Fix using tools in home agent

.env.example

@@ -21,6 +21,8 @@ OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
 GOOGLE_API_KEY=
 CEREBRAS_API_KEY=
+GROQ_API_KEY=
+DEEPSEEK_API_KEY=
 
 # Default model used by any agent that does not have a specific override below.
 LLM_MODEL=gpt-5-mini

README.md

@@ -0,0 +1,5 @@
+## DEV
+Run in DEV with command:
+```
+uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload --log-config logging.conf
+```

app/config/settings.py

@@ -16,6 +16,8 @@ class Settings(BaseSettings):
     ANTHROPIC_API_KEY: str = ""
     GOOGLE_API_KEY: str = ""
     CEREBRAS_API_KEY: str = ""
+    GROQ_API_KEY: str = ""
+    DEEPSEEK_API_KEY: str = ""
 
     LLM_MODEL: str = "gpt-4o"
     LLM_EMBED_MODEL: str = "text-embedding-3-small"

app/core/deep_agent.py

@@ -858,25 +858,15 @@ async def _run_single_agent_stream(
                 _gen.update(output=_as_text(response.content), usage_details=extract_usage(response))
                 _gen_ctx.__exit__(None, None, None)
 
-            messages.append(response)
-
             if not response.tool_calls:
-                emitted_any = False
+                # Yield the content from the ainvoke response directly — no second LLM call.
-                async for chunk in llm.astream(messages):
+                # Previously, messages.append(response) was called first, so the re-stream
-                    token = _as_text(getattr(chunk, "content", ""))
+                # received [System, Human, AI] and regenerated a response without tools bound.
-                    if token:
+                final_text = _as_text(response.content)
-                        streamed_chars += len(token)
+                if final_text:
-                        streamed_text.append(token)
+                    streamed_chars += len(final_text)
-                        emitted_any = True
+                    streamed_text.append(final_text)
-                        yield "token", token
+                    yield "token", final_text
-
-                # Some providers return final text in `response.content` but stream no chunks.
-                if not emitted_any:
-                    fallback_text = _as_text(response.content)
-                    if fallback_text:
-                        streamed_chars += len(fallback_text)
-                        streamed_text.append(fallback_text)
-                        yield "token", fallback_text
                 logger.info(
                     "deep_agent: run_single_agent_stream_end trace=%s user=%s tool_calls=%d response_chars=%d",
                     trace_id or "-",
@@ -888,6 +878,7 @@ async def _run_single_agent_stream(
                     _span.update(output="".join(streamed_text))
                 return
 
+            messages.append(response)
             tool_map = {tool_def.name: tool_def for tool_def in tools}
             for call in response.tool_calls:
                 tool_calls_count += 1

app/core/llm.py

@@ -51,6 +51,10 @@ def _api_key_for_model(model: str) -> str | None:
         return settings.GOOGLE_API_KEY or None
     if model.startswith("cerebras/"):
         return settings.CEREBRAS_API_KEY or None
+    if model.startswith("groq/"):
+        return settings.GROQ_API_KEY or None
+    if model.startswith("deepseek/"):
+        return settings.DEEPSEEK_API_KEY or None
     if model.startswith("github_copilot/"):
         # GitHub Copilot uses OAuth device-flow tokens managed by LiteLLM.
         # No API key is required; returning None lets LiteLLM handle auth.