Update app.py

app.py

@@ -14,7 +14,7 @@ st.set_page_config(
     layout="wide"
 )
 
-# Initialize Gemini with better error handling
+# Initialize Gemini 1.5 Pro with better error handling
 @st.cache_resource
 def init_gemini():
     try:
@@ -40,25 +40,75 @@ def init_gemini():
             except:
                 pass
         
+        # Method 4: Direct input fallback
+        if not api_key:
+            try:
+                api_key = st.secrets.get("api_key", "")
+            except:
+                pass
+        
         if api_key and api_key.strip():
+            # Configure with API key
             genai.configure(api_key=api_key.strip())
-            model = genai.GenerativeModel('gemini-1.5-flash')
+            
+            # Use Gemini 1.5 Pro model
+            model = genai.GenerativeModel('gemini-1.5-pro-latest')
+            
+            # Configure safety settings to avoid blocking
+            safety_settings = [
+                {
+                    "category": "HARM_CATEGORY_HARASSMENT",
+                    "threshold": "BLOCK_NONE"
+                },
+                {
+                    "category": "HARM_CATEGORY_HATE_SPEECH",
+                    "threshold": "BLOCK_NONE"
+                },
+                {
+                    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+                    "threshold": "BLOCK_NONE"
+                },
+                {
+                    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+                    "threshold": "BLOCK_NONE"
+                }
+            ]
             
             # Test the model with a simple query to verify it works
             try:
-                test_response = model.generate_content("Hello, respond with 'API working'")
+                test_response = model.generate_content(
+                    "Hello, respond with 'Gemini 1.5 Pro API working'",
+                    safety_settings=safety_settings,
+                    generation_config={
+                        'temperature': 0.1,
+                        'top_p': 0.8,
+                        'top_k': 40,
+                        'max_output_tokens': 100,
+                    }
+                )
                 if test_response and test_response.text:
+                    st.success(f"✅ {test_response.text}")
                     return model
             except Exception as e:
-                st.warning(f"API key provided but model test failed: {str(e)}")
+                error_msg = str(e).lower()
+                if "403" in error_msg:
+                    st.error("❌ API Key 权限不足 - 请检查 Google AI Studio 中的 API 设置")
+                elif "quota" in error_msg:
+                    st.error("❌ API 配额已用完 - 请检查使用限制")
+                elif "billing" in error_msg:
+                    st.error("❌ 需要启用计费 - Gemini 1.5 Pro 可能需要付费账户")
+                else:
+                    st.error(f"❌ 模型测试失败: {str(e)}")
                 return None
+        else:
+            st.warning("⚠️ 未找到 GOOGLE_API_KEY")
+            return None
         
-        return None
     except ImportError:
-        st.error("Google Generative AI library not installed")
+        st.error("❌ Google Generative AI 库未安装")
         return None
     except Exception as e:
-        st.warning(f"Error initializing Gemini: {str(e)}")
+        st.error(f"❌ 初始化 Gemini 时出错: {str(e)}")
         return None
 
 # Data processing functions
@@ -193,7 +243,7 @@ def create_plots(df):
     return plots
 
 def query_llm(model, data_summary, user_question):
-    """Query Gemini with production data context"""
+    """Query Gemini 1.5 Pro with production data context"""
     if not model:
         return "AI Assistant is not available. Please check API configuration."
     
@@ -215,32 +265,62 @@ def query_llm(model, data_summary, user_question):
         
         context += f"\nUser Question: {user_question}\n\nPlease provide a concise, data-driven answer based on this production data."
         
-        # Add timeout and retry logic
+        # Configure safety settings for Gemini 1.5 Pro
+        safety_settings = [
+            {
+                "category": "HARM_CATEGORY_HARASSMENT",
+                "threshold": "BLOCK_NONE"
+            },
+            {
+                "category": "HARM_CATEGORY_HATE_SPEECH",
+                "threshold": "BLOCK_NONE"
+            },
+            {
+                "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+                "threshold": "BLOCK_NONE"
+            },
+            {
+                "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+                "threshold": "BLOCK_NONE"
+            }
+        ]
+        
+        # Gemini 1.5 Pro generation config
+        generation_config = {
+            'temperature': 0.2,
+            'top_p': 0.8,
+            'top_k': 40,
+            'max_output_tokens': 2048,
+            'candidate_count': 1
+        }
+        
         response = model.generate_content(
             context,
-            generation_config={
-                'temperature': 0.1,
-                'top_p': 0.8,
-                'top_k': 40,
-                'max_output_tokens': 1024,
-            }
+            safety_settings=safety_settings,
+            generation_config=generation_config
         )
         
         if response and response.text:
             return response.text
+        elif response and hasattr(response, 'candidates') and response.candidates:
+            return "Response was blocked by safety filters. Please try rephrasing your question."
         else:
-            return "No response received from AI model."
+            return "No response received from Gemini 1.5 Pro."
             
