Luigi commited on
Commit
9ac8eab
·
1 Parent(s): 185fa8e

downgrade outlines to 0.0.36 to avoid issue 820

Browse files
Files changed (2) hide show
  1. app.py +11 -7
  2. requirements.txt +1 -1
app.py CHANGED
@@ -11,8 +11,8 @@ from pathlib import Path
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  from faster_whisper import WhisperModel
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  from huggingface_hub import hf_hub_download
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- llm_repo_id = "Qwen/Qwen2.5-3B-Instruct-GGUF"
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- llm_filename="qwen2.5-3b-instruct-q2_k.gguf"
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  asr_repo_id = "Luigi/whisper-small-zh_tw-ct2"
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  llm_model_path = hf_hub_download(repo_id=llm_repo_id, filename=llm_filename)
@@ -55,14 +55,18 @@ def predict_with_llm(text):
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  model = load_outlines_model()
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  prompt = f"""
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- You are an agent specialized in classifying reservation information.
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- I'm going to provide you with a consumer restaurant reservation message.
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- You need to categorize it under one of the two labels.
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- Please reply with *only* the name of the labels in a JSON object like:
 
 
 
 
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  {{\"result\": \"Reservation\"}} or {{\"result\": \"Others\"}}
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- Here is the reservation information: {text}
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  """.strip()
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  classifier = choice(model, ["Reservation", "Others"])
 
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  from faster_whisper import WhisperModel
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  from huggingface_hub import hf_hub_download
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+ llm_repo_id = "Qwen/Qwen2.5-1.5B-Instruct-GGUF"
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+ llm_filename="qwen2.5-1.5b-instruct-q8_0.gguf"
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  asr_repo_id = "Luigi/whisper-small-zh_tw-ct2"
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  llm_model_path = hf_hub_download(repo_id=llm_repo_id, filename=llm_filename)
 
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  model = load_outlines_model()
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  prompt = f"""
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+ You are an expert in classification of restautant customers' message.
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+ I'm going to provide you with a message from a restautant customer.
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+ You have to classify it in one of the follwing two intents:
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+
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+ Reservation: Inquiries and requests highly related to table reservations and seating
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+ Others: All other messages that do not involve table booking or reservations
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+
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+ Please reply with *only* the name of the intent labels in a JSON object like:
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  {{\"result\": \"Reservation\"}} or {{\"result\": \"Others\"}}
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+ Here is the message to classify: {text}
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  """.strip()
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  classifier = choice(model, ["Reservation", "Others"])
requirements.txt CHANGED
@@ -5,6 +5,6 @@ torch
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  torchaudio
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  faster-whisper
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  soundfile
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- outlines[llamacpp]==0.0.36 # https://github.com/dottxt-ai/outlines/issues/820
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  numpy>=1.24,<2.0
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  llama-cpp-python
 
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  torchaudio
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  faster-whisper
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  soundfile
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+ outlines[llamacpp]==0.0.36 # issue beyond 0.0.36 https://github.com/dottxt-ai/outlines/issues/820
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  numpy>=1.24,<2.0
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  llama-cpp-python