fix structuretool bug

agent.py

@@ -5,7 +5,7 @@ import operator as op
 from pathlib import Path
 from typing import List, TypedDict, Annotated, Optional
 
-from langchain.tools import tool
+from langchain.tools import tool, StructuredTool
 from langchain_community.document_loaders import (
     CSVLoader, PyPDFLoader, YoutubeLoader
 )
@@ -23,6 +23,10 @@ from PIL import Image
 import pytesseract
 import fitz  # PyMuPDF
 
+# Load environment variables from .env file
+from dotenv import load_dotenv
+load_dotenv()
+
 # === System Prompt ===
 SYSTEM_PROMPT = """
 You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template:
@@ -151,13 +155,14 @@ def transcribe_audio(audio_path: str) -> str:
 #claude_sonnet = init_chat_model(anthropic:claude-3-5-sonnet-latest", temperature=0)
 #gemini_2_flash = init_chat_model("google_vertexai:gemini-2.0-flash", temperature=0)
 
-_ = os.getenv("ANTHROPIC_API_KEY")
 
-tools = [
-            calculate, web_search, wikipedia_search, image_recognition,
-            read_pdf, read_csv, read_spreadsheet, transcribe_audio,
-            youtube_transcript_tool, youtube_transcript_api
-        ]
+
+tools: List[StructuredTool] = [
+    calculate, web_search, wikipedia_search, image_recognition,
+    read_pdf, read_csv, read_spreadsheet, transcribe_audio,
+    youtube_transcript_tool, youtube_transcript_api
+]
+
 class AgentState(TypedDict):
     # The document provided
     input_file: Optional[str]  # Contains file path (PDF/PNG)
@@ -208,11 +213,9 @@ class MyAgent:
             return
         self.retriever = BM25Retriever.from_documents(self.docs)
 
-        @tool
+        @tool(name="rag_search")
         def rag_search(query: str) -> str:
-            """
-            Retrieve top-3 relevant document chunks via BM25.
-            """
+            """Retrieve top-3 relevant document chunks via BM25."""
             res = self.retriever.invoke(query)
             if res:
                 return "\n\n".join([doc.page_content for doc in res[:3]])
@@ -230,9 +233,8 @@ class MyAgent:
         # Prepare state graph
         state: Dict[str, Any] = {"messages": [], "input_file": None}
 
-        # Add system message
-        tool_desc = "\n".join(f"{tool_func.__name__}: {tool_func.__doc__.strip()}" \
-                               for tool_func in self.tools)
+        # Use structured tool attributes
+        tool_desc = "\n".join(f"{t.name}: {t.description}" for t in self.tools)
         sys_msg = SystemMessage(content=f"{SYSTEM_PROMPT}\n\nTools:\n{tool_desc}")
         state["messages"].append(sys_msg)
 
@@ -251,18 +253,23 @@ class MyAgent:
         builder.add_node("assistant", self._assistant_node)
         builder.add_node("tools", ToolNode(self.tools))
         builder.add_edge(START, "assistant")
+        
+        # Updated tool detection logic
         builder.add_conditional_edges(
             "assistant",
-            lambda s: any(t.__name__ in s["messages"][-1].content for t in self.tools),
+            lambda s: any(t.name in s["messages"][-1].content for t in self.tools),
             "tools"
         )
         builder.add_edge("tools", "assistant")
         graph = builder.compile()
 
-        # Run graph until completion
-        out = graph.run(state)
+        # Use invoke() instead of run()
+        out = graph.invoke(state)
         return out["messages"][-1].content
-
+    
+    def run(self, question: str, file_paths: Optional[List[str]] = None) -> str:
+        return self(question, file_paths)
+    
     def _assistant_node(self, state: dict) -> dict:
         # Invoke LLM on current messages
         resp = self.llm.invoke(state["messages"])