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Update app.py
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app.py
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@@ -21,7 +21,15 @@ from transformers import (
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# Configuration Constants
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MODEL_ID = "critical-hf/MAI_phd_ltd"
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DEFAULT_SYSTEM_PROMPT = """
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# UI Configuration
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TITLE = "<h1><center>AI Reasoning Assistant</center></h1>"
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@@ -140,7 +148,7 @@ def chat_response(
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chat_display: str,
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system_prompt: str,
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temperature: float = 0.2,
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max_new_tokens: int =
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top_p: float = 0.8,
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top_k: int = 40,
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penalty: float = 1.2,
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@@ -251,7 +259,7 @@ def main():
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minimum=128,
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maximum=32000,
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step=128,
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value=
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label="Max Tokens",
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)
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top_p = gr.Slider(
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# Configuration Constants
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MODEL_ID = "critical-hf/MAI_phd_ltd"
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DEFAULT_SYSTEM_PROMPT = """
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You are a highly intelligent reasoning assistant. For every question, follow these steps and use tags to structure your response for clarity and transparency:
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[Understand]: Analyze the question to identify key details and clarify the goal.
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[Plan]: Outline a logical, step-by-step approach to address the question or problem.
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[Reason]: Execute the plan, applying logical reasoning, calculations, or analysis to reach a conclusion. Document each step clearly.
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[Reflect]: Review the reasoning and the final answer to ensure it is accurate, complete, and adheres to the principle of openness.
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[Respond]: Present a well-structured and transparent answer, enriched with supporting details as needed.
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Use these tags as headers in your response to make your thought process easy to follow and aligned with the principle of openness."""
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# UI Configuration
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TITLE = "<h1><center>AI Reasoning Assistant</center></h1>"
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chat_display: str,
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system_prompt: str,
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temperature: float = 0.2,
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max_new_tokens: int = 8192,
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top_p: float = 0.8,
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top_k: int = 40,
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penalty: float = 1.2,
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minimum=128,
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maximum=32000,
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step=128,
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value=8192,
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label="Max Tokens",
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)
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top_p = gr.Slider(
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