Upload folder using huggingface_hub

.github/workflows/update_space.yml

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+name: Run Python script
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.9'
+
+    - name: Install Gradio
+      run: python -m pip install gradio
+
+    - name: Log in to Hugging Face
+      run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
+
+    - name: Deploy to Spaces
+      run: gradio deploy

README.md

@@ -1,12 +1,6 @@
 ---
-title: Board Of Advisors Assistant
-emoji: 🌍
-colorFrom: gray
-colorTo: blue
-sdk: gradio
-sdk_version: 4.44.1
+title: Board_of_Advisors_Assistant
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 3.35.2
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from openai import OpenAI
+import gradio as gr
+import json
+from bot_actions import functions_dictionary
+import os
+ 
+CSS ="""
+.contain { display: flex; flex-direction: column; }
+.svelte-vt1mxs div:first-child { flex-grow: 1; overflow: auto;}
+#chatbot { flex-grow: 1; overflow: auto;}
+footer {display: none !important;}
+.app.svelte-182fdeq.svelte-182fdeq {
+  max-width: 100vw !important;
+}
+#main_container {
+  height: 95vh;
+}
+#markup_container {
+  height: 100%;
+  overflow:auto;
+}
+"""
+
+openAIToken = os.environ['openAIToken']
+assistantId = os.environ['assistantId']
+initial_message = os.environ['initialMessage']
+
+client = OpenAI(api_key=openAIToken)
+
+def handle_requires_action(data):
+  actions_results = []
+  for tool in data.required_action.submit_tool_outputs.tool_calls:
+    function_name = tool.function.name
+    function_args = json.loads(tool.function.arguments)
+    print(function_name)
+    print(function_args)
+    try:
+      result = functions_dictionary[tool.function.name](**function_args)
+      print("Function result:", result)
+      actions_results.append({"tool_output" : {"tool_call_id": tool.id, "output": result["message"]}})
+    except Exception as e:
+      print(e)
+
+    
+  # Submit all tool_outputs at the same time
+  return actions_results 
+
+
+def create_thread_openai(sessionStorage):
+  streaming_thread = client.beta.threads.create()
+  sessionStorage["threadId"] = streaming_thread.id
+  return sessionStorage
+
+def add_message_to_openai(text, threadId):
+  print("User message: ", text)
+  return client.beta.threads.messages.create(
+    thread_id=threadId,
+    role="user",
+    content=text
+  )
+
+
+def process_text_chunk(text, storage):
+  print(text, end="", flush=True)
+  local_message = None
+  accumulative_string = storage["accumulative_string"] + text
+  local_message = accumulative_string
+  return local_message, storage
+
+def handle_events(threadId, chat_history, storage):
+  storage.update({
+    "accumulative_string" : "",
+    "markup_string": "",
+  })
+  try:
+    with client.beta.threads.runs.stream(
+      thread_id=threadId,
+      assistant_id=assistantId
+    ) as stream:
+      for event in stream:
+        if event.event == "thread.message.delta" and event.data.delta.content:
+          text = event.data.delta.content[0].text.value
+          local_message, storage = process_text_chunk(text, storage)
+          if local_message is not None:
+            chat_history[-1][1] += local_message 
+          yield [chat_history,  storage]
+        if event.event == 'thread.run.requires_action':
+          result = handle_requires_action(event.data)
+          tool_outputs = [x["tool_output"] for x in result]
+          with client.beta.threads.runs.submit_tool_outputs_stream(
+            thread_id=stream.current_run.thread_id,
+            run_id=event.data.id,
+            tool_outputs=tool_outputs,
+          ) as action_stream:
+            for text in action_stream.text_deltas:
+              local_message, storage = process_text_chunk(text, storage)
+              if local_message is not None:
+                chat_history[-1][1] += local_message
+              yield [chat_history, storage]
+            action_stream.close()
+      stream.until_done()
+      print("")
+      return [chat_history, storage]
+  except Exception as e:
+    print(e)
+    chat_history[-1][1] = "Error occured during processing your message. Please try again"
+    yield [chat_history, storage]
+
+def initiate_chatting(chat_history, storage):
+  threadId = storage["threadId"]
+  chat_history = [[None, ""]]
+  add_message_to_openai(initial_message, threadId)
+  for response in handle_events(threadId, chat_history, storage):
+    yield response
+
+def respond_on_user_msg(chat_history, storage):
+  message = chat_history[-1][0]
+  threadId = storage["threadId"]
+  print("Responding for threadId: ", threadId)
+  chat_history[-1][1] = ""
+  add_message_to_openai(message, threadId)
+  for response in handle_events(threadId, chat_history, storage):
+    yield response
+
+def create_tabs():
+
+  pass
+
+def create_login_tab():
+  with gr.Blocks(fill_height=True) as login:
+    with gr.Row():
+      login_input = gr.Textbox(label="Login")
+    with gr.Row():
+      password_input = gr.Textbox(label="Password", type="password")
+  return login
+
+def create_chat_tab():
+  with gr.Blocks(css=CSS, fill_height=True) as demo:
+    storage = gr.State({"accumulative_string": ""})
+    btn_list = []
+    with gr.Row(elem_id="main_container"):
+      with gr.Column(scale=4):
+        chatbot = gr.Chatbot(label="Facility managment bot", line_breaks=False, height=300, show_label=False, show_share_button=False, elem_id="chatbot")
+        with gr.Row():
+          for i in range(6):
+              btn = gr.Button(visible=False, size="sm")
+              btn_list.append(btn)
+        msg = gr.Textbox(label="Answer", interactive=False)
+
+    def user(user_message, history):
+        return "", history + [[user_message, None]]
+
+    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_on_user_msg, [chatbot, storage], [chatbot, storage]]
+    disable_msg_flow = [disable_msg, None, msg] 
+    enable_msg_flow = [enable_msg, None, msg]
+
+    msg.submit(*add_user_message_flow
+        ).then(*disable_msg_flow
+        ).then(*chat_response_flow
+        ).then(*enable_msg_flow)
+    
+    demo.load(create_thread_openai, inputs=storage, outputs=storage
+        ).then(initiate_chatting, inputs=[chatbot, storage], outputs=[chatbot, storage]
+        ).then(*enable_msg_flow)
+  return demo
+
+demo = create_chat_tab()
+if __name__ == "__main__":
+  demo.launch(auth=(os.environ['login'], os.environ['password']), auth_message="Enter your Username and Password")

app.pyZone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+ReferrerUrl=https://huggingface.co/spaces/oleksandrburlakov/boardOfAdvisors/tree/main
+HostUrl=https://huggingface.co/spaces/oleksandrburlakov/boardOfAdvisors/resolve/main/app.py?download=true

bot_actions.py

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+def method_example(arg_json):
+  pass
+
+functions_dictionary = {
+  "method_example": method_example,
+}

bot_actions.pyZone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+ReferrerUrl=https://huggingface.co/spaces/oleksandrburlakov/boardOfAdvisors/tree/main
+HostUrl=https://huggingface.co/spaces/oleksandrburlakov/boardOfAdvisors/resolve/main/bot_actions.py?download=true

requirements.txt

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+huggingface_hub==0.22.2
+openai==1.28.0