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10 Commits

Author SHA1 Message Date
Shroominic
dd4ed7541f undo 43e9732 2025-12-22 11:31:19 +01:00
Shroominic
cc42534a97 manual alias due to openrouter api bug 2025-12-22 11:30:51 +01:00
9qeklajc
43e97326e0 fix model naming issue in response 2025-12-12 20:14:43 +01:00
9qeklajc
06770a0702 Merge branch 'v0.2.1' into embeddings-integration 2025-12-12 19:44:45 +01:00
Shroominic
547365894d add simple test 2025-12-11 13:58:57 +08:00
Shroominic
c0176a5274 Merge branch 'v0.2.1' into embeddings-integration 2025-12-11 13:06:20 +08:00
Shroominic
329d22363f Merge branch 'v0.2.1' into embeddings-integration 2025-12-11 12:59:41 +08:00
9qeklajc
9438bc957f clean up 2025-12-03 22:24:43 +01:00
9qeklajc
5d2219880d embedding integration 2025-12-03 22:23:03 +01:00
9qeklajc
195da0c9da embedding integration 2025-12-03 22:22:57 +01:00
5 changed files with 201 additions and 59 deletions

View File

@@ -93,12 +93,32 @@ async def async_fetch_openrouter_models(source_filter: str | None = None) -> lis
try:
async with httpx.AsyncClient() as client:
response = await client.get(f"{base_url}/models", timeout=30)
response.raise_for_status()
data = response.json()
models_response, embeddings_response = await asyncio.gather(
client.get(f"{base_url}/models", timeout=30),
client.get(f"{base_url}/embeddings/models", timeout=30),
return_exceptions=True,
)
def process_models_response(
response: httpx.Response | BaseException,
) -> list[dict]:
if not isinstance(response, BaseException):
response.raise_for_status()
data = response.json()
return [
model
for model in data.get("data", [])
if ":free" not in model.get("id", "").lower()
]
return []
models_data: list[dict] = []
for model in data.get("data", []):
models_data.extend(process_models_response(models_response))
models_data.extend(process_models_response(embeddings_response))
# Apply source filter and exclusions
filtered_models = []
for model in models_data:
model_id = model.get("id", "")
if source_filter:
@@ -116,9 +136,9 @@ async def async_fetch_openrouter_models(source_filter: str | None = None) -> lis
if not _has_valid_pricing(model):
continue
models_data.append(model)
filtered_models.append(model)
return models_data
return filtered_models
except Exception as e:
logger.error(f"Error (async) fetching models from OpenRouter API: {e}")
return []

View File

@@ -65,7 +65,7 @@ def get_upstreams() -> list[BaseUpstreamProvider]:
def get_model_instance(model_id: str) -> Model | None:
"""Get Model instance by ID from global cache."""
return _model_instances.get(model_id)
return _model_instances.get(model_id.lower())
def get_provider_for_model(model_id: str) -> BaseUpstreamProvider | None:

View File

@@ -734,51 +734,53 @@ class BaseUpstreamProvider:
await client.aclose()
return mapped_error
if path.endswith("chat/completions"):
client_wants_streaming = False
if request_body:
try:
request_data = json.loads(request_body)
client_wants_streaming = request_data.get("stream", False)
logger.debug(
"Chat completion request analysis",
extra={
"client_wants_streaming": client_wants_streaming,
"model": request_data.get("model", "unknown"),
"key_hash": key.hashed_key[:8] + "...",
},
)
except json.JSONDecodeError:
logger.warning(
"Failed to parse request body JSON for streaming detection"
)
if path.endswith("chat/completions") or path.endswith("embeddings"):
if path.endswith("chat/completions"):
client_wants_streaming = False
if request_body:
try:
request_data = json.loads(request_body)
client_wants_streaming = request_data.get("stream", False)
logger.debug(
"Chat completion request analysis",
extra={
"client_wants_streaming": client_wants_streaming,
"model": request_data.get("model", "unknown"),
"key_hash": key.hashed_key[:8] + "...",
},
)
except json.JSONDecodeError:
logger.warning(
"Failed to parse request body JSON for streaming detection"
)
content_type = response.headers.get("content-type", "")
upstream_is_streaming = "text/event-stream" in content_type
is_streaming = client_wants_streaming and upstream_is_streaming
content_type = response.headers.get("content-type", "")
upstream_is_streaming = "text/event-stream" in content_type
is_streaming = client_wants_streaming and upstream_is_streaming
logger.debug(
"Response type analysis",
extra={
"is_streaming": is_streaming,
"client_wants_streaming": client_wants_streaming,
"upstream_is_streaming": upstream_is_streaming,
"content_type": content_type,
"key_hash": key.hashed_key[:8] + "...",
},
)
if is_streaming and response.status_code == 200:
result = await self.handle_streaming_chat_completion(
response, key, max_cost_for_model
logger.debug(
"Response type analysis",
extra={
"is_streaming": is_streaming,
"client_wants_streaming": client_wants_streaming,
"upstream_is_streaming": upstream_is_streaming,
"content_type": content_type,
"key_hash": key.hashed_key[:8] + "...",
},
)
background_tasks = BackgroundTasks()
background_tasks.add_task(response.aclose)
background_tasks.add_task(client.aclose)
result.background = background_tasks
return result
elif response.status_code == 200:
if is_streaming and response.status_code == 200:
result = await self.handle_streaming_chat_completion(
response, key, max_cost_for_model
)
background_tasks = BackgroundTasks()
background_tasks.add_task(response.aclose)
background_tasks.add_task(client.aclose)
result.background = background_tasks
return result
# Handle both non-streaming chat completions and embeddings
if response.status_code == 200:
try:
return await self.handle_non_streaming_chat_completion(
response, key, session, max_cost_for_model
@@ -1519,9 +1521,9 @@ class BaseUpstreamProvider:
error_response.headers["X-Cashu"] = refund_token
return error_response
if path.endswith("chat/completions"):
if path.endswith("chat/completions") or path.endswith("embeddings"):
logger.debug(
"Processing chat completion response",
"Processing completion/embeddings response",
extra={"path": path, "amount": amount, "unit": unit},
)
@@ -1770,15 +1772,32 @@ class BaseUpstreamProvider:
async def _fetch_openrouter_models(self) -> list[dict]:
"""Fetch models from OpenRouter API."""
url = "https://openrouter.ai/api/v1/models"
embeddings_url = "https://openrouter.ai/api/v1/embeddings/models"
async with httpx.AsyncClient(timeout=30.0) as client:
response = await client.get(url)
response.raise_for_status()
models = response.json()
return [
model
for model in models.get("data", [])
if ":free" not in model.get("id", "").lower()
]
models_response, embeddings_response = await asyncio.gather(
client.get(url), client.get(embeddings_url), return_exceptions=True
)
all_models = []
def process_models_response(
response: httpx.Response | BaseException,
) -> list[dict]:
if not isinstance(response, BaseException):
response.raise_for_status()
data = response.json()
return [
model
for model in data.get("data", [])
if ":free" not in model.get("id", "").lower()
]
return []
all_models.extend(process_models_response(models_response))
all_models.extend(process_models_response(embeddings_response))
return all_models
async def _fetch_provider_models(self) -> dict:
"""Fetch models from provider's API."""

