Delete app.py

app.py

@@ -1,419 +0,0 @@
-import gradio as gr
-import openai
-import json
-import os
-import time
-from typing import List, Tuple, Optional
-import requests
-from datetime import datetime
-
-class ChatbotManager:
-    def __init__(self):
-        self.conversation_history = []
-        self.current_api_key = None
-        self.current_model = "gpt-3.5-turbo"
-        self.system_prompt = "You are a helpful AI assistant. Respond in a friendly and informative manner."
-        self.max_tokens = 150
-        self.temperature = 0.7
-        
-    def set_api_key(self, api_key: str) -> str:
-        if not api_key.strip():
-            return "❌ Please enter a valid API key"
-        
-        self.current_api_key = api_key.strip()
-        openai.api_key = self.current_api_key
-        
-        try:
-            openai.Model.list()
-            return "✅ API key validated successfully!"
-        except Exception as e:
-            return f"❌ Invalid API key: {str(e)}"
-    
-    def update_settings(self, model: str, system_prompt: str, max_tokens: int, temperature: float) -> str:
-        self.current_model = model
-        self.system_prompt = system_prompt
-        self.max_tokens = max_tokens
-        self.temperature = temperature
-        return f"✅ Settings updated: Model={model}, Max Tokens={max_tokens}, Temperature={temperature}"
-    
-    def preprocess_data(self, data_text: str) -> str:
-        if not data_text.strip():
-            return "No custom data provided"
-        
-        base_prompt = "You are a helpful AI assistant. Respond in a friendly and informative manner."
-        self.system_prompt = base_prompt + f"\n\nAdditional Context:\n{data_text}"
-        return f"✅ Custom data integrated ({len(data_text)} characters)"
-    
-    def generate_response(self, user_input: str, history: List[Tuple[str, str]]) -> Tuple[str, List[Tuple[str, str]]]:
-        if not self.current_api_key:
-            return "❌ Please set your API key first!", history
-        
-        if not user_input.strip():
-            return "Please enter a message.", history
-        
-        try:
-            messages = [{"role": "system", "content": self.system_prompt}]
-            
-            for user_msg, assistant_msg in history:
-                messages.append({"role": "user", "content": user_msg})
-                messages.append({"role": "assistant", "content": assistant_msg})
-            
-            messages.append({"role": "user", "content": user_input})
-            
-            response = openai.ChatCompletion.create(
-                model=self.current_model,
-                messages=messages,
-                max_tokens=self.max_tokens,
-                temperature=self.temperature,
-                n=1,
-                stop=None,
-            )
-            
-            assistant_response = response.choices[0].message.content.strip()
-            history.append((user_input, assistant_response))
-            
-            return assistant_response, history
-            
-        except Exception as e:
-            error_msg = f"❌ Error generating response: {str(e)}"
-            return error_msg, history
-    
-    def clear_conversation(self) -> Tuple[str, List[Tuple[str, str]]]:
-        self.conversation_history = []
-        return "", []
-    
-    def export_conversation(self, history: List[Tuple[str, str]]) -> Tuple[str, Optional[str]]:
-        if not history:
-            return "No conversation to export", None
-        
-        export_data = {
-            "timestamp": datetime.now().isoformat(),
-            "model": self.current_model,
-            "conversation": [
-                {"user": user_msg, "assistant": assistant_msg}
-                for user_msg, assistant_msg in history
-            ]
-        }
-        
-        filename = f"conversation_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
-        
-        try:
-            os.makedirs("/tmp", exist_ok=True)
-            filepath = os.path.join("/tmp", filename)
-            with open(filepath, 'w', encoding='utf-8') as f:
-                json.dump(export_data, f, indent=2, ensure_ascii=False)
-            return f"✅ Conversation exported as {filename}", filepath
-        except Exception as e:
-            return f"❌ Export failed: {str(e)}", None
-
-# Initialize chatbot manager
-chatbot = ChatbotManager()
-
-# Define available models for OpenAI 0.28
-AVAILABLE_MODELS = [
-    "gpt-3.5-turbo",
-    "gpt-3.5-turbo-16k",
-    "gpt-4",
-    "gpt-4-32k",
-    "gpt-4-0613",
-    "gpt-4-32k-0613"
-]
-
-def create_interface():
-    with gr.Blocks(title="LLM-Based Chatbot", theme=gr.themes.Ocean()) as demo:
-        gr.Markdown("""
-        # 🤖 LLM-Based Conversational AI Chatbot
-        This chatbot leverages powerful Language Models to provide intelligent conversations.
-        Enter your OpenAI API key to get started!
-        """)
-        
-        with gr.Tab("💬 Chat Interface"):
-            with gr.Row():
-                with gr.Column(scale=3):
-                    chatbot_interface = gr.Chatbot(
-                        label="Conversation",
-                        height=400,
-                        show_label=True,
-                        avatar_images=("user.png", "assistant.png"),
-                        show_copy_button=True,
-                        bubble_full_width=False,
-                    )
-                    
-                    with gr.Row():
-                        user_input = gr.Textbox(
-                            placeholder="Type your message here...",
-                            scale=4,
-                            show_label=False,
-                            container=False
-                        )
-                        send_btn = gr.Button("📤 Send", variant="primary", scale=1)
-                    
-                    with gr.Row():
-                        clear_btn = gr.Button("🗑️ Clear Chat", variant="secondary")
-                        regenerate_btn = gr.Button("🔄 Regenerate", variant="secondary")
-                
-                with gr.Column(scale=1):
-                    gr.Markdown("### 🔧 Quick Settings")
-                    
-                    api_key_input = gr.Textbox(
-                        label="🔑 OpenAI API Key",
-                        placeholder="sk-...",
-                        type="password"
-                    )
-                    api_status = gr.Textbox(
-                        label="API Status",
-                        interactive=False,
-                        value="❌ No API key provided"
-                    )
-                    
-                    model_dropdown = gr.Dropdown(
-                        choices=AVAILABLE_MODELS,
-                        value="gpt-3.5-turbo",
-                        label="🤖 Model"
-                    )
-                    
-                    max_tokens_slider = gr.Slider(
-                        minimum=50,
-                        maximum=4096,
-                        value=150,
-                        step=10,
-                        label="📏 Max Tokens"
-                    )
-                    
-                    temperature_slider = gr.Slider(
-                        minimum=0.0,
-                        maximum=1.0,
-                        value=0.7,
-                        step=0.1,
-                        label="🌡️ Temperature"
-                    )
-                    
-                    gr.Markdown("### 📊 Current Settings")
-                    current_settings = gr.Textbox(
-                        value="Model: gpt-3.5-turbo\nTokens: 150\nTemp: 0.7",
-                        label="Active Configuration",
-                        interactive=False,
-                        lines=3
-                    )
-        
-        with gr.Tab("⚙️ Advanced Settings"):
-            gr.Markdown("### 🎯 System Prompt Configuration")
-            system_prompt_input = gr.Textbox(
-                label="System Prompt",
-                value="You are a helpful AI assistant. Respond in a friendly and informative manner.",
-                lines=5,
-                placeholder="Enter custom system prompt..."
-            )
-            
-            gr.Markdown("### 📚 Custom Data Integration")
-            custom_data_input = gr.Textbox(
-                label="Custom Training Data",
-                lines=10,
-                placeholder="Enter custom data, FAQs, or domain-specific information..."
-            )
-            
-            with gr.Row():
-                update_settings_btn = gr.Button("✅ Update Settings", variant="primary")
-                integrate_data_btn = gr.Button("📊 Integrate Custom Data", variant="secondary")
-                reset_prompt_btn = gr.Button("🔄 Reset to Default", variant="secondary")
-            
-            settings_status = gr.Textbox(
-                label="Settings Status",
-                interactive=False
-            )
-            
-            gr.Markdown("### 🎭 Preset System Prompts")
-            with gr.Row():
-                preset_customer_support = gr.Button("👥 Customer Support", variant="secondary")
-                preset_tutor = gr.Button("🎓 Educational Tutor", variant="secondary")
-                preset_creative = gr.Button("✨ Creative Assistant", variant="secondary")
-                preset_technical = gr.Button("🔧 Technical Writer", variant="secondary")
-        
-        with gr.Tab("📋 Usage Guide"):
-            gr.Markdown("""
-            ## 🚀 Getting Started
-            
-            ### 1. **Set Up API Key**
-            - Obtain an OpenAI API key from [OpenAI Platform](https://platform.openai.com/)
-            - Enter your API key in the "🔑 OpenAI API Key" field
-            - Wait for the green checkmark confirmation
-            
-            ### 2. **Configure Settings**
-            - **Model**: Choose from available GPT models
-            - **Max Tokens**: Control response length (50-4096)
-            - **Temperature**: Adjust creativity (0.0 = focused, 1.0 = creative)
-            
-            ### 3. **Advanced Customization**
-            - **System Prompt**: Define the AI's personality and behavior
-            - **Custom Data**: Add domain-specific information or FAQs
-            - **Presets**: Use pre-configured prompts for common use cases
-            
-            ### 4. **Chat Features**
-            - Type messages and get intelligent responses
-            - Clear conversation history anytime
-            - Regenerate the last response
-            - Copy responses using the copy button
-            
-            ## 🛠️ Technical Features
-            
-            - **Multi-model support**: GPT-3.5, GPT-4, and variants
-            - **Conversation memory**: Maintains context throughout the session
-            - **Custom data integration**: Enhance responses with your own data
-            - **Real-time validation**: API key and settings verification
-            - **Visual indicators**: User and AI avatars
-            
-            ## 💡 Use Cases
-            
-            - **Customer Support**: Create domain-specific support chatbots
-            - **Education**: Build tutoring assistants with custom curriculum
