| import gradio as gr | |
| # from langchain_community.llms import GooglePalm | |
| # from langchain_community.embeddings import HuggingFaceInstructEmbeddings | |
| # from langchain.text_splitter import CharacterTextSplitter | |
| # from langchain_community.embeddings import GooglePalmEmbeddings | |
| # from langchain_community.vectorstores import FAISS | |
| # from langchain_community.document_loaders import PyPDFLoader | |
| # from langchain_community.chains import RetrievalQA | |
| # from secret1 import GOOGLE_API as google_api | |
| # import PyPDF2 | |
| # def chatbot_response(user_input, history): | |
| # # This is a placeholder function. Replace with your actual chatbot logic. | |
| # bot_response = "You said: " + user_input | |
| # history.append((user_input, bot_response)) | |
| # return history, history | |
| # def text_splitter_function(text): | |
| # text_splitter = CharacterTextSplitter( | |
| # separator = '\n', | |
| # chunk_size = 1000, | |
| # chunk_overlap = 40, | |
| # length_function = len, | |
| # ) | |
| # texts = text_splitter.split_text(text) | |
| # return texts; | |
| # def text_extract(file): | |
| # pdf_reader = PyPDF2.PdfReader(file.name) | |
| # # Get the number of pages | |
| # num_pages = len(pdf_reader.pages) | |
| # # Extract text from each page | |
| # text = "" | |
| # for page_num in range(num_pages): | |
| # page = pdf_reader.pages[page_num] | |
| # text += page.extract_text() | |
| # text_splitter=text_splitter_function(text); | |
| # db = FAISS.from_texts(text_splitter, embeddings); | |
| # retriever = db.as_retriever(search_type="similarity", search_kwargs={"k": 2}) | |
| # llm=GooglePalm(google_api_key=google_api) | |
| # qa = RetrievalQA.from_chain_type( | |
| # llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True | |
| # ) | |
| # print(db) | |
| # return text | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Chat with ChatGPT-like Interface") | |
| chatbot = gr.Chatbot() | |
| state = gr.State([]) | |
| with gr.Row(): | |
| with gr.Column(): | |
| user_input = gr.Textbox(show_label=False, placeholder="Type your message here...") | |
| send_btn = gr.Button("Send") | |
| with gr.Column(): | |
| input_file=gr.File(label="Upload PDF", file_count="single") | |
| submit_btn=gr.Button("Submit") | |
| # submit_btn.click(text_extract, [input_file], [user_input]) | |
| #send_btn.click(chatbot_response,[user_input,state],[chatbot, state]) | |
| if __name__ == "__main__": | |
| # embeddings=GooglePalmEmbeddings(google_api_key=google_api) | |
| demo.launch() | |