View File

@@ -50,7 +50,13 @@ class OpenRouterUpstreamProvider(BaseUpstreamProvider):
async def fetch_models(self) -> list[Model]:
"""Fetch all OpenRouter models."""
models_data = await async_fetch_openrouter_models()
return [Model(**model) for model in models_data] # type: ignore
models = [Model(**model) for model in models_data] # type: ignore
# manual alias for openai/text-embedding-ada-002 due to openrouter api bug
for model in models:
if model.id == "openai/text-embedding-ada-002":
model.alias_ids = ["text-embedding-ada-002-v2"]
break
return models
async def get_balance(self) -> float | None:
"""Get the current account balance from OpenRouter.

View File

@@ -0,0 +1,97 @@
import json
from typing import Any
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from httpx import AsyncClient
@pytest.mark.integration
@pytest.mark.asyncio
async def test_proxy_embeddings_endpoint(authenticated_client: AsyncClient) -> None:
"""Test the embeddings endpoint proxy functionality"""
test_payload = {
"model": "text-embedding-ada-002",
"input": "The quick brown fox",
}
mock_response_data = {
"object": "list",
"data": [
{"object": "embedding", "embedding": [0.0023, -0.0012, 0.0045], "index": 0}
],
"model": "text-embedding-ada-002",
"usage": {"prompt_tokens": 5, "total_tokens": 5},
}
with patch("httpx.AsyncClient.send") as mock_send:
# Create a proper async generator for iter_bytes
async def mock_iter_bytes(*args: Any, **kwargs: Any) -> Any:
yield json.dumps(mock_response_data).encode()
mock_response = AsyncMock()
mock_response.status_code = 200
mock_response.headers = {"content-type": "application/json"}
mock_response.text = json.dumps(mock_response_data)
# Use MagicMock for synchronous .json() method
mock_response.json = MagicMock(return_value=mock_response_data)
mock_response.iter_bytes = mock_iter_bytes
mock_response.aiter_bytes = mock_iter_bytes
mock_send.return_value = mock_response
# Make POST request to embeddings endpoint
response = await authenticated_client.post("/v1/embeddings", json=test_payload)
assert response.status_code == 200
response_data = response.json()
assert response_data["object"] == "list"
assert len(response_data["data"]) == 1
assert response_data["data"][0]["object"] == "embedding"
# Verify request was forwarded
mock_send.assert_called_once()
forwarded_request = mock_send.call_args[0][0]
# Verify the path ends with embeddings
# Note: forwarded path might be full URL
assert str(forwarded_request.url).endswith("embeddings")
@pytest.mark.integration
@pytest.mark.asyncio
async def test_model_case_insensitivity(authenticated_client: AsyncClient) -> None:
"""Test that model lookups are case insensitive"""
# We'll use a mixed-case model ID that should match the lowercase one in the system
# We assume 'gpt-3.5-turbo' is available in the mock env/database
test_payload = {
"model": "GPT-3.5-TURBO",
"messages": [{"role": "user", "content": "Hello"}],
}
with patch("httpx.AsyncClient.send") as mock_send:
mock_response_data = {
"id": "chatcmpl-123",
"object": "chat.completion",
"choices": [{"message": {"content": "Hi"}}],
"usage": {"total_tokens": 10},
}
async def mock_iter_bytes(*args: Any, **kwargs: Any) -> Any:
yield json.dumps(mock_response_data).encode()
mock_response = AsyncMock()
mock_response.status_code = 200
mock_response.headers = {"content-type": "application/json"}
mock_response.text = json.dumps(mock_response_data)
mock_response.json = MagicMock(return_value=mock_response_data)
mock_response.iter_bytes = mock_iter_bytes
mock_response.aiter_bytes = mock_iter_bytes
mock_send.return_value = mock_response
response = await authenticated_client.post(
"/v1/chat/completions", json=test_payload
)
assert response.status_code == 200