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import os
import gradio as gr
from langchain.document_loaders import OnlinePDFLoader
from langchain.text_splitter import CharacterTextSplitter
from langchain.chat_models import ChatAnthropic
from langchain.prompts import ChatPromptTemplate
# Set API keys from environment variables
os.environ['ANTHROPIC_API_KEY'] = os.getenv("Your_Anthropic_API_Key")
pdf_content = ""
def load_pdf(pdf_doc):
global pdf_content
try:
if pdf_doc is None:
return "No PDF uploaded."
# Load and split PDF content
loader = OnlinePDFLoader(pdf_doc.name)
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
pdf_content = ' '.join(text_splitter.split_documents(documents))
return "PDF Loaded Successfully."
except Exception as e:
return f"Error processing PDF: {e}"
def chat_with_pdf(question):
# Create an instance of the ChatAnthropic model
model = ChatAnthropic()
# Define the chat prompt template
prompt = ChatPromptTemplate.from_messages([
("human", pdf_content),
("human", question),
])
# Invoke the model using the chain
chain = prompt | model
response = chain.invoke({})
return response.content
# Define Gradio UI
def gradio_interface(pdf_doc, question):
if not pdf_content:
return load_pdf(pdf_doc)
else:
return chat_with_pdf(question)
gr.Interface(fn=gradio_interface,
inputs=[gr.File(label="Load a pdf", file_types=['.pdf'], type="file"),
gr.Textbox(label="Ask a question about the PDF")],
outputs="text",
live=True,
title="Chat with PDF content using Anthropic",
description="Upload a .PDF and interactively chat about its content."
).launch()
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