bug fix sending component

.gitignore

@@ -31,3 +31,4 @@ Thumbs.db
 
 # Claude Code
 .claude/
+logs/

app/api/routes/device_ws.py

@@ -233,10 +233,19 @@ async def _handle_home_request(
     executor = await _make_ws_executor(websocket, user_id)
     set_client_executor(executor)
     response_chunks: list[str] = []
+    agent_holder: list = []
     try:
-        token_stream = orchestrate_v3_stream(user_id, message, context)
+        token_stream = orchestrate_v3_stream(
+            user_id, message, context, agent_holder=agent_holder
+        )
         formatter = HomeFormatter(request_id=request_id, tool_results=[])
         async for ws_frame in formatter.format(token_stream):
+            # Inject mutations from agent tool_results into stream_end
+            if ws_frame.type == "stream_end" and agent_holder:  # type: ignore[union-attr]
+                ws_frame.mutations = [  # type: ignore[union-attr]
+                    {"action": r["action"], "table": r["table"], "data": r["data"]}
+                    for r in getattr(agent_holder[0], "tool_results", [])
+                ]
             await websocket.send_text(ws_frame.model_dump_json())
             # Collect text chunks to build the full response for episode storage
             if ws_frame.type == "stream_text":  # type: ignore[union-attr]
@@ -278,10 +287,18 @@ async def _handle_floating_request(
     executor = await _make_ws_executor(websocket, user_id)
     set_client_executor(executor)
     response_chunks: list[str] = []
+    agent_holder: list = []
     try:
-        token_stream = orchestrate_v3_stream(user_id, message, context)
+        token_stream = orchestrate_v3_stream(
+            user_id, message, context, agent_holder=agent_holder
+        )
         formatter = FloatingFormatter(request_id=request_id)
         async for ws_frame in formatter.format(token_stream):
+            if ws_frame.type == "stream_end" and agent_holder:  # type: ignore[union-attr]
+                ws_frame.mutations = [  # type: ignore[union-attr]
+                    {"action": r["action"], "table": r["table"], "data": r["data"]}
+                    for r in getattr(agent_holder[0], "tool_results", [])
+                ]
             await websocket.send_text(ws_frame.model_dump_json())
             if ws_frame.type == "stream_text":  # type: ignore[union-attr]
                 response_chunks.append(ws_frame.chunk)  # type: ignore[union-attr]

app/core/llm.py

@@ -23,10 +23,15 @@ from openai import AsyncOpenAI
 import litellm
 
 from langchain_openai import ChatOpenAI
+from langchain_litellm import ChatLiteLLM
 from litellm import get_supported_openai_params  # noqa: F401 – validates install
 
 from app.config.settings import settings
 
+# Some models (e.g. gpt-5, o-series) reject unsupported params like temperature.
+# Drop them silently instead of raising UnsupportedParamsError.
+litellm.drop_params = True
+
 
 def _api_key_for_model(model: str) -> str | None:
     """Return the most appropriate API key for the given LiteLLM model string."""
@@ -48,7 +53,7 @@ def get_llm(
     *,
     model: str | None = None,
     temperature: float = 0,
-) -> ChatOpenAI:
+) -> ChatOpenAI | ChatLiteLLM:
     """Return a LangChain chat model backed by LiteLLM.
 
     LiteLLM exposes an OpenAI-compatible API, so we use ``ChatOpenAI`` pointed
@@ -69,6 +74,11 @@ def get_llm(
     if settings.GITHUB_COPILOT_TOKEN_DIR:
         os.environ.setdefault("GITHUB_COPILOT_TOKEN_DIR", settings.GITHUB_COPILOT_TOKEN_DIR)
 
