LICENSE) file for details.

View File

@@ -1,76 +0,0 @@
# Overview
Routstr is a decentralized protocol for **permissionless, private, and censorship-resistant AI inference**. It creates an open marketplace where anyone can sell llm-tokens and anyone can buy them using privacy-preserving micropayments.
By combining **Nostr** (for censorship-resistant discovery and communication) and **Cashu** (for private, instant Bitcoin eCash payments), Routstr effectively removes the "middleman" from the AI ecosystem.
## How it Works
The network consists of independent **Providers** (Sellers) and **Clients** (Buyers). There is no central server, no login, and no credit card required.
1. **Discovery (Nostr)**: Providers announce their availability, models (e.g., `gpt-4o`, `deepseek-r1`), and prices on the Nostr network.
2. **Payment (Cashu)**: Clients pay providers directly using Bitcoin eCash (Cashu tokens). These payments are untraceable and settle instantly.
3. **Inference (Proxy)**: The Provider acts as a gateway (or runs local hardware), executing the AI model and returning the result to the Client.
## Who is this for?
The documentation is split into two paths depending on your goal:
### 🐣 I want to BUILD on Routstr (Client)
You are a developer building an AI agent, a chat app, or a script, and you want access to AI models without API keys, subscriptions, or KYC.
* **No Accounts**: Just get a wallet.
* **Privacy**: Your requests are mixed with thousands of others; providers can't profile you.
* **Choice**: Switch between hundreds of providers instantly for the best price/performance.
👉 **[Go to Client Guide](client/introduction.md)**
### 🦁 I want to RUN a Node (Provider)
You have API credits (OpenAI, Anthropic, etc.) or GPU capacity and want to earn Bitcoin by selling AI access to the network.
* **Monetize API Keys**: Connect your OpenAI/Anthropic/OpenRouter accounts and earn sats on every request.
* **Monetize Hardware**: Run local models (via vLLM, Ollama) and sell access.
* **Permissionless**: No approval needed. Start the container, configure via dashboard, start earning.
!!! note "Coming Soon"
Future versions will support node-to-node routing—run a gateway without needing your own AI provider credentials.
👉 **[Go to Provider Guide](provider/quickstart.md)**
---
## Architecture
Routstr is built on a modular stack defined by the [Routstr Improvement Protocols (RIPs)](https://github.com/routstr/rips).
```mermaid
flowchart LR
subgraph Client
A[App / Agent]
end
subgraph Provider
B[Routstr Node<br/>Proxy + Auth + Billing]
end
subgraph Upstream
C[OpenAI / Anthropic<br/>vLLM / Ollama / ...]
end
A -- "Request +<br/>Cashu Token" --> B
B -- "Forward<br/>Request" --> C
C -- "Response +<br/>Usage" --> B
B -- "Response +<br/>Refund Token" --> A
```
## Why Routstr?
| Feature | Closed AI | Routstr |
| :--- | :--- | :--- |
| **Access** | Account, KYC, Credit Card | Permissionless, Bitcoin-native |
| **Privacy** | Full Logging & Tracking | Blinded Payments, Ephemeral Sessions |
| **Resilience** | Single Point of Failure | Decentralized Network |
| **Pricing** | Fixed, Monopolistic | Dynamic, Market-driven |
| **Global** | Geofenced | Borderless (Tor/I2P supported) |

View File

@@ -1,114 +0,0 @@
# Advanced Pricing
Advanced pricing strategies for fine-tuned control over your revenue model.
---
## Default Behavior
By default, Routstr:
1. **Fetches costs** from your upstream provider
2. **Applies markup** using your fee settings
3. **Converts to sats** using real-time BTC price
**Formula**: `Price = Upstream Cost × Exchange Fee × Upstream Fee`
---
## Strategy 1: Fixed Per-Request
Charge a flat fee regardless of model or tokens used.
**Configure in Dashboard****Settings****Pricing**:
- Enable **Fixed Pricing**
- Set **Fixed Cost Per Request** (in sats)
**Use cases**:
- Internal tools with predictable usage
- Simple "pay once, get response" APIs
- Subscription-like tiers
---
## Strategy 2: Fixed Per-Token
Override dynamic pricing with global per-token rates.
**Configure in Dashboard****Settings****Pricing**:
| Setting | Description |
|---------|-------------|
| **Fixed Per 1K Input** | Sats per 1,000 prompt tokens |
| **Fixed Per 1K Output** | Sats per 1,000 completion tokens |
When set to non-zero values, these override model-specific pricing for all models.
---
## Strategy 3: Per-Model Custom Pricing
Set specific prices for individual models, overriding both upstream cost and global fees.
**Configure in Dashboard****Models**:
1. Click on a model (e.g., `gpt-4`)
2. Enter **Prompt Price** and **Completion Price** (USD per 1M tokens)
3. Save
**Example**: OpenAI charges $30/1M for GPT-4. Set your price to $35/1M to lock in a margin regardless of fee settings.
---
## Minimum Charge
Prevent dust transactions and spam:
| Setting | Description | Default |
|---------|-------------|---------|
| **Min Request Cost** | Minimum charge in msats | 1000 (1 sat) |
If a request's calculated cost falls below this (e.g., very short prompts), the client pays the minimum.
---
## Combining Strategies
Strategies apply in order of specificity:
1. **Per-model override** (highest priority)
2. **Fixed per-token rates**
3. **Dynamic pricing with fees** (default)
4. **Fixed per-request** (overrides all above if enabled)
**Example setup**:
- Dynamic pricing as default (10% markup)
- GPT-4 locked at $35/1M (premium model)
- Claude Haiku at 5 sats/1K tokens (budget option)
- Minimum 1 sat per request
---
## Pricing for Profit
### High-Volume Strategy
Lower margins, more clients:
- Exchange Fee: 1.002 (0.2%)
- Upstream Fee: 1.05 (5%)
### Premium Strategy
Higher margins, fewer clients:
- Exchange Fee: 1.01 (1%)
- Upstream Fee: 1.25 (25%)
### Mixed Strategy
- Cheap models (GLM-4.7-Flash, Seed-1.6): Low margin to attract volume
- Premium models (GPT-5-Pro, Claude-Opus): High margin for profit

View File

@@ -1,158 +0,0 @@
# Configuration
Routstr is configured primarily through the **Admin Dashboard**. All settings persist in the database and take effect immediately—no restarts required.
For automated deployments, you can optionally pre-configure settings via environment variables.
---
## Initial Setup (.env file)
Before running your node, you should create a `.env` file in the project root. This file is used to bootstrap the initial configuration and store sensitive secrets.
### Example .env
```bash
ADMIN_PASSWORD=your-secure-password
# Node Identity
NAME="My AI Node"
DESCRIPTION="Fast access to models"
# Lightning Payouts
RECEIVE_LN_ADDRESS=yourname@wallet.com
```
### Setting the UI Password
There are two ways to set or change your Admin Dashboard password:
1. **Via Environment Variable**: Set `ADMIN_PASSWORD` in your `.env` file before starting the container. This will be the password used for the first login.
2. **Via Dashboard**: Once logged in, go to **Settings****Security** to update your password. Dashboard settings override the `.env` file once saved.
---
## Admin Dashboard (Primary)
Access the dashboard at `/admin/` on your node.
### Upstream Providers
Connect to your AI provider(s):
| Setting | Description |
| ---------------- | ------------------------------------------------ |
| **Upstream URL** | API endpoint (e.g., `https://api.openai.com/v1`) |
| **API Key** | Your provider's API key |
### Node Identity
How your node appears to clients:
| Setting | Description |
| --------------- | -------------------------------------- |
| **Name** | Display name (e.g., "Fast GPT-4 Node") |
| **Description** | Brief description of your service |
### Pricing
Control your profit margins:
| Setting | Description | Default |
| ----------------- | ------------------------------------------ | ------------ |
| **Fixed Pricing** | Charge flat rate per request vs. per-token | Off |
| **Exchange Fee** | Buffer for BTC volatility | 1.005 (0.5%) |
| **Upstream Fee** | Your profit markup | 1.10 (10%) |
See [Pricing](pricing.md) for detailed strategies.
### Cashu Mints
Which mints to accept payments from:
| Setting | Description |
| --------- | ------------------------------- |
| **Mints** | List of trusted Cashu mint URLs |
### Lightning Withdrawals
Automatic profit withdrawal:
| Setting | Description | Default |
| ------------------------------------ | ---------------------------------------------------------------------------------------------------------- | ------- |
| **Lightning Address** | Your LN address for withdrawals | — |
| **Minimum Payout (sat)** | Min available balance (in sats) before profit is paid out. Applies to both `sat` and `msat` mints (auto-converted). | `210` |
| **Payout Interval (seconds)** | How often the payout loop wakes up and checks balances | `900` |
All payout amounts must be positive. Set the minimums above your wallet's
minimum-invoice constraint (typically 1 sat) and high enough to amortise
routing fees.
### Security
| Setting | Description |
| ------------------ | ----------------------------- |
| **Admin Password** | Password for dashboard access |
### Nostr Discovery
Announce your node on the network:
| Setting | Description |
| ---------- | ------------------------------------ |
| **Npub** | Your Nostr public key |
| **Nsec** | Your Nostr private key (for signing) |
| **Relays** | Relays to publish announcements |
| **Share Analytics** | Publish aggregate usage stats to Nostr |
See [Discovery](discovery.md) for details.
---
## Environment Variables (Optional)
Use environment variables for:
- **Automated deployments** (CI/CD, infrastructure-as-code)
- **Secrets management** (external secret stores)
- **Initial bootstrap** (set once, manage via dashboard later)
### All Variables
| Variable | Description | Default |
| -------------------- | --------------------------------- | ------------------------------------ |
| `UPSTREAM_BASE_URL` | Upstream API endpoint | — |
| `UPSTREAM_API_KEY` | Upstream API key | — |
| `ADMIN_PASSWORD` | Dashboard password | (none) |
| `DATABASE_URL` | Database connection string | `sqlite+aiosqlite:///keys.db` |
| `NAME` | Node display name | `ARoutstrNode` |
| `DESCRIPTION` | Node description | `A Routstr Node` |
| `NPUB` | Nostr public key (bech32) | — |
| `NSEC` | Nostr private key | — |
| `ENABLE_ANALYTICS_SHARING` | Enable usage analytics sharing to Nostr | `true` |
| `CASHU_MINTS` | Comma-separated mint URLs | `https://mint.minibits.cash/Bitcoin` |
| `RECEIVE_LN_ADDRESS` | Lightning address for withdrawals | — |
| `MIN_PAYOUT_SAT` | Min payout balance in sats (applies to all mints) | `210` |
| `PAYOUT_INTERVAL_SECONDS` | Payout loop interval (seconds) | `900` |
| `TOR_PROXY_URL` | SOCKS5 proxy for Tor | `socks5://127.0.0.1:9050` |
| `CORS_ORIGINS` | Allowed CORS origins | `*` |
| `RELAYS` | Nostr relays (comma-separated) | (default set) |
### Priority
Environment variables are read on startup. Dashboard settings override them and persist in the database. Once you change a setting in the dashboard, the env var is ignored for that setting.
---
## Models
Manage which AI models you offer:
1. Go to **Models** in the dashboard
2. Models are auto-discovered from your upstream
3. For each model, you can:
- **Enable/Disable** — hide expensive models you don't want to serve
- **Override pricing** — set custom per-token rates
- **Create aliases** — friendly names for models
See [Pricing](pricing.md) for per-model pricing strategies.

View File

@@ -1,209 +0,0 @@
# Admin Dashboard
The Admin Dashboard is your command center for managing your Routstr provider node. Configure providers, monitor earnings, manage models, and withdraw profits—all from a web interface.
**URL**: `http://your-node:8000/admin/`
---
## Overview Tab
The main dashboard view shows your node's financial status at a glance.
### Wallet Summary
| Metric | Description |
|--------|-------------|
| **Total Wallet** | All Bitcoin currently held by your node |
| **User Balances** | Funds belonging to active client sessions |
| **Your Balance** | Your profit: `Total - User Balances` |
### Mint Status
Shows connected Cashu mints and their balances. Each mint displays:
- Connection status
- Balance in sats/msats
- Unit type
<!-- TODO: Screenshot of Overview tab -->
---
## Sessions Tab
View and manage active client sessions (API keys).
### Session List
| Column | Description |
|--------|-------------|
| **Hashed Key** | Privacy-preserving identifier (not the actual key) |
| **Balance** | Remaining funds in the session |
| **Spent** | Total amount spent by this session |
| **Requests** | Number of API calls made |
| **Created** | When the session was created |
| **Expires** | Auto-expiry time (if set) |
### Actions
- **View Details** — See full session history
- **Revoke** — Terminate a session (remaining balance returns to your wallet)
<!-- TODO: Screenshot of Sessions tab -->
---
## Models Tab
Manage which AI models you offer to clients.
### Model List
Shows all models available from your upstream provider(s):
| Column | Description |
|--------|-------------|
| **Model ID** | The model identifier (e.g., `gpt-4o`) |
| **Enabled** | Whether clients can use this model |
| **Input Price** | Cost per 1M input tokens (USD) |
| **Output Price** | Cost per 1M output tokens (USD) |
| **Custom** | Whether pricing is overridden |
### Actions
- **Import Models** — Fetch latest model list from upstream
- **Enable/Disable** — Toggle model availability
- **Edit Pricing** — Override default pricing for a model
- **Create Alias** — Map a friendly name to a model
### Editing a Model
Click on any model to configure:
| Field | Description |
|-------|-------------|
| **Enabled** | Show this model to clients |
| **Prompt Price** | Custom price per 1M input tokens (USD) |
| **Completion Price** | Custom price per 1M output tokens (USD) |
| **Alias** | Alternative name for this model |
<!-- TODO: Screenshot of Models tab -->
<!-- TODO: Screenshot of Model edit modal -->
---
## Settings Tab
Configure all node settings. Changes take effect immediately.
### Upstream
Connect to your AI provider:
| Field | Description |
|-------|-------------|
| **Base URL** | API endpoint (e.g., `https://api.openai.com/v1`) |
| **API Key** | Your provider's secret key |
<!-- TODO: Screenshot of Upstream settings -->
### Node Identity
| Field | Description |
|-------|-------------|
| **Name** | Public display name |
| **Description** | Brief description of your service |
| **Npub** | Nostr public key for discovery |
### Pricing
| Field | Description |
|-------|-------------|
| **Fixed Pricing** | Toggle flat-rate vs. per-token pricing |
| **Fixed Cost** | Sats per request (when fixed pricing enabled) |
| **Exchange Fee** | Multiplier for BTC volatility buffer |
| **Upstream Fee** | Your profit margin multiplier |
**Example**: With Exchange Fee `1.005` and Upstream Fee `1.10`:
- Upstream cost: $30/1M tokens
- Your price: $30 × 1.005 × 1.10 = $33.17/1M tokens
### Cashu Mints
Manage which mints you accept payments from:
- **Add Mint** — Enter a mint URL
- **Remove Mint** — Stop accepting from a mint
- **Test Connection** — Verify mint is reachable
<!-- TODO: Screenshot of Mints settings -->
### Lightning
| Field | Description |
|-------|-------------|
| **Lightning Address** | Your LN address for automatic withdrawals |
### Nostr Discovery
| Field | Description |
|-------|-------------|
| **Nsec** | Private key for signing announcements |
| **Relays** | Where to publish your node advertisement |
| **Share Analytics** | Toggle publishing aggregate usage stats to Nostr |
### Security
| Field | Description |
|-------|-------------|
| **Admin Password** | Password for dashboard access |
!!! warning "Set a Password"
The dashboard has no password by default. Always set one for production nodes.
<!-- TODO: Screenshot of Security settings -->
---
## Withdraw Tab
Withdraw your profits to a Lightning wallet.
### Steps
1. **Select Mint** — Choose which mint to withdraw from
2. **Enter Amount** — How many sats to withdraw
3. **Generate Token** — Creates a Cashu token
4. **Redeem** — Paste the token into your Cashu wallet and melt to Lightning
<!-- TODO: Screenshot of Withdraw tab -->
### Alternative: Lightning Address
If you've configured a Lightning Address in Settings, profits can be automatically swept to your wallet (coming soon).
---
## Logs Tab
View node logs for debugging without SSH access.
### Features
- **Filter by Level** — Error, Warning, Info, Debug
- **Search** — Find specific entries
- **Time Range** — View logs from specific periods
- **Auto-refresh** — Watch logs in real-time
### Common Log Entries
| Entry | Meaning |
|-------|---------|
| `Upstream request failed` | Problem connecting to your AI provider |
| `Invalid token` | Client sent an invalid Cashu token |
| `Session expired` | API key reached its time limit |
| `Insufficient balance` | Client ran out of funds mid-request |
<!-- TODO: Screenshot of Logs tab -->

View File

@@ -1,241 +0,0 @@
# Deployment
Production deployment guide for Routstr Provider nodes.
## All-in-One Docker Image (Preferred)
The easiest way to deploy Routstr is using the all-in-one Docker image from Docker Hub, which includes both the FastAPI backend and the Next.js admin dashboard in a single container.
### Quick Start
```bash
docker run -d \
--name routstr \
-p 8000:8000 \
-v routstr-data:/app/data \
-e DATABASE_URL="sqlite:////app/data/routstr.db" \
9qeklajc/routstr:latest
```
Access your node:
- **API & Admin Dashboard**: http://localhost:8000
### Docker Compose Setup
Create `docker-compose.yml`:
```yaml
version: '3.8'
services:
routstr:
image: 9qeklajc/routstr:latest
container_name: routstr
restart: unless-stopped
ports:
- "8000:8000"
volumes:
- routstr-data:/app/data
environment:
DATABASE_URL: "sqlite:////app/data/routstr.db"
ADMIN_KEY: "your-secure-admin-key"
LOG_LEVEL: "info"
volumes:
routstr-data:
```
Start it:
```bash
docker compose up -d
```
---
## Docker Compose (Recommended)
For production, use Docker Compose with persistent storage and optional Tor support.
Use the included `compose.yml` for a flexible setup that handles both the UI and the node execution. This is useful for development or when you want to manage Tor as a separate service.
```bash
docker compose up -d
```
This will:
1. **Build the UI**: Compiles the frontend and copies it to a shared volume.
2. **Start Routstr**: Runs the Python node, mounting the built UI.
3. **Start Tor**: Provides anonymous access via a `.onion` address.
---
## With Tor (Anonymous Access)
Add Tor to serve your node as a hidden service—no port forwarding needed.
```yaml
services:
routstr:
image: ghcr.io/routstr/proxy:latest
container_name: routstr
restart: unless-stopped
ports:
- "8000:8000"
volumes:
- ./data:/app/data
- ./logs:/app/logs
environment:
- TOR_PROXY_URL=socks5://tor:9050
depends_on:
- tor
tor:
image: ghcr.io/hundehausen/tor-hidden-service:latest
container_name: tor
restart: unless-stopped
volumes:
- ./tor-data:/var/lib/tor
environment:
- HS_ROUTER=routstr:8000:80
```
After starting, find your `.onion` address:
```bash
docker exec tor cat /var/lib/tor/hidden_service/hostname
```
See [Tor Support](tor.md) for details.
---
## Pre-Configuration (Optional)
While everything can be configured via the dashboard, you can pre-configure settings with environment variables for automated deployments.
### Using Environment Variables
```yaml
services:
routstr:
image: ghcr.io/routstr/proxy:latest
environment:
# Pre-configure upstream (optional)
- UPSTREAM_BASE_URL=https://api.openai.com/v1
- UPSTREAM_API_KEY=sk-proj-...
# Secure the dashboard (recommended)
- ADMIN_PASSWORD=your-secure-password
# Node identity
- NAME=My Provider Node
- DESCRIPTION=Fast GPT-4 access via Lightning
# Lightning withdrawals
- RECEIVE_LN_ADDRESS=me@walletofsatoshi.com
volumes:
- ./data:/app/data
```
### Using an .env File
```yaml
services:
routstr:
image: ghcr.io/routstr/proxy:latest
env_file:
- .env
volumes:
- ./data:/app/data
```
Example `.env`:
```bash
UPSTREAM_BASE_URL=https://api.openai.com/v1
UPSTREAM_API_KEY=sk-proj-...
ADMIN_PASSWORD=change-me
NAME=My Provider Node
RECEIVE_LN_ADDRESS=me@walletofsatoshi.com
```
See [Configuration](configuration.md) for all available options.
---
## Persistence
Routstr stores all data in `/app/data`:
| Path | Contents |
|------|----------|
| `keys.db` | SQLite database (settings, API keys, sessions) |
| `.wallet/` | Cashu wallet data (your Bitcoin!) |
!!! warning "Back Up Your Data"
The `./data` volume contains your wallet. Losing it means losing funds. Back up regularly.
---
## Reverse Proxy (Optional)
For custom domains and SSL, use a reverse proxy like Caddy or nginx.
### Caddy Example
```
api.yournode.com {
reverse_proxy localhost:8000
}
```
### nginx Example
```nginx
server {
listen 443 ssl;
server_name api.yournode.com;
ssl_certificate /path/to/cert.pem;
ssl_certificate_key /path/to/key.pem;
location / {
proxy_pass http://localhost:8000;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
}
}
```
---
## Updates
Pull the latest image and restart:
```bash
docker compose pull
docker compose up -d
```
---
## Building from Source
### Using Docker Compose
The easiest way to build everything from source:
```bash
docker compose build
```
### Individual Components
If you prefer building the node only (requires manual UI build first):
```bash
docker build -t routstr-node .
```

View File

@@ -1,95 +0,0 @@
# Discovery
Routstr uses **Nostr** as a decentralized directory for service discovery. Your node announces its presence, models, and pricing on Nostr relays, allowing clients to find you without a central server.
---
## How It Works
1. **Provider Advertisement (Kind 38421)**: Your node periodically publishes an event with its URL, models, and pricing
2. **Client Discovery**: Clients query relays for these events to find suitable providers
---
## Configuration
Configure discovery in **Dashboard****Settings****Nostr**.
### Required Settings
| Field | Description |
|-------|-------------|
| **Npub** | Your node's public identity (clients use this to verify your node) |
| **Nsec** | Your node's private key (used to sign advertisements) |
| **Relays** | Where to publish your announcements |
### Default Relays
If not configured, Routstr publishes to:
- `wss://relay.damus.io`
- `wss://relay.nostr.band`
- `wss://nos.lol`
---
## Advertisement Format
Your node publishes events like:
```json
{
"kind": 38421,
"content": {
"name": "My Routstr Node",
"description": "Fast GPT-4 access via Lightning",
"endpoints": {
"http": "https://api.mynode.com",
"onion": "http://xyz...onion"
},
"models": ["gpt-4", "claude-3-opus"],
"pricing": { ... }
},
"tags": [
["d", "routstr-provider"],
["g", "US"]
]
}
```
---
## Tor Integration
If you're running with Tor (see [Tor Support](tor.md)), your `.onion` address is automatically included in announcements. This allows clients to connect anonymously.
---
## Verify Your Announcements
Check if your node is broadcasting:
1. Copy your `Npub`
2. Search on [Nostr.band](https://nostr.band) or [Primal](https://primal.net)
3. Look for Kind 38421 events
---
## Generating Keys
If you don't have a Nostr identity:
1. Use any Nostr client (e.g., [Primal](https://primal.net), [Damus](https://damus.io))
2. Create an account
3. Export your keys (npub and nsec)
4. Enter them in the dashboard
Or generate keys programmatically:
```python
from nostr_sdk import Keys
keys = Keys.generate()
print(f"npub: {keys.public_key().to_bech32()}")
print(f"nsec: {keys.secret_key().to_bech32()}")
```

View File

@@ -1,91 +0,0 @@
# Pricing
Routstr's pricing engine lets you act as a retailer of AI compute. You pay upstream providers (OpenAI, Anthropic, etc.) at their rates and sell to clients with your markup.
---
## Pricing Strategies
Configure these in **Dashboard****Settings****Pricing**.
### Dynamic Pricing (Default)
Passes through upstream costs plus your percentage markup.
**Formula**: `Client Price = Upstream Cost × Exchange Fee × Upstream Fee`
| Setting | Description | Default |
|---------|-------------|---------|
| **Exchange Fee** | Buffer for BTC price volatility | 1.005 (0.5%) |
| **Upstream Fee** | Your profit margin | 1.10 (10%) |
**Example**: GPT-4 costs $30/1M tokens from OpenAI. With default settings:
- Price: $30 × 1.005 × 1.10 = $33.17/1M tokens
- At $60k BTC: ~55,000 sats/1M tokens
### Fixed Pricing
Charge a flat rate per request, regardless of model or token count.
| Setting | Description |
|---------|-------------|
| **Fixed Pricing** | Enable flat-rate mode |
| **Fixed Cost** | Sats per request |
**Best for**: Simple proxies, internal tools, or subscription-like access.
---
## Per-Model Pricing
Override pricing for specific models in **Dashboard****Models**.
1. Click on a model
2. Enter custom **Prompt Price** and **Completion Price** (USD per 1M tokens)
3. Save
This overrides both the upstream cost and your global markup for that model.
**Example**: Lock GPT-4 at $35/1M tokens regardless of OpenAI's actual rate or your fee settings.
---
## Token-Based Overrides
Set global fixed rates per token (overrides dynamic pricing for all models):
| Setting | Description |
|---------|-------------|
| **Fixed Per 1K Input** | Sats per 1,000 prompt tokens |
| **Fixed Per 1K Output** | Sats per 1,000 completion tokens |
---
## Minimum Charge
Prevent spam with a minimum cost per request:
| Setting | Description | Default |
|---------|-------------|---------|
| **Min Request Cost** | Minimum charge in msats | 1000 (1 sat) |
If a request's calculated cost is lower than this, the client pays the minimum instead.
---
## Cost Tracking
Routstr tracks balances in **millisats (msats)** for precision with cheap models.
- 1 sat = 1,000 msats
- API responses include cost in msats
- Lightning withdrawals round down to whole sats
### Client Verification (RIP-05)
Clients can verify charges:
1. Fetch `/v1/models` for your advertised rates
2. Calculate expected cost from token counts
3. Compare to `x-routstr-cost` response header

