feat: :zap: App connected to PO

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 
-from back_end import next_annotation, submit_correction
+from back_end import next_annotation, submit_correction, enable_buttons
 from utils import diff_texts
 
 
@@ -11,30 +11,42 @@ with gr.Blocks() as demo:
         ### 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. 👷*  
-        """)
-    
+        To update a product in the Open Food Facts database, you need to indicate your Open Food Facts username and password.
+        If you're not registered yet, you can do it [here](https://world.openfoodfacts.org/cgi/user.pl)!
+        """
+    )
     
     with gr.Row():
         with gr.Column():
             insight_id = gr.Textbox(
                 label="Insight Id",
-                interactive=False,
                 visible=False,
             )
 
-            original_text = gr.Textbox(
+            with gr.Row():
+                off_username = gr.Textbox(
+                    label="OFF Username",
+                )
+                off_password = gr.Textbox(
+                   label="OFF Password",
+                   type="password",
+                )
+
+            # Saved to detect change from annotator
+            model_correction = gr.Text(visible=False)
+
+            original = 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(
+            annotator_correction = 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
+                lines=3,
             )
             
             # Diff Display using HighlightedText
@@ -49,31 +61,51 @@ with gr.Blocks() as demo:
     
     # Validate button to move to next annotation
     with gr.Row():
-        validate_button = gr.Button("Validate")
-        skip_button = gr.Button("Skip")
+        validate_button = gr.Button("Validate", interactive=False)
+        skip_button = gr.Button("Skip", interactive=False)
     
-    # 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, image]  # Load next pair of texts
+        submit_correction,
+        inputs=[insight_id, annotator_correction, model_correction, off_username, off_password],
+        outputs=[insight_id, original, model_correction, annotator_correction, image]
     )
 
     skip_button.click(
-        next_annotation,  # Function to handle submission
-        inputs=[],  # Original and edited texts as inputs
-        outputs=[insight_id, original_text, corrected_text, image]  # Load next pair of texts
+        next_annotation,
+        inputs=[],
+        outputs=[insight_id, original, model_correction, annotator_correction, image]
     )
     
-    # Update diff display dynamically when corrected text is modified
-    corrected_text.change(
+    annotator_correction.change(
         diff_texts,  # Call diff function
-        inputs=[original_text, corrected_text],  # Compare original and corrected texts
-        outputs=diff_display  # Update diff display
+        inputs=[original, annotator_correction],
+        outputs=diff_display
+    )
+
+    off_username.change(
+        enable_buttons, 
+        inputs=[off_username, off_password], 
+        outputs=[validate_button, skip_button]
     )
     
+    off_password.change(
+        enable_buttons,
+        inputs=[off_username, off_password],
+        outputs=[validate_button, skip_button],
+    )
+
     # Load the first set of texts when the demo starts
-    demo.load(next_annotation, inputs=[], outputs=[insight_id, original_text, corrected_text, image])
+    demo.load(
+        next_annotation,
+        inputs=[],
+        outputs=[
+            insight_id,
+            original,
+            model_correction,
+            annotator_correction,
+            image,
+        ],
+    )
 
 
 if __name__ == "__main__":

back_end.py

@@ -1,33 +1,81 @@
-from typing import Dict, Tuple
+from typing import Dict, Tuple, Optional, TypeAlias
 import requests
+import base64
+import json
+from dataclasses import dataclass
+
+from utils import get_logger
 
 from openfoodfacts.api import ProductResource, APIConfig
+import gradio as gr
+
+
+logger = get_logger()
+
+BASE_URL = "https://robotoff.openfoodfacts.org/api/v1" # Prod
+# BASE_URL = "http://localhost:5500/api/v1" # Dev
+UPDATE = 1
+
+Annotation: TypeAlias = Tuple[str, str, str, str, str]
 
 
-BASE_URL = "https://robotoff.openfoodfacts.org/api/v1/"
+@dataclass
+class Authentification:
+    username: str
+    password: str
 
+    def get_credentials(self) -> str:
+        credentials = f"{self.username}:{self.password}"
+        return base64.b64encode(credentials.encode()).decode()
 