-            - **Business**: Develop FAQ bots with company-specific information
-            - **Research**: Analyze conversations and response patterns
-            
-            ## 🔧 Troubleshooting
-            
-            - **API Key Issues**: Ensure your key is valid and has credits
-            - **Model Errors**: Some models may not be available in your region
-            - **Long Response Times**: Reduce max tokens or switch to faster models
-            - **Context Limits**: Clear chat history if responses become inconsistent
-            
-            ## 📦 Installation Requirements
-            
-            This version is compatible with OpenAI 0.28.0. Install dependencies:
-            ```bash
-            pip install openai==0.28.0
-            pip install gradio
-            pip install requests
-            ```
-            """)
-        
-        # Event handlers
-        def handle_api_key(api_key):
-            status = chatbot.set_api_key(api_key)
-            return status
-        
-        def handle_chat(user_input, history):
-            if not user_input.strip():
-                return history or [], ""
-            
-            response, updated_history = chatbot.generate_response(user_input, history or [])
-            return updated_history, ""
-        
-        def handle_settings_update(model, system_prompt, max_tokens, temperature):
-            status = chatbot.update_settings(model, system_prompt, max_tokens, temperature)
-            settings_display = f"Model: {model}\nTokens: {max_tokens}\nTemp: {temperature}"
-            return status, settings_display
-        
-        def handle_data_integration(custom_data):
-            status = chatbot.preprocess_data(custom_data)
-            return status
-        
-        def handle_clear():
-            return chatbot.clear_conversation()
-        
-        def handle_regenerate(history):
-            if not history:
-                return history or []
-            
-            last_user_msg = history[-1][0]
-            history_without_last = history[:-1]
-            response, updated_history = chatbot.generate_response(last_user_msg, history_without_last)
-            return updated_history
-        
-        def update_settings_display(model, max_tokens, temperature):
-            return f"Model: {model}\nTokens: {max_tokens}\nTemp: {temperature}"
-        
-        def reset_prompt():
-            default_prompt = "You are a helpful AI assistant. Respond in a friendly and informative manner."
-            return default_prompt, "✅ System prompt reset to default"
-        
-        def load_preset_prompt(preset_type):
-            presets = {
-                "customer_support": "You are a helpful customer support representative. You are friendly, professional, and knowledgeable. Always try to resolve customer issues and provide clear solutions. If you cannot solve a problem, escalate it politely.",
-                "tutor": "You are an experienced tutor. Explain concepts clearly, use examples, and encourage students when they struggle. Break down complex problems into smaller, manageable steps. Always check for understanding.",
-                "creative": "You are a creative writing assistant who helps with stories, poems, and creative content. Provide constructive feedback, suggest improvements, and inspire creativity while maintaining quality standards.",
-                "technical": "You are a technical writer who creates clear, concise documentation. Use precise language, provide examples when relevant, and structure information logically for developers and technical users."
-            }
-            return presets.get(preset_type, ""), f"✅ Loaded {preset_type.replace('_', ' ').title()} preset"
-        
-        # Connect events
-        api_key_input.change(
-            handle_api_key,
-            inputs=[api_key_input],
-            outputs=[api_status]
-        )
-        
-        send_btn.click(
-            handle_chat,
-            inputs=[user_input, chatbot_interface],
-            outputs=[chatbot_interface, user_input]
-        )
-        
-        user_input.submit(
-            handle_chat,
-            inputs=[user_input, chatbot_interface],
-            outputs=[chatbot_interface, user_input]
-        )
-        
-        update_settings_btn.click(
-            handle_settings_update,
-            inputs=[model_dropdown, system_prompt_input, max_tokens_slider, temperature_slider],
-            outputs=[settings_status, current_settings]
-        )
-        
-        integrate_data_btn.click(
-            handle_data_integration,
-            inputs=[custom_data_input],
-            outputs=[settings_status]
-        )
-        
-        clear_btn.click(
-            handle_clear,
-            outputs=[user_input, chatbot_interface]
-        )
-        
-        regenerate_btn.click(
-            handle_regenerate,
-            inputs=[chatbot_interface],
-            outputs=[chatbot_interface]
-        )
-        
-        for component in [model_dropdown, max_tokens_slider, temperature_slider]:
-            component.change(
-                update_settings_display,
-                inputs=[model_dropdown, max_tokens_slider, temperature_slider],
-                outputs=[current_settings]
-            )
-        
-        reset_prompt_btn.click(
-            reset_prompt,
-            outputs=[system_prompt_input, settings_status]
-        )
-        
-        preset_customer_support.click(
-            lambda: load_preset_prompt("customer_support"),
-            outputs=[system_prompt_input, settings_status]
-        )
-        
-        preset_tutor.click(
-            lambda: load_preset_prompt("tutor"),
-            outputs=[system_prompt_input, settings_status]
-        )
-        
-        preset_creative.click(
-            lambda: load_preset_prompt("creative"),
-            outputs=[system_prompt_input, settings_status]
-        )
-        
-        preset_technical.click(
-            lambda: load_preset_prompt("technical"),
-            outputs=[system_prompt_input, settings_status]
-        )
-    
-    return demo
-
-if __name__ == "__main__":
-    demo = create_interface()
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860
-    )