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llm steering
Browse files
app.py
CHANGED
@@ -48,15 +48,20 @@ def scrape_and_summarize(prompt, source):
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# Gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("# Scrape websites, no-code version")
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gr.Markdown("""
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It's a basic demo and a work in progress. Please contribute to it to make it more useful!""")
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with gr.Row():
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with gr.Column():
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model_dropdown = gr.Textbox(label="Model", value="Qwen/Qwen2.5-72B-Instruct")
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prompt_input = gr.Textbox(label="Prompt", value="List all the press releases with their headlines and urls.")
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source_input = gr.Textbox(label="Source URL", value="https://www.whitehouse.gov/")
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scrape_button = gr.Button("Scrape and Summarize")
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# Gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("# Scrape websites, no-code version")
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gr.Markdown("""
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Easily scrape and summarize web content using advanced AI models on the Hugging Face Hub without writing any code. Input your desired prompt and source URL to get started.
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This is a no-code version of the excellent library [ScrapeGraphAI](https://github.com/VinciGit00/Scrapegraph-ai).
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It's a basic demo and a work in progress. Please contribute to it to make it more useful!
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*Note: You might need to add "Output only the results; do not add any comments or include 'JSON OUTPUT' or similar phrases" in your prompt to ensure the LLM only provides the result.*
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""")
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with gr.Row():
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with gr.Column():
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model_dropdown = gr.Textbox(label="Model", value="Qwen/Qwen2.5-72B-Instruct")
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prompt_input = gr.Textbox(label="Prompt", value="List all the press releases with their headlines and urls. Output only the results; do not add any comments or include 'JSON OUTPUT' or similar phrases.")
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source_input = gr.Textbox(label="Source URL", value="https://www.whitehouse.gov/")
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scrape_button = gr.Button("Scrape and Summarize")
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