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| from groq import Groq | |
| import gradio as gr | |
| from gtts import gTTS | |
| import uuid | |
| import os | |
| from PIL import Image | |
| import pytesseract | |
| # Initialize the Groq client | |
| client = Groq(api_key=os.getenv("GROQ_API_KEY_2")) | |
| # Function to initialize conversation messages | |
| def initialize_messages(): | |
| return [{ | |
| "role": "system", | |
| "content": '''You are Dr. HealthBuddy, a highly experienced and professional virtual doctor chatbot...''' | |
| }] | |
| # Function to handle user input and history | |
| def customLLMBot(user_input, image_path, history): | |
| messages_prmt = history or initialize_messages() | |
| image_analysis = "" | |
| # Process the uploaded image | |
| if image_path: | |
| try: | |
| img = Image.open(image_path) | |
| extracted_text = pytesseract.image_to_string(img) | |
| image_analysis = f"Analyzed Image: {extracted_text.strip()}" | |
| except Exception as e: | |
| image_analysis = f"Error processing the image: {str(e)}" | |
| # Add user input and image analysis to the conversation | |
| messages_prmt.append({"role": "user", "content": user_input}) | |
| if image_analysis: | |
| messages_prmt.append({"role": "user", "content": image_analysis}) | |
| # Generate response using Groq | |
| try: | |
| response = client.chat.completions.create( | |
| messages=messages_prmt, | |
| model="llama3-8b-8192", | |
| ) | |
| LLM_reply = response.choices[0].message.content | |
| messages_prmt.append({"role": "assistant", "content": LLM_reply}) | |
| except Exception as e: | |
| LLM_reply = f"Error generating response: {str(e)}" | |
| # Generate audio response | |
| audio_file = f"response_{uuid.uuid4().hex}.mp3" | |
| try: | |
| tts = gTTS(LLM_reply, lang='en') | |
| tts.save(audio_file) | |
| except Exception as e: | |
| audio_file = None | |
| LLM_reply += f"\n\nError generating audio: {str(e)}" | |
| return [(user_input, LLM_reply)], audio_file, messages_prmt | |
| # Chatbot UI | |
| def chatbot_ui(): | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Healthcare Chatbot Doctor") | |
| chatbot = gr.Chatbot(label="English Responses") | |
| user_input = gr.Textbox( | |
| label="Ask anything related to your health condition", | |
| placeholder="Enter your symptoms here...", | |
| lines=1 | |
| ) | |
| image_input = gr.Image(label="Upload an image", type="filepath") | |
| audio_output = gr.Audio(label="Audio Response") | |
| submit_btn = gr.Button("Submit") | |
| clear_btn = gr.Button("Clear") | |
| # Combine submit button and Enter key functionality | |
| submit_action = submit_btn.click( | |
| customLLMBot, | |
| inputs=[user_input], | |
| outputs=[chatbot, audio_output], | |
| ) | |
| user_input_action = user_input.submit( | |
| customLLMBot, | |
| inputs=[user_input], | |
| outputs=[chatbot, audio_output], | |
| ) | |
| # Reset the textbox after submission | |
| for action in [submit_action, user_input_action]: | |
| action.then( | |
| lambda: "", # Clear input box | |
| inputs=[], | |
| outputs=user_input, | |
| ) | |
| # Clear button functionality | |
| clear_btn.click( | |
| lambda: ([], "", None, [], None), | |
| inputs=[], | |
| outputs=[chatbot, user_input, audio_output], | |
| ) | |
| return demo | |
| # Launch the chatbot UI | |
| chatbot_ui().launch(server_name="0.0.0.0", server_port=7860) | |