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Tinfoil PR #385 added model=<name> to the X-Tinfoil-Usage-Metrics header/trailer. This commit uses that field for accurate billing. Changes in routstr/upstream/ehbp.py: - parse_tinfoil_usage_metrics(): extract the model= field as a string alongside the existing token counts (previously silently discarded because int() failed on it). - _build_cost_info(): accept optional actual_model parameter propagated through to callers when a real mismatch is detected. - _compute_ehbp_actual_cost(): compare the served model against model_obj.forwarded_model_id (the expected upstream ID) rather than model_obj.id (the client-facing alias). This prevents spurious mismatches when a node runner maps e.g. tinfoil-glm-5-2 -> glm-5-2 and the header correctly reports glm-5-2. On a genuine mismatch (failover to a different upstream model), look up the actual model's pricing via get_model_instance() (forwarded_model_id values are registered as routable aliases in the global model map). - forward_ehbp_request() / forward_ehbp_x_cashu_request(): use the actual served model for payment finalization and logging when a mismatch is detected. Tests: 6 new scenarios (alias match, real mismatch with alias, unknown model fallback, old-format compat, cache token details + model), plus forwarded_model_id set on all existing mock model objects to keep them passing. All 49 Tinfoil/EHBP unit tests pass.
Routstr Payment Proxy
Routstr is a decentralized protocol for permissionless, private, and censorship-resistant AI inference. It combines Nostr for discovery and Cashu for private Bitcoin micropayments.
This repo contains Routstr Core: a FastAPI-based reverse proxy that sits in front of OpenAI-compatible APIs and handles pay-per-request billing.
Start Here
- Overview: https://docs.routstr.com/overview/
- Provider Guide: https://docs.routstr.com/provider/quickstart/
- User Guide: https://docs.routstr.com/user-guide/introduction/
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
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)
cURL
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"}]
}'
Quick Start (Docker)
If you are a node runner, start a Routstr Core instance using Docker Compose:
-
Prepare your
.env:ADMIN_PASSWORD=mysecretpassword NAME="My AI Node" DESCRIPTION="Fast access to models" NSEC=yournsec RECEIVE_LN_ADDRESS=yourname@wallet.com -
Start the services:
docker compose up -d -
Configure: Open http://localhost:8000/admin/ to connect your AI providers and set pricing.
For full instructions, see the Provider Quick Start Guide.
Development
make setup
cp .env.example .env
fastapi run routstr