Update app.py

app.py

@@ -17,7 +17,7 @@ from langchain.chains import RetrievalQA
 def loading_pdf():
     return "Loading..."
 
-def pdf_changes(pdf_doc):
+def pdf_changes(pdf_doc, repo_id):
     
     loader = OnlinePDFLoader(pdf_doc.name)
     documents = loader.load()
@@ -26,7 +26,7 @@ def pdf_changes(pdf_doc):
     embeddings = HuggingFaceHubEmbeddings()
     db = Chroma.from_documents(texts, embeddings)
     retriever = db.as_retriever()
-    llm = HuggingFaceHub(repo_id="google/flan-ul2", model_kwargs={"temperature":0.1, "max_new_tokens":300})
+    llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature":0.1, "max_new_tokens":300})
     global qa 
     qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True)
     return "Ready"
@@ -66,6 +66,7 @@ with gr.Blocks(css=css) as demo:
         
         with gr.Column():
             pdf_doc = gr.File(label="Load a pdf", file_types=['.pdf'], type="file")
+            repo_id = gr.Dropdown(label="LLM", choices=["google/flan-ul2", "stabilityai/stablelm-tuned-alpha-3b", "databricks/dolly-v2-3b", "Writer/camel-5b-hf" ], value="google/flan-ul2")
             with gr.Row():
                 langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False)
                 load_pdf = gr.Button("Load pdf to langchain")
@@ -73,8 +74,9 @@ with gr.Blocks(css=css) as demo:
         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)    
-    load_pdf.click(pdf_changes, pdf_doc, langchain_status, queue=False)
+    #load_pdf.click(loading_pdf, None, langchain_status, queue=False)    
+    repo_id.change(pdf_changes, inputs=[pdf_doc, repo_id], langchain_status, queue=False)
+    load_pdf.click(pdf_changes, inputs=[pdf_doc, repo_id], langchain_status, queue=False)
     question.submit(add_text, [chatbot, question], [chatbot, question]).then(
         bot, chatbot, chatbot
     )