gjj

app/ai_agent/agent.py

@@ -1,5 +1,10 @@
 from typing import List, Dict, Any, Optional
-from langchain.agents import create_react_agent, initialize_agent, AgentType
+try:
+    # Newer LC may or may not expose create_react_agent
+    from langchain.agents import create_react_agent, initialize_agent, AgentType  # type: ignore
+except Exception:  # pragma: no cover - be resilient to LC API changes
+    from langchain.agents import initialize_agent, AgentType  # type: ignore
+    create_react_agent = None  # type: ignore
 from langchain_openai import ChatOpenAI
 from langchain_community.chat_models import ChatOllama
 from langchain_community.tools import Tool
@@ -482,7 +487,7 @@ N'oublie pas : tu es empathique, humain, et tu adaptes toujours ton niveau de la
             logger.info("Legacy/string agent created successfully")
             return legacy_agent
 
-        # Messages-based ReAct agent with Pydantic output parser guidance
+        # Messages-based ReAct agent (fallbacks if create_react_agent is unavailable)
         logger.info("Creating messages-based ReAct agent")
         # Combine system prompt with ReAct-style instructions (no JSON)
         template = system_message + """
@@ -503,10 +508,36 @@ Begin!
             tool_names=", ".join([t.name for t in tools]) if tools else "none",
             tools="\n".join([f"- {t.name}: {t.description}" for t in tools]) if tools else "No tools available",
         )
-        agent = create_react_agent(llm, tools, prompt)
-        logger.info("Messages-based agent created successfully")
-        # Return the runnable agent directly (compatible with newer LangChain versions)
-        return agent
+        if create_react_agent is not None:
+            try:
+                agent = create_react_agent(llm, tools, prompt)
+                logger.info("Messages-based agent created successfully (create_react_agent)")
+                return agent
+            except Exception as e:
+                logger.warning(f"create_react_agent unavailable or failed: {e}; falling back to initialize_agent")
+
+        # Fallback: initialize_agent ZERO_SHOT_REACT_DESCRIPTION with our prompt
+        try:
+            legacy_agent = initialize_agent(
+                tools=tools,
+                llm=llm,
+                agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
+                prompt=prompt,
+                **common_kwargs,
+            )
+            logger.info("Messages-based agent created successfully via initialize_agent fallback")
+            return legacy_agent
+        except Exception as e:
+            logger.warning(f"initialize_agent with prompt failed: {e}; trying minimal initialize_agent")
+            # Last resort minimal init without prompt arg (for very new/old LC variants)
+            legacy_agent = initialize_agent(
+                tools=tools,
+                llm=llm,
+                agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
+                **common_kwargs,
+            )
+            logger.info("Messages-based agent created via minimal initialize_agent")
+            return legacy_agent
         
     except Exception as e:
         logger.error(f"Error creating agent: {str(e)}", exc_info=True)

requirements.txt

@@ -10,7 +10,7 @@ PyPDF2
 httpx
 openai
 python-dotenv
-langchain-openai
+langchain-openai<0.3
 langchain-huggingface
 huggingface-hub
 cachetools
@@ -28,7 +28,7 @@ langdetect
 requests
 serpapi
 googlemaps
-langchain
-langchain-community
-langchain-core
+langchain<0.3
+langchain-community<0.3
+langchain-core<0.3
 langsmith