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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)
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