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| import gradio as gr | |
| import os | |
| import re | |
| from groq import Groq | |
| def validate_api_key(api_key): | |
| """Validate if the API key has the correct format.""" | |
| # Basic format check for Groq API keys (they typically start with 'gsk_') | |
| if not api_key.strip(): | |
| return False, "API key cannot be empty" | |
| if not api_key.startswith("gsk_"): | |
| return False, "Invalid API key format. Groq API keys typically start with 'gsk_'" | |
| return True, "API key looks valid" | |
| def test_api_connection(api_key): | |
| """Test the API connection with a minimal request.""" | |
| try: | |
| client = Groq(api_key=api_key) | |
| # Making a minimal API call to test the connection | |
| client.chat.completions.create( | |
| model="llama3-70b-8192", | |
| messages=[{"role": "user", "content": "test"}], | |
| max_tokens=5 | |
| ) | |
| return True, "API connection successful" | |
| except Exception as e: | |
| # Handle all exceptions since Groq might not expose specific error types | |
| if "authentication" in str(e).lower() or "api key" in str(e).lower(): | |
| return False, "Authentication failed: Invalid API key" | |
| else: | |
| return False, f"Error connecting to Groq API: {str(e)}" | |
| def chat_with_groq(api_key, model, user_message, temperature, max_tokens, top_p, chat_history): | |
| """ | |
| Interact with the Groq API to get a response. | |
| """ | |
| # Validate API key | |
| is_valid, message = validate_api_key(api_key) | |
| if not is_valid: | |
| return chat_history + [[user_message, f"Error: {message}"]] | |
| # Test API connection | |
| connection_valid, connection_message = test_api_connection(api_key) | |
| if not connection_valid: | |
| return chat_history + [[user_message, f"Error: {connection_message}"]] | |
| try: | |
| # Format history for the API | |
| messages = [] | |
| for human, assistant in chat_history: | |
| messages.append({"role": "user", "content": human}) | |
| messages.append({"role": "assistant", "content": assistant}) | |
| # Add the current message | |
| messages.append({"role": "user", "content": user_message}) | |
| # Create the client and make the API call | |
| client = Groq(api_key=api_key) | |
| response = client.chat.completions.create( | |
| model=model, | |
| messages=messages, | |
| temperature=temperature, | |
| max_tokens=max_tokens, | |
| top_p=top_p | |
| ) | |
| # Extract the response text | |
| assistant_response = response.choices[0].message.content | |
| # Return updated chat history | |
| return chat_history + [[user_message, assistant_response]] | |
| except Exception as e: | |
| error_message = f"Error: {str(e)}" | |
| return chat_history + [[user_message, error_message]] | |
| def clear_conversation(): | |
| """Clear the conversation history.""" | |
| return [] | |
| # Define available models | |
| models = [ | |
| "llama3-70b-8192", | |
| "llama3-8b-8192", | |
| "mistral-saba-24b", | |
| "gemma2-9b-it", | |
| "allam-2-7b" | |
| ] | |
| # Create the Gradio interface | |
| with gr.Blocks(title="Groq AI Chat Playground") as app: | |
| gr.Markdown("# Groq AI Chat Playground") | |
| # New model information accordion | |
| with gr.Accordion("ℹ️ Model Information - Learn about available models", open=False): | |
| gr.Markdown(""" | |
| ### Available Models and Use Cases | |
| **llama3-70b-8192** | |
| - Meta's most powerful language model | |
| - 70 billion parameters with 8192 token context window | |
| - Best for: Complex reasoning, sophisticated content generation, creative writing, and detailed analysis | |
| - Optimal for users needing the highest quality AI responses | |
| **llama3-8b-8192** | |
| - Lighter version of Llama 3 | |
| - 8 billion parameters with 8192 token context window | |
| - Best for: Faster responses, everyday tasks, simpler queries | |
| - Good balance between performance and speed | |
| **mistral-saba-24b** | |
| - Mistral AI's advanced model | |
| - 24 billion parameters | |
| - Best for: High-quality reasoning, code generation, and structured outputs | |
| - Excellent for technical and professional use cases | |
| **gemma2-9b-it** | |
| - Google's instruction-tuned model | |
| - 9 billion parameters | |
| - Best for: Following specific instructions, educational content, and general knowledge queries | |
| - Well-rounded performance for various tasks | |
| **allam-2-7b** | |
| - Specialized model from Aleph Alpha | |
| - 7 billion parameters | |
| - Best for: Multilingual support, concise responses, and straightforward Q&A | |
| - Good for international users and simpler applications | |
| *Note: Larger models generally provide higher quality responses but may take slightly longer to generate.* | |
| """) | |
| gr.Markdown("Enter your Groq API key to start chatting with AI models.") | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| api_key_input = gr.Textbox( | |
| label="Groq API Key", | |
| placeholder="Enter your Groq API key (starts with gsk_)", | |
| type="password" | |
| ) | |
| with gr.Column(scale=1): | |
| test_button = gr.Button("Test API Connection") | |
| api_status = gr.Textbox(label="API Status", interactive=False) | |
| with gr.Row(): | |
| with gr.Column(): | |
| model_dropdown = gr.Dropdown( | |
| choices=models, | |
| label="Select Model", | |
| value="llama3-70b-8192" | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Accordion("Advanced Settings", open=False): | |
| temperature_slider = gr.Slider( | |
| minimum=0.0, maximum=1.0, value=0.7, step=0.01, | |
| label="Temperature (higher = more creative, lower = more focused)" | |
| ) | |
| max_tokens_slider = gr.Slider( | |
| minimum=256, maximum=8192, value=4096, step=256, | |
| label="Max Tokens (maximum length of response)" | |
| ) | |
| top_p_slider = gr.Slider( | |
| minimum=0.0, maximum=1.0, value=0.95, step=0.01, | |
| label="Top P (nucleus sampling probability threshold)" | |
| ) | |
| chatbot = gr.Chatbot(label="Conversation", height=500) | |
| with gr.Row(): | |
| message_input = gr.Textbox( | |
| label="Your Message", | |
| placeholder="Type your message here...", | |
| lines=3 | |
| ) | |
| with gr.Row(): | |
| submit_button = gr.Button("Send", variant="primary") | |
| clear_button = gr.Button("Clear Conversation") | |
| # Connect components with functions | |
| submit_button.click( | |
| fn=chat_with_groq, | |
| inputs=[ | |
| api_key_input, | |
| model_dropdown, | |
| message_input, | |
| temperature_slider, | |
| max_tokens_slider, | |
| top_p_slider, | |
| chatbot | |
| ], | |
| outputs=chatbot | |
| ).then( | |
| fn=lambda: "", | |
| inputs=None, | |
| outputs=message_input | |
| ) | |
| message_input.submit( | |
| fn=chat_with_groq, | |
| inputs=[ | |
| api_key_input, | |
| model_dropdown, | |
| message_input, | |
| temperature_slider, | |
| max_tokens_slider, | |
| top_p_slider, | |
| chatbot | |
| ], | |
| outputs=chatbot | |
| ).then( | |
| fn=lambda: "", | |
| inputs=None, | |
| outputs=message_input | |
| ) | |
| clear_button.click( | |
| fn=clear_conversation, | |
| inputs=None, | |
| outputs=chatbot | |
| ) | |
| test_button.click( | |
| fn=test_api_connection, | |
| inputs=[api_key_input], | |
| outputs=[api_status] | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| app.launch(share=False) |