+    # Use ChatLiteLLM for provider-prefixed models (github_copilot/, anthropic/, etc.)
+    # so LiteLLM handles routing and auth. ChatOpenAI for plain OpenAI model names.
+    if "/" in model:
+        return ChatLiteLLM(model=model, temperature=temperature)
+
     return ChatOpenAI(
         model=model,
         temperature=temperature,
@@ -79,7 +89,7 @@ def get_llm(
 def get_router_llm(
     *,
     temperature: float = 0,
-) -> ChatOpenAI:
+) -> ChatOpenAI | ChatLiteLLM:
     """Return the lighter model used for intent classification / routing."""
     return get_llm(model=settings.LLM_ROUTER_MODEL, temperature=temperature)
 

app/core/orchestrator.py

@@ -162,17 +162,23 @@ async def orchestrate_v3_stream(
     message: str,
     context: dict[str, Any],
     reg: AgentRegistry | None = None,
+    agent_holder: list | None = None,
 ) -> AsyncGenerator[tuple[str, str], None]:
     """v3 streaming orchestration — yields (agent_name, token) pairs.
 
     The first yield always carries the agent_name with an empty token so that
     callers (e.g. FloatingFormatter) can detect the routing domain before any text
     tokens arrive.
+
+    If *agent_holder* is provided (a list), the agent instance is appended so
+    callers can access ``agent.tool_results`` after the stream completes.
     """
     if reg is None:
         reg = _default_registry
     agent_name = await classify_intent(message, context, reg)
     agent = reg.get(agent_name)
+    if agent_holder is not None:
+        agent_holder.append(agent)
     yield agent_name, ""  # domain signal — no token yet
     async for token in agent.handle_stream(message, context):
         yield agent_name, token

app/core/ws_context.py

@@ -84,5 +84,9 @@ async def execute_on_client(
     result = await callback(payload)
     collector = _tool_result_collector.get(None)
     if collector is not None:
-        collector.append(result)
+        collector.append({
+            "action": action,
+            "table": table,
+            "data": result,
+        })
     return result

app/db.py

@@ -24,7 +24,7 @@ from app.config.settings import settings
 engine = create_async_engine(
     settings.DATABASE_URL,
     pool_pre_ping=True,
-    echo=settings.ENV == "dev",
+    echo=False,
 )
 
 async_session = async_sessionmaker(engine, expire_on_commit=False)

app/main.py

@@ -1,8 +1,16 @@
 from contextlib import asynccontextmanager
+import logging
 
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s %(levelname)s %(name)s: %(message)s",
+)
+logging.getLogger("sqlalchemy.engine").setLevel(logging.WARNING)
+logging.getLogger("sqlalchemy.pool").setLevel(logging.WARNING)
+
 from app.api.middleware.rate_limit import TierRateLimitMiddleware
 from app.api.middleware.sanitizer import SanitizerMiddleware
 from app.config.settings import settings

logging.conf

@@ -0,0 +1,56 @@
+[loggers]
+keys=root,uvicorn,uvicorn.error,uvicorn.access,sqlalchemy,watchfiles
+
+[handlers]
+keys=console,file
+
+[formatters]
+keys=default
+
+[logger_root]
+level=INFO
+handlers=console,file
+
+[logger_uvicorn]
+level=INFO
+handlers=
+qualname=uvicorn
+propagate=1
+
+[logger_uvicorn.error]
+level=INFO
+handlers=
+qualname=uvicorn.error
+propagate=1
+
+[logger_uvicorn.access]
+level=INFO
+handlers=
+qualname=uvicorn.access
+propagate=1
+
+[logger_sqlalchemy]
+level=WARNING
+handlers=
+qualname=sqlalchemy
+propagate=1
+
+[logger_watchfiles]
+level=WARNING
+handlers=
+qualname=watchfiles
+propagate=1
+
+[handler_console]
+class=StreamHandler
+formatter=default
+args=(sys.stderr,)
+
+[handler_file]
+class=logging.handlers.RotatingFileHandler
+formatter=default
+args=('logs/app.log', 'a', 10485760, 5, 'utf-8')
+
+[formatter_default]
+format=%(asctime)s %(levelname)s %(name)s: %(message)s
+datefmt=%Y-%m-%d %H:%M:%S

requirements.txt

@@ -3,6 +3,7 @@ uvicorn[standard]>=0.34.0
 gunicorn>=22.0.0
 langchain>=0.3.0
 langchain-openai>=0.3.0
+langchain-litellm>=0.1.0
 litellm>=1.50.0
 pydantic>=2.10.0
 pydantic-settings>=2.7.0