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import os | |
from langchain_core.prompts import PromptTemplate | |
from langchain.chains.question_answering import load_qa_chain | |
from langchain_community.document_loaders import PyPDFLoader | |
import google.generativeai as genai | |
import gradio as gr | |
# Function for initialization | |
def initialize(pdf_file, question): | |
try: | |
# Access the uploaded file information from Gradio | |
file_info = pdf_file | |
# Check if a file was uploaded | |
if file_info is not None: | |
# Construct potential file path based on temporary directory and filename | |
file_path = os.path.join("/tmp", file_info.name) # Adjust temporary directory if needed | |
if os.path.exists(file_path): | |
# ... rest of your code for processing the PDF using the file path | |
else: | |
return "Error: The uploaded file could not be found." | |
else: | |
return "Error: No PDF file was uploaded." | |
except Exception as e: | |
return f"An error occurred: {e}" # Generic error handling | |
# Create a Gradio interface | |
interface = gr.Interface( | |
fn=initialize, | |
inputs=[ | |
gr.File(label="Upload PDF"), # No need for 'type' argument | |
gr.Textbox(label="Question") | |
], | |
outputs="text", | |
title="GeminiPro Q&A Bot", | |
description="Ask questions about the uploaded PDF document.", | |
) | |
# Launch the interface | |
interface.launch() | |