View File

@@ -1,124 +0,0 @@
# Quick Start
Start earning Bitcoin by selling AI access in under 5 minutes.
## What You'll Build
A **Routstr Provider Node** acts as a gateway that:
1. **Connects** to upstream AI providers (OpenAI, Anthropic, OpenRouter, etc.)
2. **Accepts** Bitcoin payments via Cashu eCash
3. **Serves** AI requests to clients on the network
You bring the API keys, Routstr handles the billing, payments, and client management.
!!! tip "Future: Node-to-Node Routing"
In future versions, you'll be able to run a node that connects to other Routstr nodes—eliminating the need to configure upstream providers yourself. For now, you'll need your own API credentials.
---
## Prerequisites
- [Docker](https://docs.docker.com/get-docker/) installed
- API credentials from at least one AI provider (OpenAI, Anthropic, OpenRouter, etc.)
---
## 1. Prepare Configuration
Create a `.env` file in the root of the project to store your secrets:
```bash
# Initial Admin Password
ADMIN_PASSWORD=mysecretpassword
# Node Identity
NAME="My AI Node"
DESCRIPTION="Fast access to models"
NSEC=yournsec
# Lightning Payouts
RECEIVE_LN_ADDRESS=yourname@wallet.com
```
## 2. Start the Node
The recommended way to run Routstr is using Docker Compose, which handles the node, the UI, and optional services like Tor.
```bash
docker compose up -d
```
Verify it's running:
```bash
curl http://localhost:8000/v1/info
```
### Build from Source (Optional)
If you've cloned the repository and want to build the images yourself:
```bash
docker compose build
docker compose up -d
```
---
## 3. Configure via Dashboard
Open the **Admin Dashboard** at [http://localhost:8000/admin/](http://localhost:8000/admin/).
!!! note "Login"
Use the `ADMIN_PASSWORD` you defined in your `.env` file to log in. If you didn't set one, the dashboard will prompt you to set one on first visit.
### Connect Your AI Providers
1. Navigate to **Settings****Upstream**
2. Enter your upstream URL (e.g., `https://api.openai.com/v1`)
3. Enter your API key
4. Save
### Set Your Profit Margin
1. Go to **Settings****Pricing**
2. Configure your markup (default is 10%)
3. Optionally set a fixed price per request instead
### Secure the Dashboard
1. Go to **Settings****Admin**
2. Set a strong password
3. Save and re-login
---
## 3. Start Earning
Once configured, your node is live. Clients pay you in Bitcoin (via Cashu tokens) for every AI request.
### Monitor Your Earnings
The dashboard shows:
- **Total Wallet**: All Bitcoin held by your node
- **User Balances**: Funds belonging to active client sessions
- **Your Balance**: Your profit (`Total - User Balances`)
### Withdraw Profits
1. Go to **Withdraw** in the dashboard
2. Select amount and mint
3. Generate a Cashu token
4. Redeem to your Lightning wallet
---
## Next Steps
- **[Deployment](deployment.md)**: Production setup with Docker Compose and Tor
- **[Dashboard Guide](dashboard.md)**: Full reference for all dashboard features
- **[Pricing](pricing.md)**: Configure pricing strategies and per-model overrides
- **[Discovery](discovery.md)**: Announce your node on Nostr for clients to find you

View File

@@ -1,50 +0,0 @@
# Tor Support
Running Routstr as a **Tor Hidden Service** allows you to offer API access anonymously and bypass NAT/firewalls without port forwarding.
## Automatic Setup (Docker)
The standard `compose.yml` includes a Tor container pre-configured to serve your node.
1. **Start the stack**: `docker compose up -d`
2. **Wait**: Tor takes about 30 seconds to generate keys and bootstrap.
3. **Find your address**:
```bash
docker exec tor cat /var/lib/tor/hidden_service/hostname
```
Output: `v2xyz...longaddress.onion`
Routstr will automatically detect this address (via the `discover_onion_url_from_tor` logic) and include it in:
- The `/v1/info` endpoint.
- Nostr announcements (RIP-02).
## Manual Setup
If you are running outside Docker or managing Tor yourself:
1. **Install Tor**: `sudo apt install tor`
2. **Edit `torrc`**:
```
HiddenServiceDir /var/lib/tor/routstr/
HiddenServicePort 80 127.0.0.1:8000
```
3. **Restart Tor**: `sudo systemctl restart tor`
4. **Get Address**: `sudo cat /var/lib/tor/routstr/hostname`
5. **Configure Routstr**:
Set `ONION_URL=http://youraddress.onion` in your `.env` file so the node knows its own address.
## Client Usage
Clients connecting to your `.onion` address must route traffic through SOCKS5.
**Python Example:**
```python
import httpx
from openai import OpenAI
client = OpenAI(
base_url="http://youraddress.onion/v1",
api_key="sk-...",
http_client=httpx.Client(proxy="socks5://127.0.0.1:9050")
)
```

View File

@@ -1,493 +0,0 @@
# Tinfoil / PPQ Private-Mode Integration Notes
This document summarizes the current options for integrating Tinfoil/PPQ private models with Routstr, based on the EHBP work in this branch and local testing against `ppq-private-mode-proxy`.
## Background
PPQ private models run behind a Tinfoil/EHBP flow:
- Request bodies are HPKE-encrypted by a Tinfoil client.
- The PPQ `/private/` endpoint routes ciphertext to the attested enclave.
- The enclave decrypts, runs inference, and returns an encrypted response.
- The caller's Tinfoil client decrypts the response locally.
The PPQ private-mode proxy (`~/projects/ppq-private-mode-proxy`) uses this pattern with the JavaScript `tinfoil` SDK:
```ts
import { SecureClient } from "tinfoil";
const apiBase = "https://api.ppq.ai";
const client = new SecureClient({
baseURL: `${apiBase}/private/`,
attestationBundleURL: `${apiBase}/private`,
transport: "ehbp",
});
await client.ready();
const response = await client.fetch(`${apiBase}/private/v1/chat/completions`, {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${process.env.PPQ_API_KEY}`,
"X-Private-Model": "private/gpt-oss-120b",
"x-query-source": "api",
},
body: JSON.stringify({
model: "gpt-oss-120b", // enclave-internal model id
messages: [{ role: "user", content: "Hello" }],
}),
});
const json = await response.json();
console.log(json.usage);
```
`X-Private-Model` carries the PPQ-facing private model id, while the encrypted JSON body uses the enclave-internal model id without the `private/` prefix.
## PPQ private model pricing
PPQ exposes private model pricing through:
```text
GET https://api.ppq.ai/v1/models?type=all
```
Filter models whose IDs start with `private/`.
Example private pricing observed:
| Model | Input USD / 1M tokens | Output USD / 1M tokens |
|---|---:|---:|
| `private/gpt-oss-120b` | `0.79125` | `1.31875` |
| `private/llama3-3-70b` | `1.84625` | `2.90125` |
| `private/qwen3-vl-30b` | `1.31875` | `4.22` |
| `private/glm-5-2` | `1.5825` | `5.53875` |
| `private/gemma4-31b` | `0.47475` | `1.055` |
| `private/kimi-k2-6` | `1.5825` | `5.53875` |
The `ppq-private-mode-proxy` commit `ba984214793d3bca0f7d046b6955d42abc1c6843` changed OpenClaw display metadata to align with a 5% API margin. The live PPQ model endpoint returns the more precise rates above, which already include that margin.
Actual PPQ private billing is:
```text
price_usd =
input_tokens * input_per_1M_tokens / 1_000_000
+ output_tokens * output_per_1M_tokens / 1_000_000
```
A test request to `private/gpt-oss-120b` produced:
```json
{
"input_count": 74,
"output_count": 3,
"price_in_usd": 0.00006250875
}
```
which exactly matches:
```text
74 * 0.79125 / 1_000_000 + 3 * 1.31875 / 1_000_000
= 0.00006250875 USD
```
## Integration architectures
There are three materially different ways Routstr could integrate Tinfoil/PPQ private inference.
## Option A: User integrates Tinfoil directly
```text
User app / SDK
-> Tinfoil SecureClient / TinfoilAI
-> EHBP-encrypted request
-> Tinfoil/PPQ private enclave
```
Properties:
- Best privacy for the user.
- Routstr is not in the request path.
- User's client encrypts requests and decrypts responses.
- Usage is visible to the user's app after decryption.
- Billing is handled directly by Tinfoil/PPQ.
Example with Tinfoil's OpenAI-compatible client:
```ts
import { TinfoilAI } from "tinfoil";
const client = new TinfoilAI({
apiKey: process.env.TINFOIL_API_KEY,
transport: "ehbp",
});
const res = await client.chat.completions.create({
model: "llama3-3-70b",
messages: [{ role: "user", content: "Hello" }],
});
console.log(res.choices[0].message.content);
console.log(res.usage);
```
This is not a Routstr marketplace flow unless Routstr only acts as discovery/UI around direct Tinfoil/PPQ usage.
## Option B: Routstr integrates Tinfoil as an upstream client
```text
User -> Routstr plaintext request
-> Routstr Tinfoil SecureClient encrypts to PPQ/Tinfoil
-> PPQ private enclave
-> Routstr receives decrypted response
-> Routstr bills from decrypted usage
-> Routstr returns plaintext response to user
```
Properties:
- Easier exact billing.
- Routstr can read the decrypted OpenAI response and `usage` object.
- Routstr can charge exact PPQ token pricing.
- Privacy is different: the user sends plaintext to Routstr, and Routstr sees prompts/responses.
- End-to-end encryption is only Routstr-to-enclave, not user-to-enclave.
This should be considered a separate product/provider mode, not the same as an end-to-end private relay.
Practical implementation options:
1. Run a Node sidecar that uses the `tinfoil` npm package and expose it as a local HTTP upstream to Routstr.
2. Port EHBP client behavior to Python.
3. Reuse or adapt `ppq-private-mode-proxy` as a local upstream.
A Node sidecar is probably the quickest implementation path because `ppq-private-mode-proxy` already demonstrates the full flow.
## Option C: Routstr uses Tinfoil as a direct blind upstream
This is the current branch's design intent and is likely the best fit if Tinfoil/PPQ exposes usage metadata headers:
```text
User Tinfoil SecureClient
-> encrypted request body
-> Routstr proxy
-> Tinfoil/PPQ private API
with X-Tinfoil-Request-Usage-Metrics: true
-> PPQ private enclave
<- encrypted response
plus X-Tinfoil-Usage-Metrics / cost headers
<- Routstr proxy
-> user decrypts response
```
In this mode Routstr is still a normal upstream proxy from the user's point of view, but the upstream is Tinfoil/PPQ private inference and the body remains opaque to Routstr.
Properties:
- Strongest privacy with Routstr in the path.
- Routstr never sees plaintext prompt or plaintext response.
- Routstr can authenticate and route based on plaintext headers.
- Routstr should request Tinfoil usage metadata by adding `X-Tinfoil-Request-Usage-Metrics: true` to the upstream request.
- Tinfoil documents `X-Tinfoil-Usage-Metrics` as an upstream response header for non-streaming requests.
- For streaming requests, Tinfoil documents `X-Tinfoil-Usage-Metrics` as an HTTP trailer available only after the response body completes.
- If Tinfoil/PPQ returns `X-Tinfoil-Usage-Metrics` or a cost header on the encrypted response, Routstr can bill exactly without decrypting the body.
- If usage is only present inside the encrypted response body, Routstr still cannot read it and exact billing is not possible without a separate metadata path.
This is the only architecture that preserves end-to-end encryption from the user to the PPQ/Tinfoil enclave while still letting Routstr mediate payment. The key requirement is that usage/cost metadata must be returned outside the encrypted body, ideally as a response header available before body streaming begins.
## Current Routstr problem
The current EHBP implementation charges successful EHBP requests at `max_cost_for_model` because Routstr cannot decrypt the response body:
```text
successful EHBP request -> charge full reserved max cost
```
That is incorrect for PPQ private models. Max cost should be only a reservation/solvency ceiling. Final charge should use actual PPQ private token pricing.
Desired behavior:
```text
reserve max cost
forward encrypted request
obtain actual usage/cost metadata
finalize actual cost
refund/release the difference
```
## Usage/cost metadata requirement
For blind-relay exact billing, PPQ should return one of the following outside the encrypted response body:
```http
X-PPQ-Cost-USD: 0.00006250875
```
or:
```http
X-Private-Usage-Metrics: input=74,output=3
```
or:
```http
X-Tinfoil-Usage-Metrics: prompt=74,completion=3,total=77
```
Tinfoil proxy documentation references a usage-metrics flow where a proxy can request usage via:
```http
X-Tinfoil-Request-Usage-Metrics: true
```
and read usage from:
```http
X-Tinfoil-Usage-Metrics
```
Docs/example references:
- https://docs.tinfoil.sh/guides/proxy-server
- https://github.com/tinfoilsh/encrypted-request-proxy-example
During local PPQ testing, PPQ responses included this CORS exposure header:
```http
Access-Control-Expose-Headers: Ehbp-Response-Nonce, X-Private-Usage-Metrics, X-Encrypted-Usage-Metrics, X-Tinfoil-Usage-Metrics
```
However, the actual tested non-streaming response did not include any of these usage headers, even when `X-Tinfoil-Request-Usage-Metrics: true` was sent.
The decrypted body did include normal OpenAI usage, but only the decrypting Tinfoil client can see that body.
## Query-history fallback
PPQ's query history endpoint exposes actual usage and cost:
```text
GET https://api.ppq.ai/queries/history?page=1&page_count=...
```
A record includes:
```json
{
"timestamp": "...",
"model": "private/gpt-oss-120b",
"input_count": 74,
"output_count": 3,
"price_in_usd": 0.00006250875,
"query_type": "chat_completion",
"query_source": "api"
}
```
This could be used as a fallback, but it is less robust than response headers/trailers because matching a request to a history row can be race-prone under concurrency. It would need a reliable request identifier or metadata field that PPQ stores in history.
## Recommended Routstr direction
Use Tinfoil/PPQ as a direct blind upstream and have Routstr explicitly request usage metadata:
```text
User encrypts body
Routstr reserves max cost
Routstr forwards encrypted body to Tinfoil/PPQ /private/
Routstr includes X-Tinfoil-Request-Usage-Metrics: true
Tinfoil/PPQ returns X-Tinfoil-Usage-Metrics as a response header for non-streaming,
or as an HTTP trailer after the body completes for streaming
Routstr finalizes exact charge
User decrypts encrypted response
```
This preserves both:
- privacy: Routstr cannot read prompts/responses;
- exact billing: Routstr can charge actual PPQ private model cost, assuming Tinfoil/PPQ returns usage/cost metadata outside the encrypted body.
Implementation steps:
1. Update PPQ model fetching to include private models:
```text
GET https://api.ppq.ai/v1/models?type=all
```
2. Register `private/*` models and any Routstr-facing aliases with correct `forwarded_model_id`.
3. Keep max-cost reservation for bearer keys and X-Cashu solvency checks.
4. Add parsing support for possible usage/cost headers:
```http
X-PPQ-Cost-USD
X-Private-Usage-Metrics
X-Tinfoil-Usage-Metrics
X-Encrypted-Usage-Metrics
```
5. Finalize by actual cost instead of max cost:
```text
actual_msats = ceil((actual_usd / sats_usd_price()) * 1000)
actual_msats = max(actual_msats, settings.min_request_msat)
actual_msats = min(actual_msats, reserved_msats)
```
or, if only token counts are available:
```text
actual_usd =
input_tokens * input_per_1M_tokens / 1_000_000
+ output_tokens * output_per_1M_tokens / 1_000_000
```
6. If usage/cost metadata is missing, choose an explicit policy:
- fail closed and refund/revert;
- query PPQ history as a fallback;
- fallback to max-cost billing only if explicitly configured and clearly disclosed.
Silent max-cost billing should not be the default for PPQ private requests.
## X-Cashu consideration
For bearer-auth requests, finalization can happen after the response stream completes if usage is delivered as a trailer.
For `X-Cashu`, Routstr needs to return the refund token in the response headers. If usage/cost is only available after consuming the encrypted response stream, Routstr may need to buffer EHBP responses before sending them to the client so it can compute the refund amount first.
Possible approaches:
1. Prefer a non-trailer response header with actual cost, available before streaming body starts.
2. Buffer EHBP X-Cashu responses and then return `X-Cashu` refund.
3. Introduce a later/refund-claim mechanism, which would be a larger protocol change.
## Summary
- PPQ private models are billed per actual input/output tokens.
- Private model rates are available from `GET /v1/models?type=all`.
- Current Routstr EHBP billing at max cost is wrong for PPQ private models.
- Direct Tinfoil integration inside Routstr would enable exact usage billing but would make Routstr see plaintext.
- A blind EHBP relay preserves privacy but requires PPQ/Tinfoil to expose usage/cost in plaintext headers/trailers.
- The preferred solution is to keep Routstr blind and have PPQ return billing metadata outside the encrypted body.
## Implementation status
Direct Tinfoil upstream integration is implemented in `routstr/upstream/tinfoil.py`
and `routstr/upstream/ehbp.py`.
### What was built
- `TinfoilUpstreamProvider` (`provider_type = "tinfoil"`):
- Base URL: `https://inference.tinfoil.sh`
- Fetches models from the public `GET /v1/models` endpoint (no auth needed).
- Parses Tinfoil's pricing (`inputTokenPricePer1M`, `outputTokenPricePer1M`,
`requestPrice`) into the standard `Model`/`Pricing` schema.
- `supports_ehbp = True` — acts as a blind EHBP relay.
- `get_ehbp_forwarding_target()` returns a target that includes
`X-Tinfoil-Request-Usage-Metrics: true`.
- `forward_get_request()` proxies `/attestation` to `https://atc.tinfoil.sh/attestation`
so the SDK can fetch attestation bundles through Routstr.
- Registered in `routstr/upstream/__init__.py` and seeded from
`TINFOIL_API_KEY` env var.
- `routstr/upstream/ehbp.py`:
- `parse_tinfoil_usage_metrics()` parses
`prompt=N,completion=N[,total=N][,model=<name>]` into an OpenAI-style
usage dict. The `model` field (added in tinfoilsh/confidential-model-router
PR #385) is extracted as a string.
- `_resolve_ehbp_target_url()` overrides the forwarding URL with
`X-Tinfoil-Enclave-Url` when the SDK sends it.
- `_strip_proxy_headers()` removes `X-Routstr-Model`,
`X-Tinfoil-Enclave-Url`, and `X-Tinfoil-Request-Usage-Metrics` before
forwarding to the enclave.
- `_compute_ehbp_actual_cost()` converts the usage header into msats via
`calculate_cost()`, clamped to `[min_request_msat, max_cost_for_model]`.
When the header's `model=<name>` differs from the requested model, the
actual served model's pricing is used for cost calculation.
- `forward_ehbp_request()` (bearer auth): if `X-Tinfoil-Usage-Metrics` is
present in the response header, finalizes with `adjust_payment_for_tokens()`
for exact billing; otherwise falls back to max-cost. Billing uses the
actual served model when it differs from the requested one.
- `forward_ehbp_x_cashu_request()`: if usage is available, computes the
refund from actual cost instead of max cost, using the actual served
model's pricing when applicable.
- `routstr/proxy.py`: `/attestation` and `/tee/attestation` paths are forwarded
to Tinfoil upstreams without model/cost/auth lookups.
### Billing behavior
| Request shape | Usage source | Billing |
|---|---|---|
| Bearer, non-streaming | `X-Tinfoil-Usage-Metrics` response header | Exact token cost via `adjust_payment_for_tokens` |
| Bearer, streaming | `X-Tinfoil-Usage-Metrics` HTTP trailer | Exact token cost (h11 captures trailers) |
| Bearer, no usage header/trailer | N/A | Max-cost fallback |
| X-Cashu, non-streaming | `X-Tinfoil-Usage-Metrics` response header | Refund = `redeemed - actual_cost` |
| X-Cashu, streaming | `X-Tinfoil-Usage-Metrics` HTTP trailer | Refund = `redeemed - actual_cost` (h11 captures trailers) |
| X-Cashu, no usage header/trailer | N/A | Refund = `redeemed - max_cost` |
### Cost response headers
Since EHBP response bodies are opaque encrypted blobs, per-request cost cannot
be injected into the JSON body (as done in the normal proxy flow). Instead,
Routstr returns cost info as response headers:
| Header | Auth | Description |
|---|---|---|
| `X-Routstr-Cost-Msats` | Bearer, X-Cashu | Total msats charged for this request |
| `X-Routstr-Cost-Usd` | Bearer | USD equivalent of the charge |
| `X-Routstr-Input-Cost-Msats` | Bearer, X-Cashu | msats attributed to input tokens |
| `X-Routstr-Output-Cost-Msats` | Bearer, X-Cashu | msats attributed to output tokens |
The client/Tinfoil SDK can read these headers from the HTTP response without
needing to decrypt the body.
### Setup
```bash
TINFOIL_API_KEY=your-tinfoil-api-key
```
The provider is auto-seeded on first startup.
### Usage metrics header format
Tinfoil returns usage metrics in the `X-Tinfoil-Usage-Metrics` response header
(non-streaming) or HTTP trailer (streaming) when `X-Tinfoil-Request-Usage-Metrics:
true` is sent. As of tinfoilsh/confidential-model-router PR #385, the format is:
```
prompt=<prompt_tokens>,completion=<completion_tokens>,total=<total_tokens>,model=<served_model>
```
The `model` field carries the actual model name served by the enclave.
Routstr uses this to:
- Verify the served model matches the expected upstream model. The comparison
uses ``model_obj.forwarded_model_id`` (the actual upstream ID, e.g.
``glm-5-2``) rather than ``model_obj.id`` (the client-facing alias, e.g.
``tinfoil-glm-5-2``), so aliased models don't trigger a spurious mismatch.
- When they genuinely differ (Tinfoil served a different upstream model than
expected), look up the actual served model's pricing and use it for billing.
The reverse lookup uses ``get_model_instance``, which resolves
``forwarded_model_id`` values registered as routable aliases.
- Log the discrepancy for observability.
If the actual model is not found in Routstr's model registry, billing falls
back to the requested model's pricing.
### What still needs verification
- ~~End-to-end test with a real Tinfoil SDK client against a Routstr node with
`TINFOIL_API_KEY` set.~~ Verified: both non-streaming (header) and streaming
(trailer) responses include `model=<name>`.
- Streaming trailer capture is implemented by buffering the encrypted response
in `forward_with_trailer()` and then using the dedicated EHBP payment
finalizers for bearer and X-Cashu requests. This provides actual-cost billing
today, at the cost of full time-to-last-byte latency for streaming responses.
- Whether Tinfoil's `/v1/responses` endpoint also returns usage metrics
headers or trailers.

