PierreBrunelle
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -39,7 +39,7 @@ def calculate_readability(text: str) -> float:
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return 206.835 - 1.015 * average_words_per_sentence
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# Function to run inference and analysis
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-
def run_inference_and_analysis(task, system_prompt, input_text, temperature, top_p, max_tokens,
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# Initialize Pixeltable
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pxt.drop_table('mistral_prompts', ignore_errors=True)
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t = pxt.create_table('mistral_prompts', {
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@@ -50,6 +50,7 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
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'temperature': pxt.Float,
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'top_p': pxt.Float,
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'max_tokens': pxt.Int,
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'random_seed': pxt.Int,
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'safe_prompt': pxt.Bool
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})
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@@ -63,6 +64,7 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
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'temperature': temperature,
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'top_p': top_p,
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'max_tokens': max_tokens,
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'random_seed': random_seed,
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'safe_prompt': safe_prompt
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}])
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@@ -78,6 +80,7 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
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'temperature': temperature,
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'top_p': top_p,
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'max_tokens': max_tokens if max_tokens is not None else 300,
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'random_seed': random_seed,
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'safe_prompt': safe_prompt
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}
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@@ -122,6 +125,7 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
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t.temperature,
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t.top_p,
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t.max_tokens,
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t.random_seed,
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t.safe_prompt
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).order_by(t.timestamp, asc=False).collect().to_pandas()
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@@ -147,7 +151,7 @@ def gradio_interface():
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gr.HTML(
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"""
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<div style="margin-bottom: 20px;">
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-
<img src="https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/
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</div>
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"""
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)
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@@ -198,6 +202,7 @@ def gradio_interface():
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temperature = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Temperature")
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top_p = gr.Slider(minimum=0, maximum=1, value=0.9, step=0.1, label="Top P")
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max_tokens = gr.Number(label="Max Tokens", value=300)
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random_seed = gr.Number(label="Random Seed", value=None)
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safe_prompt = gr.Checkbox(label="Safe Prompt", value=False)
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@@ -238,6 +243,7 @@ def gradio_interface():
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"Top P",
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"Max Tokens",
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"Min Tokens",
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"Random Seed",
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"Safe Prompt"
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],
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@@ -277,7 +283,7 @@ def gradio_interface():
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gr.Examples(
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examples=examples,
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inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, random_seed, safe_prompt],
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outputs=[omn_response, ml_response, large_sentiment, open_sentiment, large_keywords, open_keywords, large_readability, open_readability],
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fn=run_inference_and_analysis,
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cache_examples=True,
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@@ -291,7 +297,7 @@ def gradio_interface():
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submit_btn.click(
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run_inference_and_analysis,
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inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, random_seed, safe_prompt],
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outputs=[omn_response, ml_response, large_sentiment, open_sentiment, large_keywords, open_keywords, large_readability, open_readability, history, responses, analysis, params]
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)
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return 206.835 - 1.015 * average_words_per_sentence
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# Function to run inference and analysis
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+
def run_inference_and_analysis(task, system_prompt, input_text, temperature, top_p, max_tokens, stop, random_seed, safe_prompt):
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# Initialize Pixeltable
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pxt.drop_table('mistral_prompts', ignore_errors=True)
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t = pxt.create_table('mistral_prompts', {
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'temperature': pxt.Float,
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'top_p': pxt.Float,
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'max_tokens': pxt.Int,
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'stop': pxt.String,
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'random_seed': pxt.Int,
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'safe_prompt': pxt.Bool
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})
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'temperature': temperature,
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'top_p': top_p,
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'max_tokens': max_tokens,
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'stop': stop,
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'random_seed': random_seed,
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'safe_prompt': safe_prompt
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}])
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'temperature': temperature,
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'top_p': top_p,
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'max_tokens': max_tokens if max_tokens is not None else 300,
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'stop': stop.split(',') if stop else None,
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'random_seed': random_seed,
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'safe_prompt': safe_prompt
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}
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t.temperature,
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t.top_p,
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t.max_tokens,
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t.stop,
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t.random_seed,
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t.safe_prompt
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).order_by(t.timestamp, asc=False).collect().to_pandas()
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gr.HTML(
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"""
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<div style="margin-bottom: 20px;">
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<img src="https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/source/data/pixeltable-logo-large.png" alt="Pixeltable" style="max-width: 150px;" />
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</div>
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"""
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)
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temperature = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Temperature")
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top_p = gr.Slider(minimum=0, maximum=1, value=0.9, step=0.1, label="Top P")
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max_tokens = gr.Number(label="Max Tokens", value=300)
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stop = gr.Textbox(label="Stop Sequences (comma-separated)")
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random_seed = gr.Number(label="Random Seed", value=None)
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safe_prompt = gr.Checkbox(label="Safe Prompt", value=False)
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"Top P",
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"Max Tokens",
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"Min Tokens",
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"Stop Sequences",
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"Random Seed",
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"Safe Prompt"
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],
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gr.Examples(
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examples=examples,
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inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, stop, random_seed, safe_prompt],
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outputs=[omn_response, ml_response, large_sentiment, open_sentiment, large_keywords, open_keywords, large_readability, open_readability],
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fn=run_inference_and_analysis,
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cache_examples=True,
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submit_btn.click(
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run_inference_and_analysis,
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inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, stop, random_seed, safe_prompt],
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outputs=[omn_response, ml_response, large_sentiment, open_sentiment, large_keywords, open_keywords, large_readability, open_readability, history, responses, analysis, params]
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)
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