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import gradio as gr
import PyPDF2
import openai
from config import OPENAI_API_KEY
import os
openai.api_key = os.getenv("OPENAI_API_KEY")
def extract_text_from_pdf(pdf_file):
text = ""
with open(pdf_file.name, "rb") as file:
reader = PyPDF2.PdfReader(file)
for page in reader.pages:
text += page.extract_text() + "\n"
return text
def answer_question(pdf_file, question):
# Extract text from the PDF
text = extract_text_from_pdf(pdf_file)
# Define the assistant's behavior
assistant_prompt = f"""
You are a helpful assistant that answers questions based on the content of the PDF provided.
Here is the content of the PDF:
{text}
User question: {question}
"""
# Call OpenAI API to get the answer using GPT-4 Turbo
response = openai.ChatCompletion.create(
model="gpt-4-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": assistant_prompt}
]
)
answer = response.choices[0].message['content']
return answer
# Create Gradio interface using the updated input/output classes
iface = gr.Interface(
fn=answer_question,
inputs=[
gr.File(label="Upload PDF"),
gr.Textbox(label="Ask a question about the PDF", placeholder="What do you want to know?")
],
outputs="text",
title="PDF Q&A with OpenAI Assistant",
description="Upload a PDF document and ask questions about its content. The assistant will provide answers based on the PDF.",
examples=[
["renesas-ra6m1-group-datasheet.pdf", "Which Renesas products are mentioned in this PDF?"]
]
)
# Launch the interface
iface.launch()
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