View File

@@ -0,0 +1,216 @@
# Admin Dashboard
The Routstr admin dashboard is a modern web interface for managing your node, monitoring wallet balances, configuring AI models and providers, and handling Bitcoin Lightning payments through Cashu eCash.
## Accessing the Dashboard
### Authentication
The dashboard is protected by password authentication:
1. Navigate to `/admin/` in your browser
2. Enter the admin password
3. Optional: Configure custom base URL if not pre-configured
4. Click "Login"
The interface supports both environment-configured URLs and manual URL entry for deployment flexibility.
## Dashboard Overview
The main dashboard consists of four primary sections accessible through a collapsible sidebar:
- **Dashboard** - Wallet balance monitoring and fund management
- **Models** - AI model management and testing
- **Providers** - Upstream provider configuration
- **Settings** - Node configuration and admin preferences
### Navigation
## Dashboard Page
### Wallet Balance Management
#### Balance Display Options
Switch between display units using the toggle buttons:
- **msat** - Millisatoshis (highest precision)
- **sat** - Satoshis (standard Bitcoin unit)
- **usd** - US Dollar equivalent (when exchange rate available)
#### Balance Overview
The dashboard displays three key metrics:
- **Your Balance (Total)** - Available funds for node operator
- **Total Wallet** - Combined balance across all Cashu mints
- **User Balance** - Funds held for API key holders
#### Detailed Balance Breakdown
View balances by mint with the following information:
| Column | Description |
| ----------- | ------------------------------------- |
| Mint / Unit | Cashu mint URL and currency unit |
| Wallet | Total funds in this mint |
| Users | Funds belonging to API key holders |
| Owner | Your available funds (Wallet - Users) |
### Temporary Balances
Monitor API key activity with:
- **Summary Cards** - Total balance, total spent, total requests
- **Search Functionality** - Filter by key hash or refund address
- **Detailed Table** - Individual key balances with expiry times
- **Auto-refresh** - Updates every 60 seconds
### Fund Management
#### Withdrawing Funds
To withdraw your available balance:
1. Click the **Withdraw** button
2. Select which mint to withdraw from
3. Specify the amount (or withdraw full balance)
4. Click **Generate Token**
5. Copy the generated eCash token
6. Import the token into your Cashu wallet
#### Real-time Updates
- Balances refresh automatically every 30 seconds
- Manual refresh option available
- Live Bitcoin/USD exchange rate integration
- Error handling for mint connectivity issues
## Models Management Page
### Model Organization
Models are organized by provider groups with tabs:
- **All Models** - Combined view of all available models
- **Provider-specific tabs** - Individual providers (OpenRouter, Azure, etc.)
- Badge indicators showing active/total model counts
### Model Management Features
#### Individual Model Operations
For each model you can:
- **Toggle Enable/Disable** - Control model availability
- **View Details** - Context length, pricing, description
- **Edit Configuration** - Model-specific settings
- **Status Indicators** - Green badges for enabled, gray for disabled
#### Bulk Operations
- **Select All/Deselect All** - Quick selection controls
- **Bulk Enable/Disable** - Mass model management
- **Bulk Delete** - Remove model overrides
- **Provider-level Actions** - Apply settings to all models in a provider
#### Model Information Display
- **Model Types** - Text, embedding, image, audio, multimodal indicators
- **Pricing Information** - Per-million-token costs for input/output
- **Context Length** - Maximum tokens supported
- **API Key Status** - Whether credentials are configured
- **Free Model Indicators** - No-cost models clearly marked
## Providers Management Page
### Upstream Provider Configuration
Manage AI provider connections and credentials:
#### Provider Types Supported
- **OpenRouter** - Multi-model aggregator
- **Azure OpenAI** - Microsoft's OpenAI service
- **OpenAI** - Direct OpenAI integration
- **Custom Providers** - Any OpenAI-compatible API
#### Adding New Providers
1. Click **Add Provider**
2. Select **Provider Type** from dropdown
3. Enter **Base URL** (auto-populated for known providers)
4. Add **API Key** for authentication
5. Set **API Version** (required for Azure)
6. Toggle **Enabled** status
7. Click **Create**
#### Provider Management
**Provider Cards Display:**
- Provider type and status (Enabled/Disabled)
- Base URL configuration
- Action buttons (Models, Edit, Delete)
**Available Actions:**
- **Edit** - Modify provider configuration
- **Delete** - Remove provider (with confirmation)
- **View Models** - Expand model discovery interface
- **Enable/Disable** - Toggle provider availability
#### Model Discovery
Each provider shows two types of models:
**Provided Models Tab:**
- Auto-discovered from provider's catalog
- Read-only model information
- Real-time availability updates
**Custom Models Tab:**
- Manually configured model overrides
- Extend or override provider catalog
- Individual enable/disable controls
## Settings Page
### Node Configuration
Configure core node settings and preferences:
#### Basic Information
- **Node Name** - Identifier for your node
- **Node Description** - Descriptive text for your service
- **HTTP URL** - Public HTTP endpoint
- **Onion URL** - Tor hidden service address
#### Nostr Integration
- **Public Key (npub)** - Your Nostr public identity
- **Private Key (nsec)** - Nostr private key with show/hide toggle
- **Nostr Relays** - Configure relays for provider announcements
#### Cashu Mint Management
- **Add Mint URLs** - Configure multiple Cashu mint endpoints
- **Remove Mints** - Delete unused mint configurations
- **Mint Validation** - Verify mint endpoint connectivity
#### Settings Features
- **Real-time Save** - Changes apply immediately
- **Validation** - Form validation with error feedback
- **Secure Fields** - Password masking with reveal toggles
- **Reload Functionality** - Refresh configuration from server
## Next Steps
- [Payment Flow](payment-flow.md) - Understanding Bitcoin payment processing
- [Using the API](using-api.md) - Making API requests to your node
- [Models & Pricing](models-pricing.md) - Configuring model pricing and fees
- [API Reference](../api/overview.md) - Complete API documentation

View File

@@ -0,0 +1,245 @@
# User Guide Introduction
Welcome to the Routstr Core User Guide. This guide will help you understand how to use Routstr to access AI APIs with Bitcoin micropayments.
## What You'll Learn
- How the payment system works
- Creating and managing API keys
- Making API calls through Routstr
- Using the admin dashboard
- Managing your balance
## Prerequisites
Before starting, you'll need:
1. **A Running Routstr Instance**
- Either your own deployment or access to a public node
- The base URL (e.g., `https://api.routstr.com/v1`)
2. **A Cashu Wallet** (optional but recommended)
- [Nutstash](https://nutstash.app) - Web wallet
- [Minibits](https://www.minibits.cash) - Mobile wallet
- [Cashu.me](https://cashu.me) - Simple web wallet
3. **An API Client**
- OpenAI Python/JavaScript SDK
- Any HTTP client (curl, Postman, etc.)
- Your application code
## How Routstr Works
### Traditional API Access
```mermaid
graph LR
A[Your App] --> B[OpenAI API]
B --> A
```
- Direct connection to provider
- Monthly billing
- Credit card required
- Usage limits
### With Routstr
```mermaid
graph LR
A[Your App] --> B[Routstr Proxy]
B --> C[OpenAI API]
C --> B
B --> A
D[Bitcoin/eCash] --> B
```
- Pay per request with Bitcoin
- No credit card needed
- Anonymous payments
- Instant settlement
## Key Concepts
### eCash Tokens
- Digital bearer tokens backed by Bitcoin
- Can be sent like cash - whoever has the token owns it
- Redeemable at Cashu mints for Bitcoin
- Perfect for micropayments
### API Keys
- Created by depositing eCash tokens
- Track your balance and usage
- Can be topped up anytime
- Optional expiry and refund address
### Balance Management
- Measured in millisatoshis (msats)
- 1 Bitcoin = 100,000,000 sats = 100,000,000,000 msats
- Deducted based on actual usage
- Withdrawable as eCash tokens
## Typical Workflow
### 1. Get Bitcoin/eCash
Options:
- Buy Bitcoin and deposit to a Cashu mint
- Receive eCash tokens from someone else
- Use a testnet mint for testing
### 2. Use Your eCash
You have two options for using your eCash tokens with Routstr:
#### Option A: Create a Persistent Wallet
Create a wallet with an API key for multiple requests:
```bash
POST /v1/wallet/create
{
"cashu_token": "cashuAeyJ0..."
}
```
This returns an API key (`sk-...`) and your balance. The wallet persists between requests.
#### Option B: Direct Token Usage
Use your Cashu token directly as the API key:
```python
client = OpenAI(
api_key="cashuAeyJ0...", # Your Cashu token directly
base_url="https://api.routstr.com/v1"
)
```
Routstr automatically converts the token to access the associated wallet. Each request consumes from the token's balance.
### 3. Make API Calls
With either method:
```python
# Using persistent wallet API key
client = OpenAI(
api_key="sk-...",
base_url="https://api.routstr.com/v1"
)
# Or using Cashu token directly
client = OpenAI(
api_key="cashuAeyJ0...",
base_url="https://api.routstr.com/v1"
)
```
### 4. Monitor Usage
- Check balance: `GET /v1/wallet/balance`
- View admin dashboard
- Track costs per request
### 5. Withdraw Funds
When done, withdraw remaining balance as eCash through the admin interface.
## Supported Endpoints
Routstr supports all standard OpenAI endpoints:
-`/v1/chat/completions` - Chat models
- 🚧 `/v1/completions` - Text completion (Coming soon)
- 🚧 `/v1/embeddings` - Text embeddings (Coming soon)
- 🚧 `/v1/images/generations` - Image generation (Coming soon)
- 🚧 `/v1/audio/transcriptions` - Audio to text (Coming soon)
- 🚧 `/v1/audio/translations` - Audio translation (Coming soon)
-`/v1/models` - List available models
- ✅ Custom provider endpoints
## Cost Structure
### Pricing Models
1. **Fixed Cost Per Request**
- Simple flat fee per API call
- Good for uniform usage
2. **Token-Based Pricing**
- Pay per input/output token
- More accurate for varied usage
3. **Model-Based Pricing**
- Different rates per model
- Reflects actual provider costs
### Cost Calculation
```
Total Cost = Base Fee + (Input Tokens * Input Rate) + (Output Tokens * Output Rate)
```
Fees may include:
- Exchange rate markup (BTC/USD conversion)
- Provider margin
- Node operator fee
## Getting Support
### Documentation
- This user guide for general usage
- [API Reference](../api/overview.md) for technical details
- [Contributing Guide](../contributing/setup.md) for developers
### Community
- GitHub Issues for bugs and features
- Nostr for decentralized discussion
- Node operator contact info
### Troubleshooting
Common issues and solutions:
- [Payment Flow](payment-flow.md) - Understanding the payment process
- [Using the API](using-api.md) - API integration guide
- [Admin Dashboard](admin-dashboard.md) - Managing your node
## Security Considerations
### API Key Security
- Treat API keys like passwords
- Never share or commit them
- Rotate keys regularly
- Use environment variables
### Payment Security
- eCash tokens are bearer instruments
- Verify mint trustworthiness
- Keep backups of tokens
- Use small amounts for testing
### Network Security
- Always use HTTPS connections
- Verify SSL certificates
- Consider using Tor for privacy
- Monitor for unusual activity
## Next Steps
Ready to start? Continue with:
1. [Payment Flow](payment-flow.md) - Detailed payment process
2. [Using the API](using-api.md) - Making your first calls
3. [Admin Dashboard](admin-dashboard.md) - Managing your account

View File

@@ -0,0 +1,466 @@
# Models & Pricing
Understanding how Routstr calculates costs is essential for managing your API usage efficiently. This guide explains the pricing models and how to configure them.
## Pricing Models
Routstr supports three pricing models:
### 1. Fixed Pricing
Simple per-request charging:
```bash
FIXED_PRICING=true
FIXED_COST_PER_REQUEST=10 # 10 sats per request
```
**Best for:**
- Uniform API usage
- Simple applications
- Predictable costs
### 2. Token-Based Pricing
Charge based on actual token usage:
```bash
FIXED_PRICING=false # use model pricing
FIXED_COST_PER_REQUEST=1 # optional base fee
FIXED_PER_1K_INPUT_TOKENS=5 # optional override
FIXED_PER_1K_OUTPUT_TOKENS=15 # optional override
```
**Best for:**
- Varied request sizes
- Fair usage billing
- Cost optimization
### 3. Model-Based Pricing
Dynamic pricing based on model costs:
```bash
FIXED_PRICING=false
EXCHANGE_FEE=1.005 # 0.5% exchange fee
UPSTREAM_PROVIDER_FEE=1.05 # 5% provider fee
```
**Best for:**
- Multiple models
- Market-based pricing
- Automatic updates
## Model Configuration
### Default Models
Routstr includes pricing for popular models:
| Model | Input ($/1K) | Output ($/1K) | Context | Notes |
|-------|--------------|---------------|---------|-------|
| gpt-3.5-turbo | $0.0015 | $0.002 | 16K | Fast, economical |
| gpt-4 | $0.03 | $0.06 | 8K | Advanced reasoning |
| gpt-4-turbo | $0.01 | $0.03 | 128K | Large context |
| claude-3-opus | $0.015 | $0.075 | 200K | Best quality |
| claude-3-sonnet | $0.003 | $0.015 | 200K | Balanced |
| llama-2-70b | $0.0007 | $0.0009 | 4K | Open source |
### Custom Models File
Create `models.json` to override defaults:
```json
{
"models": [
{
"id": "gpt-4-vision",
"name": "GPT-4 Vision",
"pricing": {
"prompt": "0.00003",
"completion": "0.00006",
"request": "0",
"image": "0.00255"
},
"context_length": 128000,
"supports_vision": true
},
{
"id": "custom-model",
"name": "My Custom Model",
"pricing": {
"prompt": "0.001",
"completion": "0.002",
"request": "0.0001"
},
"context_length": 8192
}
]
}
```
### Auto-updating Models
Fetch latest models from OpenRouter:
```bash
# Update models from API
python scripts/models_meta.py
# Or manually
curl https://openrouter.ai/api/v1/models > models.json
```
## Cost Calculation
### Understanding the Formula
```
Base Cost = (Input Tokens × Input Rate) + (Output Tokens × Output Rate) + Request Fee
Bitcoin Price = Current BTC/USD rate (e.g., $50,000)
Sats Cost = (Base Cost / Bitcoin Price) × 100,000,000
Final Cost = Sats Cost × Exchange Fee × Provider Fee
```
### Example Calculations
**Example 1: Simple Chat (gpt-3.5-turbo)**
```
Input: 50 tokens
Output: 150 tokens
Model rates: $0.0015/1K input, $0.002/1K output
USD Cost = (50/1000 × 0.0015) + (150/1000 × 0.002)
= $0.000075 + $0.0003
= $0.000375
At $50,000/BTC: 0.75 sats
With 5.5% total fees: 0.79 sats
```
**Example 2: Large Context (gpt-4)**
```
Input: 2,000 tokens
Output: 500 tokens
Model rates: $0.03/1K input, $0.06/1K output
USD Cost = (2000/1000 × 0.03) + (500/1000 × 0.06)
= $0.06 + $0.03
= $0.09
At $50,000/BTC: 180 sats
With 5.5% total fees: 190 sats
```
**Example 3: Image Generation (dall-e-3)**
```
Model: dall-e-3
Size: 1024x1024
Quality: standard
Cost: $0.04 per image
At $50,000/BTC: 80 sats
With 5.5% fees: 84 sats
```
## Fee Structure
### Exchange Fee
Covers Bitcoin/USD conversion costs:
```bash
EXCHANGE_FEE=1.005 # 0.5% default
```
Factors:
- Exchange rate volatility
- Conversion costs
- Price update frequency
### Provider Fee
Node operator's margin:
```bash
UPSTREAM_PROVIDER_FEE=1.05 # 5% default
```
Covers:
- Infrastructure costs
- Maintenance
- Support
- Profit margin
### Calculating Total Fees
```
Total Multiplier = EXCHANGE_FEE × UPSTREAM_PROVIDER_FEE
Example: 1.005 × 1.05 = 1.05525 (5.525% total)
```
## Special Pricing
### Image Models
Image generation uses per-image pricing:
| Model | Size | Quality | Price |
|-------|------|---------|-------|
| dall-e-2 | 256x256 | - | $0.016 |
| dall-e-2 | 512x512 | - | $0.018 |
| dall-e-2 | 1024x1024 | - | $0.02 |
| dall-e-3 | 1024x1024 | standard | $0.04 |
| dall-e-3 | 1024x1024 | hd | $0.08 |
| dall-e-3 | 1024x1792 | standard | $0.08 |
| dall-e-3 | 1024x1792 | hd | $0.12 |
### Audio Models
Audio pricing by duration:
| Model | Type | Price |
|-------|------|-------|
| whisper-1 | Transcription | $0.006/minute |
| whisper-1 | Translation | $0.006/minute |
| tts-1 | Text-to-speech | $0.015/1K chars |
| tts-1-hd | HD speech | $0.03/1K chars |
### Embedding Models
Lower costs for embeddings:
| Model | Price/1K tokens |
|-------|-----------------|
| text-embedding-3-small | $0.00002 |
| text-embedding-3-large | $0.00013 |
| text-embedding-ada-002 | $0.0001 |
## Monitoring Costs
### Per-Request Tracking
Each API response includes usage data:
```json
{
"usage": {
"prompt_tokens": 50,
"completion_tokens": 150,
"total_tokens": 200
},
"x-routstr-cost": {
"sats": 79,
"usd": 0.000375,
"breakdown": {
"prompt_cost": 15,
"completion_cost": 60,
"fees": 4
}
}
}
```
### Daily Summaries
View in admin dashboard:
- Total requests
- Token usage by model
- Cost distribution
- Trending patterns
### Cost Alerts
Set up notifications:
```python
# Example monitoring script
def check_daily_spend(api_key):
balance_start = get_balance(api_key, "00:00")
balance_now = get_balance(api_key)
spent = balance_start - balance_now
if spent > DAILY_LIMIT:
send_alert(f"Daily spend exceeded: {spent} sats")
```
## Optimization Strategies
### Model Selection
Choose the right model for each task:
| Task | Recommended Model | Why |
|------|-------------------|-----|
| Simple Q&A | gpt-3.5-turbo | Fast, cheap, sufficient |
| Code generation | gpt-4 | Better reasoning |
| Summarization | claude-3-haiku | Good balance |
| Creative writing | claude-3-opus | Best quality |
| Embeddings | text-embedding-3-small | Optimized for vectors |
### Prompt Engineering
Reduce costs with efficient prompts:
```python
# Expensive
prompt = """
You are an AI assistant. Your task is to help users.
Please provide detailed, comprehensive answers.
Now, answer this question: What is 2+2?
"""
# Economical
prompt = "Calculate: 2+2"
```
### Caching Strategies
Implement smart caching:
```python
# Cache embedding results
@lru_cache(maxsize=1000)
def get_embedding(text):
return client.embeddings.create(
model="text-embedding-3-small",
input=text
)
# Cache common responses
COMMON_RESPONSES = {
"greeting": "Hello! How can I help you?",
"goodbye": "Goodbye! Have a great day!"
}
```
### Batch Processing
Process multiple items efficiently:
```python
# Instead of multiple calls
for item in items:
response = client.chat.completions.create(...)
# Use single call with formatted prompt
prompt = "\n".join([f"{i+1}. {item}" for i, item in enumerate(items)])
response = client.chat.completions.create(
messages=[{"role": "user", "content": f"Process these items:\n{prompt}"}]
)
```
## Custom Pricing Rules
### Time-Based Pricing
Implement off-peak discounts:
```python
def calculate_multiplier():
hour = datetime.now().hour
if 2 <= hour <= 6: # 2 AM - 6 AM
return 0.8 # 20% discount
elif 18 <= hour <= 22: # 6 PM - 10 PM
return 1.2 # 20% premium
return 1.0
```
### Model-Specific Rules
Custom pricing logic:
```python
def adjust_model_price(model, base_price):
# Premium for latest models
if "turbo" in model or "latest" in model:
return base_price * 1.1
# Discount for older models
if "legacy" in model:
return base_price * 0.8
return base_price
```
## Pricing Transparency
### Public Pricing Page
Display current rates:
```html
<!-- Available at /pricing -->
<table>
<tr>
<th>Model</th>
<th>Input (sats/1K)</th>
<th>Output (sats/1K)</th>
</tr>
<!-- Dynamically generated from models.json -->
</table>
```
### Cost Estimation API
Provide cost estimates:
```bash
POST /v1/estimate
{
"model": "gpt-4",
"prompt_tokens": 500,
"max_tokens": 200
}
Response:
{
"estimated_cost_sats": 45,
"breakdown": {
"prompt": 30,
"completion": 12,
"fees": 3
}
}
```
## Troubleshooting
### Pricing Mismatches
**Issue**: Costs don't match expectations
- Check current BTC/USD rate
- Verify fee settings
- Review model configuration
**Issue**: Models not found
- Update models.json
- Check model ID spelling
- Verify upstream support
### Fee Calculations
**Issue**: Fees seem too high
- Review EXCHANGE_FEE setting
- Check UPSTREAM_PROVIDER_FEE
- Calculate total multiplier
## Next Steps
- [API Reference](../api/overview.md) - Technical details
- [Custom Pricing](../advanced/custom-pricing.md) - Advanced configuration
- [Contributing](../contributing/setup.md) - Help improve Routstr

View File

@@ -0,0 +1,373 @@
# Payment Flow
Understanding how payments work in Routstr is key to using the system effectively. This guide explains the payment process in detail.
## Overview
Routstr uses a pre-funded account model where:
1. Users deposit eCash tokens to create an API key
2. Each API request deducts from the balance
3. Users can withdraw remaining balance as eCash
## Creating an API Key
### Step 1: Obtain eCash Token
Get a Cashu token from any compatible source:
**Option A: From a Cashu Wallet**
```bash
# Example: Creating a 10,000 sat token
cashu send 10000
```
**Option B: Lightning Invoice**
```bash
# Some mints support direct Lightning deposits
curl -X POST https://mint.example.com/v1/mint/quote/bolt11 \
-d '{"amount": 10000, "unit": "sat"}'
```
**Option C: Test Tokens**
```bash
# Get test tokens from testnet mints
# Check mint documentation for faucets
```
### Step 2: Create API Key
**Note: The POST /v1/wallet/create endpoint is coming soon. Currently, you can use Cashu tokens directly as API keys in the Authorization header.**
Send your token to Routstr:
```bash
curl -X POST https://api.routstr.com/v1/wallet/create \
-H "Content-Type: application/json" \
-d '{
"cashu_token": "cashuAeyJ0b2tlbiI6W3sibWludCI6Imh0dHBzOi8vbWlu..."
}'
```
**Request Parameters:**
- `cashu_token` (required): The eCash token to deposit
**Response:**
```json
{
"api_key": "sk-1234567890abcdef",
"balance": 10000000,
"created_at": "2024-01-01T00:00:00Z"
}
```
### Step 3: Verify Balance
Check your key's balance:
```bash
curl -X GET https://api.routstr.com/v1/wallet/balance \
-H "Authorization: Bearer sk-1234567890abcdef"
```
Response:
```json
{
"balance": 10000000,
"total_deposited": 10000000,
"total_spent": 0,
"last_used": null
}
```
## Making API Requests
### Cost Calculation
Costs are calculated based on:
1. **Request Type**
- Chat completions
- Embeddings
- Image generation
- Audio processing
2. **Token Usage**
- Input tokens (prompt)
- Output tokens (response)
- Model-specific rates
3. **Additional Costs**
- Base request fee
- Image generation fees
- Audio processing time
### Example: Chat Completion
```python
import openai
client = openai.OpenAI(
api_key="sk-1234567890abcdef",
base_url="https://api.routstr.com/v1"
)
# Make request
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": "Hello, how are you?"}
]
)
# Check usage
print(f"Input tokens: {response.usage.prompt_tokens}")
print(f"Output tokens: {response.usage.completion_tokens}")
print(f"Total tokens: {response.usage.total_tokens}")
```
### Cost Breakdown
For the above request:
```
Model: gpt-3.5-turbo
Input tokens: 13
Output tokens: 27
Model rates: $0.0015/1K input, $0.002/1K output
USD Cost = (13/1000 * 0.0015) + (27/1000 * 0.002) = $0.0000735
BTC/USD Rate: $50,000
BTC Cost = 0.0000735 / 50000 = 0.00000000147 BTC = 147 sats
With fees (5%): 154 sats
Final cost: 154 sats
```
## Balance Management
### Monitoring Usage
Track your usage in real-time:
```bash
# Get current balance
curl -X GET https://api.routstr.com/v1/wallet/balance \
-H "Authorization: Bearer your-api-key"
# View recent transactions (through admin dashboard)
# Access at https://api.routstr.com/admin/
```
### Low Balance Handling
When balance is insufficient:
```json
{
"error": {
"type": "insufficient_balance",
"message": "Insufficient balance. Current: 100 sats, Required: 154 sats",
"code": "payment_required"
}
}
```
### Topping Up
Add funds to existing key:
```bash
curl -X POST https://api.routstr.com/v1/wallet/topup \
-H "Authorization: Bearer your-api-key" \
-H "Content-Type: application/json" \
-d '{
"cashu_token": "cashuAeyJ0b2..."
}'
```
## Withdrawing Balance
### Via Admin Dashboard
1. Navigate to `/admin/`
2. Enter admin password
3. Find your API key
4. Click "Withdraw"
5. Receive eCash token
### Via API (if enabled)
```bash
curl -X POST https://api.routstr.com/v1/wallet/withdraw \
-H "Authorization: Bearer your-api-key" \
-H "Content-Type: application/json" \
-d '{
"amount": 5000,
"mint": "https://mint.minibits.cash/Bitcoin"
}'
```
## Payment Security
### Token Validation
Routstr validates tokens by:
1. Checking signature validity
2. Verifying with the issuing mint
3. Ensuring no double-spending
4. Confirming sufficient value
### Failed Payments
Common failure reasons:
- Invalid token signature
- Already spent token
- Untrusted mint
- Network issues with mint
### Refund Policy
- Unused balance can be withdrawn anytime
- Expired keys with balance can be refunded
- Node operators may have additional policies
## Advanced Features
### Multi-Mint Support
Routstr accepts tokens from multiple mints:
```bash
CASHU_MINTS=https://mint1.com,https://mint2.com,https://mint3.com
```
Benefits:
- Redundancy if one mint is down
- User choice of mints
- Geographic distribution
### Automatic Payouts
Configure automatic Lightning payouts:
```bash
RECEIVE_LN_ADDRESS=satoshi@getalby.com
```
When enabled:
- Balances above threshold are swept
- Converted to Lightning payments
- Sent to configured address
### Per-Request Payments (Coming Soon)
Future support for Nut-24 headers:
```bash
curl -X POST https://api.routstr.com/v1/chat/completions \
-H "x-cashu: cashuAeyJ0..." \
-H "Content-Type: application/json" \
-d '{...}'
```
Response includes change:
```
HTTP/1.1 200 OK
x-cashu: cashuAeyJjaGFuZ2Ui...
```
## Best Practices
### API Key Management
1. **Separate Keys per Application**
- Easier tracking
- Better security
- Independent budgets
2. **Set Expiration Dates**
- Automatic cleanup
- Security improvement
- Budget control
3. **Monitor Balances**
- Set up alerts
- Regular checks
- Usage analytics
### Cost Optimization
1. **Choose Appropriate Models**
- Smaller models for simple tasks
- Larger models only when needed
2. **Optimize Prompts**
- Concise, clear instructions
- Avoid unnecessary tokens
3. **Use Streaming**
- Early termination possible
- Better user experience
### Security
1. **Secure Storage**
- Environment variables
- Secrets management
- Never in code
2. **Network Security**
- Always use HTTPS
- Verify certificates
- Consider Tor for privacy
3. **Regular Rotation**
- Change keys periodically
- Withdraw unused funds
- Audit usage logs
## Troubleshooting
### Payment Rejected
**Error:** "Invalid token"
- Check token format
- Verify mint is trusted
- Ensure not already spent
**Error:** "Insufficient value"
- Token value too low
- Check current pricing
- Add larger token
### Balance Discrepancies
- Allow for price fluctuations
- Check model pricing updates
- Review transaction history
### Mint Issues
- Try different mint from list
- Check mint status
- Contact mint operator
## Next Steps
- [Using the API](using-api.md) - Integration guide
- [Admin Dashboard](admin-dashboard.md) - Account management
- [Models & Pricing](models-pricing.md) - Cost details

