Update app.py

app.py

@@ -231,6 +231,14 @@ def display_docs(docs):
   return output_str
 
 
+def display_docs_modal(docs):
+  output_list = []
+  for i, doc in enumerate(docs):
+      source = doc.metadata['source'].split('/')[-1]
+      output_str.append(f"Ref: {i+1}\n{repr(doc.page_content)}\nSource: {source}\n*§*§*\n")
+  return output_list
+
+
 def ask_llm(system, user_input):
     messages = [
         {
@@ -289,9 +297,9 @@ def ask_gpt(query, ui_session_id, history):
       print("ASKGPT after loading",session_id,len(db.index_to_docstore_id))
     except:
       print(f"SESSION: {session_id} database does not exist")
-      return f"SESSION: {session_id} database does not exist","",""
+      return f"SESSION: {session_id} database does not exist","","".
 
-    docs = db.similarity_search(query)
+    docs = db.similarity_search(query, k=5)
 
     documents = "\n\n*-*-*-*-*-*\n\n".join(f"Content: {doc.page_content}\n" for doc in docs)
     system = f"# Instructions\nTake a deep breath and resonate step by step.\nYou are a helpful standard assistant. Your have only one mission and that consists in answering to the user input based on the **provided documents**. If the answer to the question that is asked by the user isn't contained in the **provided documents**, say so but **don't make up an answer**. I chose you because you can say 'I don't know' so please don't do like the other LLMs and don't define acronyms that aren\'t present in the following **PROVIDED DOCUMENTS** double check if it is present before answering. If some of the information can be useful for the user you can tell him.\nFinish your response by **ONE** follow up question that the provided documents could answer.\n\nThe documents are separated by the string \'*-*-*-*-*-*\'. Do not provide any explanations or details.\n\n# **Provided documents**: {documents}."    
@@ -314,6 +322,36 @@ def auth_user(ui_session_id):
     else:
         return gr.Textbox(label='Username', visible=True), gr.File(file_count="multiple", file_types=[".txt", ".pdf",".zip",".docx"], visible=False), gr.Button("Reset AI Knowledge", visible=False), gr.Markdown(label='AI Answer', visible=False), gr.Textbox(placeholder="Type your question", label="Question ❔", scale=9, visible=False), gr.Button("▶", scale=1, visible=False), gr.Textbox(label='Sources', show_copy_button=True, visible=False), gr.File(label="Zipped database", visible=False), gr.Textbox(label='History', show_copy_button=True, visible=False)
 
+def display_info0(documents):
+    try:
+        gr.Info(documents.split("\n*§*§*\n")[0])
+    except Exception as e:
+        gr.Info("No Document")
+
+def display_info1(documents):
+    try:
+        gr.Info(documents.split("\n*§*§*\n")[1])
+    except Exception as e:
+        gr.Info("No Document")
+        
+def display_info2(documents):
+    try:
+        gr.Info(documents.split("\n*§*§*\n")[2])
+    except Exception as e:
+        gr.Info("No Document")
+    
+def display_info3(documents):
+    try:
+        gr.Info(documents.split("\n*§*§*\n")[3])
+    except Exception as e:
+        gr.Info("No Document")
+    
+def display_info4(documents):
+    try:
+        gr.Info(documents.split("\n*§*§*\n")[4])
+    except Exception as e:
+        gr.Info("No Document")
+
 with gr.Blocks() as demo:
     gr.Markdown("# Enrich an LLM knowledge with your own documents 🧠🤖")
         
@@ -328,6 +366,13 @@ with gr.Blocks() as demo:
         with gr.Row():
             query_input = gr.Textbox(placeholder="Type your question", label="Question ❔", scale=9, visible=False)
             btn_askGPT = gr.Button("▶", scale=1, visible=False)
+        with gr.Row():
+            btn1 = gr.Button("Ref 1")
+            btn2 = gr.Button("Ref 2")
+            btn3 = gr.Button("Ref 3")
+            btn4 = gr.Button("Ref 4")
+            btn5 = gr.Button("Ref 5")
+        
         
         tb_sources = gr.Textbox(label='Sources', show_copy_button=True, visible=False)
         
@@ -344,5 +389,12 @@ with gr.Blocks() as demo:
     btn_askGPT.click(ask_gpt, inputs=[query_input, tb_session_id, tb_history], outputs=[answer_output, tb_sources, tb_history])
     query_input.submit(ask_gpt, inputs=[query_input, tb_session_id, tb_history], outputs=[answer_output, tb_sources, tb_history])
 
+    btn1.click(display_info0, inputs=tb_sources, outputs=None)
+    btn2.click(display_info1, inputs=tb_sources, outputs=None)
+    btn3.click(display_info2, inputs=tb_sources, outputs=None)
+    btn4.click(display_info3, inputs=tb_sources, outputs=None)
+    btn5.click(display_info4, inputs=tb_sources, outputs=None)
+    
+
 
 demo.launch(debug=False,share=False)