mshetairy commited on
Commit
001179f
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1 Parent(s): b329030

Update app.py

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Files changed (1) hide show
  1. app.py +27 -18
app.py CHANGED
@@ -1,5 +1,6 @@
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  import gradio as gr
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  from huggingface_hub import InferenceClient
 
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  """
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  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
@@ -15,29 +16,37 @@ def respond(
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  temperature,
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  top_p,
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  ):
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- messages = [{"role": "system", "content": system_message}]
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- for val in history:
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- if val[0]:
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- messages.append({"role": "user", "content": val[0]})
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- if val[1]:
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- messages.append({"role": "assistant", "content": val[1]})
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- messages.append({"role": "user", "content": message})
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- response = ""
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- for message in client.chat_completion(
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- messages,
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- max_tokens=max_tokens,
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- stream=True,
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- temperature=temperature,
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- top_p=top_p,
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- ):
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- token = message.choices[0].delta.content
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- response += token
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- yield response
 
 
 
 
 
 
 
 
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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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  import gradio as gr
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  from huggingface_hub import InferenceClient
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+ from naive_chatbot import NaiveChatbot
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  """
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  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
 
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  temperature,
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  top_p,
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  ):
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+ # messages = [{"role": "system", "content": system_message}]
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+ # for val in history:
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+ # if val[0]:
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+ # messages.append({"role": "user", "content": val[0]})
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+ # if val[1]:
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+ # messages.append({"role": "assistant", "content": val[1]})
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+ # messages.append({"role": "user", "content": message})
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+ # response = ""
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+ # for message in client.chat_completion(
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+ # messages,
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+ # max_tokens=max_tokens,
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+ # stream=True,
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+ # temperature=temperature,
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+ # top_p=top_p,
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+ # ):
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+ # token = message.choices[0].delta.content
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+ # response += token
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+ my_bot = NaiveChatbot(pretrained=True,
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+ query_tokenizer_path="utils/query_tokenizer.pickle",
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+ intent_tokenizer_path="utils/intent_tokenizer.pickle",
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+ model_weights_path="utils/checkpoint.ckpt",
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+ db_responses2text_path="utils/db_responses2text.pickle",
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+ db_intent2response_path="utils/db_intent2response.pickle",
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+ db_transliteration_path="utils/db_ar2safebw.pickle")
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+ response = my_bot.get_reply(user_input, 0.97)
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+ yield response
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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