feat: :art: init

.gitignore

@@ -0,0 +1 @@
+__pycache__

README.md

@@ -1,8 +1,8 @@
 ---
 title: Ingredients Spellcheck Annotate
-emoji: 🐨
+emoji: 🍊✍️
 colorFrom: red
-colorTo: gray
+colorTo: blue
 sdk: gradio
 sdk_version: 4.44.1
 app_file: app.py

app.py

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+import gradio as gr
+
+from back_end import next_annotation, submit_correction
+from utils import diff_texts
+
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """# Ingredients Spellcheck 🍊
+        ### You can review corrections generated by our model and validate or correct the predictions.\n
+        Your feedback will be integrated to the OFF database!
+
+        *Note: We are working on connecting this tool to OFF Product Opener. 👷*  
+        """)
+    
+    insight_id = gr.Textbox(
+        label="Insight Id",
+        interactive=False,
+        visible=False,
+    )
+
+    original_text = gr.Textbox(
+        label="Original Text (Uneditable)",
+        info="This is the original text.",
+        interactive=False,  # Make this text box uneditable
+        lines=3
+    )
+    
+    corrected_text = gr.Textbox(
+        label="Corrected Text (Editable)",
+        info="This is the AI-corrected text. You can modify it.",
+        interactive=True,  # Make this text box editable
+        lines=3
+    )
+    
+    # Diff Display using HighlightedText
+    diff_display = gr.HighlightedText(
+        label="Difference Between Original and Corrected Text",
+        combine_adjacent=True,
+        show_legend=True,
+        color_map={"+": "green", "-": "red"}  # "+" for inserted text, "-" for deleted text
+    )
+    
+    # Validate button to move to next annotation
+    with gr.Row():
+        validate_button = gr.Button("Validate")
+        skip_button = gr.Button("Skip")
+    
+    # Define action when validate button is clicked
+    validate_button.click(
+        submit_correction,  # Function to handle submission
+        inputs=[insight_id, original_text, corrected_text],  # Original and edited texts as inputs
+        outputs=[insight_id, original_text, corrected_text]  # Load next pair of texts
+    )
+
+    skip_button.click(
+        next_annotation,  # Function to handle submission
+        inputs=[],  # Original and edited texts as inputs
+        outputs=[insight_id, original_text, corrected_text]  # Load next pair of texts
+    )
+    
+    # Update diff display dynamically when corrected text is modified
+    corrected_text.change(
+        diff_texts,  # Call diff function
+        inputs=[original_text, corrected_text],  # Compare original and corrected texts
+        outputs=diff_display  # Update diff display
+    )
+    
+    # Load the first set of texts when the demo starts
+    demo.load(next_annotation, inputs=[], outputs=[insight_id, original_text, corrected_text])
+
+
+if __name__ == "__main__":
+    demo.launch()

back_end.py

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+from typing import Dict, Tuple
+import requests
+
+
+BASE_URL = "https://robotoff.openfoodfacts.org/api/v1/"
+
+
+def next_annotation() -> Tuple[str, str, str]:
+    insight = import_random_insight()
+    return insight["id"], insight["data"]["original"], insight["data"]["correction"]
+
+
+def submit_correction(insight_id: str, original: str, correction: str) -> Tuple[str, str, str]:
+    # Not implemented yet
+    return next_annotation()
+
+
+def import_random_insight(
+    insight_type: str = "ingredient_spellcheck",
+    count: int = 1,
+    predictor: str = "fine-tuned-mistral-7b",
+) -> Dict:
+    url = f"{BASE_URL}/insights/random?count={count}&type={insight_type}&predictor={predictor}"
+    response = requests.get(url)
+    data = response.json()
+    insight = data["insights"][0]
+    return insight
+
+
+def submit_to_product_opener(
+    insight_id: str,
+    skipped: bool,
+    update: int = 0,
+) -> None:
+    url = f"{BASE_URL}/insights/annotate"
+    annotation = -1 if skipped else 1
+    data = {
+        "insight_id": insight_id,
+        "annotation": annotation,
+        "update": update,
+    }
+    requests.post(url, data=data)

requirements.txt

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+gradio==4.44.1

utils.py

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+from difflib import Differ  
+
+
+def diff_texts(text1, text2):
+    d = Differ()
+    return [
+        (token[2:], token[0] if token[0] != " " else None)
+        for token in d.compare(text1, text2)
+    ]