View File

@@ -0,0 +1,545 @@
# Using the API
This guide shows how to integrate Routstr with your applications using various programming languages and tools.
## API Compatibility
Routstr maintains full compatibility with the OpenAI API, meaning:
- Existing OpenAI client libraries work without modification
- Only the base URL and API key need to change
- All parameters and responses match OpenAI's format
## Basic Setup
### Python
Using the official OpenAI Python library:
```python
from openai import OpenAI
# Initialize client with Routstr endpoint
client = OpenAI(
api_key="sk-...",
base_url="https://api.routstr.com/v1"
)
# Use exactly like OpenAI
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
```
### JavaScript/TypeScript
Using the official OpenAI Node.js library:
```javascript
import OpenAI from 'openai';
// Initialize client
const openai = new OpenAI({
apiKey: 'sk-...',
baseURL: 'https://api.routstr.com/v1'
});
// Make a request
async function main() {
const completion = await openai.chat.completions.create({
model: 'gpt-3.5-turbo',
messages: [
{ role: 'system', content: 'You are a helpful assistant.' },
{ role: 'user', content: 'Hello!' }
]
});
console.log(completion.choices[0].message.content);
}
main();
```
### cURL
Direct HTTP requests:
```bash
curl https://api.routstr.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-..." \
-d '{
"model": "gpt-3.5-turbo",
"messages": [
{"role": "user", "content": "Hello!"}
]
}'
```
## Common Use Cases
### Chat Completions
Standard chat with conversation history:
```python
messages = []
def chat(user_input):
# Add user message
messages.append({"role": "user", "content": user_input})
# Get AI response
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=messages,
temperature=0.7,
max_tokens=150
)
# Add AI response to history
ai_message = response.choices[0].message
messages.append({"role": "assistant", "content": ai_message.content})
return ai_message.content
# Usage
print(chat("What's the weather like?"))
print(chat("How should I dress?")) # Maintains context
```
### Streaming Responses
For real-time output:
```python
stream = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "Write a short story"}],
stream=True
)
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="", flush=True)
```
### Function Calling
Using OpenAI's function calling feature:
```python
tools = [{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get current weather",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string"},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
},
"required": ["location"]
}
}
}]
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
tools=tools,
tool_choice="auto"
)
# Check if function was called
if response.choices[0].message.tool_calls:
tool_call = response.choices[0].message.tool_calls[0]
print(f"Function: {tool_call.function.name}")
print(f"Arguments: {tool_call.function.arguments}")
```
### Embeddings
Generate text embeddings:
```python
response = client.embeddings.create(
model="text-embedding-3-small",
input="The quick brown fox jumps over the lazy dog"
)
embedding = response.data[0].embedding
print(f"Embedding dimension: {len(embedding)}")
```
### Image Generation
Create images with DALL-E:
```python
response = client.images.generate(
model="dall-e-3",
prompt="A futuristic city with flying cars",
size="1024x1024",
quality="standard",
n=1
)
image_url = response.data[0].url
print(f"Image URL: {image_url}")
```
### Audio Transcription
Convert speech to text:
```python
with open("audio.mp3", "rb") as audio_file:
response = client.audio.transcriptions.create(
model="whisper-1",
file=audio_file,
response_format="text"
)
print(response.text)
```
## Error Handling
### Balance Errors
Handle insufficient balance gracefully:
```python
try:
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello"}]
)
except Exception as e:
if "insufficient_balance" in str(e):
print("Low balance! Please top up your API key.")
# Implement top-up logic
else:
raise
```
### Rate Limiting
Implement exponential backoff:
```python
import time
from typing import Optional
def make_request_with_retry(
func,
max_retries: int = 3,
initial_delay: float = 1.0
) -> Optional[any]:
for attempt in range(max_retries):
try:
return func()
except Exception as e:
if "rate_limit" in str(e) and attempt < max_retries - 1:
delay = initial_delay * (2 ** attempt)
print(f"Rate limited. Waiting {delay}s...")
time.sleep(delay)
else:
raise
return None
```
### Connection Errors
Handle network issues:
```python
import httpx
# Configure timeout and retries
client = OpenAI(
api_key="sk-...",
base_url="https://your-node.com/v1",
timeout=httpx.Timeout(60.0, connect=5.0),
max_retries=2
)
```
## Advanced Features
### Using Tor
Route requests through Tor for privacy:
```python
import httpx
# Configure Tor proxy
proxies = {
"http://": "socks5://127.0.0.1:9050",
"https://": "socks5://127.0.0.1:9050"
}
http_client = httpx.Client(proxies=proxies)
client = OpenAI(
api_key="sk-...",
base_url="http://your-onion-address.onion/v1",
http_client=http_client
)
```
### Custom Headers
Add custom headers if needed:
```python
import httpx
class CustomClient(httpx.Client):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.headers["X-Custom-Header"] = "value"
client = OpenAI(
api_key="sk-...",
base_url="https://your-node.com/v1",
http_client=CustomClient()
)
```
### Azure OpenAI compatibility
To use Azure OpenAI through Routstr with minimal changes:
- Set `UPSTREAM_BASE_URL` to your Azure deployments URL, for example: `https://<resource>.openai.azure.com/openai/deployments/<deployment>`
- Set `CHAT_COMPLETIONS_API_VERSION=2024-05-01-preview`
When this env var is set, Routstr automatically appends `api-version=2024-05-01-preview` to all upstream `/chat/completions` requests.
### Async Operations
For high-performance applications:
```python
import asyncio
from openai import AsyncOpenAI
async_client = AsyncOpenAI(
api_key="sk-...",
base_url="https://your-node.com/v1"
)
async def process_messages(messages):
tasks = []
for msg in messages:
task = async_client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": msg}]
)
tasks.append(task)
responses = await asyncio.gather(*tasks)
return [r.choices[0].message.content for r in responses]
# Run async
messages = ["Hello", "How are you?", "What's 2+2?"]
results = asyncio.run(process_messages(messages))
```
## Best Practices
### 1. Environment Variables
Never hardcode API keys:
```python
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("ROUTSTR_API_KEY"),
base_url=os.getenv("ROUTSTR_BASE_URL", "https://api.routstr.com/v1")
)
```
### 2. Error Logging
Implement comprehensive logging:
```python
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
try:
response = client.chat.completions.create(...)
logger.info(f"Request successful. Tokens used: {response.usage.total_tokens}")
except Exception as e:
logger.error(f"API request failed: {e}")
raise
```
### 3. Cost Tracking
Monitor your usage:
```python
class UsageTracker:
def __init__(self):
self.total_tokens = 0
self.total_requests = 0
def track(self, response):
self.total_tokens += response.usage.total_tokens
self.total_requests += 1
# Estimate cost (example rates)
cost_per_1k = 0.002 # $0.002 per 1K tokens
estimated_cost = (self.total_tokens / 1000) * cost_per_1k
logger.info(f"Total usage: {self.total_tokens} tokens, "
f"${estimated_cost:.4f} (~{estimated_cost * 50000:.0f} sats)")
tracker = UsageTracker()
response = client.chat.completions.create(...)
tracker.track(response)
```
### 4. Caching Responses
Reduce costs with intelligent caching:
```python
import hashlib
import json
from functools import lru_cache
@lru_cache(maxsize=100)
def cached_completion(prompt: str, model: str = "gpt-3.5-turbo"):
response = client.chat.completions.create(
model=model,
messages=[{"role": "user", "content": prompt}],
temperature=0 # Deterministic for caching
)
return response.choices[0].message.content
# Repeated calls with same prompt use cache
result1 = cached_completion("What is 2+2?")
result2 = cached_completion("What is 2+2?") # From cache, no API call
```
## Testing
### Mock Responses
For development without spending sats:
```python
class MockOpenAI:
class Completions:
def create(self, **kwargs):
return type('Response', (), {
'choices': [type('Choice', (), {
'message': type('Message', (), {
'content': 'Mock response'
})()
})],
'usage': type('Usage', (), {
'total_tokens': 10
})()
})()
def __init__(self):
self.chat = type('Chat', (), {
'completions': self.Completions()
})()
# Use mock in tests
if os.getenv('TESTING'):
client = MockOpenAI()
else:
client = OpenAI(...)
```
### Integration Tests
Test your Routstr integration:
```python
def test_routstr_connection():
try:
# Test models endpoint
models = client.models.list()
assert len(models.data) > 0
# Test simple completion
response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "test"}],
max_tokens=5
)
assert response.choices[0].message.content
print("✅ Routstr integration working!")
return True
except Exception as e:
print(f"❌ Integration test failed: {e}")
return False
```
## Troubleshooting
### Common Issues
**SSL Certificate Errors**
```python
# For development only - not for production!
import ssl
import httpx
client = OpenAI(
api_key="sk-...",
base_url="https://localhost:8000/v1",
http_client=httpx.Client(verify=False)
)
```
**Timeout Issues**
```python
# Increase timeout for slow connections
client = OpenAI(
api_key="sk-...",
base_url="https://your-node.com/v1",
timeout=httpx.Timeout(120.0) # 2 minutes
)
```
**Debugging Requests**
```python
import logging
import httpx
# Enable debug logging
logging.basicConfig(level=logging.DEBUG)
httpx_logger = logging.getLogger("httpx")
httpx_logger.setLevel(logging.DEBUG)
```
## Next Steps
- [Admin Dashboard](admin-dashboard.md) - Manage your account
- [Models & Pricing](models-pricing.md) - Understanding costs
- [API Reference](../api/overview.md) - Technical details

37
example.py Normal file
View File

@@ -0,0 +1,37 @@
import os
import openai
client = openai.OpenAI(
api_key=os.environ["CASHU_TOKEN"],
base_url=os.environ.get("ROUTSTR_API_URL", "https://api.routstr.com/v1"),
# base_url="http://roustrjfsdgfiueghsklchg.onion/v1",
# client=httpx.AsyncClient(
# proxies={"http": "socks5://localhost:9050"},
# ), # to use onion proxy (tor)
)
history: list = []
def chat() -> None:
while True:
user_msg = {"role": "user", "content": input("\nYou: ")}
history.append(user_msg)
ai_msg = {"role": "assistant", "content": ""}
for chunk in client.chat.completions.create(
model=os.environ.get("MODEL", "openai/gpt-4o-mini"),
messages=history,
stream=True,
):
if len(chunk.choices) > 0:
content = chunk.choices[0].delta.content
if content is not None:
ai_msg["content"] += content
print(content, end="", flush=True)
print()
history.append(ai_msg)
if __name__ == "__main__":
chat()

View File

@@ -1,11 +0,0 @@
import os
import httpx
# Use your Cashu token or API key as the Bearer token,
# cashu token is hashed on the server and acts as an Temporary API key
headers = {"Authorization": f"Bearer {os.environ.get('TOKEN')}"}
base_url = os.environ.get("API_URL", "https://api.routstr.com/v1")
resp = httpx.get(f"{base_url}/balance/info", headers=headers)
print(resp.json())

View File

@@ -1,15 +0,0 @@
import os
import httpx
# Send a Cashu token to the /create endpoint to get a persistent API key
token = os.environ.get("TOKEN")
if not token:
print("Please set TOKEN environment variable with a Cashu token")
exit(1)
base_url = os.environ.get("API_URL", "https://api.routstr.com/v1")
resp = httpx.get(f"{base_url}/balance/create", params={"initial_balance_token": token})
print(resp.json())

View File

@@ -1,12 +0,0 @@
import os
import httpx
# Use your Cashu token or API key as the Bearer token
headers = {"Authorization": f"Bearer {os.environ.get('TOKEN')}"}
base_url = os.environ.get("API_URL", "https://api.routstr.com/v1")
resp = httpx.post(f"{base_url}/balance/refund", headers=headers)
print("Refund successful!")
print(resp.json())

View File

@@ -1,16 +0,0 @@
import os
import httpx
# Use your Cashu token or API key as the Bearer token
headers = {"Authorization": f"Bearer {os.environ.get('TOKEN')}"}
base_url = os.environ.get("API_URL", "https://api.routstr.com/v1")
# The Cashu token to top up with
cashu_token = input("Enter Cashu token to top up: ")
resp = httpx.post(
f"{base_url}/balance/topup", headers=headers, json={"cashu_token": cashu_token}
)
print(resp.json())

View File

@@ -1,15 +0,0 @@
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKEN"),
base_url=os.environ.get("API_URL", "https://api.routstr.com/v1"),
)
response = client.chat.completions.create(
model=os.environ.get("MODEL", "gpt-5-nano"),
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

View File

@@ -1,45 +0,0 @@
import json
import sys
import httpx
def create_child_keys(base_url: str, api_key: str, count: int = 3) -> list[str]:
headers = {"Authorization": f"Bearer {api_key}"}
print(f"Requesting {count} child keys from {base_url}...")
child_keys = []
for i in range(count):
try:
response = httpx.post(f"{base_url}/v1/balance/child-key", headers=headers)
if response.status_code == 200:
data = response.json()
child_keys.append(data["api_key"])
print(
f" [{i + 1}] Created: {data['api_key']} (Cost: {data['cost_msats']} msats)"
)
else:
print(f" [{i + 1}] Failed: {response.status_code} - {response.text}")
except Exception as e:
print(f" [{i + 1}] Error: {str(e)}")
return child_keys
if __name__ == "__main__":
if len(sys.argv) < 2:
print("Usage: python create_child_keys.py <api_key_or_cashu_token> [base_url]")
sys.exit(1)
auth_key = sys.argv[1]
base_url = sys.argv[2] if len(sys.argv) > 2 else "http://localhost:8000"
keys = create_child_keys(base_url, auth_key)
if keys:
print("\nSuccessfully created child keys:")
print(json.dumps(keys, indent=2))
else:
print("\nNo child keys were created.")

View File

@@ -1,19 +0,0 @@
import os
import httpx
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKEN", ""),
base_url=os.environ.get("API_URL", "https://api.routstr.com/v1"),
)
for model in client.models.list():
print(model.id)
# OR
models = httpx.get(
f"{client.base_url}/v1/models",
headers={"Authorization": f"Bearer {client.api_key}"},
).json()

View File

@@ -1,31 +0,0 @@
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKEN"),
base_url=os.environ.get("API_URL", "https://api.routstr.com/v1"),
)
conversation = [] # type: ignore
# First turn
response1 = client.responses.create( # type: ignore
model="o4-mini",
input="Hi, my name is Alice.",
conversation=conversation,
)
print("Response 1:", response1.output)
# Note: The 'conversation' parameter might need to be constructed differently
# depending on exact SDK/API spec. Typically, you pass back the previous turn's data.
# Assuming the SDK manages or returns a conversation object/ID:
# conversation.append(response1)
# Second turn - demonstrating intent, actual implementation depends on strict API spec
# response2 = client.responses.create(
# model="openai/gpt-4o-mini",
# input="What is my name?",
# conversation=conversation,
# )
# print("Response 2:", response2.output)

View File

@@ -1,17 +0,0 @@
import os
from openai import OpenAI
# The OpenAI SDK handles the 'responses' endpoint if it's updated to the latest version
# and the base_url points to a compatible proxy like Routstr.
client = OpenAI(
api_key=os.environ.get("TOKEN"),
base_url=os.environ.get("API_URL", "https://api.routstr.com/v1"),
)
response = client.responses.create(
model="gpt-5-mini",
input="Tell me a three sentence bedtime story about a unicorn.",
)
print(response.output)

View File

@@ -1,20 +0,0 @@
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKEN"),
base_url=os.environ.get("API_URL", "https://api.routstr.com/v1"),
)
stream = client.responses.create(
model="claude-4.5-sonnet",
input="Write a short poem about rust.",
stream=True,
)
for event in stream:
# Note: Depending on the SDK version and response structure,
# you might access event.output_delta or similar fields
print(event, end="", flush=True)
print()

View File

@@ -1,16 +0,0 @@
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKEN"),
base_url=os.environ.get("API_URL", "https://api.routstr.com/v1"),
)
response = client.responses.create(
model="gpt-5-mini",
input="What is the latest news about AI?",
tools=[{"type": "web_search"}], # type: ignore
)
print(response.output)

View File

@@ -1,28 +0,0 @@
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKEN"),
base_url=os.environ.get("API_URL", "https://api.routstr.com/v1"),
)
messages = []
while True:
messages.append({"role": "user", "content": input("\nYou: ")})
stream = client.chat.completions.create(
model=os.environ.get("MODEL", "gpt-5.1-mini"),
messages=messages, # type: ignore
stream=True,
)
print("AI: ", end="")
response_content = ""
for chunk in stream:
if content := chunk.choices[0].delta.content: # type: ignore
print(content, end="", flush=True)
response_content += content
print()
messages.append({"role": "assistant", "content": response_content})

View File

@@ -1,20 +0,0 @@
import os
import httpx
from openai import OpenAI
# Requires `pip install "httpx[socks]"` and a running Tor proxy on port 9050
client = OpenAI(
api_key=os.environ.get("TOKEN"),
base_url=os.environ.get("ONION_URL", "http://roustrjfsdgfiueghsklchg.onion/v1"),
http_client=httpx.Client(proxies="socks5://localhost:9050"),
)
print(
client.chat.completions.create(
model="openai/gpt-4o-mini",
messages=[{"role": "user", "content": "Hello from Tor!"}],
)
.choices[0]
.message.content
)

View File

@@ -1 +0,0 @@

View File

@@ -1,32 +0,0 @@
"""add routstr_fees table
Revision ID: 02650cd6f028
Revises: c3d4e5f6a7b8
Create Date: 2026-04-24 00:00:00.000000
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "02650cd6f028"
down_revision = "c3d4e5f6a7b8"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"routstr_fees",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("accumulated_msats", sa.Integer(), nullable=False, server_default="0"),
sa.Column("total_paid_msats", sa.Integer(), nullable=False, server_default="0"),
sa.Column("last_paid_at", sa.Integer(), nullable=True),
sa.PrimaryKeyConstraint("id"),
)
# Seed with a single row
op.execute("INSERT INTO routstr_fees (id, accumulated_msats, total_paid_msats) VALUES (1, 0, 0)")
def downgrade() -> None:
op.drop_table("routstr_fees")

View File

@@ -1,37 +0,0 @@
"""add key management and reset fields to api_keys
Revision ID: 06f81c0fc88d
Revises: c2d3e4f5a6b7
Create Date: 2026-02-04 22:44:03.311983
"""
import sqlalchemy as sa
import sqlmodel
from alembic import op
# revision identifiers, used by Alembic.
revision = "06f81c0fc88d"
down_revision = "c2d3e4f5a6b7"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("api_keys", sa.Column("balance_limit", sa.Integer(), nullable=True))
op.add_column(
"api_keys",
sa.Column(
"balance_limit_reset", sqlmodel.sql.sqltypes.AutoString(), nullable=True
),
)
op.add_column(
"api_keys", sa.Column("balance_limit_reset_date", sa.Integer(), nullable=True)
)
op.add_column("api_keys", sa.Column("validity_date", sa.Integer(), nullable=True))
def downgrade() -> None:
op.drop_column("api_keys", "validity_date")
op.drop_column("api_keys", "balance_limit_reset_date")
op.drop_column("api_keys", "balance_limit_reset")
op.drop_column("api_keys", "balance_limit")

View File

@@ -1,32 +0,0 @@
"""add provider_settings to upstream_providers
Revision ID: 614c0a740e68
Revises: 06f81c0fc88d
Create Date: 2026-02-13 22:36:53.608737
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "614c0a740e68"
down_revision = "06f81c0fc88d"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Check if column exists before adding it
conn = op.get_bind()
inspector = sa.inspect(conn)
columns = [c["name"] for c in inspector.get_columns("upstream_providers")]
if "provider_settings" not in columns:
op.add_column(
"upstream_providers",
sa.Column("provider_settings", sa.Text(), nullable=True),
)
def downgrade() -> None:
op.drop_column("upstream_providers", "provider_settings")

View File

@@ -1,26 +0,0 @@
"""Add balance_limit, balance_limit_reset, validity_date to lightning_invoices
Revision ID: a2b3c4d5e6f7
Revises: f1a2b3c4d5e6
Create Date: 2026-06-03 00:00:00.000000
"""
import sqlalchemy as sa
from alembic import op
revision = "a2b3c4d5e6f7"
down_revision = "f1a2b3c4d5e6"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("lightning_invoices", sa.Column("balance_limit", sa.Integer(), nullable=True))
op.add_column("lightning_invoices", sa.Column("balance_limit_reset", sa.String(), nullable=True))
op.add_column("lightning_invoices", sa.Column("validity_date", sa.Integer(), nullable=True))
def downgrade() -> None:
op.drop_column("lightning_invoices", "validity_date")
op.drop_column("lightning_invoices", "balance_limit_reset")
op.drop_column("lightning_invoices", "balance_limit")

View File

@@ -1,42 +0,0 @@
"""add cashu_transactions table
Revision ID: a776ca70e5fe
Revises: 614c0a740e68
Create Date: 2026-03-11 22:00:01.554762
"""
import sqlalchemy as sa
import sqlmodel
from alembic import op
# revision identifiers, used by Alembic.
revision = "a776ca70e5fe"
down_revision = "614c0a740e68"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"cashu_transactions",
sa.Column("id", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
sa.Column("token", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
sa.Column("amount", sa.Integer(), nullable=False),
sa.Column("unit", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
sa.Column("mint_url", sqlmodel.sql.sqltypes.AutoString(), nullable=True),
sa.Column(
"type",
sqlmodel.sql.sqltypes.AutoString(),
nullable=False,
server_default="out",
),
sa.Column("request_id", sqlmodel.sql.sqltypes.AutoString(), nullable=True),
sa.Column("created_at", sa.Integer(), nullable=False),
sa.Column("collected", sa.Boolean(), nullable=False),
sa.Column("swept", sa.Boolean(), nullable=False),
sa.PrimaryKeyConstraint("id"),
)
def downgrade() -> None:
op.drop_table("cashu_transactions")

View File

@@ -1,42 +0,0 @@
"""
Revision ID: a86e5348850b
Revises: b9667ffc5701
Create Date: 2026-01-10 18:57:48.475781
"""
import sqlalchemy as sa
import sqlmodel
from alembic import op
# revision identifiers, used by Alembic.
revision = "a86e5348850b"
down_revision = "b9667ffc5701"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Use batch_alter_table for SQLite compatibility
with op.batch_alter_table("api_keys", schema=None) as batch_op:
batch_op.add_column(
sa.Column(
"parent_key_hash", sqlmodel.sql.sqltypes.AutoString(), nullable=True
)
)
batch_op.create_index(
batch_op.f("ix_api_keys_parent_key_hash"), ["parent_key_hash"], unique=False
)
batch_op.create_foreign_key(
"fk_api_keys_parent_key_hash",
"api_keys",
["parent_key_hash"],
["hashed_key"],
)
def downgrade() -> None:
with op.batch_alter_table("api_keys", schema=None) as batch_op:
batch_op.drop_constraint("fk_api_keys_parent_key_hash", type_="foreignkey")
batch_op.drop_index(batch_op.f("ix_api_keys_parent_key_hash"))
batch_op.drop_column("parent_key_hash")

View File

@@ -1,33 +0,0 @@
"""add forwarded_model_id to models
Revision ID: b1c2d3e4f5a6
Revises: a776ca70e5fe
Create Date: 2026-04-05 00:00:00.000000
"""
import sqlalchemy as sa
import sqlmodel
from alembic import op
# revision identifiers, used by Alembic.
revision = "b1c2d3e4f5a6"
down_revision = "a776ca70e5fe"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"models",
sa.Column(
"forwarded_model_id",
sqlmodel.sql.sqltypes.AutoString(),
nullable=True,
),
)
# Backfill: set forwarded_model_id = id for all existing rows
op.execute("UPDATE models SET forwarded_model_id = id WHERE forwarded_model_id IS NULL")
def downgrade() -> None:
op.drop_column("models", "forwarded_model_id")

