react_removed

agent.py

@@ -1,13 +1,10 @@
 from __future__ import annotations
 import os
 from langchain_openai import ChatOpenAI
-from langgraph.graph import StateGraph, START, END
-from langchain.schema import HumanMessage, SystemMessage, AIMessage
-from state import AgentState
+from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
+from langgraph.prebuilt import ToolExecutor
 from typing import Any, Dict, List, Optional
 import json
-from langgraph.prebuilt import create_react_agent
-import signal
 
 # ─────────────────────────── External tools ──────────────────────────────
 from tools import (
@@ -26,21 +23,43 @@ from tools import (
 # ─────────────────────────── Configuration ───────────────────────────────
 MAX_TOOL_CALLS = 5
 
-# ─────────────────────────── Helper utilities ────────────────────────────
+class CustomReActAgent:
+    def __init__(self, tools: List, model_name="gpt-4o-mini"):
+        self.llm = ChatOpenAI(model_name=model_name, temperature=0.3)
+        self.tool_executor = ToolExecutor(tools)
 
-# ─────────────────────────── Agent state ⬇ ───────────────────────────────
+    def run(self, question: str, task_id: Optional[str] = None, max_turns: int = 15, system_prompt: str = "") -> str:
+        messages = [SystemMessage(content=system_prompt)]
+        if task_id:
+            messages[0].content += f"\n\nIMPORTANT: Your current task_id is: {task_id}."
+        messages.append(HumanMessage(content=question))
 
-# ───────────────────────────── Nodes  ⬇ ───────────────────────────────────
+        for _ in range(max_turns):
+            ai_response = self.llm.invoke(messages)
+            messages.append(ai_response)
+            print("AI said:", ai_response.content)
 
-# ------------- tool adapters -------------
+            # Final answer?
+            if "FINAL ANSWER:" in ai_response.content.upper():
+                return ai_response.content.split("FINAL ANSWER:")[-1].strip()
 
+            # Tool call expected
+            if "Action:" in ai_response.content and "Action Input:" in ai_response.content:
+                try:
+                    tool_name = ai_response.content.split("Action:")[1].split("Action Input:")[0].strip()
+                    tool_input = ai_response.content.split("Action Input:")[1].strip()
+                    tool_result = self.tool_executor.run(tool_name, tool_input)
+                    messages.append(HumanMessage(content=f"Observation: {tool_result}"))
+                except Exception as e:
+                    messages.append(HumanMessage(content=f"Observation: Tool execution failed: {str(e)}"))
+            else:
+                messages.append(HumanMessage(content="Observation: No valid action. Please clarify."))
 
-# ─────────────────────────── Graph wiring ───────────────────────────────
+        return "No FINAL ANSWER found within allowed steps."
 
 def build_graph():
-    """Build and return a create_react_agent."""
-    llm = ChatOpenAI(model_name="gpt-4o-mini", temperature=0.3)
-
+    """Build and return a CustomReActAgent."""
+    
     llm_tools = [
         wikipedia_search_tool,
         arxiv_search_tool,
@@ -54,7 +73,7 @@ def build_graph():
         divide_tool
     ]
     
-    # Create the react agent - it will use the system prompt from the messages
-    agent = create_react_agent(model=llm, tools=llm_tools)
+    # Create the custom react agent
+    agent = CustomReActAgent(tools=llm_tools)
 
     return agent 

app.py

@@ -14,20 +14,46 @@ from state import AgentState
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 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: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
+You are a general AI assistant using the ReAct (Reasoning and Acting) approach. I will ask you a question, and you should think step by step and use tools when needed.
 
-IMPORTANT: When using tools that require file access (such as audio_transcriber_tool, excel_tool, analyze_code_tool, or image_tool), ALWAYS use the task_id parameter only. Do NOT use any file names mentioned by the user - ignore them completely and only pass the task_id.
+FORMAT:
+For each step, use this exact format:
+Thought: [your reasoning about what to do next]
+Action: [tool name]
+Action Input: [input to the tool]
+
+After using a tool, you'll receive:
+Observation: [tool result]
+
+Continue this cycle until you have enough information, then provide:
+FINAL ANSWER: [YOUR FINAL ANSWER]
+
+ANSWER FORMAT: 
+YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise.
+
+IMPORTANT: When using tools that require file access (such as audio_transcriber_tool, excel_tool, analyze_code_tool, or image_tool), ALWAYS use the task_id parameter only. Do NOT use any file names mentioned by the user.
+
+AVAILABLE TOOLS:
+- wikipedia_search_tool: For historical, biographical, scientific facts
+- arxiv_search_tool: For academic research papers
+- audio_transcriber_tool: For transcribing audio files
+- excel_tool: For analyzing spreadsheet data
+- analyze_code_tool: For understanding code files
+- image_tool: For describing images
+- add_tool: For adding numbers
+- subtract_tool: For subtracting numbers
+- multiply_tool: For multiplying numbers
+- divide_tool: For dividing numbers
 
