Create app.py

app.py

@@ -11,11 +11,15 @@ from pydub import AudioSegment # Import pydub for audio manipulation
 import tempfile # Import tempfile for temporary file handling
 import numpy as np # Import numpy for image processing
 
+print("All libraries imported successfully.") # Debugging print
 
 # Import libraries for SerpAPI
-from serpapi import GoogleSearch
+# Corrected import: Import GoogleSearch from google_search_results
+from google_search_results import GoogleSearch
 import google.generativeai as genai # Keep the import as the user might add LLM functionality back later
 
+print("SerpAPI and GenAI libraries imported successfully.") # Debugging print
+
 # Removed the import of google.colab.userdata as it's not available outside Colab
 # from google.colab import userdata # To access the API key from secrets
 
@@ -29,9 +33,13 @@ print(f"SERPAPI_API_KEY (first 5 chars): {SERPAPI_API_KEY[:5] if SERPAPI_API_KEY
 GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
 print(f"GOOGLE_API_KEY (first 5 chars): {GOOGLE_API_KEY[:5] if GOOGLE_API_KEY else 'None'}...") # Debugging API key
 
+print("API keys retrieved (or attempted).") # Debugging print
+
 # --- Define the default API URL ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" # Updated API URL
 
+print(f"DEFAULT_API_URL set to: {DEFAULT_API_URL}") # Debugging print
+
 
 # --- Google Generative AI LLM Initialization ---
 # Keep LLM initialization but handle potential errors and None state
@@ -58,8 +66,11 @@ else:
         print(f"An error occurred during Google Generative AI initialization: {e}")
         gemini_model = None # Ensure model is None if initialization fails
 
+print("LLM initialization attempted.") # Debugging print
+
 
 # --- Web Search Function (using SerpAPI) ---
+print("Defining web_search function...") # Debugging print
 def web_search(query: str) -> list[dict]:
     # Removed global gemini_model declaration as it's not used here
     """
@@ -87,14 +98,14 @@ def web_search(query: str) -> list[dict]:
     results = []
 
     try:
-        search = GoogleSearch(params)
+        search = GoogleSearch(params) # Use GoogleSearch from the correct package
         search_results_dict = search.get_dict() # Get results as a dictionary
         print(f"SerpAPI raw response keys: {search_results_dict.keys() if isinstance(search_results_dict, dict) else 'Response is not a dictionary'}") # Debugging response keys
 
         # Log the full SerpAPI response for debugging if organic_results is missing or empty
         if not isinstance(search_results_dict, dict) or "organic_results" not in search_results_dict or not isinstance(search_results_dict["organic_results"], list) or not search_results_dict["organic_results"]:
              print(f"SerpAPI response did not contain organic results or had invalid format. Response: {search_results_dict}")
-
+             search_results = [] # Ensure search_results is empty if no organic results
 
         # Extract organic results
         # Add check that search_results_dict and organic_results are valid
@@ -110,21 +121,19 @@ def web_search(query: str) -> list[dict]:
                     'url': result.get('link'),
                     'snippet': result.get('snippet', 'No snippet available')
                 }
-                results.append(item)
-        else:
-            print(f"No 'organic_results' key found or invalid format in SerpAPI response. Response type: {type(search_results_dict)}")
+                search_results.append(item) # Append to search_results
 
 
     except Exception as e:
         print(f"An error occurred during SerpAPI web search: {e}")
-        # Ensure an empty list is returned on error
-        return []
+        return f"An error occurred during web search: {e}"
 
-    print(f"web_search returning {len(results)} results.") # Debugging return count
-    return results # Always return a list (empty or with results)
+    print(f"web_search returning {len(search_results)} results.") # Debugging return count
+    return search_results # Always return a list (empty or with results)
 
 
 # --- Basic Agent Definition (Modified to remove LLM dependency for now) ---
+print("Defining BasicAgent class...") # Debugging print
 class BasicAgent:
 
     def __init__(self):
@@ -343,13 +352,44 @@ class BasicAgent:
             if needs_search:
                 print(f"Question likely requires search. Searching for: {search_query}")
                 try:
-                    search_results = web_search(search_query) # Call the web_search function with the generated query
-                    print(f"Received {len(search_results)} search results from web_search.") # Debugging results received
-                    print(f"Type of search_results: {type(search_results)}") # Debugging type of search_results
+                    params = { # Define params here, before calling GoogleSearch
+                        "q": search_query,
+                        "api_key": SERPAPI_API_KEY,
+                        "engine": "google",  # Use Google search engine
+                        "num": 5 # Number of results to fetch
+                    }
+                    search = GoogleSearch(params) # Use GoogleSearch from the correct package
+                    search_results_dict = search.get_dict() # Get results as a dictionary
+                    print(f"SerpAPI raw response keys: {search_results_dict.keys() if isinstance(search_results_dict, dict) else 'Response is not a dictionary'}") # Debugging response keys
+
+                    # Log the full SerpAPI response for debugging if organic_results is missing or empty
+                    if not isinstance(search_results_dict, dict) or "organic_results" not in search_results_dict or not isinstance(search_results_dict["organic_results"], list) or not search_results_dict["organic_results"]:
+                         print(f"SerpAPI response did not contain organic results or had invalid format. Response: {search_results_dict}")
+                         search_results = [] # Ensure search_results is empty if no organic results
+
+                    # Extract organic results
+                    # Add check that search_results_dict and organic_results are valid
+                    if isinstance(search_results_dict, dict) and "organic_results" in search_results_dict and isinstance(search_results_dict["organic_results"], list):
+                        print(f"Found {len(search_results_dict['organic_results'])} organic results.") # Debugging result count
+                        for result in search_results_dict["organic_results"]:
+                            # Add check for None or non-dict result item
+                            if result is None or not isinstance(result, dict):
+                                print(f"Skipping invalid search result item: {result}")
+                                continue
+                            item = {
+                                'title': result.get('title'),
+                                'url': result.get('link'),
+                                'snippet': result.get('snippet', 'No snippet available')
+                            }
+                            search_results.append(item) # Append to search_results
+
+
                 except Exception as e:
-                    print(f"An error occurred during web search: {e}")
+                    print(f"An error occurred during SerpAPI web search: {e}")
                     return f"An error occurred during web search: {e}"
 
+                print(f"web_search returning {len(search_results)} results.") # Debugging return count
+
                 # --- Use LLM to process search results if available (Removed LLM Synthesis) ---
                 # Check that search_results is a list and is not empty
                 if isinstance(search_results, list) and search_results and gemini_model is not None:
@@ -613,6 +653,7 @@ def test_audio_processing(audio_source: str) -> str:
 
 
 # Move Gradio interface definition and launch outside the function
+print("Defining Gradio interface...") # Debugging print
 with gr.Blocks(theme=gr.themes.Soft(), title="Basic Agent Evaluation Runner") as demo:
     gr.Markdown(
         """
@@ -665,7 +706,11 @@ with gr.Blocks(theme=gr.themes.Soft(), title="Basic Agent Evaluation Runner") as
         outputs=[audio_test_output]
     )
 
+print("Gradio interface defined.") # Debugging print
 
 # Ensure the app launches when the script is run
+print("Checking if script is run directly...") # Debugging print
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0") # Ensure binding to all interfaces
+    print("Launching Gradio demo...") # Debugging print
+    demo.launch(server_name="0.0.0.0") # Ensure binding to all interfaces
+print("Script finished.") # Debugging print