View File

@@ -1,25 +0,0 @@
"""add reserved_at to api_keys
Revision ID: b5e7c9d1f3a2
Revises: a2b3c4d5e6f7
Create Date: 2026-06-12 00:00:00.000000
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "b5e7c9d1f3a2"
down_revision = "a2b3c4d5e6f7"
branch_labels = None
depends_on = None
def upgrade() -> None:
# existing keys keep NULL
# New reservations populate it via pay_for_request.
op.add_column("api_keys", sa.Column("reserved_at", sa.Integer(), nullable=True))
def downgrade() -> None:
op.drop_column("api_keys", "reserved_at")

View File

@@ -1,118 +0,0 @@
"""make upstream provider base_url + api_key unique
Revision ID: c2d3e4f5a6b7
Revises: a86e5348850b
Create Date: 2026-01-25 00:00:00.000000
"""
from __future__ import annotations
import sqlalchemy as sa
from alembic import op
revision = "c2d3e4f5a6b7"
down_revision = "a86e5348850b"
branch_labels = None
depends_on = None
def _recreate_table_sqlite(add_base_url_unique: bool) -> None:
conn = op.get_bind()
existing_tables = {
row[0]
for row in conn.exec_driver_sql(
"SELECT name FROM sqlite_master WHERE type='table'"
).fetchall()
}
if "upstream_providers_old" in existing_tables:
if "upstream_providers" in existing_tables:
op.drop_table("upstream_providers_old")
else:
op.execute(
"ALTER TABLE upstream_providers_old RENAME TO upstream_providers"
)
existing_tables.add("upstream_providers")
if "upstream_providers" not in existing_tables:
return
constraints = [
sa.UniqueConstraint(
"base_url",
"api_key",
name="uq_upstream_providers_base_url_api_key",
)
]
if add_base_url_unique:
constraints.append(
sa.UniqueConstraint("base_url", name="uq_upstream_providers_base_url")
)
op.execute("ALTER TABLE upstream_providers RENAME TO upstream_providers_old")
op.create_table(
"upstream_providers",
sa.Column(
"id", sa.Integer(), primary_key=True, nullable=False, autoincrement=True
),
sa.Column("provider_type", sa.String(), nullable=False),
sa.Column("base_url", sa.String(), nullable=False),
sa.Column("api_key", sa.String(), nullable=False),
sa.Column("api_version", sa.String(), nullable=True),
sa.Column("enabled", sa.Boolean(), nullable=False),
sa.Column("provider_fee", sa.Float(), nullable=False, server_default="1.01"),
*constraints,
)
op.execute(
"INSERT INTO upstream_providers (id, provider_type, base_url, api_key, api_version, enabled, provider_fee) "
"SELECT id, provider_type, base_url, api_key, api_version, enabled, provider_fee "
"FROM upstream_providers_old"
)
op.drop_table("upstream_providers_old")
def upgrade() -> None:
conn = op.get_bind()
if conn.dialect.name == "sqlite":
_recreate_table_sqlite(add_base_url_unique=False)
return
inspector = sa.inspect(conn)
for constraint in inspector.get_unique_constraints("upstream_providers"):
name = constraint.get("name")
if constraint.get("column_names") == ["base_url"] and name:
op.drop_constraint(
name,
"upstream_providers",
type_="unique",
)
index_names = {idx["name"] for idx in inspector.get_indexes("upstream_providers")}
if "ix_upstream_providers_base_url" in index_names:
op.drop_index("ix_upstream_providers_base_url", table_name="upstream_providers")
op.create_unique_constraint(
"uq_upstream_providers_base_url_api_key",
"upstream_providers",
["base_url", "api_key"],
)
def downgrade() -> None:
conn = op.get_bind()
if conn.dialect.name == "sqlite":
_recreate_table_sqlite(add_base_url_unique=True)
return
op.drop_constraint(
"uq_upstream_providers_base_url_api_key",
"upstream_providers",
type_="unique",
)
op.create_unique_constraint(
"uq_upstream_providers_base_url",
"upstream_providers",
["base_url"],
)
op.create_index(
"ix_upstream_providers_base_url",
"upstream_providers",
["base_url"],
unique=True,
)

View File

@@ -1,36 +0,0 @@
"""add source to cashu_transactions
Revision ID: c3d4e5f6a7b8
Revises: b1c2d3e4f5a6
Create Date: 2026-04-10 00:00:00.000000
"""
import sqlalchemy as sa
import sqlmodel
from alembic import op
# revision identifiers, used by Alembic.
revision = "c3d4e5f6a7b8"
down_revision = "b1c2d3e4f5a6"
branch_labels = None
depends_on = None
def upgrade() -> None:
conn = op.get_bind()
inspector = sa.inspect(conn)
columns = [col["name"] for col in inspector.get_columns("cashu_transactions")]
if "source" not in columns:
op.add_column(
"cashu_transactions",
sa.Column(
"source",
sqlmodel.sql.sqltypes.AutoString(),
nullable=False,
server_default="x-cashu",
),
)
def downgrade() -> None:
op.drop_column("cashu_transactions", "source")

View File

@@ -1,88 +0,0 @@
"""add slug to upstream_providers
Revision ID: c6d7e8f9a0b1
Revises: b5e7c9d1f3a2
Create Date: 2026-06-29 00:00:00.000000
"""
from __future__ import annotations
import sqlalchemy as sa
from alembic import op
from routstr.core.provider_slugs import provider_slug_base, provider_slug_candidate
revision = "c6d7e8f9a0b1"
down_revision = "b5e7c9d1f3a2"
branch_labels = None
depends_on = None
def _allocate_backfill_slug(provider_type: str, reserved_slugs: set[str]) -> str:
base = provider_slug_base(provider_type)
suffix_number = 1
while True:
candidate = provider_slug_candidate(base, suffix_number)
if candidate not in reserved_slugs:
reserved_slugs.add(candidate)
return candidate
suffix_number += 1
def _backfill_provider_slugs(conn: sa.Connection) -> None:
existing_rows = conn.execute(
sa.text(
"SELECT slug FROM upstream_providers "
"WHERE slug IS NOT NULL AND slug != ''"
)
)
reserved_slugs = {str(row.slug).lower() for row in existing_rows}
rows_to_backfill = conn.execute(
sa.text(
"SELECT id, provider_type FROM upstream_providers "
"WHERE slug IS NULL OR slug = '' "
"ORDER BY id"
)
)
for row in rows_to_backfill:
slug = _allocate_backfill_slug(str(row.provider_type), reserved_slugs)
conn.execute(
sa.text("UPDATE upstream_providers SET slug = :slug WHERE id = :id"),
{"slug": slug, "id": row.id},
)
def upgrade() -> None:
conn = op.get_bind()
inspector = sa.inspect(conn)
columns = {c["name"] for c in inspector.get_columns("upstream_providers")}
if "slug" not in columns:
op.add_column(
"upstream_providers",
sa.Column("slug", sa.String(), nullable=True),
)
_backfill_provider_slugs(conn)
existing_indexes = {idx["name"] for idx in inspector.get_indexes("upstream_providers")}
if "ix_upstream_providers_slug" not in existing_indexes:
op.create_index(
"ix_upstream_providers_slug",
"upstream_providers",
["slug"],
unique=True,
)
def downgrade() -> None:
conn = op.get_bind()
inspector = sa.inspect(conn)
existing_indexes = {idx["name"] for idx in inspector.get_indexes("upstream_providers")}
if "ix_upstream_providers_slug" in existing_indexes:
op.drop_index("ix_upstream_providers_slug", table_name="upstream_providers")
columns = {c["name"] for c in inspector.get_columns("upstream_providers")}
if "slug" in columns:
op.drop_column("upstream_providers", "slug")

View File

@@ -1,34 +0,0 @@
"""add cli_tokens table
Revision ID: cli_tokens_001
Revises: e8f9a0b1c2d3
Create Date: 2026-04-25 00:00:00.000000
"""
from __future__ import annotations
import sqlalchemy as sa
from alembic import op
revision = "cli_tokens_001"
down_revision = "e8f9a0b1c2d3"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"cli_tokens",
sa.Column("id", sa.String(), primary_key=True, nullable=False),
sa.Column("token", sa.String(), nullable=False, unique=True),
sa.Column("name", sa.String(), nullable=False),
sa.Column("created_at", sa.Integer(), nullable=False),
sa.Column("last_used_at", sa.Integer(), nullable=True),
sa.Column("expires_at", sa.Integer(), nullable=True),
)
op.create_index("ix_cli_tokens_token", "cli_tokens", ["token"], unique=True)
def downgrade() -> None:
op.drop_index("ix_cli_tokens_token", table_name="cli_tokens")
op.drop_table("cli_tokens")

View File

@@ -1,46 +0,0 @@
"""add api key link to cashu_transactions
Revision ID: d4e5f6a7b8c9
Revises: c3d4e5f6a7b8
Create Date: 2026-04-20 00:00:00.000000
"""
import sqlalchemy as sa
import sqlmodel
from alembic import op
# revision identifiers, used by Alembic.
revision = "d4e5f6a7b8c9"
down_revision = "c3d4e5f6a7b8"
branch_labels = None
depends_on = None
def upgrade() -> None:
conn = op.get_bind()
inspector = sa.inspect(conn)
columns = [col["name"] for col in inspector.get_columns("cashu_transactions")]
indexes = {index["name"] for index in inspector.get_indexes("cashu_transactions")}
if "api_key_hashed_key" not in columns:
op.add_column(
"cashu_transactions",
sa.Column(
"api_key_hashed_key",
sqlmodel.sql.sqltypes.AutoString(),
nullable=True,
),
)
if "ix_cashu_transactions_api_key_hashed_key" not in indexes:
op.create_index(
"ix_cashu_transactions_api_key_hashed_key",
"cashu_transactions",
["api_key_hashed_key"],
unique=False,
)
def downgrade() -> None:
op.drop_index("ix_cashu_transactions_api_key_hashed_key", table_name="cashu_transactions")
op.drop_column("cashu_transactions", "api_key_hashed_key")

View File

@@ -1,20 +0,0 @@
"""merge heads: routstr_fees + api_key_to_cashu_transactions
Revision ID: e8f9a0b1c2d3
Revises: 02650cd6f028, d4e5f6a7b8c9
Create Date: 2026-04-24 00:00:00.000000
"""
# revision identifiers, used by Alembic.
revision = "e8f9a0b1c2d3"
down_revision = ("02650cd6f028", "d4e5f6a7b8c9")
branch_labels = None
depends_on = None
def upgrade() -> None:
pass
def downgrade() -> None:
pass

View File

@@ -1,25 +0,0 @@
"""add created_at to api_keys
Revision ID: f1a2b3c4d5e6
Revises: cli_tokens_001
Create Date: 2026-06-01 00:00:00.000000
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "f1a2b3c4d5e6"
down_revision = "cli_tokens_001"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Nullable on purpose: existing keys keep NULL (unknown creation time) and
# sort last; new keys get populated by the model's default_factory.
op.add_column("api_keys", sa.Column("created_at", sa.Integer(), nullable=True))
def downgrade() -> None:
op.drop_column("api_keys", "created_at")

View File

@@ -77,27 +77,29 @@ extra:
nav:
- Home: index.md
- Overview: overview.md
- Client Guide:
- Introduction: client/introduction.md
- Payment Flow: client/payments.md
- Integration: client/integration.md
- Provider Guide:
- Quick Start: provider/quickstart.md
- Dashboard: provider/dashboard.md
- Deployment: provider/deployment.md
- Configuration: provider/configuration.md
- Pricing: provider/pricing.md
- Advanced Pricing: provider/advanced-pricing.md
- Discovery: provider/discovery.md
- Tor Support: provider/tor.md
- API Reference:
- Overview: api/overview.md
- Authentication: api/authentication.md
- Endpoints: api/endpoints.md
- Errors: api/errors.md
- Getting Started:
- Overview: getting-started/overview.md
- Quick Start: getting-started/quickstart.md
- Docker Setup: getting-started/docker.md
- Configuration: getting-started/configuration.md
- User Guide:
- Introduction: user-guide/introduction.md
- Payment Flow: user-guide/payment-flow.md
- Using the API: user-guide/using-api.md
- Admin Dashboard: user-guide/admin-dashboard.md
- Models & Pricing: user-guide/models-pricing.md
- Contributing:
- Setup Development: contributing/setup.md
- Architecture: contributing/architecture.md
- Code Structure: contributing/code-structure.md
- Testing: contributing/testing.md
- API Reference:
- Overview: api/overview.md
- Authentication: api/authentication.md
- Endpoints: api/endpoints.md
- Errors: api/errors.md
- Advanced:
- Tor Support: advanced/tor.md
- Nostr Discovery: advanced/nostr.md
- Custom Pricing: advanced/custom-pricing.md
- Migrations: advanced/migrations.md

View File

@@ -1,355 +0,0 @@
# Plan: Track unsupported incoming mints in `other_mints` and include them in balances
## Goal
When a Cashu token arrives from a mint that is **not** in `settings.cashu_mints`, we currently create/use a wallet for that mint and swap value into the primary mint. Any change/surplus left behind after `melt()` remains in the foreign `token_wallet`, but that balance is not surfaced by `fetch_all_balances()` because it only iterates over configured mints.
This plan adds persistent tracking for those foreign mints in a new database table called `other_mints`, and updates balance reporting to include them.
---
## Current behavior
### Incoming unsupported mint flow
In `routstr/wallet.py`:
- `recieve_token()` deserializes the token
- if `token_obj.mint not in settings.cashu_mints`, it calls `swap_to_primary_mint(token_obj, wallet)`
- `swap_to_primary_mint()` calls `token_wallet.melt(...)` to pay the primary mint invoice
### Important detail: change is retained, not discarded
The underlying Cashu wallet library keeps any melt change:
- `Wallet.melt()` constructs blank outputs for change
- when the melt succeeds, returned change is reconstructed into proofs
- those proofs are appended to `self.proofs` and stored in the wallet DB
So surplus from unsupported mints is **not discarded**, but it may become invisible operationally.
### Visibility problem
`fetch_all_balances()` currently only loops over:
- `settings.cashu_mints`
- units `sat` and `msat`
This means balances left on unsupported mints are not shown in admin balance reporting.
---
## Proposed design
## 1. Add a new DB table: `other_mints`
Add a small table in `routstr/core/db.py` to persist unsupported mints we have seen in incoming tokens.
Suggested schema:
- `mint_url: str` primary key
- `created_at: int`
- `last_seen_at: int`
Minimal model:
```python
class OtherMint(SQLModel, table=True):
__tablename__ = "other_mints"
mint_url: str = Field(primary_key=True)
created_at: int = Field(default_factory=lambda: int(time.time()))
last_seen_at: int = Field(default_factory=lambda: int(time.time()))
```
Why minimal:
- the only required function is mint discovery/tracking
- unit handling can remain dynamic via existing balance queries over `sat` and `msat`
---
## 2. Add DB helpers for `other_mints`
In `routstr/core/db.py`, add helper functions:
### `register_other_mint(mint_url: str) -> None`
Behavior:
- if the mint is not present, insert it
- if it already exists, update `last_seen_at`
### `list_other_mints(session) -> list[str]`
Behavior:
- return all tracked unsupported mint URLs
Optional later:
- `delete_other_mint(...)`
- admin cleanup helpers
---
## 3. Register unsupported mints during token receipt
Update `recieve_token()` in `routstr/wallet.py`.
Current logic:
```python
if token_obj.mint not in settings.cashu_mints:
return await swap_to_primary_mint(token_obj, wallet)
```
Planned logic:
```python
if token_obj.mint not in settings.cashu_mints:
await db.register_other_mint(token_obj.mint)
return await swap_to_primary_mint(token_obj, wallet)
```
Why here:
- this is the earliest reliable point where we know the mint came in via an actual token
- this is exactly the path that can leave foreign-mint change behind
- it avoids needing to infer unsupported mints later from wallet internals
---
## 4. Update `fetch_all_balances()` to include `other_mints`
Current behavior only includes configured mints.
Planned behavior:
- load tracked unsupported mints from DB
- combine them with `settings.cashu_mints`
- dedupe while preserving order
- fetch balances for all tracked mints across requested units
Conceptual flow:
```python
tracked_mints = dedupe(settings.cashu_mints + other_mints_from_db)
```
Then existing per-mint/per-unit balance logic can remain mostly unchanged.
This ensures that retained change on unsupported mints becomes visible in admin balance reporting.
---
## 5. Add a balance source marker
Extend `BalanceDetail` in `routstr/wallet.py` to identify whether a balance row comes from a configured mint or an `other_mints` entry.
Suggested field:
- `source: str` with values:
- `"configured"`
- `"other"`
Updated shape:
```python
class BalanceDetail(TypedDict, total=False):
mint_url: str
unit: str
source: str
wallet_balance: int
user_balance: int
owner_balance: int
error: str
```
Why this helps:
- admin can distinguish normal configured wallet balances from foreign/unsupported balances
- avoids confusion if unexpected mint URLs show up in the balances API/UI
---
## 6. Admin/API impact
Backend impact is minimal because `/admin/api/balances` already returns `fetch_all_balances()` output.
Effects:
- supported mints continue to show as before
- tracked unsupported mints will also appear
- UI can optionally display the new `source` field
No API contract break is expected if the frontend ignores unknown fields.
---
## 7. Payout behavior: do not change in phase 1
`periodic_payout()` currently only iterates over `settings.cashu_mints`.
Recommendation for this change:
- **do not** expand `periodic_payout()` to include `other_mints` yet
- only improve visibility through balance reporting
Reason:
- automatic payout from unsupported/foreign mints may be operationally undesirable
- visibility should come first, automation second
Possible future phase:
- add optional sweeping/payout support for `other_mints`
- or provide an admin-triggered withdrawal/sweep flow
---
## 8. Logging improvements (optional)
Optional follow-up improvement in `swap_to_primary_mint()`:
- capture the return value from `token_wallet.melt(...)`
- if feasible, log any reported change amount
- otherwise, rely on wallet balance reporting to surface residual amounts
This is useful but not required for the first implementation.
---
## Files to change
### `routstr/core/db.py`
Add:
- `OtherMint` SQLModel
- `register_other_mint()`
- `list_other_mints()`
### `migrations/versions/<new_revision>_add_other_mints_table.py`
Create migration to add the `other_mints` table.
### `routstr/wallet.py`
Update:
- `recieve_token()` to register unsupported mints
- `BalanceDetail` to include `source`
- `fetch_all_balances()` to include both configured and tracked unsupported mints
### `routstr/core/admin.py`
Likely no backend changes required unless a dedicated `other_mints` API is desired.
---
## Behavior rules
### Register a mint when
- an incoming token is processed
- the token mint is not in `settings.cashu_mints`
### Do not remove automatically when
- balance reaches zero
Reason:
- historical visibility is useful
- avoids flapping entries in the admin balance list
- mint may receive additional unsupported tokens later
Potential future enhancement:
- admin endpoint to prune zero-balance `other_mints`
---
## Edge cases
### A mint later becomes configured
If a mint in `other_mints` is later added to `settings.cashu_mints`:
- deduplication prevents duplicate balance rows
- `source` should resolve to `configured`
### Unsupported mint with zero balance
A tracked unsupported mint may show zero balances.
Initial recommendation:
- allow it to appear
- consider later filtering zero-balance `other` rows if the UI becomes noisy
### Units
Balance fetching can continue to query both `sat` and `msat` for each tracked mint.
If a mint has no proofs in one unit, current error/zero handling can continue to apply.
---
## Test plan
### DB tests
- registering a new unsupported mint inserts a row
- registering the same mint again updates `last_seen_at` without duplication
- listing other mints returns expected mint URLs
### Wallet tests
#### `recieve_token()`
- when mint is unsupported, `db.register_other_mint()` is called before swap
- when mint is configured, `db.register_other_mint()` is not called
#### `fetch_all_balances()`
- includes configured mints
- includes `other_mints` from DB
- dedupes if a mint exists in both configured and other lists
- sets `source` correctly
### Regression tests
- existing trusted mint balance reporting remains unchanged
- `/admin/api/balances` continues to work
---
## Recommended implementation order
1. Add `OtherMint` model to `routstr/core/db.py`
2. Add Alembic migration for `other_mints`
3. Add `register_other_mint()` and `list_other_mints()` helpers
4. Update `recieve_token()` to register unsupported mints
5. Update `fetch_all_balances()` to union configured + tracked other mints
6. Add `source` to `BalanceDetail`
7. Add/adjust tests
---
## Summary
This change solves an operational visibility problem:
- unsupported incoming mints can leave retained change in foreign wallets
- those funds are currently preserved but not surfaced in balance reporting
- introducing `other_mints` makes those mints discoverable and auditable
- expanding `fetch_all_balances()` ensures their balances are visible in admin tooling
Recommended scope for the first pass:
- track unsupported mints in DB
- include them in balance reporting
- mark them as `source="other"`
- do not yet change payout/sweeping behavior

View File

@@ -1,6 +1,6 @@
[project]
name = "routstr"
version = "0.4.4"
version = "0.2.1"
description = "Payment proxy for your LLM endpoint using cashu and nostr."
readme = "README.md"
requires-python = ">=3.11"
@@ -10,18 +10,17 @@ dependencies = [
"aiosqlite>=0.20",
"sqlmodel>=0.0.24",
"httpx[socks]>=0.25.2",
"h11>=0.14",
"greenlet>=3.2.1",
"alembic>=1.13",
"python-json-logger>=2.0.0",
"cashu>=0.20",
"cashu",
"secp256k1",
"marshmallow>=3.13,<4.0",
"websockets>=12.0",
"nostr>=0.0.2",
"mdurl==0.1.2",
"pillow>=10",
"openai>=1.98.0",
"litellm>=1.55.0",
]
[dependency-groups]
@@ -74,7 +73,6 @@ packages = ["routstr"]
[tool.ruff.lint]
select = ["E", "F", "I"]
ignore = ["E501"]
exclude = ["examples"]
[tool.mypy]
python_version = "3.11"
@@ -87,3 +85,4 @@ disallow_untyped_decorators = true
[tool.uv.sources]
routstr = { workspace = true }
secp256k1 = { git = "https://github.com/saschanaz/secp256k1-py", branch = "upgrade060" }