 SEARCH STRATEGY: 
-- If wikipedia_search_tool fails or returns insufficient/irrelevant results, try these fallback strategies:
-  1. Try wikipedia_search_tool again with a broader, more general query (remove specific terms, use synonyms)
-  2. If Wikipedia still doesn't help, try arxiv_search_tool for academic/research topics
-  3. You can use multiple search attempts with different keywords to find better information
-- Always evaluate if the search results are relevant and sufficient before proceeding to your final answer
-- IMPORTANT: When you see [END_OF_SEARCH] in tool results, this means the search is complete and you have all available information
-- Do NOT perform additional searches after seeing [END_OF_SEARCH] - immediately proceed to analyze the provided information and give your final answer
-
-You MUST always provide a FINAL ANSWER. If you reach the recursion limit or tools fail, provide the best answer possible with available information.
+- If wikipedia_search_tool fails, try with broader queries or use arxiv_search_tool for academic topics
+- When you see [END_OF_SEARCH] in results, stop searching and provide your final answer
+- You MUST always provide a FINAL ANSWER, even if tools fail
+
+Example:
+Thought: I need to find information about quantum computing.
+Action: wikipedia_search_tool
+Action Input: quantum computing
 """
 
 
@@ -37,48 +63,15 @@ class BasicAgent:
         self.graph = build_graph()
 
     def __call__(self, question: str, task_id: Optional[str] = None) -> str:
-        """Run the agent and return whatever FINAL_ANSWER the graph produces."""
+        """Run the agent and return whatever FINAL_ANSWER the agent produces."""
         print(f"Agent received question: {question}")
         
         try:
-            # Create system prompt with task_id included
-            system_prompt_with_task = SYSTEM_PROMPT
-            if task_id:
-                system_prompt_with_task += f"\n\nIMPORTANT: Your current task_id is: {task_id}. When using any tools that require a task_id parameter (audio_transcriber_tool, excel_tool, analyze_code_tool, image_tool), use this exact task_id: {task_id}"
-            
-            # Initialize the state properly with all required fields
-            init_state = {
-                "messages": [
-                    SystemMessage(content=system_prompt_with_task),
-                    HumanMessage(content=question)
-                ]
-            }
-            
-            # Run the agent with increased steps
-            out_state = self.graph.invoke(init_state, {"recursion_limit": 15})
-            
-            # Extract the final answer from the last message
-            if out_state and "messages" in out_state:
-                last_message = out_state["messages"][-1]
-                if hasattr(last_message, 'content') and last_message.content:
-                    content = last_message.content
-                    print("content: ", content)
-                    print("\n\n\n\n")
-                    
-                    # Look for FINAL ANSWER: pattern (case insensitive)
-                    if "FINAL ANSWER:" in content.upper():
-                        # Find the last occurrence of FINAL ANSWER
-                        parts = content.upper().split("FINAL ANSWER:")
-                        if len(parts) > 1:
-                            # Get the original case version
-                            answer_start = content.upper().rfind("FINAL ANSWER:") + len("FINAL ANSWER:")
-                            final_answer = content[answer_start:].strip()
-                            return final_answer
-                    
-                    # If no FINAL ANSWER found, return the whole content
-                    return content
-                    
-            return "No valid response generated."
+            # Run the custom react agent
+            result = self.graph.run(question=question, task_id=task_id, max_turns=15, system_prompt=SYSTEM_PROMPT)
+            print("Final result: ", result)
+            print("\n\n\n\n")
+            return result
             
         except Exception as e:
             print(f"Agent execution error: {e}")

tools.py

@@ -219,18 +219,12 @@ def wikipedia_search_tool(wiki_query: str) -> str:
     - "Explain quantum entanglement"
     - "Tell me about the French Revolution"
     """
-    print(f"DEBUG: reached wikipedia_search_tool with query: {wiki_query}")
     try:
         docs = WikipediaLoader(query=wiki_query, load_max_docs=3).load()  # Reduced from 5 to 3
-        print(f"DEBUG: WikipediaLoader returned {len(docs)} documents")
         
         result = ""
         counter = 1
         for doc in docs:
-            print(f"DEBUG: Processing Wikipedia document {counter}")
-            print(f"DEBUG: Document metadata: {doc.metadata}")
-            print(f"DEBUG: Document content length: {len(doc.page_content)}")
-            
             # Handle different metadata structures
             title = "Unknown Title"
             if hasattr(doc, 'metadata') and doc.metadata:
@@ -247,8 +241,6 @@ def wikipedia_search_tool(wiki_query: str) -> str:
                         first_key = list(doc.metadata.keys())[0]
                         title = f"Wikipedia: {doc.metadata[first_key]}"
             
-            print(f"DEBUG: Using Wikipedia title: {title}")
-            
             # Trim content to key information only (reduced from 2000 to 800 characters)
             content = doc.page_content[:800] if len(doc.page_content) > 800 else doc.page_content
             
@@ -266,12 +258,11 @@ def wikipedia_search_tool(wiki_query: str) -> str:
         # Add clear end marker
         result += "\n\n[END_OF_SEARCH] - Wikipedia search complete. Use this information to answer the question."
         
-        print(f"DEBUG: Final Wikipedia result length: {len(result)}")
+        print("Wikipedia search completed successfully")
         return result
         
     except Exception as e:
         error_msg = f"Error during Wikipedia search: {str(e)} [END_OF_SEARCH]"
-        print(f"DEBUG: {error_msg}")
         return error_msg
     
 @tool