Update app.py

app.py

@@ -5,6 +5,7 @@ from langchain.embeddings import HuggingFaceHubEmbeddings
 from langchain.vectorstores import FAISS
 from langchain.llms import HuggingFaceHub
 from langchain.chains import RetrievalQA
+from datasets import load_dataset
 import os
 
 key = os.environ.get('RLS')
@@ -34,6 +35,17 @@ def pdf_changes(pdf_doc):
     qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff",  retriever=db.as_retriever(search_kwargs={"k": 3}))
     return "Ready"
 
+def book_changes(book):
+
+    with open( book, 'rb') as f:
+        data = pickle.load(f)
+    llm=HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature":1, "max_length":1000000})
+    global qa 
+    qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff",  retriever=db.as_retriever(search_kwargs={"k": 3}))
+    return "Ready"
+
+
+
 def add_text(history, text):
     history = history + [(text, None)]
     return history, ""
@@ -63,17 +75,16 @@ title = """
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.HTML(title)
-        
         with gr.Column():
-            pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type="file")
+            pdf_doc = gr.File(label="Load a PDF", file_types=['.pdf'], type="file")
             load_pdf = gr.Button("Load PDF")
-            Books = gr.Dropdown(label="Books", choices=["Book 1", "Book 2", "Book 3"], value=["Book 1", "Book 2", "Book 3"])
+            Books = gr.Dropdown(label="Books", choices=["Book 1", "Book 2", "Book 3"], value=["https://huggingface.co/datasets/SCLRM/pdf_chatbot/blob/main/embeddings/embeddings.pickle", "Book 2", "Book 3"])
             langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
         chatbot = gr.Chatbot([], elem_id="chatbot").style(height=350)
         question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ")
         submit_btn = gr.Button("Send message")
     #load_pdf.click(loading_pdf, None, langchain_status, queue=False)    
-    Books.change(pdf_changes, inputs=[Books], outputs=[langchain_status], queue=False)
+    Books.change(book_changes, inputs=[Books], outputs=[langchain_status], queue=False)
     load_pdf.click(pdf_changes, inputs=[pdf_doc], outputs=[langchain_status], queue=False)
     question.submit(add_text, [chatbot, question], [chatbot, question]).then(
         bot, chatbot, chatbot