iamthewalrus67 commited on
Commit
c550f81
·
1 Parent(s): 2dd438d

Remove dropdown

Browse files
Files changed (1) hide show
  1. app.py +17 -17
app.py CHANGED
@@ -23,6 +23,15 @@ login(token=HF_LE_LLM_READ_TOKEN)
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  DEFAULT_MODEL = "le-llm/manipulative-score-model"
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  DEVICE = "cuda"
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  # --- Cache to avoid repeated reloads ---
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  _model_cache: Dict[str, tuple[torch.nn.Module, AutoTokenizer]] = {}
@@ -63,29 +72,23 @@ def compute_score(text: str, model: torch.nn.Module, tokenizer: AutoTokenizer) -
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  # --- Main scoring logic ---
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  @spaces.GPU
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- def bot(user_message: str, history: list[dict[str, Any]], model_choice: str):
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  if not user_message.strip():
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  return "", history
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- model, tokenizer = load_model(model_choice) # returns embedding model
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  history = history + [{"role": "user", "content": user_message}]
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- score = compute_score(user_message, model, tokenizer)["score"]
 
 
 
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- history.append({"role": "assistant", "content": f"{model_choice}: {score}"})
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  return "", history
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  # --- UI ---
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  THEME = gr.themes.Soft(primary_hue="blue", secondary_hue="amber", neutral_hue="stone")
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- MODEL_OPTIONS = [
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- "le-llm/manipulative-score-model",
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- "le-llm/gec-score-model",
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- "le-llm/fineweb-mixtral-edu-score",
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- "le-llm/fineweb-nemotron-edu-score",
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- "le-llm/alignment-score-model",
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- "le-llm/fasttext-quality-score",
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-
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- ]
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  def _clear_chat():
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  return "", []
@@ -94,14 +97,11 @@ def _clear_chat():
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  with gr.Blocks(theme=THEME, fill_height=True) as demo:
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  gr.Markdown("### 🤔 LAPA Quality Estimation")
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- with gr.Row():
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- model_choice = gr.Dropdown(MODEL_OPTIONS, value=DEFAULT_MODEL, label="Select Model")
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-
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  chatbot = gr.Chatbot(type="messages", height=480)
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  msg = gr.Textbox(label=None, placeholder="Type your text…", lines=1)
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  clear_btn = gr.Button("Clear")
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- msg.submit(bot, inputs=[msg, chatbot, model_choice], outputs=[msg, chatbot])
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  clear_btn.click(_clear_chat, outputs=[msg, chatbot])
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107
  if __name__ == "__main__":
 
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  DEFAULT_MODEL = "le-llm/manipulative-score-model"
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  DEVICE = "cuda"
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+ MODEL_OPTIONS = [
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+ "le-llm/manipulative-score-model",
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+ "le-llm/gec-score-model",
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+ "le-llm/fineweb-mixtral-edu-score",
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+ "le-llm/fineweb-nemotron-edu-score",
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+ "le-llm/alignment-score-model",
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+ "le-llm/fasttext-quality-score",
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+
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+ ]
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  # --- Cache to avoid repeated reloads ---
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  _model_cache: Dict[str, tuple[torch.nn.Module, AutoTokenizer]] = {}
 
72
 
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  # --- Main scoring logic ---
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  @spaces.GPU
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+ def bot(user_message: str, history: list[dict[str, Any]]):
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  if not user_message.strip():
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  return "", history
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+ res = ""
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  history = history + [{"role": "user", "content": user_message}]
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+ for model_choice in MODEL_OPTIONS:
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+ model, tokenizer = load_model(model_choice) # returns embedding model
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+ score = compute_score(user_message, model, tokenizer)["score"]
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+ res += f"{model_choice}: {score}\n"
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+ history.append({"role": "assistant", "content": res.strip()})
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  return "", history
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  # --- UI ---
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  THEME = gr.themes.Soft(primary_hue="blue", secondary_hue="amber", neutral_hue="stone")
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  def _clear_chat():
94
  return "", []
 
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  with gr.Blocks(theme=THEME, fill_height=True) as demo:
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  gr.Markdown("### 🤔 LAPA Quality Estimation")
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  chatbot = gr.Chatbot(type="messages", height=480)
101
  msg = gr.Textbox(label=None, placeholder="Type your text…", lines=1)
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  clear_btn = gr.Button("Clear")
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+ msg.submit(bot, inputs=[msg, chatbot], outputs=[msg, chatbot])
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  clear_btn.click(_clear_chat, outputs=[msg, chatbot])
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  if __name__ == "__main__":