creating chatbot

app.py

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+import gradio as gr
+from langchain.llms import GooglePalm
+from langchain.embeddings import HuggingFaceInstructEmbeddings
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.embeddings import GooglePalmEmbeddings
+from langchain.vectorstores import FAISS
+from langchain.document_loaders import PyPDFLoader
+from langchain.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()