feat: enhance agent configuration and model management with per-agent overrides

app/core/llm.py

@@ -19,6 +19,7 @@ from __future__ import annotations
 
 import os
 import warnings
+from collections.abc import Callable
 
 from openai import AsyncOpenAI
 import litellm
@@ -95,6 +96,35 @@ def get_llm(
     )
 
 
+_AGENT_MODEL_SETTINGS: dict[str, Callable[[], str]] = {
+    "classifier":          lambda: settings.LLM_MODEL_CLASSIFIER or settings.LLM_MODEL,
+    "home-agent":          lambda: settings.LLM_MODEL_HOME_AGENT or settings.LLM_MODEL,
+    "floating-agent":      lambda: settings.LLM_MODEL_FLOATING_AGENT or settings.LLM_MODEL,
+    "unified-processor":   lambda: settings.LLM_MODEL_UNIFIED_PROCESSOR or settings.LLM_MODEL,
+    "cloud-processor":     lambda: settings.LLM_MODEL_CLOUD_PROCESSOR or settings.LLM_MODEL,
+    "setup":               lambda: settings.LLM_MODEL_SETUP_AGENT or settings.LLM_MODEL,
+}
+
+
+def model_for_agent(agent_name: str) -> str:
+    """Return the resolved model string for *agent_name* (for Langfuse tracking)."""
+    return _AGENT_MODEL_SETTINGS.get(agent_name, lambda: settings.LLM_MODEL)()
+
+
+def get_agent_llm(
+    agent_name: str,
+    *,
+    temperature: float = 0,
+) -> ChatOpenAI | ChatLiteLLM:
+    """Return an LLM configured for *agent_name*, respecting per-agent overrides.
+
+    Falls back to ``settings.LLM_MODEL`` for unknown agent names or when the
+    per-agent override is left empty in ``.env``.
+    """
+    model = model_for_agent(agent_name)
+    return get_llm(model=model, temperature=temperature)
+
+
 async def embed(text: str) -> list[float]:
     """Return an embedding vector for *text*.