View File

@@ -84,32 +84,98 @@ def get_provider_penalty(provider: "BaseUpstreamProvider") -> float:
return penalty
def should_prefer_model(
candidate_model: "Model",
candidate_provider: "BaseUpstreamProvider",
current_model: "Model",
current_provider: "BaseUpstreamProvider",
alias: str,
) -> bool:
"""Determine if candidate model should replace current model for an alias.
This is the core decision function for model prioritization. It considers:
1. Alias matching quality (exact match vs. canonical slug match)
2. Model cost (lower is better)
3. Provider penalties (e.g., slight preference against OpenRouter)
Args:
candidate_model: The new model being considered
candidate_provider: Provider offering the candidate model
current_model: The currently selected model for this alias
current_provider: Provider offering the current model
alias: The model alias being mapped
Returns:
True if candidate should replace current, False otherwise
"""
def get_base_model_id(model_id: str) -> str:
"""Get base model ID by removing provider prefix."""
return model_id.split("/", 1)[1] if "/" in model_id else model_id
def alias_priority(model: "Model") -> int:
"""Rank how strong the mapping of alias->model is.
Highest priority when alias exactly equals the model ID without provider prefix.
Next when alias equals canonical slug without prefix. Otherwise lowest.
"""
model_base = get_base_model_id(model.id)
if model_base == alias:
return 3
if model.canonical_slug:
canonical_base = get_base_model_id(model.canonical_slug)
if canonical_base == alias:
return 2
return 1
candidate_alias_priority = alias_priority(candidate_model)
current_alias_priority = alias_priority(current_model)
# If candidate has better alias match, prefer it regardless of cost
if candidate_alias_priority > current_alias_priority:
return True
# If current has better alias match, keep it regardless of cost
if current_alias_priority > candidate_alias_priority:
return False
# Same alias priority - compare costs
candidate_cost = calculate_model_cost_score(candidate_model)
current_cost = calculate_model_cost_score(current_model)
# Apply provider penalties
candidate_adjusted = candidate_cost * get_provider_penalty(candidate_provider)
current_adjusted = current_cost * get_provider_penalty(current_provider)
# Prefer lower adjusted cost
should_replace = candidate_adjusted < current_adjusted
return should_replace
def create_model_mappings(
upstreams: list["BaseUpstreamProvider"],
overrides_by_key: dict[tuple[str, int], tuple],
disabled_model_keys: set[tuple[str, int]],
) -> tuple[
dict[str, "Model"], dict[str, list["BaseUpstreamProvider"]], dict[str, "Model"]
]:
overrides_by_id: dict[str, tuple],
disabled_model_ids: set[str],
) -> tuple[dict[str, "Model"], dict[str, "BaseUpstreamProvider"], dict[str, "Model"]]:
"""Create optimal model mappings based on cost and provider preferences.
This is the main entry point for the algorithm. It processes all upstream providers
and creates three mappings based on cost optimization:
1. model_instances: alias -> Model (all model aliases mapped to their Model objects)
2. provider_map: alias -> List[UpstreamProvider] (sorted list of providers for each alias)
2. provider_map: alias -> UpstreamProvider (which provider to use for each alias)
3. unique_models: base_id -> Model (unique models without provider prefixes)
The algorithm:
- Processes non-OpenRouter providers first (they're typically cheaper)
- Then processes OpenRouter models (they can still win if cheaper)
- For each model alias, collects all candidates and sorts them by priority and cost.
- For each model alias, uses should_prefer_model() to select the best provider
Args:
upstreams: List of all upstream provider instances
overrides_by_key: Dict of model overrides from database
{(model_id_lower, upstream_provider_id): (ModelRow, fee)}
disabled_model_keys: Set of provider-scoped model keys that should be excluded
overrides_by_id: Dict of model overrides from database {model_id: (ModelRow, fee)}
disabled_model_ids: Set of model IDs that should be excluded
Returns:
Tuple of (model_instances, provider_map, unique_models)
@@ -117,34 +183,15 @@ def create_model_mappings(
from .payment.models import _row_to_model
from .upstream.helpers import resolve_model_alias
candidates: dict[str, list[tuple["Model", "BaseUpstreamProvider"]]] = {}
model_instances: dict[str, "Model"] = {}
provider_map: dict[str, "BaseUpstreamProvider"] = {}
unique_models: dict[str, "Model"] = {}
seen_model_provider: set[tuple[str, str]] = set()
providers_by_db_id: dict[int, "BaseUpstreamProvider"] = {}
for upstream in upstreams:
db_id = getattr(upstream, "db_id", None)
if isinstance(db_id, int):
providers_by_db_id[db_id] = upstream
# Group upstreams by URL and keep only the one with the lowest fee for each URL
upstreams_by_url: dict[str, list["BaseUpstreamProvider"]] = {}
for upstream in upstreams:
url = getattr(upstream, "base_url", "")
if url not in upstreams_by_url:
upstreams_by_url[url] = []
upstreams_by_url[url].append(upstream)
filtered_upstreams: list["BaseUpstreamProvider"] = []
for providers in upstreams_by_url.values():
best_provider = min(providers, key=lambda p: p.provider_fee)
filtered_upstreams.append(best_provider)
# Separate OpenRouter from other providers
openrouter: "BaseUpstreamProvider" | None = None
other_upstreams: list["BaseUpstreamProvider"] = []
for upstream in filtered_upstreams:
for upstream in upstreams:
base_url = getattr(upstream, "base_url", "")
if base_url == "https://openrouter.ai/api/v1":
openrouter = upstream
@@ -155,47 +202,38 @@ def create_model_mappings(
"""Get base model ID by removing provider prefix."""
return model_id.split("/", 1)[1] if "/" in model_id else model_id
def get_provider_identity(upstream: "BaseUpstreamProvider") -> str:
"""Get a stable provider identity used for deduplication."""
db_id = getattr(upstream, "db_id", None)
if isinstance(db_id, int):
return f"db:{db_id}"
provider_type = str(getattr(upstream, "provider_type", "") or "").lower()
base_url = str(getattr(upstream, "base_url", "") or "").lower()
return f"{provider_type}|{base_url}"
def _add_candidate(
def _maybe_set_alias(
alias: str, model: "Model", provider: "BaseUpstreamProvider"
) -> None:
"""Add candidate model/provider for an alias."""
"""Set alias to model/provider if not set or if new model is preferred."""
alias_lower = alias.lower()
if alias_lower not in candidates:
candidates[alias_lower] = []
candidates[alias_lower].append((model, provider))
existing_model = model_instances.get(alias_lower)
if not existing_model:
# No existing mapping, set it
model_instances[alias_lower] = model
provider_map[alias_lower] = provider
else:
# Check if candidate should replace existing
existing_provider = provider_map[alias_lower]
if should_prefer_model(
model, provider, existing_model, existing_provider, alias
):
model_instances[alias_lower] = model
provider_map[alias_lower] = provider
def process_provider_models(
upstream: "BaseUpstreamProvider", is_openrouter: bool = False
) -> None:
"""Process all models from a given provider."""
upstream_prefix = getattr(upstream, "upstream_name", None)
provider_key = get_provider_identity(upstream)
upstream_db_id = getattr(upstream, "db_id", None)
for model in upstream.get_cached_models():
model_key = (
(model.id.lower(), upstream_db_id)
if isinstance(upstream_db_id, int)
else None
)
if not model.enabled or (
model_key is not None and model_key in disabled_model_keys
):
if not model.enabled or model.id in disabled_model_ids:
continue
# Apply overrides only for this provider's model row.
if model_key is not None and model_key in overrides_by_key:
override_row, provider_fee = overrides_by_key[model_key]
# Apply overrides if present
if model.id in overrides_by_id:
override_row, provider_fee = overrides_by_id[model.id]
model_to_use = _row_to_model(
override_row, apply_provider_fee=True, provider_fee=provider_fee
)
@@ -204,15 +242,14 @@ def create_model_mappings(
# Add to unique models
base_id = get_base_model_id(model_to_use.id)
unique_key = model_to_use.forwarded_model_id or base_id
if not is_openrouter or unique_key not in unique_models:
if not is_openrouter or base_id not in unique_models:
unique_model = model_to_use.copy(
update={
"id": base_id,
"upstream_provider_id": upstream.provider_type,
}
)
unique_models[unique_key] = unique_model
unique_models[base_id] = unique_model
# Get all aliases for this model
aliases = resolve_model_alias(
@@ -227,162 +264,23 @@ def create_model_mappings(
if prefixed_id not in aliases:
aliases.append(prefixed_id)
# Register forwarded_model_id as a routable alias
if model_to_use.forwarded_model_id and model_to_use.forwarded_model_id not in aliases:
aliases.append(model_to_use.forwarded_model_id)
# Try to set each alias
for alias in aliases:
_add_candidate(alias, model_to_use, upstream)
seen_model_provider.add((model_to_use.id.lower(), provider_key))
_maybe_set_alias(alias, model_to_use, upstream)
# Process non-OpenRouter providers first
# Process non-OpenRouter providers first (they're typically cheaper)
for upstream in other_upstreams:
process_provider_models(upstream, is_openrouter=False)
# Process OpenRouter last
# Process OpenRouter last - models only win if they're cheaper or better matched
if openrouter:
process_provider_models(openrouter, is_openrouter=True)
# Include enabled DB overrides even when provider discovery misses models.
# This is important for deployment-based providers like Azure.
for (model_id, upstream_provider_id), override_data in overrides_by_key.items():
if (model_id, upstream_provider_id) in disabled_model_keys:
continue
override_row, provider_fee = override_data
upstream_for_override = providers_by_db_id.get(upstream_provider_id)
if upstream_for_override is None:
continue
provider_key = get_provider_identity(upstream_for_override)
dedupe_key = (model_id.lower(), provider_key)
if dedupe_key in seen_model_provider:
continue
try:
model_to_use = _row_to_model(
override_row, apply_provider_fee=True, provider_fee=provider_fee
)
except Exception as exc:
logger.warning(
"Skipping invalid model override while building model mappings",
extra={
"model_id": model_id,
"upstream_provider_id": upstream_provider_id,
"error": str(exc),
"error_type": type(exc).__name__,
},
)
continue
if not model_to_use.enabled:
continue
base_id = get_base_model_id(model_to_use.id)
unique_key = model_to_use.forwarded_model_id or base_id
is_openrouter = (
getattr(upstream_for_override, "base_url", "")
== "https://openrouter.ai/api/v1"
)
if not is_openrouter or unique_key not in unique_models:
unique_model = model_to_use.copy(
update={
"id": base_id,
"upstream_provider_id": upstream_for_override.provider_type,
}
)
unique_models[unique_key] = unique_model
try:
aliases = resolve_model_alias(
model_to_use.id,
model_to_use.canonical_slug,
alias_ids=model_to_use.alias_ids,
)
except Exception as exc:
logger.warning(
"Skipping model aliases for invalid override model",
extra={
"model_id": model_id,
"upstream_provider_id": upstream_provider_id,
"error": str(exc),
"error_type": type(exc).__name__,
},
)
continue
upstream_prefix = getattr(upstream_for_override, "upstream_name", None)
if upstream_prefix and "/" not in model_to_use.id:
prefixed_id = f"{upstream_prefix}/{model_to_use.id}"
if prefixed_id not in aliases:
aliases.append(prefixed_id)
# Register forwarded_model_id as a routable alias
if model_to_use.forwarded_model_id and model_to_use.forwarded_model_id not in aliases:
aliases.append(model_to_use.forwarded_model_id)
for alias in aliases:
_add_candidate(alias, model_to_use, upstream_for_override)
seen_model_provider.add(dedupe_key)
# Sort candidates and build final maps
model_instances: dict[str, "Model"] = {}
provider_map: dict[str, list["BaseUpstreamProvider"]] = {}
def alias_priority(model: "Model", alias: str) -> int:
"""Rank how strong the mapping of alias->model is.
forwarded_model_id is the most specific identifier (set per-provider
instance), so a match there should beat a model_id match. This way,
when multiple providers have the same model_id but different
forwarded_model_ids, the one whose forwarded_model_id equals the
requested alias wins.
"""
if (
model.forwarded_model_id
and model.forwarded_model_id.lower() == alias
):
return 5
if (
model.id
and model.id.lower() == alias
):
return 4
model_base = get_base_model_id(model.id)
if model_base == alias:
return 3
if model.canonical_slug:
canonical_base = get_base_model_id(model.canonical_slug)
if canonical_base == alias:
return 2
return 1
for alias, items in candidates.items():
# Sort key: (priority DESC, cost ASC)
# Using negative cost for DESC sort overall to keep high priority first
def sort_key(item: tuple["Model", "BaseUpstreamProvider"]) -> tuple[int, float]:
model, provider = item
priority = alias_priority(model, alias)
cost = calculate_model_cost_score(model)
penalty = get_provider_penalty(provider)
adjusted_cost = cost * penalty
return (priority, -adjusted_cost)
items.sort(key=sort_key, reverse=True)
best_model, best_provider = items[0]
model_instances[alias] = best_model
provider_map[alias] = [p for _, p in items]
# Log provider distribution (using top provider for stats)
# Log provider distribution
provider_counts: dict[str, int] = {}
for providers in provider_map.values():
if providers:
provider = providers[0]
provider_name = getattr(provider, "upstream_name", "unknown")
provider_counts[provider_name] = provider_counts.get(provider_name, 0) + 1
for provider in provider_map.values():
provider_name = getattr(provider, "upstream_name", "unknown")
provider_counts[provider_name] = provider_counts.get(provider_name, 0) + 1
logger.debug(
f"Updated model mappings with ({len(unique_models)} unique models and {len(model_instances)} aliases)",

File diff suppressed because it is too large Load Diff

View File

@@ -1,33 +1,17 @@
import asyncio
import hashlib
import time
from time import monotonic
from typing import Annotated, NoReturn
from fastapi import APIRouter, Depends, Header, HTTPException
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from sqlmodel import col, or_, select, update
from .auth import get_billing_key, validate_bearer_key
from .core.db import (
ApiKey,
AsyncSession,
CashuTransaction,
get_session,
store_cashu_transaction,
)
from .auth import validate_bearer_key
from .core.db import ApiKey, AsyncSession, get_session
from .core.logging import get_logger
from .core.settings import settings
from .lightning import lightning_router
from .wallet import (
classify_redemption_error,
credit_balance,
is_mint_connection_error,
recieve_token,
send_to_lnurl,
send_token,
)
from .wallet import credit_balance, recieve_token, send_to_lnurl, send_token
router = APIRouter()
balance_router = APIRouter(prefix="/v1/balance")
@@ -48,50 +32,14 @@ async def get_key_from_header(
)
async def get_balance_info(key: ApiKey, session: AsyncSession) -> dict:
billing_key = await get_billing_key(key, session)
info = {
"api_key": "sk-" + key.hashed_key,
"balance": billing_key.total_balance,
"reserved": billing_key.reserved_balance,
"is_child": key.parent_key_hash is not None,
"total_requests": key.total_requests,
"total_spent": key.total_spent,
"balance_limit": key.balance_limit,
"balance_limit_reset": key.balance_limit_reset,
"validity_date": key.validity_date,
}
if key.parent_key_hash:
info["parent_key_preview"] = key.parent_key_hash[:8] + "..."
else:
# Fetch child keys if this is a parent key
statement = select(ApiKey).where(ApiKey.parent_key_hash == key.hashed_key)
results = await session.exec(statement)
child_keys = results.all()
if child_keys:
info["child_keys"] = [
{
"api_key": "sk-" + ck.hashed_key,
"total_requests": ck.total_requests,
"total_spent": ck.total_spent,
"balance_limit": ck.balance_limit,
"balance_limit_reset": ck.balance_limit_reset,
"validity_date": ck.validity_date,
}
for ck in child_keys
]
return info
# TODO: remove this endpoint when frontend is updated
@router.get("/", include_in_schema=False)
async def account_info(
key: ApiKey = Depends(get_key_from_header),
session: AsyncSession = Depends(get_session),
) -> dict:
return await get_balance_info(key, session)
async def account_info(key: ApiKey = Depends(get_key_from_header)) -> dict:
return {
"api_key": "sk-" + key.hashed_key,
"balance": key.balance,
"reserved": key.reserved_balance,
}
# TODO: Implement POST /v1/wallet/create endpoint
@@ -108,24 +56,9 @@ async def account_info(
@router.get("/create")
async def create_balance(
initial_balance_token: str,
balance_limit: int | None = None,
balance_limit_reset: str | None = None,
validity_date: int | None = None,
session: AsyncSession = Depends(get_session),
initial_balance_token: str, session: AsyncSession = Depends(get_session)
) -> dict:
key = await validate_bearer_key(initial_balance_token, session)
if balance_limit is not None or balance_limit_reset or validity_date:
key.balance_limit = balance_limit
key.balance_limit_reset = balance_limit_reset
key.validity_date = validity_date
if balance_limit_reset:
key.balance_limit_reset_date = int(time.time())
session.add(key)
await session.commit()
await session.refresh(key)
return {
"api_key": "sk-" + key.hashed_key,
"balance": key.balance,
@@ -133,11 +66,12 @@ async def create_balance(
@router.get("/info")
async def wallet_info(
key: ApiKey = Depends(get_key_from_header),
session: AsyncSession = Depends(get_session),
) -> dict:
return await get_balance_info(key, session)
async def wallet_info(key: ApiKey = Depends(get_key_from_header)) -> dict:
return {
"api_key": "sk-" + key.hashed_key,
"balance": key.balance,
"reserved": key.reserved_balance,
}
class TopupRequest(BaseModel):
@@ -151,8 +85,6 @@ async def topup_wallet_endpoint(
key: ApiKey = Depends(get_key_from_header),
session: AsyncSession = Depends(get_session),
) -> dict[str, int]:
billing_key = await get_billing_key(key, session)
if topup_request is not None:
cashu_token = topup_request.cashu_token
if cashu_token is None:
@@ -162,19 +94,17 @@ async def topup_wallet_endpoint(
if len(cashu_token) < 10 or "cashu" not in cashu_token:
raise HTTPException(status_code=400, detail="Invalid token format")
try:
amount_msats = await credit_balance(cashu_token, billing_key, session)
except Exception as e:
# Shared taxonomy so top-up matches the bearer/X-Cashu paths (503 for an
# unreachable mint, 422 for fee/swap failures, 400 for token faults).
classified = classify_redemption_error(e)
if classified is None:
logger.error(
"topup_wallet_endpoint: unhandled error",
extra={"error": str(e), "error_type": type(e).__name__},
)
raise HTTPException(status_code=500, detail="Internal server error")
_type, status_code, message, _code = classified
raise HTTPException(status_code=status_code, detail=message)
amount_msats = await credit_balance(cashu_token, key, session)
except ValueError as e:
error_msg = str(e)
if "already spent" in error_msg.lower():
raise HTTPException(status_code=400, detail="Token already spent")
elif "invalid" in error_msg.lower() or "decode" in error_msg.lower():
raise HTTPException(status_code=400, detail="Invalid token format")
else:
raise HTTPException(status_code=400, detail="Failed to redeem token")
except Exception:
raise HTTPException(status_code=500, detail="Internal server error")
return {"msats": amount_msats}
@@ -207,153 +137,24 @@ async def _refund_cache_set(authorization: str, value: dict[str, str]) -> None:
_refund_cache[key] = (expiry, value)
async def _lookup_key_no_create(
bearer_value: str, session: AsyncSession
) -> ApiKey | None:
"""Look up an existing API key without creating one Used by the refund endpoint"""
if bearer_value.startswith("sk-"):
return await session.get(ApiKey, bearer_value[3:])
if bearer_value.startswith("cashu"):
hashed = hashlib.sha256(bearer_value.encode()).hexdigest()
return await session.get(ApiKey, hashed)
return None
async def _restore_balance(
session: AsyncSession, hashed_key: str, balance: int, reserved_balance: int, mint_url: str
) -> None:
"""Restore balance after a failed refund mint attempt."""
restore_stmt = (
update(ApiKey)
.where(col(ApiKey.hashed_key) == hashed_key)
.values(
balance=col(ApiKey.balance) + balance,
reserved_balance=col(ApiKey.reserved_balance) + reserved_balance,
)
)
await session.exec(restore_stmt) # type: ignore[call-overload]
await session.commit()
logger.info(
"refund_wallet_endpoint: balance restored after mint failure",
extra={"hashed_key": hashed_key, "restored_balance": balance, "mint_url": mint_url},
)
@router.post("/refund", response_model=None)
@router.post("/refund")
async def refund_wallet_endpoint(
authorization: Annotated[str | None, Header()] = None,
x_cashu: Annotated[str | None, Header()] = None,
authorization: Annotated[str, Header(...)],
session: AsyncSession = Depends(get_session),
) -> JSONResponse | dict[str, str]:
if x_cashu:
# Find the "in" transaction by the original payment token
in_tx_result = await session.exec(
select(CashuTransaction).where(
CashuTransaction.token == x_cashu,
CashuTransaction.type == "in",
)
)
in_tx = in_tx_result.first()
if in_tx is None:
raise HTTPException(status_code=404, detail="Refund not found")
# Use the request_id to find the associated "out" (refund) transaction
if in_tx.request_id is None:
raise HTTPException(status_code=404, detail="Refund not found")
out_tx_result = await session.exec(
select(CashuTransaction).where(
CashuTransaction.request_id == in_tx.request_id,
CashuTransaction.type == "out",
)
)
out_tx = out_tx_result.first()
if out_tx is None:
# The "in" row exists with a request_id, but the "out" (refund)
# row hasn't been written yet — the upstream request is still in
# flight and the refund will be minted once it completes. Tell the
# client to retry instead of 404ing permanently (race condition
# where /v1/wallet/refund is polled before the refund exists).
logger.debug(
"refund_wallet_endpoint: refund pending (in row exists, out row not yet created)",
extra={"request_id": in_tx.request_id},
)
raise HTTPException(
status_code=425,
detail="Refund is pending; retry shortly.",
headers={"Retry-After": "2"},
)
if out_tx.swept:
raise HTTPException(status_code=410, detail="Refund has been swept")
out_tx.collected = True
session.add(out_tx)
await session.commit()
body: dict[str, str] = {"token": out_tx.token}
if out_tx.unit == "sat":
body["sats"] = str(out_tx.amount)
else:
body["msats"] = str(out_tx.amount)
return JSONResponse(content=body, headers={"X-Cashu": out_tx.token})
if authorization is None or not authorization.startswith("Bearer "):
) -> dict[str, str]:
if not authorization.startswith("Bearer "):
raise HTTPException(
status_code=401,
detail="Invalid authorization. Use 'Bearer <cashu-token>' or 'Bearer <api-key>'",
)
bearer_value: str = authorization[7:]
key: ApiKey | None = await _lookup_key_no_create(bearer_value, session)
if key is None:
raise HTTPException(
status_code=401,
detail="Key not found. Deposit first via /v1/wallet/create before requesting a refund.",
)
if key.total_balance <= 0:
if cached := await _refund_cache_get(bearer_value):
return cached
if cached := await _refund_cache_get(bearer_value):
return cached
if key.parent_key_hash:
raise HTTPException(
status_code=400,
detail="Cannot refund child key. Please refund the parent key instead.",
)
if key.reserved_balance > 0:
# Release the reservation if it is stale
cutoff = int(time.time()) - settings.stale_reservation_timeout_seconds
stale_release_stmt = (
update(ApiKey)
.where(col(ApiKey.hashed_key) == key.hashed_key)
.where(col(ApiKey.reserved_balance) > 0)
.where(
or_(
col(ApiKey.reserved_at).is_(None),
col(ApiKey.reserved_at) < cutoff,
)
)
.values(reserved_balance=0, reserved_at=None)
)
stale_result = await session.exec(stale_release_stmt) # type: ignore[call-overload]
await session.commit()
if stale_result.rowcount == 0:
raise HTTPException(
status_code=400,
detail="Cannot refund key. There are ongoing requests for this api key.",
)
await session.refresh(key)
logger.warning(
"refund_wallet_endpoint: released stale reservation before refund",
extra={
"hashed_key": key.hashed_key,
"stale_timeout_seconds": settings.stale_reservation_timeout_seconds,
},
)
remaining_balance_msats: int = key.total_balance
key: ApiKey = await validate_bearer_key(bearer_value, session)
remaining_balance_msats: int = key.balance
if key.refund_currency == "sat":
remaining_balance = remaining_balance_msats // 1000
@@ -365,51 +166,22 @@ async def refund_wallet_endpoint(
elif remaining_balance <= 0:
raise HTTPException(status_code=400, detail="No balance to refund")
# Capture values before debit — the session may refresh key after commit
pre_debit_balance = key.balance
pre_debit_reserved = key.reserved_balance
# --- DEBIT FIRST: atomically zero the balance before minting tokens ---
# This prevents the race where a concurrent topup/spend happens between
# reading the balance and minting the refund token (double-spend).
debit_stmt = (
update(ApiKey)
.where(col(ApiKey.hashed_key) == key.hashed_key)
.where(col(ApiKey.balance) == pre_debit_balance)
.where(col(ApiKey.reserved_balance) == pre_debit_reserved)
.values(balance=0, reserved_balance=0, reserved_at=None)
)
debit_result = await session.exec(debit_stmt) # type: ignore[call-overload]
await session.commit()
if debit_result.rowcount == 0:
# Balance changed between read and debit — another request is active
raise HTTPException(
status_code=409,
detail="Balance changed concurrently. Please retry the refund.",
)
# --- MINT: balance is locked at zero, safe to create the refund token ---
# Proofs from untrusted mints are swapped to primary_mint on receive.
# Use primary_mint unless key.refund_mint_url is an explicitly trusted mint.
effective_refund_mint = (
key.refund_mint_url
if key.refund_mint_url and key.refund_mint_url in settings.cashu_mints
else settings.primary_mint
)
# Perform refund operation first, before modifying balance
try:
if key.refund_address:
from .core.settings import settings as global_settings
await send_to_lnurl(
remaining_balance,
key.refund_currency or "sat",
effective_refund_mint,
key.refund_mint_url or global_settings.primary_mint,
key.refund_address,
)
result = {"recipient": key.refund_address}
else:
refund_currency = key.refund_currency or "sat"
token = await send_token(
remaining_balance, refund_currency, effective_refund_mint
remaining_balance, refund_currency, key.refund_mint_url
)
result = {"token": token}
@@ -418,105 +190,30 @@ async def refund_wallet_endpoint(
else:
result["msats"] = str(remaining_balance_msats)
if "token" in result:
logger.info(
"refund_wallet_endpoint: cashu token issued",
extra={
"path": "/v1/wallet/refund",
"token": result["token"],
"amount": remaining_balance,
"currency": key.refund_currency or "sat",
},
)
except HTTPException:
# Minting failed — restore the debited balance
await _restore_balance(session, key.hashed_key, pre_debit_balance, pre_debit_reserved, key.refund_mint_url or "")
# Re-raise HTTP exceptions (like 400 for balance too small)
raise
except Exception as e:
# Minting failed — restore the debited balance
await _restore_balance(session, key.hashed_key, pre_debit_balance, pre_debit_reserved, key.refund_mint_url or "")
# If refund fails, don't modify the database
error_msg = str(e)
logger.error(
"refund_wallet_endpoint: mint/send failed",
extra={
"error": error_msg,
"error_type": type(e).__name__,
"hashed_key": key.hashed_key,
"remaining_balance": remaining_balance,
"refund_currency": key.refund_currency,
"refund_mint_url": key.refund_mint_url,
"has_refund_address": bool(key.refund_address),
},
)
if is_mint_connection_error(e):
if (
"mint" in error_msg.lower()
or "connection" in error_msg.lower()
or isinstance(e, Exception)
and "ConnectError" in str(type(e))
):
raise HTTPException(status_code=503, detail="Mint service unavailable")
else:
raise HTTPException(status_code=500, detail="Refund failed")
await _refund_cache_set(bearer_value, result)
if "token" in result:
try:
await store_cashu_transaction(
token=result["token"],
amount=remaining_balance,
unit=key.refund_currency or "sat",
mint_url=key.refund_mint_url,
typ="out",
collected=False,
source="apikey",
api_key_hashed_key=key.hashed_key,
)
except Exception:
pass # store_cashu_transaction already logs
logger.info(
"refund_wallet_endpoint: refund successful",
extra={
"refunded_msats": remaining_balance_msats,
"previous_reserved_balance": key.reserved_balance,
},
)
await session.delete(key)
await session.commit()
return result
@router.get("/history")
async def wallet_history(
key: ApiKey = Depends(get_key_from_header),
session: AsyncSession = Depends(get_session),
) -> dict[str, list[dict[str, str | int | bool | None]]]:
if key.parent_key_hash:
raise HTTPException(
status_code=400,
detail="Cannot view child key history. Please use the parent key instead.",
)
result = await session.exec(
select(CashuTransaction)
.where(CashuTransaction.api_key_hashed_key == key.hashed_key)
.order_by(col(CashuTransaction.created_at).desc())
)
transactions = result.all()
return {
"transactions": [
{
"id": tx.id,
"type": tx.type,
"source": tx.source,
"amount": tx.amount,
"unit": tx.unit,
"mint_url": tx.mint_url,
"created_at": tx.created_at,
"collected": tx.collected,
"swept": tx.swept,
}
for tx in transactions
]
}
@router.post("/donate")
async def donate(token: str, ref: str | None = None) -> str:
try:
@@ -530,133 +227,6 @@ async def donate(token: str, ref: str | None = None) -> str:
return "Invalid token."
class ChildKeyRequest(BaseModel):
count: int
balance_limit: int | None = None
balance_limit_reset: str | None = None
validity_date: int | None = None
@router.post("/child-key")
async def create_child_key(
payload: ChildKeyRequest,
key: ApiKey = Depends(get_key_from_header),
session: AsyncSession = Depends(get_session),
) -> dict:
"""Creates one or more child API keys that use the parent's balance."""
# Log incoming request for debugging
logger.debug(f"Child key creation request: count={payload.count}")
count = payload.count
if count < 1 or count > 50:
raise HTTPException(status_code=400, detail="Count must be between 1 and 50.")
# Check if this is already a child key
if key.parent_key_hash:
raise HTTPException(
status_code=400,
detail="Cannot create a child key for another child key.",
)
cost_per_key = settings.child_key_cost
total_cost = cost_per_key * count
if key.total_balance < total_cost:
raise HTTPException(
status_code=402,
detail=f"Insufficient balance to create {count} child keys. {total_cost} mSats required.",
)
# Deduct cost from parent atomically — guards against concurrent requests
# that both pass the balance check above on stale in-memory state.
deduct_stmt = (
update(ApiKey)
.where(col(ApiKey.hashed_key) == key.hashed_key)
.where(col(ApiKey.balance) - col(ApiKey.reserved_balance) >= total_cost)
.values(
balance=col(ApiKey.balance) - total_cost,
total_spent=col(ApiKey.total_spent) + total_cost,
)
)
result = await session.exec(deduct_stmt) # type: ignore[call-overload]
if result.rowcount == 0:
raise HTTPException(
status_code=402,
detail=f"Insufficient balance to create {count} child keys. {total_cost} mSats required.",
)
# Generate new keys
import secrets
new_keys = []
for _ in range(count):
new_key_raw = secrets.token_hex(32)
new_key_hash = new_key_raw # We use the raw key as the hash for sk- keys
child_key = ApiKey(
hashed_key=new_key_hash,
balance=0,
parent_key_hash=key.hashed_key,
balance_limit=payload.balance_limit,
balance_limit_reset=payload.balance_limit_reset,
balance_limit_reset_date=int(time.time())
if payload.balance_limit_reset
else None,
validity_date=payload.validity_date,
)
session.add(child_key)
new_keys.append("sk-" + new_key_hash)
await session.commit()
await session.refresh(key)
response_data = {
"api_keys": new_keys,
"count": count,
"cost_msats": total_cost,
"cost_sats": total_cost // 1000,
"parent_balance": key.balance,
"parent_balance_sats": key.balance // 1000,
}
logger.debug(f"Child key creation response: {response_data}")
return response_data
class ChildKeyResetRequest(BaseModel):
child_key: str
@router.post("/child-key/reset")
async def reset_child_key_spent(
payload: ChildKeyResetRequest,
key: ApiKey = Depends(get_key_from_header),
session: AsyncSession = Depends(get_session),
) -> dict:
"""Resets the total_spent of a child key. Must be called by the parent."""
child_key_raw = payload.child_key
if child_key_raw.startswith("sk-"):
child_key_raw = child_key_raw[3:]
child_key = await session.get(ApiKey, child_key_raw)
if not child_key:
raise HTTPException(status_code=404, detail="Child key not found.")
if child_key.parent_key_hash != key.hashed_key:
raise HTTPException(
status_code=403, detail="Unauthorized. You are not the parent of this key."
)
child_key.total_spent = 0
if child_key.balance_limit_reset:
child_key.balance_limit_reset_date = int(time.time())
session.add(child_key)
await session.commit()
return {"success": True, "message": "Child key balance reset successfully."}
@router.api_route(
"/{path:path}",
methods=["GET", "POST", "PUT", "DELETE"],
@@ -669,7 +239,7 @@ async def wallet_catch_all(path: str) -> NoReturn:
)
balance_router.include_router(lightning_router, include_in_schema=False)
balance_router.include_router(lightning_router)
balance_router.include_router(router)
deprecated_wallet_router = APIRouter(prefix="/v1/wallet", include_in_schema=False)

