Spaces:
Running
on
Zero
Running
on
Zero
Daemontatox
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -16,7 +16,7 @@ from threading import Thread
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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MODEL = "Daemontatox/SphinX"
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TITLE = "<h1><center>
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PLACEHOLDER = """
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<center>
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@@ -79,8 +79,8 @@ def stream_chat(
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message: str,
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history: list,
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system_prompt: str,
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temperature: float = 0
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max_new_tokens: int =
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top_p: float = 1.0,
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top_k: int = 20,
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penalty: float = 1.2,
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@@ -138,23 +138,46 @@ with gr.Blocks(css=CSS, theme="soft") as demo:
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additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
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additional_inputs=[
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gr.Textbox(
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value="""You are
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1.
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2. **Self-Critique:** Now, critically evaluate your initial response. Specifically consider:
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* **Accuracy:** Is it factually correct and verifiable?
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* **Clarity:** Is it easy to understand and free of ambiguity?
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* **Completeness:** Does it fully address the user's request?
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* **Improvement:** What specific aspects could be better?
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label="System Prompt",
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lines=5,
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render=False,
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@@ -169,7 +192,7 @@ If you need a new Tag create on and use it .""",
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),
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gr.Slider(
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minimum=128,
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maximum=
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step=1,
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value= 8192,
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label="Max new tokens",
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@@ -195,7 +218,7 @@ If you need a new Tag create on and use it .""",
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minimum=0.0,
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maximum=2.0,
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step=0.1,
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value=
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label="Repetition penalty",
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render=False,
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),
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@@ -203,7 +226,7 @@ If you need a new Tag create on and use it .""",
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examples=[
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["What is meant by a Singularity? "],
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["Explain the theory of Relativty"],
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["Explain
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["Explain how mamba2 structure LLMs work and how do they differ from transformers? "],
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],
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cache_examples=False,
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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MODEL = "Daemontatox/SphinX"
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TITLE = "<h1><center>Sphinx Reasoner</center></h1>"
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PLACEHOLDER = """
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<center>
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message: str,
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history: list,
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system_prompt: str,
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temperature: float = 1.0,
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max_new_tokens: int = 8192,
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top_p: float = 1.0,
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top_k: int = 20,
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penalty: float = 1.2,
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additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
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additional_inputs=[
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gr.Textbox(
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value="""You are an AI expert at providing high-quality answers. Your process involves these steps:
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1. Initial Thought: Use the <Thinking> tag to reason step-by-step and generate your best possible response to the following request: [User's Request Here].
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Example:
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<Thinking> Step 1: Understand the request. Step 2: Analyze potential solutions. Step 3: Choose the optimal response. </Thinking>
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2. Self-Critique: Critically evaluate your initial response within <Critique> tags, focusing on:
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Accuracy: Is it factually correct and verifiable?
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Clarity: Is it easy to understand and free of ambiguity?
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Completeness: Does it fully address the user's request?
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Improvement: What specific aspects could be better?
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Example:
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<Critique> Accuracy: Verified. Clarity: Needs simplification. Completeness: Add examples. </Critique>
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3. Revision: Based on your critique, use <Revising> tags to refine and improve your response.
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Example:
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<Revising> Adjusting for clarity and adding an example to improve understanding. </Revising>
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4. Final Response: Present your revised answer clearly within <Final> tags.
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Example:
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<Final> This is the improved response. </Final>
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5. Tag Innovation: If necessary, create and define new tags to better structure your reasoning or enhance clarity. Use them consistently.
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Example:
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<Definition> This tag defines a new term introduced in the response. </Definition>
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Ensure every part of your thought process and output is properly enclosed in appropriate tags for clarity and organization.
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""",
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label="System Prompt",
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lines=5,
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render=False,
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),
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gr.Slider(
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minimum=128,
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maximum=32000,
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step=1,
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value= 8192,
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label="Max new tokens",
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minimum=0.0,
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maximum=2.0,
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step=0.1,
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value=1.2,
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label="Repetition penalty",
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render=False,
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),
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examples=[
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["What is meant by a Singularity? "],
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["Explain the theory of Relativty"],
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["Explain your thought process"],
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["Explain how mamba2 structure LLMs work and how do they differ from transformers? "],
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],
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cache_examples=False,
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