Update app.py

app.py

@@ -4,30 +4,52 @@ from typing import List, Tuple
 import requests
 import gradio as gr
 import pandas as pd
+import mimetypes
+import google.generativeai as genai
 
 # --- Constants ---
 QUESTIONS_URL = "https://agents-course-unit4-scoring.hf.space/questions"
 SUBMIT_URL = "https://agents-course-unit4-scoring.hf.space/submit"
 FILES_URL = "https://agents-course-unit4-scoring.hf.space/files"
 FILES_DIR = "files"
-SYSTEM_PROMPT = "You are a helpful AI assistant tasked with answering questions accurately."
+SYSTEM_PROMPT = "You are a helpful AI assistant tasked with answering questions accurately. Provide concise and accurate answers."
+GEMINI_API_KEY = "AIzaSyBO46AIuY3Lmq3-k2bZkABgc0gL6A1RV20"
+
+# Configure Gemini API
+genai.configure(api_key=GEMINI_API_KEY)
 
 # --- AssistantAgent Implementation ---
 class AssistantAgent:
     def __init__(self, system_prompt: str):
         self.system_prompt = system_prompt
+        self.model = genai.GenerativeModel('gemini-1.5-pro')
 
     def __call__(self, question: str, file_path: str = None) -> str:
-        # Triển khai đơn giản: trả về câu trả lời dựa trên câu hỏi
-        # Thay bằng logic AI thực tế (ví dụ: gọi API Hugging Face, Grok, hoặc mô hình khác)
+        # Prepare the prompt
+        prompt = f"{self.system_prompt}\nQuestion: {question}"
+
+        # Handle file if provided
         if file_path:
-            try:
-                with open(file_path, 'r') as f:
-                    file_content = f.read()
-                return f"Answer to '{question}' with file content: {file_content}"
-            except Exception as e:
-                return f"Error reading file: {e}"
-        return f"Answer to '{question}' (prompt: {self.system_prompt})"
+            # Determine file type
+            mime_type, _ = mimetypes.guess_type(file_path)
+            if mime_type and mime_type.startswith('text'):
+                try:
+                    with open(file_path, 'r', encoding='utf-8') as f:
+                        file_content = f.read()
+                    prompt += f"\nFile content:\n{file_content}"
+                except UnicodeDecodeError as e:
+                    return f"Error reading file: {e}. File may not be a valid text file."
+                except Exception as e:
+                    return f"Error reading file: {e}"
+            else:
+                return "Error: Gemini API does not support non-text files (e.g., images, videos). Please provide a text description instead."
+
+        # Call Gemini API
+        try:
+            response = self.model.generate_content(prompt)
+            return response.text.strip()
+        except Exception as e:
+            return f"Error calling Gemini API: {e}"
 
 # --- Functions ---
 def run_and_submit_all(profile: gr.OAuthProfile | None) -> Tuple[str, pd.DataFrame]:
@@ -148,8 +170,6 @@ def download_question_file(question_uuid: str, question_file: str) -> str:
         return file_dst
     except requests.exceptions.RequestException as e:
         raise RuntimeError(f"Error downloading file: {e}")
-    except requests.exceptions.JSONDecodeError as e:
-        raise RuntimeError(f"Error decoding JSON response from files endpoint: {e}. Response text: {response.text[:500]}")
     except Exception as e:
         raise RuntimeError(f"An unexpected error occurred downloading file: {e}")
 
@@ -200,7 +220,7 @@ with gr.Blocks() as demo:
         1. Log in to your Hugging Face account using the button below.
         2. Click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, and submit answers.
         ---
-        **Note:** This is a basic setup for the Final Assignment Template. Update AssistantAgent logic for better performance.
+        **Note:** This is a basic setup for the Final Assignment Template. Agent uses Gemini API for answering.
         """
     )