Update app.py

app.py

@@ -1,8 +1,10 @@
 import os
-import re
-import json
+import gradio as gr
 import requests
+import inspect
 import pandas as pd
+import re
+import json
 from pathlib import Path
 from typing import Optional
 from dotenv import load_dotenv
@@ -11,16 +13,16 @@ from langgraph.prebuilt import create_react_agent
 from langchain_core.messages import HumanMessage
 from langchain_core.tools import tool
 from langchain_openai import ChatOpenAI
-import inspect
 
 load_dotenv()
 
+# ------------------ CUSTOM LLM ------------------
 
 class OpenRouterLLM(ChatOpenAI):
     """Custom OpenRouter LLM wrapper for LangGraph"""
     
     def __init__(self, model: str = "deepseek/deepseek-v3.1-terminus", **kwargs):
-        api_key = os.getenv("OPENROUTER_API_KEY") or os.getenv("agentkey")
+        api_key = os.getenv("OPENROUTER_API_KEY") or os.getenv("my_key")
         super().__init__(
             model=model,
             openai_api_key=api_key,
@@ -28,12 +30,10 @@ class OpenRouterLLM(ChatOpenAI):
             **kwargs
         )
 
-
 # ------------------ TOOLS ------------------
 
 @tool
 def search_web(query: str) -> str:
-    """Search the web using DuckDuckGo for current information."""
     try:
         search_url = f"https://api.duckduckgo.com/?q={query}&format=json&no_html=1&skip_disambig=1"
         response = requests.get(search_url, timeout=10)
@@ -51,10 +51,8 @@ def search_web(query: str) -> str:
     except Exception as e:
         return f"Search error: {str(e)}"
 
-
 @tool
 def search_wikipedia(query: str) -> str:
-    """Search Wikipedia for factual information."""
     try:
         search_url = "https://en.wikipedia.org/api/rest_v1/page/summary/" + query.replace(" ", "_")
         response = requests.get(search_url, timeout=10)
@@ -66,10 +64,8 @@ def search_wikipedia(query: str) -> str:
     except Exception as e:
         return f"Wikipedia search error: {str(e)}"
 
-
 @tool
 def execute_python(code: str) -> str:
-    """Execute Python code and return the result."""
     try:
         safe_globals = {
             '__builtins__': {
@@ -95,10 +91,8 @@ def execute_python(code: str) -> str:
     except Exception as e:
         return f"Python execution error: {str(e)}"
 
-
 @tool
 def read_excel_file(file_path: str, sheet_name: Optional[str] = None) -> str:
-    """Read an Excel file and return its contents as a formatted string."""
     try:
         file_path_obj = Path(file_path)
         if not file_path_obj.exists():
@@ -120,10 +114,8 @@ def read_excel_file(file_path: str, sheet_name: Optional[str] = None) -> str:
     except Exception as e:
         return f"Error reading Excel file: {str(e)}"
 
-
 @tool
 def read_text_file(file_path: str) -> str:
-    """Read a text file and return its contents."""
     try:
         file_path_obj = Path(file_path)
         if not file_path_obj.exists():
@@ -139,14 +131,13 @@ def read_text_file(file_path: str) -> str:
     except Exception as e:
         return f"Error reading file: {str(e)}"
 
-
 # ------------------ GAIA AGENT ------------------
 
 class GaiaAgent:
-    """LangGraph-based agent for GAIA tasks using OpenRouter DeepSeek"""
+    """LangGraph-based agent using OpenRouter DeepSeek"""
     
     def __init__(self):
-        print("Initializing GaiaAgent with LangGraph and OpenRouter DeepSeek...")
+        print("Initializing GaiaAgent...")
         self.llm = OpenRouterLLM(
             model="deepseek/deepseek-v3.1-terminus",
             temperature=0.1,
@@ -154,8 +145,6 @@ class GaiaAgent:
         )
         self.tools = [search_web, search_wikipedia, execute_python, read_excel_file, read_text_file]
         prompt_modifier = self._get_system_prompt()
-
-        # Detect correct kwarg for your LangGraph version
         sig = inspect.signature(create_react_agent)
         accepted = sig.parameters.keys()
         kwargs = {}
@@ -165,55 +154,76 @@ class GaiaAgent:
             kwargs["state_modifier"] = prompt_modifier
         elif "prompt" in accepted:
             kwargs["prompt"] = prompt_modifier
-
         self.agent = create_react_agent(self.llm, self.tools, **kwargs)
         print("GaiaAgent initialized successfully!")
 
     def _get_system_prompt(self) -> str:
-        return """You are an advanced AI agent designed to answer complex questions...
-(keep your original system prompt here)"""
+        return """You are an advanced AI agent designed to answer complex questions.
+Keep answers concise and factual where possible."""
 
-    def __call__(self, task_id: str, question: str) -> str:
+    def __call__(self, question: str) -> str:
         try:
-            print(f"Processing task {task_id}: {question[:100]}...")
             messages = [HumanMessage(content=question)]
             result = self.agent.invoke({"messages": messages})
-            final_message = result["messages"][-1]
-            answer = final_message.content
+            answer = result["messages"][-1].content
             return self._clean_answer(answer)
         except Exception as e:
             return f"Agent error: {e}"
 
     def _clean_answer(self, answer: str) -> str:
-        # same cleaning code as before
         answer = answer.strip()
         if "final answer:" in answer.lower():
             parts = re.split(r'final answer:', answer, flags=re.IGNORECASE)
             if len(parts) > 1:
                 answer = parts[-1].strip()
-        prefixes = ["The answer is", "Answer:", "Result:", "Solution:",
-                    "Based on", "Therefore", "In conclusion", "So the answer is"]
+        prefixes = ["The answer is", "Answer:", "Result:", "Solution:"]
         for prefix in prefixes:
             if answer.lower().startswith(prefix.lower()):
                 answer = answer[len(prefix):].strip()
                 if answer.startswith(':'):
                     answer = answer[1:].strip()
                 break
-        if len(answer.split()) <= 3:
-            answer = answer.strip('"\'.')
         return answer
 
+# ------------------ RUN AND SUBMIT ------------------
 
-# ------------------ ENTRYPOINT ------------------
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-import gradio as gr
-
-agent = GaiaAgent()
+def run_and_submit_all(profile: gr.OAuthProfile | None):
+    if profile:
+        username = profile.username
+    else:
+        return "Please login to Hugging Face first.", None
 
-def run_agent(prompt: str) -> str:
-    return agent("gaia_task", prompt)
+    space_id = os.getenv("SPACE_ID") or "your_space_username/your_space_name"
+    api_url = DEFAULT_API_URL
+    questions_url = f"{api_url}/questions"
+    submit_url = f"{api_url}/submit"
 
-demo = gr.Interface(fn=run_agent, inputs="text", outputs="text", title="GAIA Agent")
+    # Instantiate GaiaAgent
+    try:
+        agent = GaiaAgent()
+    except Exception as e:
+        return f"Error initializing GaiaAgent: {e}", None
 
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    # Fetch questions
+    try:
+        response = requests.get(questions_url, timeout=15)
+        response.raise_for_status()
+        questions_data = response.json()
+    except Exception as e:
+        return f"Error fetching questions: {e}", None
+
+    # Run agent on questions
+    answers_payload = []
+    results_log = []
+    for item in questions_data:
+        task_id = item.get("task_id")
+        question_text = item.get("question")
+        if not task_id or question_text is None:
+            continue
+        try:
+            submitted_answer = agent(question_text)
+            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
+        except Exception as e: