Update agent.py

agent.py

@@ -15,6 +15,57 @@ from langchain_core.messages import SystemMessage, HumanMessage
 from langchain_core.tools import tool
 from langchain.tools.retriever import create_retriever_tool
 from supabase.client import Client, create_client
+# --- langchain create_retriever_tool fallback (paste near other imports) ---
+import traceback
+
+try:
+    from langchain.tools.retriever import create_retriever_tool
+    HAS_CREATE_RETRIEVER_TOOL = True
+except Exception:
+    HAS_CREATE_RETRIEVER_TOOL = False
+    print("Warning: langchain.tools.retriever.create_retriever_tool not found. Using local fallback.")
+    print(traceback.format_exc())
+
+    class _SimpleRetrieverTool:
+        def __init__(self, retriever, name="retriever", description=""):
+            self.name = name
+            self.description = description
+            self._retriever = retriever
+
+        def run(self, query: str):
+            # Try common retriever methods in order
+            docs = []
+            try:
+                if hasattr(self._retriever, "get_relevant_documents"):
+                    docs = self._retriever.get_relevant_documents(query)
+                elif hasattr(self._retriever, "retrieve"):
+                    docs = self._retriever.retrieve(query)
+                else:
+                    # try calling the retriever directly (some callables return results)
+                    docs = self._retriever(query)
+            except Exception as e:
+                return f"[retriever-fallback-error] {e}"
+
+            # Normalize docs into strings
+            out_texts = []
+            for d in docs or []:
+                text = getattr(d, "page_content", None)
+                if text is None:
+                    if isinstance(d, dict):
+                        text = d.get("page_content") or d.get("text") or str(d)
+                    else:
+                        text = str(d)
+                out_texts.append(text.strip())
+            # return compact result
+            return "\n\n".join(t for t in out_texts if t)
+
+    def create_retriever_tool(retriever, name: str = "retriever", description: str = ""):
+        """
+        Minimal drop-in fallback that returns an object with .run(query).
+        Use this if the langchain helper isn't available in the installed package.
+        """
+        return _SimpleRetrieverTool(retriever, name=name, description=description)
+
 
 load_dotenv()