adding you tube processing LLM

app.py

@@ -1,4 +1,4 @@
-import os 
+import time
 import gradio as gr
 import logging
 from langchain.document_loaders import PDFMinerLoader,CSVLoader ,UnstructuredWordDocumentLoader,TextLoader,OnlinePDFLoader
@@ -70,6 +70,36 @@ def youtube_chat(youtube_link,API_key,llm='HuggingFace',temperature=0.1,max_toke
                             )
     return "Youtube link Processing completed ..."
 
+def infer(question, history):
+    # res = []
+    # # for human, ai in history[:-1]:
+    # #     pair = (human, ai)
+    # #     res.append(pair)
+    
+    # chat_history = res
+    print("Question in infer :",question)
+    result = qa({"query": question})
+    matching_docs_score = vector_db.similarity_search_with_score(question)
+    
+    print(" Matching_doc ",matching_docs_score)
+    
+    return result["result"]
+
+def bot(history):
+   
+    response = infer(history[-1][0], history)
+    history[-1][1] = ""
+    
+    for character in response:     
+        history[-1][1] += character
+        time.sleep(0.05)
+        yield history
+
+def add_text(history, text):
+    history = history + [(text, None)]
+    return history, ""
+
+
 ##################################################
 ##################################################
 ################### GRADIO #######################
@@ -139,4 +169,7 @@ with gr.Blocks(css="""#chatbot {font-size: 14px;min-height: 300px;}""") as demo:
     load_youtube_bt.click(youtube_chat,inputs= [youtube_link,API_key,LLM_option,temperature,max_new_tokens,char_length],outputs=[langchain_status], queue=False)  
     clean_chat_btn.click(clear_chat, [], chatbot)
 
+    question.submit(add_text, inputs=[chatbot, question], outputs=[chatbot, question]).then(bot, chatbot, chatbot)
+    submit_btn.click(add_text, inputs=[chatbot, question], outputs=[chatbot, question]).then(bot, chatbot, chatbot)
+
 demo.launch()