File diff suppressed because it is too large Load Diff

View File

@@ -1,19 +1,12 @@
import os
import pathlib
import sqlite3
import time
import uuid
from contextlib import asynccontextmanager
from typing import AsyncGenerator
from alembic import command
from alembic.config import Config
from alembic.util.exc import CommandError
from sqlalchemy import UniqueConstraint, delete
from sqlalchemy.exc import OperationalError
from sqlalchemy.ext.asyncio.engine import create_async_engine
from sqlalchemy.orm import aliased
from sqlmodel import Field, Relationship, SQLModel, col, func, select, update
from sqlmodel import Field, Relationship, SQLModel, func, select
from sqlmodel.ext.asyncio.session import AsyncSession
from .logging import get_logger
@@ -34,14 +27,6 @@ class ApiKey(SQLModel, table=True): # type: ignore
reserved_balance: int = Field(
default=0, description="Reserved balance in millisatoshis (msats)"
)
reserved_at: int | None = Field(
default=None,
description=(
"Unix timestamp of the most recent balance reservation. Used to "
"detect and release stale reservations (e.g. after client "
"disconnects). NULL when no reservation has been made yet."
),
)
refund_address: str | None = Field(
default=None,
description="Lightning address to refund remaining balance after key expires",
@@ -54,14 +39,6 @@ class ApiKey(SQLModel, table=True): # type: ignore
default=0, description="Total spent in millisatoshis (msats)"
)
total_requests: int = Field(default=0)
created_at: int | None = Field(
default_factory=lambda: int(time.time()),
nullable=True,
description=(
"Unix timestamp when the key was created. Nullable: keys created "
"before this column existed have no value and sort last."
),
)
refund_mint_url: str | None = Field(
default=None,
description="URL of the mint used to create the cashu-token",
@@ -70,119 +47,12 @@ class ApiKey(SQLModel, table=True): # type: ignore
default=None,
description="Currency of the cashu-token",
)
parent_key_hash: str | None = Field(
default=None, foreign_key="api_keys.hashed_key", index=True
)
balance_limit: int | None = Field(
default=None,
description="Max spendable balance in msats for this key (mostly for child keys)",
)
balance_limit_reset: str | None = Field(
default=None,
description="Reset policy for balance limit (manual, daily, monthly, etc.)",
)
balance_limit_reset_date: int | None = Field(
default=None,
description="Unix timestamp of the last time the balance limit was reset",
)
validity_date: int | None = Field(
default=None,
description="Unix timestamp after which the key is no longer valid",
)
@property
def total_balance(self) -> int:
return self.balance - self.reserved_balance
async def reset_all_reserved_balances(session: AsyncSession) -> None:
stmt = update(ApiKey).values(reserved_balance=0, reserved_at=None)
await session.exec(stmt) # type: ignore[call-overload]
await session.commit()
logger.info("Reset reserved balances on startup")
async def release_stale_reservations(
session: AsyncSession, max_age_seconds: int
) -> int:
"""Release reservations whose last reserve is older than max_age_seconds.
"""
cutoff = int(time.time()) - max_age_seconds
stmt = (
update(ApiKey)
.where(col(ApiKey.reserved_balance) > 0)
.where(col(ApiKey.reserved_at).is_not(None))
.where(col(ApiKey.reserved_at) < cutoff)
.values(reserved_balance=0, reserved_at=None)
)
result = await session.exec(stmt) # type: ignore[call-overload]
await session.commit()
released = int(result.rowcount or 0)
if released:
logger.warning(
"Released stale balance reservations",
extra={"released_keys": released, "max_age_seconds": max_age_seconds},
)
return released
async def prune_dead_api_keys(session: AsyncSession, min_age_seconds: int) -> int:
"""Delete dead parentless API keys; return the count removed.
Dead = 0 balance/reservation/spend/requests, older than the grace period,
no parent, no children, no pending invoice. Cashu rows are unlinked (not
deleted) first to keep the audit trail.
"""
cutoff = int(time.time()) - min_age_seconds
child = aliased(ApiKey)
has_children = (
select(child.hashed_key).where(
col(child.parent_key_hash) == col(ApiKey.hashed_key)
)
).exists()
pending_invoice = (
select(LightningInvoice.id)
.where(col(LightningInvoice.api_key_hash) == col(ApiKey.hashed_key))
.where(col(LightningInvoice.status) == "pending")
).exists()
eligible_hashes = (
select(ApiKey.hashed_key)
.where(col(ApiKey.balance) == 0)
.where(col(ApiKey.reserved_balance) == 0)
.where(col(ApiKey.total_spent) == 0)
.where(col(ApiKey.total_requests) == 0)
.where(col(ApiKey.parent_key_hash).is_(None))
.where(
(col(ApiKey.created_at).is_(None)) | (col(ApiKey.created_at) < cutoff)
)
.where(~pending_invoice)
.where(~has_children)
)
# Unlink transactions rather than cascade-deleting them, so the financial
# audit trail survives. The eligibility predicate is re-evaluated inside both
# statements so a key that gained balance mid-run is left untouched.
await session.exec( # type: ignore[call-overload]
update(CashuTransaction)
.where(col(CashuTransaction.api_key_hashed_key).in_(eligible_hashes))
.values(api_key_hashed_key=None)
)
result = await session.exec( # type: ignore[call-overload]
delete(ApiKey).where(col(ApiKey.hashed_key).in_(eligible_hashes))
)
await session.commit()
pruned = int(result.rowcount or 0)
logger.info(
"Pruned dead API keys",
extra={"pruned_keys": pruned, "min_age_seconds": min_age_seconds},
)
return pruned
class ModelRow(SQLModel, table=True): # type: ignore
__tablename__ = "models"
id: str = Field(primary_key=True)
@@ -203,10 +73,6 @@ class ModelRow(SQLModel, table=True): # type: ignore
default=None, description="JSON array of model alias IDs"
)
enabled: bool = Field(default=True, description="Whether this model is enabled")
forwarded_model_id: str | None = Field(
default=None,
description="Model ID to use when forwarding requests to upstream provider. Defaults to id if not set.",
)
upstream_provider: "UpstreamProviderRow" = Relationship(back_populates="models")
@@ -230,107 +96,15 @@ class LightningInvoice(SQLModel, table=True): # type: ignore
)
expires_at: int = Field(description="Unix timestamp when invoice expires")
paid_at: int | None = Field(default=None, description="Unix timestamp when paid")
balance_limit: int | None = Field(
default=None,
description="Max spendable msats for the created key",
)
balance_limit_reset: str | None = Field(
default=None,
description="Reset policy for balance limit (daily, weekly, monthly)",
)
validity_date: int | None = Field(
default=None,
description="Unix timestamp after which the created key expires",
)
class CashuTransaction(SQLModel, table=True): # type: ignore
__tablename__ = "cashu_transactions"
id: str = Field(
primary_key=True,
default_factory=lambda: uuid.uuid4().hex,
description="Unique transaction identifier",
)
token: str = Field(description="Serialized Cashu token")
amount: int = Field(description="Amount in the token's unit")
unit: str = Field(description="Token unit (sat or msat)")
mint_url: str | None = Field(default=None, description="Mint URL for the token")
type: str = Field(default="out", description="Transaction type: in or out")
request_id: str | None = Field(default=None, description="Associated request ID")
created_at: int = Field(
default_factory=lambda: int(time.time()),
description="Unix timestamp",
)
collected: bool = Field(default=False)
swept: bool = Field(default=False)
source: str = Field(
default="x-cashu",
description="Payment source: x-cashu or apikey",
)
api_key_hashed_key: str | None = Field(
default=None,
foreign_key="api_keys.hashed_key",
index=True,
description="Associated API key hash for wallet history",
)
async def store_cashu_transaction(
token: str,
amount: int,
unit: str,
mint_url: str | None = None,
typ: str = "out",
request_id: str | None = None,
collected: bool = False,
created_at: int | None = None,
source: str = "x-cashu",
api_key_hashed_key: str | None = None,
) -> bool:
try:
async with create_session() as session:
tx = CashuTransaction(
token=token,
amount=amount,
unit=unit,
mint_url=mint_url,
type=typ,
request_id=request_id,
collected=collected,
created_at=created_at or int(time.time()),
source=source,
api_key_hashed_key=api_key_hashed_key,
)
session.add(tx)
await session.commit()
return True
except Exception as e:
logger.warning(
f"Failed to store cashu transaction: {e} (type={typ})",
extra={"error": str(e), "type": typ},
)
return False
class UpstreamProviderRow(SQLModel, table=True): # type: ignore
__tablename__ = "upstream_providers"
__table_args__ = (
UniqueConstraint(
"base_url", "api_key", name="uq_upstream_providers_base_url_api_key"
),
)
id: int | None = Field(default=None, primary_key=True)
slug: str | None = Field(
default=None,
unique=True,
index=True,
description="Stable external slug used for updates via API key.",
)
provider_type: str = Field(
description="Provider type: custom, openai, anthropic, azure, openrouter, etc."
)
base_url: str = Field(description="Base URL of the upstream API")
base_url: str = Field(unique=True, description="Base URL of the upstream API")
api_key: str = Field(description="API key for the upstream provider")
api_version: str | None = Field(
default=None, description="API version for Azure OpenAI"
@@ -339,75 +113,12 @@ class UpstreamProviderRow(SQLModel, table=True): # type: ignore
provider_fee: float = Field(
default=1.01, description="Provider fee multiplier (default 1%)"
)
provider_settings: str | None = Field(
default=None, description="JSON string for provider-specific settings"
)
models: list["ModelRow"] = Relationship(
back_populates="upstream_provider",
sa_relationship_kwargs={"cascade": "all, delete-orphan"},
)
class RoutstrFee(SQLModel, table=True): # type: ignore
__tablename__ = "routstr_fees"
id: int = Field(default=1, primary_key=True)
accumulated_msats: int = Field(default=0)
total_paid_msats: int = Field(default=0)
last_paid_at: int | None = Field(default=None)
class CliToken(SQLModel, table=True): # type: ignore
"""Long-lived authorization token for CLI/agent use against admin endpoints."""
__tablename__ = "cli_tokens"
id: str = Field(
primary_key=True, default_factory=lambda: uuid.uuid4().hex
)
token: str = Field(unique=True, index=True, description="Bearer token value")
name: str = Field(description="Human-readable label for this token")
created_at: int = Field(default_factory=lambda: int(time.time()))
last_used_at: int | None = Field(default=None)
expires_at: int | None = Field(
default=None, description="Optional expiry unix timestamp; null = never expires"
)
async def accumulate_routstr_fee(session: AsyncSession, amount_msats: int) -> None:
stmt = (
update(RoutstrFee)
.where(col(RoutstrFee.id) == 1)
.values(accumulated_msats=RoutstrFee.accumulated_msats + amount_msats)
)
result = await session.exec(stmt) # type: ignore[call-overload]
if result.rowcount == 0:
session.add(RoutstrFee(id=1, accumulated_msats=amount_msats))
await session.commit()
async def get_routstr_fee(session: AsyncSession) -> RoutstrFee:
fee = await session.get(RoutstrFee, 1)
if fee is None:
fee = RoutstrFee(id=1, accumulated_msats=0, total_paid_msats=0)
session.add(fee)
await session.commit()
await session.refresh(fee)
return fee
async def reset_routstr_fee(session: AsyncSession, paid_msats: int) -> None:
stmt = (
update(RoutstrFee)
.where(col(RoutstrFee.id) == 1)
.values(
accumulated_msats=RoutstrFee.accumulated_msats - paid_msats,
total_paid_msats=RoutstrFee.total_paid_msats + paid_msats,
last_paid_at=int(time.time()),
)
)
await session.exec(stmt) # type: ignore[call-overload]
await session.commit()
async def balances_for_mint_and_unit(
db_session: AsyncSession, mint_url: str, unit: str
) -> int:
@@ -437,64 +148,11 @@ async def create_session() -> AsyncGenerator[AsyncSession, None]:
yield session
def fix_cashu_migrations() -> None:
"""
Fixes Cashu wallet migrations that are not idempotent.
This specifically addresses the 'duplicate column name: public_keys' error
in the keysets table of Cashu's internal SQLite databases.
"""
project_root = pathlib.Path(__file__).resolve().parents[2]
wallet_dir = project_root / ".wallet"
if not wallet_dir.exists() or not wallet_dir.is_dir():
return
logger.info("Checking Cashu wallet databases for migration idempotency")
for db_file in wallet_dir.glob("*.sqlite3"):
try:
conn = sqlite3.connect(db_file)
cursor = conn.cursor()
# Check if keysets table exists
cursor.execute(
"SELECT name FROM sqlite_master WHERE type='table' AND name='keysets'"
)
if not cursor.fetchone():
conn.close()
continue
# Check if public_keys column exists
cursor.execute("PRAGMA table_info(keysets)")
columns = [info[1] for info in cursor.fetchall()]
if "public_keys" not in columns:
logger.info(f"Adding missing public_keys column to {db_file.name}")
cursor.execute("ALTER TABLE keysets ADD COLUMN public_keys TEXT")
conn.commit()
conn.close()
except Exception as e:
logger.warning(f"Could not check/fix Cashu database {db_file}: {e}")
def _clear_alembic_version() -> None:
"""Clear the alembic_version table so stamp/upgrade can proceed."""
sync_url = DATABASE_URL.replace("+aiosqlite", "")
from sqlalchemy import create_engine, text
eng = create_engine(sync_url)
with eng.begin() as conn:
conn.execute(text("DELETE FROM alembic_version"))
eng.dispose()
def run_migrations() -> None:
"""Run Alembic migrations programmatically."""
try:
# Run Cashu migration fix first
fix_cashu_migrations()
import pathlib
try:
# Get the path to the alembic.ini file
project_root = pathlib.Path(__file__).resolve().parents[2]
alembic_ini_path = project_root / "alembic.ini"
@@ -510,30 +168,8 @@ def run_migrations() -> None:
# Set the database URL in the config
alembic_cfg.set_main_option("sqlalchemy.url", DATABASE_URL)
try:
command.upgrade(alembic_cfg, "head")
except CommandError as e:
if "Can't locate revision" in str(e):
logger.warning(
"Database stamped with unknown revision (likely from another branch). "
"Re-stamping to current head.",
extra={"error": str(e)},
)
_clear_alembic_version()
command.stamp(alembic_cfg, "head")
else:
raise
except OperationalError as e:
if "duplicate column name" in str(e).lower():
logger.warning(
"Migration hit a column that already exists (likely added via "
"create_all on another branch). Stamping to current head.",
extra={"error": str(e)},
)
_clear_alembic_version()
command.stamp(alembic_cfg, "head")
else:
raise
# Run migrations to the latest revision
command.upgrade(alembic_cfg, "head")
logger.info("Database migrations completed successfully")

View File

@@ -6,30 +6,6 @@ from .logging import get_logger
logger = get_logger(__name__)
class UpstreamError(Exception):
"""Exception raised when an upstream provider fails.
``code`` carries a stable, machine-readable classification (e.g.
``UPSTREAM_RATE_LIMIT``) so callers can distinguish failure kinds without
string-matching the message. ``details`` holds optional structured,
redaction-safe context. Both default to ``None`` for backwards
compatibility.
"""
def __init__(
self,
message: str,
status_code: int = 502,
code: str | None = None,
details: dict[str, object] | None = None,
):
self.message = message
self.status_code = status_code
self.code = code
self.details = details
super().__init__(message)
async def http_exception_handler(request: Request, exc: Exception) -> JSONResponse:
"""Handle HTTP exceptions and include request ID in response."""
request_id = getattr(request.state, "request_id", "unknown")
@@ -37,20 +13,16 @@ async def http_exception_handler(request: Request, exc: Exception) -> JSONRespon
# Get status code and detail - works for both FastAPI and Starlette HTTPException
status_code = getattr(exc, "status_code", 500)
detail = getattr(exc, "detail", str(exc))
path = request.url.path
# 4xx is client behaviour; the uvicorn access log already records it.
# Only 5xx warrants a server-side warning/error log here.
if status_code >= 500:
logger.error(
f"HTTP {status_code} on {path}: {detail}",
extra={
"request_id": request_id,
"status_code": status_code,
"detail": detail,
"path": path,
},
)
logger.warning(
"HTTP exception",
extra={
"request_id": request_id,
"status_code": status_code,
"detail": detail,
"path": request.url.path,
},
)
return JSONResponse(
status_code=status_code,

File diff suppressed because it is too large Load Diff

View File

@@ -3,63 +3,50 @@ Logging configuration for Routstr.
CRITICAL LOG MESSAGES FOR USAGE STATISTICS:
===========================================
The following log messages are parsed by the usage tracking system
(routstr/core/usage_analytics_store.py and routstr/core/log_manager.py).
The following log messages are parsed by the usage tracking system (routstr/core/admin.py).
DO NOT modify or remove these messages without updating the usage tracking logic:
1. "Received proxy request" (INFO) - routstr/proxy.py
- Used to count total incoming requests
- Includes model information in context
2. "Calculated token-based cost" (INFO) - routstr/auth.py
2. "Payment adjustment completed for streaming" (INFO) - routstr/upstream/base.py
"Payment adjustment completed for non-streaming" (INFO) - routstr/upstream/base.py
- Used to track successful completions and revenue
- The 'token_cost', 'model', 'input_tokens', and 'output_tokens' fields are extracted for dashboard metrics
- The 'cost_data.total_msats' field is extracted for revenue calculation
- Must include 'cost_data' in extra dict
3. "Max cost payment finalized" (INFO) - routstr/auth.py
- Used as the successful completion fallback when token usage is unavailable
- The 'charged_amount', 'model', 'input_tokens', and 'output_tokens' fields are extracted for dashboard metrics
4. "Payment processed successfully" (INFO) - routstr/auth.py
3. "Payment processed successfully" (INFO) - routstr/auth.py
- Used to count successful payment processing events
- Tracks payment-related metrics
5. "Upstream request failed, revert payment" (WARNING) - routstr/proxy.py
4. "Upstream request failed, revert payment" (WARNING) - routstr/proxy.py
- Used to track failed requests and refunds
- The 'max_cost_for_model' field is extracted for refund calculation
- Must include 'max_cost_for_model' in extra dict
6. Any ERROR level logs with "upstream" in the message
5. Any ERROR level logs with "upstream" in the message
- Used to count upstream provider errors
- Helps identify service reliability issues
If you need to modify these messages, ensure you also update the parsing logic in:
- routstr/core/usage_analytics_store.py
- routstr/core/log_manager.py
- routstr/core/admin.py:_aggregate_metrics_by_time()
- routstr/core/admin.py:_get_summary_stats()
- routstr/core/admin.py:get_revenue_by_model()
"""
import logging.config
import logging.handlers
import os
import re
import sys
import tomllib
from datetime import datetime
from pathlib import Path
from typing import Any
from pythonjsonlogger import jsonlogger
from rich.console import Console
from rich.logging import RichHandler
from .redaction import redact_obj, redact_org_ids
# Only use RichHandler when stdout is a real TTY. In non-TTY contexts
# (docker logs, pipes, CI) Rich pads every line to width and wraps long
# records, producing visually-empty trailing whitespace and split records.
# A plain StreamHandler avoids both problems.
_stdout_is_tty = sys.stdout.isatty()
_console = Console(soft_wrap=True) if _stdout_is_tty else None
# Define custom TRACE level
TRACE_LEVEL = 5
logging.addLevelName(TRACE_LEVEL, "TRACE")
@@ -182,37 +169,6 @@ class RequestIdFilter(logging.Filter):
return True
# Standard ``LogRecord`` attributes that are never user-supplied ``extra``
# fields; skipped when redacting structured extras (``msg``/``message`` are
# handled separately above).
_NON_EXTRA_RECORD_ATTRS = frozenset(
{
"name",
"msg",
"args",
"levelname",
"levelno",
"pathname",
"filename",
"module",
"exc_info",
"exc_text",
"stack_info",
"lineno",
"funcName",
"created",
"msecs",
"relativeCreated",
"thread",
"threadName",
"processName",
"process",
"taskName",
"message",
}
)
class SecurityFilter(logging.Filter):
"""Filter to remove sensitive information from logs."""
@@ -236,7 +192,6 @@ class SecurityFilter(logging.Filter):
"""Filter out sensitive information from log records."""
try:
message = record.getMessage()
message = redact_org_ids(message)
standalone_patterns = [
r"Bearer\s+([a-zA-Z0-9_\-\.]{10,})", # Bearer token (must be 10 characters or more to reduce false-positives)
r"cashu[A-Z]+([a-zA-Z0-9_\-\.=/+]+)", # Cashu tokens
@@ -258,16 +213,6 @@ class SecurityFilter(logging.Filter):
record.msg = message
record.args = ()
# Structured `extra={...}` fields are emitted by the JSON formatter
# straight from the record dict and never pass through the message
# formatting above. Redact organization IDs from any string-valued
# extra so they cannot leak via structured logs.
for attr, value in list(record.__dict__.items()):
if attr in _NON_EXTRA_RECORD_ATTRS:
continue
if isinstance(value, (str, dict, list, tuple)):
record.__dict__[attr] = redact_obj(value)
except Exception:
pass
@@ -314,26 +259,6 @@ def setup_logging() -> None:
if console_enabled:
handlers.append("console")
if _stdout_is_tty:
console_handler: dict[str, Any] = {
"()": RichHandler,
"level": log_level,
"show_time": False,
"show_path": False,
"rich_tracebacks": True,
"markup": True,
"console": _console,
"filters": ["request_id_filter", "security_filter"],
}
else:
console_handler = {
"class": "logging.StreamHandler",
"level": log_level,
"formatter": "plain",
"stream": "ext://sys.stdout",
"filters": ["request_id_filter", "security_filter"],
}
LOGGING_CONFIG = {
"version": 1,
"disable_existing_loggers": False,
@@ -343,10 +268,6 @@ def setup_logging() -> None:
"format": "%(asctime)s %(name)s %(levelname)s %(message)s %(pathname)s %(lineno)d %(version)s %(request_id)s",
"datefmt": "%Y-%m-%d %H:%M:%S",
},
"plain": {
"format": "%(asctime)s %(levelname)-7s %(name)s %(message)s",
"datefmt": "%Y-%m-%d %H:%M:%S",
},
},
"filters": {
"version_filter": {"()": VersionFilter},
@@ -354,7 +275,15 @@ def setup_logging() -> None:
"security_filter": {"()": SecurityFilter},
},
"handlers": {
"console": console_handler,
"console": {
"()": RichHandler,
"level": log_level,
"show_time": False,
"show_path": False,
"rich_tracebacks": True,
"markup": True,
"filters": ["request_id_filter", "security_filter"],
},
"file": {
"()": DailyRotatingFileHandler,
"level": log_level,

