maslionok
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README.md
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sdk: docker
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pinned: false
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short_description: Solr
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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colorTo: indigo
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sdk: docker
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pinned: false
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short_description: Demonstrate text normalization in the Impresso project using Solr functionality
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---
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# Solr Normalization Demo
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This space demonstrates how text is normalized in the **Impresso** project, replicating Solr's text processing functionality.
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Solr normalization is meant to demonstrate how text is normalized in the Impresso project. The pipeline processes text through various analyzers including tokenization, stopword removal, and language-specific transformations to prepare text for search and analysis.
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## Features
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- Multi-language support (German, French, Spanish, Italian, Portuguese, Dutch, English)
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- Automatic language detection
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- Detailed analyzer pipeline visualization
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- Stopword detection and removal
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- Token normalization
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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LANGUAGES = ["de", "fr", "es", "it", "pt", "nl", "en", "general"]
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def normalize(text, lang_choice):
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try:
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lang = None if lang_choice == "Auto-detect" else lang_choice
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print("β Pipeline error:", e)
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return f"Error: {e}"
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demo.launch(server_name="0.0.0.0", server_port=7860)
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LANGUAGES = ["de", "fr", "es", "it", "pt", "nl", "en", "general"]
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# Example text and default language
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EXAMPLE_TEXT = "The quick brown fox jumps over the lazy dog. This is a sample text for demonstration purposes."
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DEFAULT_LANGUAGE = "en"
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def normalize(text, lang_choice):
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try:
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lang = None if lang_choice == "Auto-detect" else lang_choice
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print("β Pipeline error:", e)
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return f"Error: {e}"
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# Create the interface with logo and improved description
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with gr.Blocks(title="Solr Normalization Demo") as demo:
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# Add logo at the top
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gr.Image("logo.jpeg", label=None, show_label=False, container=False, height=100)
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gr.Markdown(
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"""
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# π₯ Solr Normalization Pipeline Demo
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**Solr normalization** is meant to demonstrate how text is normalized in the **Impresso** project.
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This pipeline replicates Solr's text processing functionality, showing how text goes through various
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analyzers including tokenization, stopword removal, and language-specific transformations.
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Try the example below or enter your own text to see how it gets processed!
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"""
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)
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with gr.Row():
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with gr.Column():
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text_input = gr.Textbox(
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label="Enter Text",
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value=EXAMPLE_TEXT,
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lines=3,
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placeholder="Enter your text here..."
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)
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lang_dropdown = gr.Dropdown(
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choices=["Auto-detect"] + LANGUAGES,
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value=DEFAULT_LANGUAGE,
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label="Language"
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)
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submit_btn = gr.Button("π Normalize Text", variant="primary")
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with gr.Column():
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output = gr.Textbox(
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label="Normalized Output",
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lines=15,
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placeholder="Results will appear here..."
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)
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submit_btn.click(
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fn=normalize,
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inputs=[text_input, lang_dropdown],
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outputs=output
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)
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gr.Markdown(
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"""
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### π About the Pipeline
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- **Tokenization**: Splits text into individual tokens
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- **Stopword Removal**: Identifies and removes common words
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- **Language Detection**: Automatically detects text language
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- **Normalization**: Applies language-specific text transformations
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"""
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)
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demo.launch(server_name="0.0.0.0", server_port=7860)
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logo.jpeg
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