     except Exception as e:
         error_msg = str(e).lower()
         if "403" in error_msg or "forbidden" in error_msg:
-            return "AI service access denied. Please check your API key permissions and quota."
-        elif "quota" in error_msg:
-            return "AI service quota exceeded. Please try again later."
+            return "❌ API access denied. Please check:\n1. API Key validity\n2. Gemini API is enabled\n3. Account has sufficient permissions"
+        elif "quota" in error_msg or "resource_exhausted" in error_msg:
+            return "❌ API quota exceeded. Please try again later or upgrade your account."
         elif "timeout" in error_msg:
-            return "AI service timeout. Please try again."
+            return "⏱️ Request timeout. Please try again."
+        elif "billing" in error_msg:
+            return "💳 Billing account required for Gemini 1.5 Pro."
+        elif "safety" in error_msg:
+            return "🛡️ Content blocked by safety filters. Please rephrase your question."
         else:
-            return f"AI service error: {str(e)}"
+            return f"❌ AI service error: {str(e)}"
 
 # Load data with better error handling
 def load_data(uploaded_file):
@@ -277,22 +357,56 @@ def main():
         uploaded_file = st.file_uploader("Choose CSV file", type=['csv'])
         
         if model:
-            st.success("🤖 AI Assistant Ready")
+            st.success("🤖 Gemini 1.5 Pro AI Assistant Ready")
         else:
-            st.warning("⚠️ AI Assistant unavailable")
-            with st.expander("API Configuration Help"):
+            st.warning("⚠️ Gemini 1.5 Pro AI Assistant unavailable")
+            with st.expander("🔧 API Configuration Help"):
                 st.markdown("""
-                To enable AI features:
-                1. Get a Google AI API key from https://ai.google.dev/
-                2. Add it to your Streamlit secrets as `GOOGLE_API_KEY`
-                3. Or set it as environment variable `GOOGLE_API_KEY`
+                **Steps to enable Gemini 1.5 Pro:**
                 
-                Common 403 errors:
-                - Invalid API key
-                - API key lacks permissions
-                - Quota exceeded
-                - Service not enabled
+                1. **Get API Key**:
+                   - Visit [Google AI Studio](https://aistudio.google.com/app/apikey)
+                   - Create a new API Key
+                
+                2. **Set API Key**:
+                   ```bash
+                   # Environment variable
+                   export GOOGLE_API_KEY="your_api_key_here"
+                   ```
+                   Or in Streamlit secrets.toml:
+                   ```toml
+                   GOOGLE_API_KEY = "your_api_key_here"
+                   ```
+                
+                3. **Common 403 Error Causes**:
+                   - ❌ Invalid or expired API Key
+                   - ❌ Generative AI API not enabled
+                   - ❌ Insufficient account permissions
+                   - ❌ Billing account required (1.5 Pro may need payment)
+                   - ❌ Geographic restrictions
+                
+                4. **Solutions**:
+                   - Verify API Key is correctly copied
+                   - Enable API in Google Cloud Console
+                   - Check account billing status
+                   - Try VPN if geographic restrictions apply
                 """)
+                
+                # API Key testing tool
+                st.markdown("**🧪 API Key Testing Tool**")
+                test_api_key = st.text_input("Enter your API Key to test:", type="password")
+                if st.button("Test API Key") and test_api_key:
+                    try:
+                        import google.generativeai as genai
+                        genai.configure(api_key=test_api_key)
+                        test_model = genai.GenerativeModel('gemini-1.5-pro-latest')
+                        test_response = test_model.generate_content("Test message")
+                        if test_response.text:
+                            st.success("✅ API Key works correctly!")
+                        else:
+                            st.error("❌ API Key test failed")
+                    except Exception as e:
+                        st.error(f"❌ Error: {str(e)}")
     
     if uploaded_file is not None:
         # Load and process data