feat: support llm env in env file (#251)

src/config/loader.py

@@ -18,6 +18,8 @@ def replace_env_vars(value: str) -> str:
 
 def process_dict(config: Dict[str, Any]) -> Dict[str, Any]:
     """Recursively process dictionary to replace environment variables."""
+    if not config:
+        return {}
     result = {}
     for key, value in config.items():
         if isinstance(value, dict):

src/llms/llm.py

@@ -3,6 +3,7 @@
 
 from pathlib import Path
 from typing import Any, Dict
+import os
 
 from langchain_openai import ChatOpenAI
 
@@ -13,18 +14,40 @@ from src.config.agents import LLMType
 _llm_cache: dict[LLMType, ChatOpenAI] = {}
 
 
+def _get_env_llm_conf(llm_type: str) -> Dict[str, Any]:
+    """
+    Get LLM configuration from environment variables.
+    Environment variables should follow the format: {LLM_TYPE}__{KEY}
+    e.g., BASIC_MODEL__api_key, BASIC_MODEL__base_url
+    """
+    prefix = f"{llm_type.upper()}_MODEL__"
+    conf = {}
+    for key, value in os.environ.items():
+        if key.startswith(prefix):
+            conf_key = key[len(prefix) :].lower()
+            conf[conf_key] = value
+    return conf
+
+
 def _create_llm_use_conf(llm_type: LLMType, conf: Dict[str, Any]) -> ChatOpenAI:
     llm_type_map = {
-        "reasoning": conf.get("REASONING_MODEL"),
-        "basic": conf.get("BASIC_MODEL"),
-        "vision": conf.get("VISION_MODEL"),
+        "reasoning": conf.get("REASONING_MODEL", {}),
+        "basic": conf.get("BASIC_MODEL", {}),
+        "vision": conf.get("VISION_MODEL", {}),
     }
     llm_conf = llm_type_map.get(llm_type)
-    if not llm_conf:
-        raise ValueError(f"Unknown LLM type: {llm_type}")
     if not isinstance(llm_conf, dict):
         raise ValueError(f"Invalid LLM Conf: {llm_type}")
-    return ChatOpenAI(**llm_conf)
+    # Get configuration from environment variables
+    env_conf = _get_env_llm_conf(llm_type)
+
+    # Merge configurations, with environment variables taking precedence
+    merged_conf = {**llm_conf, **env_conf}
+
+    if not merged_conf:
+        raise ValueError(f"Unknown LLM Conf: {llm_type}")
+
+    return ChatOpenAI(**merged_conf)
 
 
 def get_llm_by_type(