Implemented facility chat

app.py

@@ -1,65 +1,130 @@
+from openai import OpenAI
 import gradio as gr
-from huggingface_hub import InferenceClient
 import os
+ 
+client = OpenAI(api_key=os.environ['openAIToken'])
+assistantId = os.environ['assistantId']
 
+def createThread():
+  return client.beta.threads.create()
+
+def addMessage(text, threadId):
+  return client.beta.threads.messages.create(
+    thread_id=threadId,
+    role="user",
+    content=text
+  )
+
+list_of_suggestions = []
+latest_suggestions = ""
+
+def handle_suggestions(string_of_suggestions):
+  local_message = None
+  parts = string_of_suggestions.split('#s#')
+  list_of_suggestions = [x.strip('"') for x in parts[0].strip('][').split('", ') if x.strip('"')]
+  print(list_of_suggestions)
+  if len(parts) > 1:
+    local_message = parts[1]
+  return list_of_suggestions, local_message
+
+def create_suggestions_list(suggestions):
+  update_show = [gr.update(visible=True, value=w) for w in suggestions]
+  update_hide = [gr.update(visible=False, value="") for _ in range(6-len(suggestions))]
+  return update_show + update_hide
+
+btn_list = []
+list_of_suggestions = ""
+
+CSS ="""
+.contain { display: flex; flex-direction: column; }
+.gradio-container { height: 100vh !important; }
+#chatbot { flex-grow: 1; overflow: auto;}
 """
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+with gr.Blocks(css=CSS, fill_height=True) as demo:
+  streaming_thread = createThread()
+  chatbot = gr.Chatbot(label="Facility managment bot", elem_id="chatbot") #just to fit the notebook
+  with gr.Row():
+      for i in range(6):
+          btn = gr.Button(visible=False)
+          btn_list.append(btn)
+  msg = gr.Textbox(label="Answer")
+  with gr.Row():
+    clear_btn = gr.ClearButton(chatbot)
+    btn = gr.Button("Submit")
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+  def user(user_message, history):
+      return "", history + [[user_message, None]]
 
-    messages.append({"role": "user", "content": message})
+  def respond(chat_history):
+    print("Responding")
+    global btn_list
+    message = chat_history[-1][0]
+    threadId = streaming_thread.id
+    chat_history[-1][1] = ""
+    addMessage(message, threadId)
+    global list_of_suggestions
+    list_of_suggestions = []
+    string_of_suggestions = ""
+    is_loading_suggestions = False
+    is_it_first_response = True
+    with client.beta.threads.runs.stream(
+      thread_id=threadId,
+      assistant_id=assistantId,
+    ) as stream:
+      for text in stream.text_deltas:
+        print(text, end="")
+        local_message = None
+        if "[" in text and is_it_first_response:
+          is_loading_suggestions = True
 
-    response = ""
+        is_it_first_response = False
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+        if is_loading_suggestions != True:
+          local_message = text
+        else:
+          string_of_suggestions = string_of_suggestions + text
+          if "#s#" in string_of_suggestions:
+            is_loading_suggestions = False
+            list_of_suggestions, local_message = handle_suggestions(string_of_suggestions)
+        if local_message is not None:
+          chat_history[-1][1] += local_message 
+          yield {chatbot: chat_history}
 
-        response += token
-        yield response
+      stream.until_done()
+
+  def update_suggestions():
+    global list_of_suggestions
+    btn_list = create_suggestions_list(list_of_suggestions)
+    return btn_list
+  
+  def hide_suggestions(): 
+    return [gr.update(visible=False, value="") for _ in range(6)]
+
+  def disable_msg():
+    message_box = gr.Textbox(value=None, interactive=False)
+    return message_box
+  
+  def enable_msg():
+    message_box = gr.Textbox(value=None, interactive=True)
+    return message_box
+
+  add_user_message_flow = [user, [msg,chatbot],  [msg,chatbot]]
+  chat_response_flow = [respond, [chatbot], [chatbot]]
+  update_suggestions_flow = [update_suggestions, None, btn_list]
+  hide_suggestions_flow = [hide_suggestions, None, btn_list]
+  disable_msg_flow = [disable_msg, None, msg] 
+  enable_msg_flow = [enable_msg, None, msg]
+
+  btn.click(*add_user_message_flow).then(*hide_suggestions_flow).then(*disable_msg_flow).then(*chat_response_flow).then(*update_suggestions_flow).then(*enable_msg_flow)
+  msg.submit(*add_user_message_flow).then(*hide_suggestions_flow).then(*disable_msg_flow).then(*chat_response_flow).then(*update_suggestions_flow).then(*enable_msg_flow)
+  for sug_btn in btn_list:
+    add_suggestion_message_flow = [user, [sug_btn, chatbot], [msg, chatbot]]
+    sug_btn.click(*add_suggestion_message_flow).then(*hide_suggestions_flow).then(*disable_msg_flow).then(*chat_response_flow).then(*update_suggestions_flow).then(*enable_msg_flow)
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-secrets = os.environ['openAIToken']
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value=secrets, label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
 
 
 if __name__ == "__main__":
-    demo.launch()
+  demo.launch()
+  gr.close_all()

requirements.txt

@@ -1 +1,2 @@
-huggingface_hub==0.22.2
+huggingface_hub==0.22.2
+openai==1.28.0