Adding sources

app.py

@@ -64,6 +64,7 @@ def document_loader(file_path,api_key,doc_type='pdf',llm='Huggingface',temperatu
     embedding_model = SentenceTransformerEmbeddings(model_name='thenlper/gte-base',model_kwargs={"device": DEVICE})
     
     texts = process_documents(documents=document)
+    global vector_db
     vector_db = FAISS.from_documents(documents=texts, embedding= embedding_model)
     global qa
     qa = RetrievalQA.from_chain_type(llm=chat_application(llm_service=llm,key=api_key,
@@ -114,6 +115,10 @@ def infer(question, history):
     # 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):
@@ -127,7 +132,6 @@ def bot(history):
         yield history
 
 def add_text(history, text):
-    
     history = history + [(text, None)]
     return history, ""
 
@@ -152,8 +156,8 @@ with gr.Blocks(css=css) as demo:
         
     with gr.Group():
         chatbot = gr.Chatbot(height=300)
-        # with gr.Row():
-        # sources = gr.HTML(value = "Source paragraphs where I looked for answers will appear here", height=300)
+        with gr.Row():
+            sources = gr.HTML(value = "Source paragraphs where I looked for answers will appear here", height=300)
     with gr.Row():
         question = gr.Textbox(label="Type your question !",lines=1).style(full_width=True)
         submit_btn = gr.Button(value="Send message", variant="primary", scale = 1)
@@ -195,8 +199,9 @@ with gr.Blocks(css=css) as demo:
         load_pdf.click(loading_file, None, langchain_status, queue=False)    
         load_pdf.click(document_loader, inputs=[pdf_doc,API_key,file_extension,LLM_option,temperature,max_new_tokens], outputs=[langchain_status], queue=False)
 
-    question.submit(add_text, [chatbot, question], [chatbot, question]).then(bot, chatbot, chatbot)
-    submit_btn.click(add_text, [chatbot, question], [chatbot, question]).then(bot, chatbot, 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)
+    # submit_btn.then(chatf.highlight_found_text, [chatbot, sources], [sources])
     clean_chat_btn.click(clear_chat, [], chatbot)