Files
api/services/chat/app/llm.py
Roberto Musso 90018af311 feat: add WS Gateway and Chat Service (Step 2)
WS Gateway:
- WebSocket lifecycle handler with RS256 JWT auth
- Redis bridge: device registry, frame publishing, tool_result routing
- Inbound routing: tool_result→LPUSH, home/floating→chat pub/sub
- Outbound: subscribes to ws:out:{user_id}, forwards to Electron
- Single-worker Dockerfile (long-lived WS connections)

Chat Service:
- Redis consumer: subscribes to chat:request:* pattern
- Redis-based ws_context: tool_call→publish, BRPOP tool_result (30s timeout)
- deep_agent: single-agent runner with home/floating/stream variants
- memory_middleware: core/associative/episodic/proactive memory with Fernet
- Domain agents: task (8 tools), note (5), project (6), timeline (4)
- LLM factory via LiteLLM (100+ providers)
- Output formatter (StreamFormatter)
- POST /chat REST fallback with Traefik header auth
- Multi-worker Dockerfile with 120s timeout for LLM calls
2026-03-22 01:20:11 +01:00

78 lines
2.1 KiB
Python

"""LLM factory — centralised model instantiation via LiteLLM.
Adapted from app/core/llm.py for the Chat Service.
Uses shared.config.settings instead of app.config.settings.
"""
from __future__ import annotations
import os
import warnings
from openai import AsyncOpenAI
import litellm
from langchain_openai import ChatOpenAI
from langchain_litellm import ChatLiteLLM
from shared.config import settings
litellm.drop_params = True
warnings.filterwarnings(
"ignore",
message=r"PydanticSerializationUnexpectedValue\(Expected `ResponseAPIUsage`",
category=UserWarning,
)
def _api_key_for_model(model: str) -> str | None:
if model.startswith("anthropic/"):
return settings.ANTHROPIC_API_KEY or None
if model.startswith("gemini/") or model.startswith("google/"):
return settings.GOOGLE_API_KEY or None
if model.startswith("cerebras/"):
return settings.CEREBRAS_API_KEY or None
if model.startswith("github_copilot/"):
return None
return settings.OPENAI_API_KEY or None
def get_llm(
*,
model: str | None = None,
temperature: float = 0,
) -> ChatOpenAI | ChatLiteLLM:
model = model or settings.LLM_MODEL
if settings.GITHUB_COPILOT_TOKEN_DIR:
os.environ.setdefault("GITHUB_COPILOT_TOKEN_DIR", settings.GITHUB_COPILOT_TOKEN_DIR)
if "/" in model:
return ChatLiteLLM(model=model, temperature=temperature)
return ChatOpenAI(
model=model,
temperature=temperature,
api_key=_api_key_for_model(model),
)
def get_router_llm(
*,
temperature: float = 0,
) -> ChatOpenAI | ChatLiteLLM:
return get_llm(model=settings.LLM_ROUTER_MODEL, temperature=temperature)
async def embed(text: str) -> list[float]:
model = settings.LLM_EMBED_MODEL
if model.startswith("github_copilot/") or "/" in model:
response = await litellm.aembedding(model=model, input=[text])
return response.data[0]["embedding"]
client = AsyncOpenAI(api_key=settings.OPENAI_API_KEY)
response = await client.embeddings.create(model=model, input=text)
return response.data[0].embedding