-def next_annotation() -> Tuple[str, str, str, str]:
+
+def next_annotation() -> Annotation:
     insight = import_random_insight()
+    logger.info("Imported insight: %s", insight)
     return (
-        insight["id"], 
-        insight["data"]["original"], 
+        insight["id"],
+        insight["data"]["original"],
+        insight["data"]["correction"], # Saved for comparison with annotator changes
         insight["data"]["correction"],
         get_image_url(insight["barcode"])
     )
 
 
-def submit_correction(insight_id: str, original: str, correction: str) -> Tuple[str, str, str]:
-    # Not implemented yet
+def submit_correction(
+    insight_id: str,
+    annotator_correction: str,
+    model_correction: str,
+    username: str,
+    password: str,
+    update: bool = UPDATE
+):
+    auth = Authentification(username, password)
+    correction = annotator_correction if annotator_correction != model_correction else None
+    try:
+        submit_to_product_opener(
+            insight_id=insight_id,
+            update=update,
+            annotator_correction=correction,
+            auth=auth,
+        )
+    except gr.Error as e:
+        gr.Warning(e.message) # We use gr.Warning instead of gr.Error to keep the flow 
+        return (
+            gr.update(),
+            gr.update(),
+            gr.update(),
+            gr.update(),
+            gr.update(),
+        ) # Stay unchanged
+    gr.Info("Product successfuly updated. Many thanks!")
     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}"
+    url = f"{BASE_URL}/insights/random?count=1&type={insight_type}&predictor={predictor}"
     response = requests.get(url)
     data = response.json()
     insight = data["insights"][0]
@@ -36,29 +84,53 @@ def import_random_insight(
 
 def submit_to_product_opener(
     insight_id: str,
-    skipped: bool,
-    update: int = 0,
+    update: bool,
+    auth: Authentification,
+    annotator_correction: Optional[str] = None,
 ) -> None:
     url = f"{BASE_URL}/insights/annotate"
-    annotation = -1 if skipped else 1
-    data = {
-        "insight_id": insight_id,
-        "annotation": annotation,
-        "update": update,
+    headers = {
+        "Authorization": f"Basic {auth.get_credentials()}",
+        'Content-Type': 'application/x-www-form-urlencoded',
     }
-    requests.post(url, data=data)
-
+    if annotator_correction:
+        logger.info("Change from annotator. New insight sent to Product Opener. New correction: %s", annotator_correction)
+        payload = {
+            "insight_id": insight_id,
+            "annotation": 2,
+            "update": update,
+            "data": json.dumps({"annotation": annotator_correction}),
+        }
+    else:
+        logger.info("No change from annotator. Original insight sent to Product Opener.")
+        payload = {
+            "insight_id": insight_id,
+            "annotation": 1,
+            "update": update,
+        }
+    try:
+        response = requests.post(url, data=payload, headers=headers)
+        response.raise_for_status()
+    except requests.RequestException as e:
+        logger.error(e)
+        logger.error(response.content)
+        raise gr.Error("Failed to submit to Product Opener. Are your username and password correct?")
+        
 
 def get_image_url(
     code: str,
     user_agent: str = "Spellcheck-Annotate",
 ) -> str:
     fields = ["image_ingredients_url"]
-    data = ProductResource(
-        api_config=APIConfig(user_agent=user_agent)
-    ).get(
+    data = ProductResource(api_config=APIConfig(user_agent=user_agent)).get(
         code=code,
         fields=fields,
     )
     image_url = data.get(fields[0])
     return image_url
+
+
+def enable_buttons(username, password):
+    # Return the updated button states: interactive if both username and password are filled
+    state = bool(username) and bool(password)
+    return gr.update(interactive=state), gr.update(interactive=state)

utils.py

@@ -1,4 +1,5 @@
-from difflib import Differ  
+from difflib import Differ
+import logging
 
 
 def diff_texts(text1, text2):
@@ -6,4 +7,12 @@ def diff_texts(text1, text2):
     return [
         (token[2:], token[0] if token[0] != " " else None)
         for token in d.compare(text1, text2)
-    ]
+    ]
+
+
+def get_logger():
+    logging.basicConfig(
+        level=logging.INFO,
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    )
+    return logging.getLogger(__name__)