adding chatbot

app.py

@@ -49,7 +49,6 @@ def summarize_contents():
     return qa.run(question)
 
 def document_loader(file_path,api_key,doc_type='pdf',llm='Huggingface'):
-    embedding_model = SentenceTransformerEmbeddings(model_name='all-mpnet-base-v2',model_kwargs={"device": DEVICE})
     document = None
     if doc_type == 'pdf':
         document = process_pdf_document(document_file=file_path)
@@ -60,6 +59,7 @@ def document_loader(file_path,api_key,doc_type='pdf',llm='Huggingface'):
     elif doc_type == 'word':
         document = process_word_document(document_file=file_path)
     if document:
+        embedding_model = SentenceTransformerEmbeddings(model_name='thenlper/gte-base',model_kwargs={"device": DEVICE})
         texts = process_documents(documents=document)
         vector_db = FAISS.from_documents(documents=texts, embedding= embedding_model)
         global qa 
@@ -72,7 +72,7 @@ def document_loader(file_path,api_key,doc_type='pdf',llm='Huggingface'):
     else:
         return "Error in loading Documents "
     
-    return "Ready..."
+    return "Document processing complete-Embeddings Created "
 
         
 def process_text_document(document_file):
@@ -143,8 +143,14 @@ with gr.Blocks(css=css) as demo:
     
     summarize_pdf.click(summarize_contents,outputs=summary)
     
-    # question.submit(add_text, [chatbot, question], [chatbot, question]).then(
-    #     bot, chatbot, chatbot
-    # )
+    with gr.Column():
+        with gr.Row():
+            chatbot = gr.Chatbot(height=300)
+            sources = gr.HTML(value = "Source paragraphs where I looked for answers will appear here", height=300)
+
+        with gr.Row():
+            message = gr.Textbox(label="Type your question?",lines=1).style(full_width=False)
+        submit_query = gr.Button(value="Send message", variant="secondary", scale = 1)
+
 
 demo.launch()