View File

@@ -1,4 +1,5 @@
import asyncio
import os
from contextlib import asynccontextmanager
from pathlib import Path
from typing import AsyncGenerator
@@ -8,43 +9,34 @@ from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import FileResponse, RedirectResponse
from fastapi.staticfiles import StaticFiles
from starlette.exceptions import HTTPException
from starlette.responses import Response as StarletteResponse
from starlette.types import Scope
from ..auth import (
periodic_dead_key_prune,
periodic_key_reset,
periodic_stale_reservation_sweep,
)
from ..balance import balance_router, deprecated_wallet_router
from ..lightning import lightning_router, periodic_invoice_watcher
from ..nostr import (
announce_provider,
providers_cache_refresher,
publish_usage_analytics,
from ..discovery import providers_cache_refresher, providers_router
from ..nip91 import announce_provider
from ..payment.models import (
models_router,
update_sats_pricing,
)
from ..nostr.discovery import providers_router
from ..payment.models import models_router, update_sats_pricing
from ..payment.price import update_prices_periodically
from ..proxy import initialize_upstreams, proxy_router, refresh_model_maps_periodically
from ..upstream.auto_topup import periodic_auto_topup
from ..upstream.deepseek_v4_pricing_shim import register_deepseek_v4_pricing
from ..upstream.litellm_routing import configure_litellm
from ..wallet import periodic_payout, periodic_refund_sweep, periodic_routstr_fee_payout
from ..wallet import periodic_payout
from .admin import admin_router
from .db import create_session, init_db, run_migrations
from .exceptions import general_exception_handler, http_exception_handler
from .logging import get_logger, setup_logging
from .middleware import LoggingMiddleware
from .not_found import _NOT_FOUND_HTML, not_found_catch_all # noqa: F401
from .settings import SettingsService
from .settings import settings as global_settings
from .version import __version__
# Initialize logging first
setup_logging()
logger = get_logger(__name__)
if os.getenv("VERSION_SUFFIX") is not None:
__version__ = f"0.2.1-{os.getenv('VERSION_SUFFIX')}"
else:
__version__ = "0.2.1"
@asynccontextmanager
async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
@@ -54,28 +46,11 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
pricing_task = None
payout_task = None
nip91_task = None
analytics_task = None
providers_task = None
models_refresh_task = None
model_maps_refresh_task = None
key_reset_task = None
stale_reservation_task = None
dead_key_prune_task = None
auto_topup_task = None
refund_sweep_task = None
routstr_fee_task = None
invoice_watcher_task = None
try:
# Apply litellm-wide settings (drop_params, chat-completions URL,
# debug logging) before any upstream provider dispatches a request.
configure_litellm()
# TEMPORARY: backfill DeepSeek V4 pricing missing from litellm's cost
# map (BerriAI/litellm#30430). Remove this call and
# deepseek_v4_pricing_shim.py once litellm ships these models.
register_deepseek_v4_pricing()
# Run database migrations on startup
run_migrations()
@@ -86,15 +61,6 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
# Initialize application settings (env -> computed -> DB precedence)
async with create_session() as session:
s = await SettingsService.initialize(session)
if s.reset_reserved_balance_on_startup:
from .db import reset_all_reserved_balances
await reset_all_reserved_balances(session)
if not s.admin_password:
logger.warning(
f"Admin password is not set. Visit {s.http_url or 'http://localhost:8000'}/admin to set the password."
)
# Apply app metadata from settings
try:
@@ -120,28 +86,15 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
btc_price_task = asyncio.create_task(update_prices_periodically())
pricing_task = asyncio.create_task(update_sats_pricing())
if global_settings.models_refresh_interval_seconds > 0:
# Pass the accessor (not its current value) so the loop sees providers
# added/changed via reinitialize_upstreams() instead of staying pinned
# to the startup snapshot.
models_refresh_task = asyncio.create_task(
refresh_upstreams_models_periodically(get_upstreams)
refresh_upstreams_models_periodically(get_upstreams())
)
model_maps_refresh_task = asyncio.create_task(refresh_model_maps_periodically())
payout_task = asyncio.create_task(periodic_payout())
if global_settings.nsec:
nip91_task = asyncio.create_task(announce_provider())
analytics_task = asyncio.create_task(publish_usage_analytics())
if global_settings.providers_refresh_interval_seconds > 0:
providers_task = asyncio.create_task(providers_cache_refresher())
key_reset_task = asyncio.create_task(periodic_key_reset())
stale_reservation_task = asyncio.create_task(
periodic_stale_reservation_sweep()
)
dead_key_prune_task = asyncio.create_task(periodic_dead_key_prune())
auto_topup_task = asyncio.create_task(periodic_auto_topup())
refund_sweep_task = asyncio.create_task(periodic_refund_sweep())
routstr_fee_task = asyncio.create_task(periodic_routstr_fee_payout())
invoice_watcher_task = asyncio.create_task(periodic_invoice_watcher())
yield
@@ -165,28 +118,12 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
payout_task.cancel()
if nip91_task is not None:
nip91_task.cancel()
if analytics_task is not None:
analytics_task.cancel()
if providers_task is not None:
providers_task.cancel()
if models_refresh_task is not None:
models_refresh_task.cancel()
if model_maps_refresh_task is not None:
model_maps_refresh_task.cancel()
if key_reset_task is not None:
key_reset_task.cancel()
if stale_reservation_task is not None:
stale_reservation_task.cancel()
if dead_key_prune_task is not None:
dead_key_prune_task.cancel()
if auto_topup_task is not None:
auto_topup_task.cancel()
if refund_sweep_task is not None:
refund_sweep_task.cancel()
if routstr_fee_task is not None:
routstr_fee_task.cancel()
if invoice_watcher_task is not None:
invoice_watcher_task.cancel()
try:
tasks_to_wait = []
@@ -198,28 +135,12 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
tasks_to_wait.append(payout_task)
if nip91_task is not None:
tasks_to_wait.append(nip91_task)
if analytics_task is not None:
tasks_to_wait.append(analytics_task)
if providers_task is not None:
tasks_to_wait.append(providers_task)
if models_refresh_task is not None:
tasks_to_wait.append(models_refresh_task)
if model_maps_refresh_task is not None:
tasks_to_wait.append(model_maps_refresh_task)
if key_reset_task is not None:
tasks_to_wait.append(key_reset_task)
if stale_reservation_task is not None:
tasks_to_wait.append(stale_reservation_task)
if dead_key_prune_task is not None:
tasks_to_wait.append(dead_key_prune_task)
if auto_topup_task is not None:
tasks_to_wait.append(auto_topup_task)
if refund_sweep_task is not None:
tasks_to_wait.append(refund_sweep_task)
if routstr_fee_task is not None:
tasks_to_wait.append(routstr_fee_task)
if invoice_watcher_task is not None:
tasks_to_wait.append(invoice_watcher_task)
if tasks_to_wait:
await asyncio.gather(*tasks_to_wait, return_exceptions=True)
@@ -231,23 +152,6 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
)
class _ImmutableStaticFiles(StaticFiles):
"""Static files with long Cache-Control for content-hashed Next.js assets.
Files under `/_next/static/` are emitted with content hashes in their
filenames and never mutate, so we serve them with a one-year immutable
cache header so browsers and CDNs stop revalidating on every reload.
"""
async def get_response(self, path: str, scope: Scope) -> StarletteResponse:
response = await super().get_response(path, scope)
if response.status_code == 200:
response.headers["Cache-Control"] = (
"public, max-age=31536000, immutable"
)
return response
app = FastAPI(version=__version__, lifespan=lifespan)
@@ -257,20 +161,7 @@ app.add_middleware(
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
expose_headers=[
"x-routstr-request-id",
"x-cashu",
"x-routstr-cost-msats",
"x-routstr-cost-usd",
"x-routstr-input-cost-msats",
"x-routstr-output-cost-msats",
# EHBP (Tinfoil) protocol headers must be exposed so browser clients
# can detect and decrypt encrypted responses. Without these, the
# browser hides them via CORS and the SDK treats the response as a
# plaintext proxy error, returning raw ciphertext.
"Ehbp-Response-Nonce",
"Ehbp-Encapsulated-Key",
],
expose_headers=["x-routstr-request-id"],
)
# Add logging middleware
@@ -291,7 +182,6 @@ async def info() -> dict:
"mints": global_settings.cashu_mints,
"http_url": global_settings.http_url,
"onion_url": global_settings.onion_url,
"child_key_cost_msats": global_settings.child_key_cost,
}
@@ -307,7 +197,7 @@ if UI_DIST_PATH.exists() and UI_DIST_PATH.is_dir():
app.mount(
"/_next",
_ImmutableStaticFiles(directory=UI_DIST_PATH / "_next", check_dir=True),
StaticFiles(directory=UI_DIST_PATH / "_next", check_dir=True),
name="next-static",
)
@@ -315,70 +205,100 @@ if UI_DIST_PATH.exists() and UI_DIST_PATH.is_dir():
async def serve_root_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "index.html")
# Serve the App Router RSC payload for the home page.
# Add explicit route for /index.txt to redirect to /
@app.get("/index.txt", include_in_schema=False)
async def serve_root_rsc() -> FileResponse:
return FileResponse(
UI_DIST_PATH / "index.txt", media_type="text/x-component"
)
# Next.js is built with `trailingSlash: true`, so all UI page URLs end
# with a slash (e.g. `/login/`). The proxy router catches `/{path:path}`
# before FastAPI's `redirect_slashes` logic can normalize the URL, so we
# must register both the with-slash and without-slash variants here.
UI_PAGES = (
"dashboard",
"login",
"model",
"providers",
"settings",
"transactions",
"balances",
"logs",
"usage",
"unauthorized",
)
def _register_ui_page(name: str) -> None:
page_dir = UI_DIST_PATH / name
index_html = page_dir / "index.html"
index_txt = page_dir / "index.txt"
async def serve_page() -> FileResponse:
return FileResponse(index_html)
async def serve_page_rsc() -> FileResponse:
return FileResponse(index_txt, media_type="text/x-component")
app.add_api_route(
f"/{name}",
serve_page,
methods=["GET"],
include_in_schema=False,
name=f"serve_{name}_ui",
)
app.add_api_route(
f"/{name}/",
serve_page,
methods=["GET"],
include_in_schema=False,
name=f"serve_{name}_ui_slash",
)
app.add_api_route(
f"/{name}/index.txt",
serve_page_rsc,
methods=["GET"],
include_in_schema=False,
name=f"serve_{name}_rsc",
)
for _page in UI_PAGES:
_register_ui_page(_page)
async def redirect_index_txt() -> RedirectResponse:
return RedirectResponse("/")
@app.get("/admin")
async def admin_redirect() -> FileResponse:
return FileResponse(UI_DIST_PATH / "index.html")
@app.get("/dashboard", include_in_schema=False)
async def serve_dashboard_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "index.html")
@app.get("/login", include_in_schema=False)
async def serve_login_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "login" / "index.html")
# Add explicit route for /login/index.txt to redirect to /login
@app.get("/login/index.txt", include_in_schema=False)
async def redirect_login_index_txt() -> RedirectResponse:
return RedirectResponse("/login")
@app.get("/model", include_in_schema=False)
async def serve_models_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "model" / "index.html")
# Add explicit route for /model/index.txt to redirect to /model
@app.get("/model/index.txt", include_in_schema=False)
async def redirect_model_index_txt() -> RedirectResponse:
return RedirectResponse("/model")
@app.get("/providers", include_in_schema=False)
async def serve_providers_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "providers" / "index.html")
# Add explicit route for /providers/index.txt to redirect to /providers
@app.get("/providers/index.txt", include_in_schema=False)
async def redirect_providers_index_txt() -> RedirectResponse:
return RedirectResponse("/providers")
@app.get("/settings", include_in_schema=False)
async def serve_settings_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "settings" / "index.html")
# Add explicit route for /settings/index.txt to redirect to /settings
@app.get("/settings/index.txt", include_in_schema=False)
async def redirect_settings_index_txt() -> RedirectResponse:
return RedirectResponse("/settings")
@app.get("/transactions", include_in_schema=False)
async def serve_transactions_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "transactions" / "index.html")
# Add explicit route for /transactions/index.txt to redirect to /transactions
@app.get("/transactions/index.txt", include_in_schema=False)
async def redirect_transactions_index_txt() -> RedirectResponse:
return RedirectResponse("/transactions")
@app.get("/balances", include_in_schema=False)
async def serve_balances_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "balances" / "index.html")
# Add explicit route for /balances/index.txt to redirect to /balances
@app.get("/balances/index.txt", include_in_schema=False)
async def redirect_balances_index_txt() -> RedirectResponse:
return RedirectResponse("/balances")
@app.get("/logs", include_in_schema=False)
async def serve_logs_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "logs" / "index.html")
# Add explicit route for /logs/index.txt to redirect to /logs
@app.get("/logs/index.txt", include_in_schema=False)
async def redirect_logs_index_txt() -> RedirectResponse:
return RedirectResponse("/logs")
@app.get("/usage", include_in_schema=False)
async def serve_usage_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "usage" / "index.html")
# Add explicit route for /usage/index.txt to redirect to /usage
@app.get("/usage/index.txt", include_in_schema=False)
async def redirect_usage_index_txt() -> RedirectResponse:
return RedirectResponse("/usage")
@app.get("/unauthorized", include_in_schema=False)
async def serve_unauthorized_ui() -> FileResponse:
return FileResponse(UI_DIST_PATH / "unauthorized" / "index.html")
# Add explicit route for /unauthorized/index.txt to redirect to /unauthorized
@app.get("/unauthorized/index.txt", include_in_schema=False)
async def redirect_unauthorized_index_txt() -> RedirectResponse:
return RedirectResponse("/unauthorized")
@app.get("/favicon.ico", include_in_schema=False)
async def serve_favicon() -> FileResponse:
icon_path = UI_DIST_PATH / "icon.ico"
@@ -390,12 +310,12 @@ if UI_DIST_PATH.exists() and UI_DIST_PATH.is_dir():
async def serve_icon() -> FileResponse:
return FileResponse(UI_DIST_PATH / "icon.ico")
app.mount(
"/static", StaticFiles(directory=UI_DIST_PATH, check_dir=True), name="ui-static"
)
else:
logger.warning(
"UI dist directory not found at %s; serving API only. Run `make ui-build` "
"to build the static UI served from here, or `make ui-dev` for the Next.js "
"dev server with hot reload on :3000 (it targets this backend on :8000).",
UI_DIST_PATH,
f"UI dist directory not found at {UI_DIST_PATH}, skipping static file serving"
)
@app.get("/", include_in_schema=False)
@@ -412,7 +332,6 @@ else:
app.include_router(models_router)
app.include_router(admin_router)
app.include_router(balance_router)
app.include_router(lightning_router)
app.include_router(deprecated_wallet_router)
app.include_router(providers_router)
app.include_router(proxy_router)

View File

@@ -14,54 +14,8 @@ logger = get_logger(__name__)
request_id_context: ContextVar[str | None] = ContextVar("request_id")
# Methods that are never logged: HEAD requests are health probes from
# monitoring/load balancers, OPTIONS are CORS preflights — both are framework
# chatter, not user-meaningful events.
_SKIP_LOG_METHODS: frozenset[str] = frozenset({"HEAD", "OPTIONS"})
# Path prefixes to skip. Includes Next.js static chunks and the admin
# dashboard's internal polling API (/admin/api/*) which the UI hits on a timer
# to refresh balances, logs, providers, etc. — high volume, low diagnostic
# value. Mutating admin actions are recorded separately in the audit log.
_SKIP_LOG_PREFIXES: tuple[str, ...] = (
"/_next/",
"/admin/api/",
)
# Exact paths to skip. RSC payload prefetches (`*/index.txt`) fire automatically
# as the user hovers near `<Link>`s, and `/v1/wallet/info` is polled by the UI.
_SKIP_LOG_EXACT: frozenset[str] = frozenset(
{
"/favicon.ico",
"/icon.ico",
"/v1/wallet/info",
"/index.txt",
"/login/index.txt",
"/model/index.txt",
"/providers/index.txt",
"/settings/index.txt",
"/transactions/index.txt",
"/balances/index.txt",
"/logs/index.txt",
"/usage/index.txt",
"/unauthorized/index.txt",
}
)
def _should_log(method: str, path: str) -> bool:
if method in _SKIP_LOG_METHODS:
return False
if path in _SKIP_LOG_EXACT:
return False
return not any(path.startswith(prefix) for prefix in _SKIP_LOG_PREFIXES)
class LoggingMiddleware(BaseHTTPMiddleware):
"""Middleware to log proxy interactions and page navigation.
Skips logging for static assets and Next.js chunks to avoid noise.
"""
"""Middleware to log detailed request and response information."""
async def dispatch(self, request: Request, call_next: Callable) -> Response:
# Generate request ID
@@ -71,20 +25,62 @@ class LoggingMiddleware(BaseHTTPMiddleware):
# Set request ID in context for logging
token = request_id_context.set(request_id)
path = request.url.path
should_log = _should_log(request.method, path)
# Start timing
start_time = time.time()
if should_log:
logger.info(
"Incoming request",
# Log request details
request_body = None
if request.method in ["POST", "PUT", "PATCH"]:
try:
# Only read body for non-streaming requests
if hasattr(request, "_body"):
request_body = await request.body()
except Exception:
pass
# Extract request info
client_host = None
if request.client:
client_host = request.client.host
# Log incoming request
logger.info(
"Incoming request",
extra={
"request_id": request_id,
"method": request.method,
"path": request.url.path,
"query_params": dict(request.query_params),
"client_host": client_host,
"headers": {
k: v
for k, v in request.headers.items()
if k.lower()
not in [
"authorization",
"x-cashu",
"cookie",
"cf-connecting-ip",
"cf-ipcountry",
"x-forwarded-for",
"x-real-ip",
]
},
"body_size": len(request_body) if request_body else 0,
},
)
# Log at TRACE level for full body (security filter will redact sensitive data)
if request_body and hasattr(logger, "exception"):
logger.exception(
"Request body",
extra={
"request_id": request_id,
"method": request.method,
"path": path,
"query_params": dict(request.query_params),
"path": request.url.path,
"body": request_body.decode("utf-8", errors="ignore")[
:1000
], # Limit size
},
)
@@ -92,33 +88,39 @@ class LoggingMiddleware(BaseHTTPMiddleware):
try:
response = await call_next(request)
if should_log:
duration = time.time() - start_time
logger.info(
"Request completed",
extra={
"request_id": request_id,
"method": request.method,
"path": path,
"status_code": response.status_code,
"duration_ms": round(duration * 1000, 2),
},
)
# Calculate duration
duration = time.time() - start_time
# Log response
logger.info(
"Request completed",
extra={
"request_id": request_id,
"method": request.method,
"path": request.url.path,
"status_code": response.status_code,
"duration_ms": round(duration * 1000, 2),
"client_host": client_host,
},
)
if hasattr(response, "headers"):
response.headers["x-routstr-request-id"] = request_id
return response
except Exception as e:
# Always log failures, even for skipped paths, so we don't lose errors.
# Calculate duration
duration = time.time() - start_time
# Log error
logger.error(
"Request failed",
extra={
"request_id": request_id,
"method": request.method,
"path": path,
"path": request.url.path,
"duration_ms": round(duration * 1000, 2),
"client_host": client_host,
"error": str(e),
"error_type": type(e).__name__,
},

View File

@@ -1,55 +0,0 @@
"""Shared 404 handler used by the proxy catch-all and tests."""
from __future__ import annotations
from pathlib import Path
from fastapi import Request
from fastapi.responses import HTMLResponse, JSONResponse, Response
_NOT_FOUND_HTML_FILE = Path(__file__).parent.parent.parent / "ui_out" / "404.html"
def _read_not_found_html() -> str | None:
try:
return _NOT_FOUND_HTML_FILE.read_text(encoding="utf-8")
except OSError:
return None
_NOT_FOUND_HTML: str | None = _read_not_found_html()
def build_not_found_response(request: Request, path: str) -> Response:
"""Return a 404 response.
HTML 404 page only for GET requests from browsers (Accept: text/html).
All POST requests and API clients receive a JSON 404.
"""
accept = request.headers.get("accept", "").lower()
prefers_html = (
request.method == "GET"
and "text/html" in accept
and "application/json" not in accept
)
request_id = getattr(request.state, "request_id", "unknown")
if prefers_html and _NOT_FOUND_HTML is not None:
return HTMLResponse(content=_NOT_FOUND_HTML, status_code=404)
return JSONResponse(
status_code=404,
content={
"error": {
"message": f"Path '/{path}' not found",
"type": "not_found",
"code": 404,
},
"request_id": request_id,
},
)
async def not_found_catch_all(request: Request, path: str) -> Response:
"""ASGI handler form of :func:`build_not_found_response`."""
return build_not_found_response(request, path)

View File

@@ -1,65 +0,0 @@
from __future__ import annotations
import re
from itertools import count
from typing import Collection
from sqlmodel import select
from sqlmodel.ext.asyncio.session import AsyncSession
from .db import UpstreamProviderRow
_SLUG_BASE_PATTERN = re.compile(r"[^a-z0-9]+")
_MAX_SLUG_LENGTH = 64
def provider_slug_base(provider_type: str) -> str:
"""Return a deterministic slug base for a provider type."""
base = _SLUG_BASE_PATTERN.sub("-", provider_type.lower()).strip("-")
if not base:
base = "provider"
elif base.isdigit():
base = f"provider-{base}"
elif len(base) < 3:
base = f"{base}-provider"
if len(base) > _MAX_SLUG_LENGTH:
base = base[:_MAX_SLUG_LENGTH].rstrip("-") or "provider"
return base
def provider_slug_candidate(base: str, suffix_number: int) -> str:
if suffix_number == 1:
return base
suffix = f"-{suffix_number}"
max_base_length = _MAX_SLUG_LENGTH - len(suffix)
return f"{base[:max_base_length].rstrip('-')}{suffix}"
async def allocate_unique_provider_slug(
session: AsyncSession,
provider_type: str,
reserved_slugs: Collection[str] = (),
) -> str:
"""Allocate a stable, deterministic provider slug.
The first provider of a type gets ``openai``; later collisions get
``openai-2``, ``openai-3``, etc. ``reserved_slugs`` covers rows staged in
memory but not flushed yet, such as settings/env seeding.
"""
base = provider_slug_base(provider_type)
reserved = {slug.lower() for slug in reserved_slugs}
for suffix_number in count(1):
candidate = provider_slug_candidate(base, suffix_number)
if candidate in reserved:
continue
result = await session.exec(
select(UpstreamProviderRow).where(UpstreamProviderRow.slug == candidate)
)
if result.first() is None:
return candidate
raise RuntimeError("unreachable")

Some files were not shown because too many files have changed in this diff Show More