| import gradio as gr |
| from groq import Groq |
| from src.utils.prompts import SYSTEM_PROMPT, EXAMPLE_QUESTIONS |
| from src.config.settings import GROQ_API_KEY, CHATBOT_NAME |
|
|
| def get_groq_client(): |
| """Initialize and return Groq client""" |
| api_key = GROQ_API_KEY |
| if not api_key: |
| raise ValueError("GROQ_API_KEY not found in .env file") |
| return Groq(api_key=api_key) |
|
|
| client = get_groq_client() |
|
|
| def respond(message, history, model, temperature, max_tokens): |
| """ |
| Generate streaming response from Instructor for Agentic AI |
| |
| Args: |
| message: User's current question |
| history: List of previous chat messages (Gradio format) |
| model: Selected AI model |
| temperature: Temperature parameter for response randomness |
| max_tokens: Maximum tokens for response length |
| |
| Returns: |
| Generator yielding response chunks |
| """ |
| messages = [{"role": "system", "content": SYSTEM_PROMPT}] |
| |
| if history: |
| for chat in history: |
| if isinstance(chat, (list, tuple)) and len(chat) >= 2: |
| user_msg, assistant_msg = chat[0], chat[1] |
| if user_msg: |
| messages.append({"role": "user", "content": str(user_msg)}) |
| if assistant_msg: |
| messages.append({"role": "assistant", "content": str(assistant_msg)}) |
| |
| messages.append({"role": "user", "content": message}) |
| try: |
| stream = client.chat.completions.create( |
| model=model, |
| messages=messages, |
| temperature=temperature, |
| max_tokens=int(max_tokens), |
| stream=True |
| ) |
| |
| response = "" |
| for chunk in stream: |
| if chunk.choices[0].delta.content: |
| response += chunk.choices[0].delta.content |
| yield response |
| |
| except Exception as e: |
| yield f"Error: {str(e)}" |
|
|
| app = gr.ChatInterface( |
| fn=respond, |
| title=f"🧭 {CHATBOT_NAME}", |
| description=f"Ask questions about designing, building, and refining agentic AI systems with {CHATBOT_NAME}.", |
| additional_inputs=[ |
| gr.Dropdown( |
| choices=[ |
| "qwen/qwen3-32b", |
| "moonshotai/kimi-k2-instruct", |
| "moonshotai/kimi-k2-instruct-0905", |
| ], |
| value="qwen/qwen3-32b", |
| label="Model", |
| info="Select the AI model to use" |
| ), |
| gr.Slider( |
| minimum=0, |
| maximum=2, |
| value=0.9, |
| step=0.1, |
| label="Temperature", |
| info="Controls randomness. Lower = more focused, Higher = more creative" |
| ), |
| gr.Slider( |
| minimum=256, |
| maximum=8192, |
| value=2048, |
| step=256, |
| label="Max Tokens", |
| info="Maximum length of the response" |
| ), |
| ], |
| examples=EXAMPLE_QUESTIONS, |
| ) |
|
|
| if __name__ == "__main__": |
| app.launch(share=True) |
