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import gradio as gr
from langchain.document_loaders import PyPDFLoader
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import FAISS
from langchain.chat_models import ChatOpenAI
from langchain.llms import OpenAI
def process_pdfs(files):
"""Process uploaded PDFs and return extracted text."""
texts = []
for file in files:
loader = PyPDFLoader(file.name)
docs = loader.load()
texts.append("\n".join([doc.page_content for doc in docs]))
return "\n\n".join(texts)
def create_gradio_interface():
"""Create and launch the Gradio interface."""
with gr.Blocks() as demo:
gr.Markdown("# PDF Text Extractor")
pdf_files = gr.Files(label="Upload PDF Documents", type="file") # Fixed multiple file issue
output_text = gr.Textbox(label="Extracted Text", lines=10)
extract_button = gr.Button("Extract Text")
extract_button.click(process_pdfs, inputs=[pdf_files], outputs=[output_text])
return demo
if __name__ == "__main__":
demo = create_gradio_interface()
demo.launch()
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