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| import gradio as gr | |
| from helper import * | |
| from prompts_and_chema import * | |
| def full_chat_pipeline(user_query, openai_key): | |
| try: | |
| # ✅ Step 1: Set the OpenAI API key | |
| openai.api_key = openai_key | |
| # Step 1: Get intent from first GPT call | |
| raw_response = chat_with_gpt(intent_system_prompt, user_query, use_schema=True, schema=intent_output_schema ) | |
| # print(f"raw_response: {raw_response}") | |
| intents = json.loads(raw_response) if isinstance(raw_response, str) else raw_response | |
| # print(f"Intents: {intents}") | |
| # Step 2: Format prompt with detected intent | |
| loaded_texts = load_intent_texts(intents, get_txt_files) | |
| #selected_intents = ', '.join(intents.get("intents", [])) | |
| selected_intent_description = load_intent_description(intents, intent_description_map) | |
| print(selected_intent_description) | |
| context_str = '\n\n'.join(f"{k}:\n{v}" for k, v in loaded_texts.items()) | |
| formatted_prompt = f''' | |
| User query: {user_query} | |
| Selected Intents: {selected_intent_description} | |
| Context: {context_str} | |
| ''' | |
| # Step 3: Get final answer from second GPT call | |
| final_response = chat_with_gpt(get_answer_system_prompt, formatted_prompt) | |
| # print("Final Response:", final_response) | |
| return f"{str(intents)}", f"{final_response}" | |
| except Exception as e: | |
| return f"Error while classifying intents: {str(e)}", f"Error while generating response: {str(e)}" | |
| # Gradio UI | |
| with gr.Blocks(title="Degirum LLM") as demo: | |
| gr.Markdown("## Degirum LLM") | |
| gr.Markdown("Ask questions...") | |
| # 🔑 OpenAI Key on top | |
| openai_key = gr.Textbox(label="🔑 OpenAI API Key", placeholder="Enter your OpenAI API key...", type="password") | |
| # Row with query input and intent output side by side | |
| with gr.Row(): | |
| user_query = gr.Textbox(label="💬 Query", placeholder="Type your question here...", lines=3) | |
| intent_output = gr.Textbox(label="🧠 Classified Intents", placeholder="will get answer by AI", lines=3, interactive=False) | |
| # 🚀 Submit Button | |
| submit_btn = gr.Button("🚀 Submit", variant="primary") | |
| # 🤖 AI Response at the bottom | |
| response_output = gr.Textbox(label="🤖 Full AI Response", lines=10, interactive=False) | |
| submit_btn.click( | |
| fn=full_chat_pipeline, | |
| inputs=[user_query, openai_key], | |
| outputs=[intent_output, response_output] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |