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import os
import streamlit as st
from groq import Groq
from PyPDF2 import PdfReader
from docx import Document
from sentence_transformers import SentenceTransformer
# Initialize Groq API Client
client = Groq(api_key=os.environ.get("Groq-Api"))
# Title with Book Icon
st.title("📖 A&Q From a File")
# File Upload
uploaded_file = st.file_uploader("Upload a PDF or DOCX file", type=["pdf", "docx"])
if uploaded_file:
st.write(f"**File Name:** {uploaded_file.name}") # Display file name
# Read PDF or DOCX content
def extract_text(file):
if file.name.endswith(".pdf"):
reader = PdfReader(file)
return "\n".join([page.extract_text() for page in reader.pages if page.extract_text()])
elif file.name.endswith(".docx"):
doc = Document(file)
return "\n".join([para.text for para in doc.paragraphs])
return ""
file_text = extract_text(uploaded_file)
if file_text:
st.success("File uploaded and text extracted successfully!")
st.write("Ask a question about the file:")
query = st.text_input("Enter your question")
if query:
# Chunk & Tokenize
model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
chunks = [file_text[i:i + 512] for i in range(0, len(file_text), 512)]
embeddings = model.encode(chunks)
# Query with Groq API
chat_completion = client.chat.completions.create(
messages=[
{"role": "user", "content": f"Answer based on this document: {query}\n\n{file_text}"},
],
model="llama-3.3-70b-versatile",
)
# Display Answer
answer = chat_completion.choices[0].message.content
st.subheader("Answer:")
st.write(answer)
else:
st.error("Failed to extract text from the file. Please check the format.")
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