ghengx commited on
Commit
7c2445a
1 Parent(s): df2e419
Files changed (3) hide show
  1. .gitignore +5 -0
  2. app.py +80 -18
  3. requirements.txt +2 -0
.gitignore ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ .env
2
+ venv
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+ test.py
4
+ __pycache__
5
+ backend_fn
app.py CHANGED
@@ -1,7 +1,27 @@
1
  import spaces
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  import gradio as gr
3
  from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
4
  from threading import Thread
 
 
5
 
6
  """
7
  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
@@ -17,14 +37,19 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
17
 
18
  streamer = TextIteratorStreamer(tokenizer, timeout=300, skip_prompt=True, skip_special_tokens=True)
19
 
 
 
 
 
 
20
  @spaces.GPU
21
  def respond(
22
  message,
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  history: list[tuple[str, str]],
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  # system_message,
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- max_tokens,
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- temperature,
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- top_p,
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  ):
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  messages = [
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  {"role": "system", "content": "You are a professional lawyer who is familiar with Malaysia Law."}
@@ -64,24 +89,61 @@ def respond(
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  """
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  For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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  """
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- demo = gr.ChatInterface(
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- respond,
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- additional_inputs=[
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- # gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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- gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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- gr.Slider(minimum=0.1, maximum=4.0, value=0.1, step=0.1, label="Temperature"),
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- gr.Slider(
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- minimum=0.1,
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- maximum=1.0,
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- value=0.95,
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- step=0.05,
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- label="Top-p (nucleus sampling)",
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- ),
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- ],
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- )
82
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
83
 
84
  if __name__ == "__main__":
85
  demo.launch(
86
 
87
  )
 
 
1
  import spaces
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+ import os
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+
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+ from huggingface_hub import Repository
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+ from huggingface_hub import login
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+
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+ login(token = os.environ['HUB_TOKEN'])
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+
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+ repo = Repository(
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+ local_dir="backend_fn",
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+ repo_type="dataset",
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+ clone_from=os.environ['DATASET'],
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+ token=True,
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+ git_email='zhiheng_dev@dahreply.ai'
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+ )
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+ repo.git_pull()
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+
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+ import json
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+ import uuid
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  import gradio as gr
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  from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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  from threading import Thread
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+ from backend_fn.feedback import feedback
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+ from gradio_modal import Modal
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26
  """
27
  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
 
37
 
38
  streamer = TextIteratorStreamer(tokenizer, timeout=300, skip_prompt=True, skip_special_tokens=True)
39
 
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+ histories = []
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+ action = None
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+
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+ session_id = uuid.uuid1().__str__()
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+
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  @spaces.GPU
46
  def respond(
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  message,
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  history: list[tuple[str, str]],
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  # system_message,
50
+ max_tokens = 4096,
51
+ temperature = 0.01,
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+ top_p = 0.95,
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  ):
54
  messages = [
55
  {"role": "system", "content": "You are a professional lawyer who is familiar with Malaysia Law."}
 
89
  """
90
  For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
91
  """
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
92
 
93
+ def submit_feedback(value):
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+ feedback(session_id, json.dumps(histories), value, action)
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+
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+
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+ with gr.Blocks() as demo:
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+ def vote(history,data: gr.LikeData):
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+ global histories
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+ global action
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+ histories = history
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+ action = data.liked
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+
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+ with Modal(visible=False) as modal:
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+ textb = gr.Textbox(
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+ label='Actual response',
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+ info='Leave blank if the answer is good enough'
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+ )
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+
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+ submit_btn = gr.Button(
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+ 'Submit'
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+ )
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+
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+ submit_btn.click(submit_feedback,textb)
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+ submit_btn.click(lambda: Modal(visible=False), None, modal)
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+ submit_btn.click(lambda x: gr.update(value=''), [],[textb])
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+
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+
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+ ci = gr.ChatInterface(
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+ respond,
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+ # fill_height=True
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+ # additional_inputs=[
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+ # # gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
124
+ # gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
125
+ # gr.Slider(minimum=0.1, maximum=4.0, value=0.1, step=0.1, label="Temperature"),
126
+ # gr.Slider(
127
+ # minimum=0.1,
128
+ # maximum=1.0,
129
+ # value=0.95,
130
+ # step=0.05,
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+ # label="Top-p (nucleus sampling)",
132
+ # ),
133
+ # ],
134
+ )
135
+
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+
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+ ci.chatbot.show_copy_button=True
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+ # ci.chatbot.value=[(None,"Hello! I'm here to assist you with understanding the laws and acts of Malaysia.")]
139
+ # ci.chatbot.height=500
140
+
141
+ ci.chatbot.like(vote, ci.chatbot, None).then(
142
+ lambda: Modal(visible=True), None, modal
143
+ )
144
 
145
  if __name__ == "__main__":
146
  demo.launch(
147
 
148
  )
149
+
requirements.txt CHANGED
@@ -11,6 +11,7 @@ filelock==3.16.1
11
  fsspec==2024.10.0
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  gradio==5.4.0
13
  gradio_client==1.4.2
 
14
  h11==0.14.0
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  httpcore==1.0.6
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  httpx==0.27.2
@@ -32,6 +33,7 @@ pydantic==2.9.2
32
  pydantic_core==2.23.4
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  pydub==0.25.1
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  Pygments==2.18.0
 
35
  python-dateutil==2.9.0.post0
36
  python-multipart==0.0.12
37
  pytz==2024.2
 
11
  fsspec==2024.10.0
12
  gradio==5.4.0
13
  gradio_client==1.4.2
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+ gradio_modal==0.0.4
15
  h11==0.14.0
16
  httpcore==1.0.6
17
  httpx==0.27.2
 
33
  pydantic_core==2.23.4
34
  pydub==0.25.1
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  Pygments==2.18.0
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+ PyMySQL==1.1.1
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  python-dateutil==2.9.0.post0
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  python-multipart==0.0.12
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  pytz==2024.2