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import re
import gradio as gr
import os
import google.generativeai as genai
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
# Now you can use hugging_face_api_key in your code
genai.configure(api_key=GOOGLE_API_KEY)
model = genai.GenerativeModel('gemini-pro') # Load the model
def get_Answer(query):
res = collection.query( # Assuming `collection` is defined elsewhere
query_texts=query,
n_results=2
)
system = f"""You are a teacher. You will be provided some context,
your task is to analyze the relevant context and answer the below question:
- {query}
"""
context = " ".join([re.sub(r'[^\x00-\x7F]+', ' ', r) for r in res['documents'][0]])
prompt = f"### System: {system} \n\n ###: User: {context} \n\n ### Assistant:\n"
answer = model.generate_content(prompt).text
return answer
# Define the Gradio interface
iface = gr.Interface(
fn=get_Answer,
inputs=gr.Textbox(lines=5, placeholder="Ask a question"), # Textbox for query
outputs="textbox", # Display the generated answer in a textbox
title="Answer Questions with Gemini-Pro",
description="Ask a question and get an answer based on context from a ChromaDB collection.",
)
# Launch the Gradio app
iface.launch(debug=True,share=True) |