Initial commit with LlamaIndex-based agent

app.py

@@ -1,4 +1,4 @@
-# Updated imports
+# app.py
 from llama_index.llms.huggingface import HuggingFaceLLM
 from llama_index.core.agent import ReActAgent
 from llama_index.core.tools import FunctionTool
@@ -8,6 +8,10 @@ import gradio as gr
 import requests
 import pandas as pd
 
+from duckduckgo_search import DDGS
+from sympy import sympify
+from sympy.core.sympify import SympifyError
+
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
@@ -15,7 +19,7 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 class SmartAgent:
     def __init__(self):
         print("Initializing Local LLM Agent...")
-        
+
         # Initialize Zephyr-7B model
         self.llm = HuggingFaceLLM(
             model_name="HuggingFaceH4/zephyr-7b-beta",
@@ -25,22 +29,22 @@ class SmartAgent:
             generate_kwargs={"temperature": 0.7, "do_sample": True},
             device_map="auto"
         )
-        
-        # Define tools
+
+        # Define tools with real implementations
         self.tools = [
             FunctionTool.from_defaults(
                 fn=self.web_search,
                 name="web_search",
-                description="Searches the web for current information when questions require up-to-date knowledge"
+                description="Searches the web for current information using DuckDuckGo."
             ),
             FunctionTool.from_defaults(
                 fn=self.math_calculator,
                 name="math_calculator",
-                description="Performs mathematical calculations when questions involve numbers or equations"
+                description="Performs symbolic math using SymPy."
             )
         ]
-        
-        # Create agent
+
+        # Create ReAct agent with tools
         self.agent = ReActAgent.from_tools(
             tools=self.tools,
             llm=self.llm,
@@ -49,18 +53,29 @@ class SmartAgent:
         print("Local LLM Agent initialized successfully.")
 
     def web_search(self, query: str) -> str:
-        """Simulated web search tool (replace with actual API)"""
+        """Real web search using DuckDuckGo"""
         print(f"Web search triggered for: {query[:50]}...")
-        return f"Web results for: {query} (implement actual search API here)"
+        try:
+            with DDGS() as ddgs:
+                results = ddgs.text(query, max_results=3)
+                if results:
+                    return "\n\n".join([f"{r['title']}: {r['href']}" for r in results])
+                else:
+                    return "No results found."
+        except Exception as e:
+            print(f"Web search error: {e}")
+            return f"Error during web search: {e}"
 
     def math_calculator(self, expression: str) -> str:
-        """Simple math calculator"""
+        """Safe math evaluation using SymPy"""
         print(f"Math calculation triggered for: {expression}")
         try:
-            result = eval(expression)  # Note: In production, use safer eval alternatives
+            result = sympify(expression).evalf()
             return str(result)
-        except:
-            return "Error: Could not evaluate the mathematical expression"
+        except SympifyError as e:
+            return f"Error: Could not parse the expression ({e})"
+        except Exception as e:
+            return f"Error: Calculation failed ({e})"
 
     def __call__(self, question: str) -> str:
         print(f"Processing question (first 50 chars): {question[:50]}...")
@@ -71,17 +86,17 @@ class SmartAgent:
             print(f"Agent error: {str(e)}")
             return f"Error processing question: {str(e)}"
 
-# --- Original Submission Logic (Keep unchanged) ---
+
+# --- Original Submission Logic ---
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the agent on them, submits all answers,
     and displays the results.
     """
-    # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
+    space_id = os.getenv("SPACE_ID")
 
     if profile:
-        username= f"{profile.username}"
+        username = f"{profile.username}"
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -91,38 +106,38 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
-    # 1. Instantiate Agent
+    # Instantiate Agent
     try:
-        agent = SmartAgent()  # Using our new SmartAgent instead of BasicAgent
+        agent = SmartAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
-    
+
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
     print(agent_code)
 
-    # 2. Fetch Questions
+    # Fetch Questions
     print(f"Fetching questions from: {questions_url}")
     try:
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
         questions_data = response.json()
         if not questions_data:
-             print("Fetched questions list is empty.")
-             return "Fetched questions list is empty or invalid format.", None
+            print("Fetched questions list is empty.")
+            return "Fetched questions list is empty or invalid format.", None
         print(f"Fetched {len(questions_data)} questions.")
     except requests.exceptions.RequestException as e:
         print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
     except requests.exceptions.JSONDecodeError as e:
-         print(f"Error decoding JSON response from questions endpoint: {e}")
-         print(f"Response text: {response.text[:500]}")
-         return f"Error decoding server response for questions: {e}", None
+        print(f"Error decoding JSON response from questions endpoint: {e}")
+        print(f"Response text: {response.text[:500]}")
+        return f"Error decoding server response for questions: {e}", None
     except Exception as e:
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
 
-    # 3. Run your Agent
+    # Run Agent on all questions
     results_log = []
     answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
@@ -137,19 +152,19 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             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:
-             print(f"Error running agent on task {task_id}: {e}")
-             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
+            print(f"Error running agent on task {task_id}: {e}")
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
 
     if not answers_payload:
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission 
+    # Prepare submission
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
 
-    # 5. Submit
+    # Submit
     print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
     try:
         response = requests.post(submit_url, json=submission_data, timeout=60)
@@ -192,7 +207,8 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
-# --- Build Gradio Interface ---
+
+# --- Gradio UI ---
 with gr.Blocks() as demo:
     gr.Markdown("# Local LLM Agent Evaluation Runner")
     gr.Markdown(
@@ -214,6 +230,7 @@ with gr.Blocks() as demo:
         outputs=[status_output, results_table]
     )
 
+
 if __name__ == "__main__":
     print("\n" + "-"*30 + " App Starting " + "-"*30)
     space_host_startup = os.getenv("SPACE_HOST")
@@ -221,17 +238,8 @@ if __name__ == "__main__":
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")
-        print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
-    else:
-        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
-
-    if space_id_startup:
         print(f"✅ SPACE_ID found: {space_id_startup}")
-        print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
     else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?).")
+        print("❌ SPACE_HOST not found. Please set environment variables.")
 
-    print("-"*(60 + len(" App Starting ")) + "\n")
-    print("Launching Gradio Interface for Local LLM Agent Evaluation...")
     demo.launch()