init

app.py

@@ -0,0 +1,188 @@
+import gradio as gr
+import mysql.connector
+import os
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+classifier_model = pipeline(
+    "zero-shot-classification", model="MoritzLaurer/deberta-v3-large-zeroshot-v1"
+)
+
+# get db info from env vars
+db_host = os.environ.get("DB_HOST")
+db_user = os.environ.get("DB_USER")
+db_pass = os.environ.get("DB_PASS")
+db_name = os.environ.get("DB_NAME")
+
+
+db_connection = mysql.connector.connect(
+    host=db_host,
+    user=db_user,
+    password=db_pass,
+    database=db_name,
+)
+
+db_cursor = db_connection.cursor()
+
+
+def get_potential_labels():
+    # get potential labels from db
+    potential_labels = db_cursor.execute(
+        "SELECT message_category_name FROM message_categorys"
+    )
+
+    potential_labels = db_cursor.fetchall()
+
+    potential_labels = [label[0] for label in potential_labels]
+
+    return potential_labels
+
+
+# make gloabl variable for potential labels
+global potential_labels
+
+potential_labels = get_potential_labels()
+
+
+# Function to handle the classification
+def classify_email(constituent_email):
+    potential_labels = get_potential_labels()
+
+    model_out = classifier_model(constituent_email, potential_labels, multi_label=True)
+    top_labels = [
+        label
+        for label, score in zip(model_out["labels"], model_out["scores"])
+        if score > 0.95
+    ]
+    if top_labels == []:
+        # Find the index of the highest score
+        max_score_index = model_out["scores"].index(max(model_out["scores"]))
+        # Return the label with the highest score
+        return model_out["labels"][max_score_index]
+
+    return ", ".join(top_labels)
+
+
+# Function to handle saving data
+def save_data(orig_user_email, constituent_email, labels, user_response):
+    # save the data to the database
+    # orig_user_email should have volley 0
+    # constituent_email should have volley 1
+    # user_response should have volley 2
+    # app_id, org_id, and person_id should be 0
+    # subject should be "Email Classification and Response Tracking"
+    # body should be the original email
+
+    try:
+        db_cursor.execute(
+            "INSERT INTO messages (app_id, org_id, person_id, communication_method_id, status_id, subject, body, send_date, message_type, volley) VALUES (0, 0, 0, 1, 1, 'Email Classification and Response Tracking', %s, NOW(), 'Email Classification and Response Tracking', 0)",
+            (orig_user_email,),
+        )
+
+        db_cursor.execute(
+            "INSERT INTO messages (app_id, org_id, person_id, communication_method_id, status_id, subject, body, send_date, message_type, volley) VALUES (0, 0, 0, 1, 1, 'Email Classification and Response Tracking', %s, NOW(), 'Email Classification and Response Tracking', 1)",
+            (constituent_email,),
+        )
+
+        db_cursor.execute(
+            "INSERT INTO messages (app_id, org_id, person_id, communication_method_id, status_id, subject, body, send_date, message_type, volley) VALUES (0, 0, 0, 1, 1, 'Email Classification and Response Tracking', %s, NOW(), 'Email Classification and Response Tracking', 2)",
+            (user_response,),
+        )
+
+        # insert a row into the message_categorys_associations table for each valid label in labels with the message_id of the constituent_email
+        labels = labels.split(", ")
+        for label in labels:
+            label_exists = db_cursor.execute(
+                "SELECT * FROM radmap_frog12.message_categorys WHERE message_category_name = %s",
+                (label,),
+            )
+            label_exists = db_cursor.fetchall()
+            if label_exists:
+                db_cursor.execute(
+                    "INSERT INTO message_category_associations (message_id, message_category_id) VALUES ((SELECT id FROM messages WHERE body = %s), (SELECT id FROM message_categorys WHERE message_category_name = %s))",
+                    (constituent_email, label),
+                )
+
+        db_connection.commit()
+
+        return "Data successfully saved to database"
+
+    except Exception as e:
+        print(e)
+        db_connection.rollback()
+        return "Error saving data to database"
+
+
+# read auth from env vars
+auth_username = os.environ.get("AUTH_USERNAME")
+auth_password = os.environ.get("AUTH_PASSWORD")
+
+# Define your username and password pairs
+auth = [(auth_username, auth_password)]
+
+# Start building the Gradio interface
+# Start building the Gradio interface with two columns
+with gr.Blocks() as app:
+    with gr.Row():
+        gr.Markdown("## Email Classification and Response Tracking")
+
+    with gr.Row():
+        with gr.Column():
+            email_labels_input = gr.Markdown(
+                "## Valid Email Labels\n ### " + ", ".join(potential_labels),
+            )
+
+            original_email_input = gr.TextArea(
+                placeholder="Enter the original email sent by you",
+                label="Your Original Email",
+            )
+
+            spacer1 = gr.Label(visible=False)
+
+            constituent_response_input = gr.TextArea(
+                placeholder="Enter the constituent's response",
+                label="Constituent's Response",
+                lines=15,
+            )
+
+            classify_button = gr.Button("Classify Email")
+
+        with gr.Column():
+            classification_output = gr.TextArea(
+                label="Current Email Labels",
+                lines=1,
+                interactive=True,
+            )
+
+            spacer2 = gr.Label(visible=False)
+
+            user_response_input = gr.TextArea(
+                placeholder="Enter your response to the constituent",
+                label="Your Response",
+                lines=25,
+            )
+
+            save_button = gr.Button("Save Data")
+            save_output = gr.Label(label="Backend Response")
+
+    # Define button actions
+    classify_button.click(
+        fn=classify_email,
+        inputs=constituent_response_input,
+        outputs=classification_output,
+    )
+
+    save_button.click(
+        fn=save_data,
+        inputs=[
+            original_email_input,
+            constituent_response_input,
+            classification_output,
+            user_response_input,
+        ],
+        outputs=save_output,
+    )
+
+# Launch the app
+app.launch(auth=auth, debug=True)

requirements.txt

@@ -0,0 +1 @@
+mysql-connector-python