Update app.py

app.py

@@ -1,12 +1,9 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# Initialize the inference client with the model
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -31,63 +28,59 @@ def respond(
     response = ""
 
     # Stream the response from the model
-    for message in client.chat_completion(
+    for msg in client.chat_completion(
         messages,
         max_tokens=max_tokens,
         stream=True,
         temperature=temperature,
         top_p=top_p,
     ):
-        token = message.choices[0].delta.content
+        token = msg.choices[0].delta.content
         response += token
 
     # Validate the response format
-    if len(response) == 13 and all(c.isdigit() or c in 'CW' for c in response):
+    if len(response) == 13 and all(c.isdigit() for c in response):
         return response
     else:
         return "Invalid response format"
 
+# Instructions for the model
+instructions = (
+    "You are tasked with labeling text data based on both emotion temperature and text type categories. "
+    "The final output must be a 13-character code that consists of the following structure:\n\n"
+    "   0 index : Emotion Temperature code\n"
+    "   1 index : Informative\n"
+    "   2 index : Hate\n"
+    "   3 index : Toxic\n"
+    "   4 index : Appreciation\n"
+    "   5 index : Constructive Criticism\n"
+    "   6 index : Genuine Questions\n"
+    "   7 index : Advice/Suggestions\n"
+    "   8 index : Requests\n"
+    "   9 index : Spam\n"
+    "   10 index : Off-Topic\n"
+    "   11 index : Engagement Boosters\n"
+    "   12 index : Neutral/General\n\n"
+    "Every index should have a number between 0-9. 0 means not applicable, 4 means normal, 9 means high. "
+    "Choose appropriate numbers to showcase how much each category is related to the text input.\n\n"
+    "Example:\n"
+    "For the text 'I love your videos but still something is missing':\n"
+    "   - Emotion: Cold and Warm (CW)\n"
+    "   - Types Detected: 2 (Appreciation), 3 (Constructive Criticism), 5 (Advice/Suggestions)\n"
+    "   - Special Categories: Neutral/General (set the 10th digit to 1), no Hate\n\n"
+    "The output would be: CW02305000010\n\n"
+    "Output Format:\n"
+    "Always return a 13-character code following this structure."
+)
 
-"""
-For information on how to customize the ChatInterface, peruse the Gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+# Create the Gradio interface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
         gr.Textbox(
-            value="You are tasked with labeling text data based on both emotion temperature and text type categories. The final output must be a 13-character code that consists of the following structure:\n\n"
-                  "1. Emotion Temperature Code (2 characters):\n"
-                  "   - If the emotion is purely Cold: Use CC\n"
-                  "   - If the emotion is purely Warm: Use WW\n"
-                  "   - If the emotion is purely Hot: Use HH\n"
-                  "   - If the emotion is a mix, use one of the following:\n"
-                  "     - Cold and Warm: Use CW\n"
-                  "     - Warm and Hot: Use WH\n"
-                  "     - Cold and Hot: Use CH\n\n"
-                  "2. Text Type Codes (next 9 digits):\n"
-                  "   Assign a digit for each of the following categories based on the presence in the text. Use 0 for categories not applicable:\n"
-                  "   1: Toxic\n"
-                  "   2: Appreciation\n"
-                  "   3: Constructive Criticism\n"
-                  "   4: Genuine Questions\n"
-                  "   5: Advice/Suggestions\n"
-                  "   6: Requests\n"
-                  "   7: Spam\n"
-                  "   8: Off-Topic\n"
-                  "   9: Engagement Boosters\n\n"
-                  "3. Special Categories (last 2 digits):\n"
-                  "   If the text is Neutral/General: Set the 10th digit to 1; otherwise, set it to 0.\n"
-                  "   If the text contains Hate: Set the last digit (11th) to 1; otherwise, set it to 0.\n\n"
-                  "Example:\n"
-                  "For the text 'I love your videos but still something is missing':\n"
-                  "   - Emotion: Cold and Warm (CW)\n"
-                  "   - Types Detected: 2 (Appreciation), 3 (Constructive Criticism), 5 (Advice/Suggestions)\n"
-                  "   - Special Categories: Neutral/General (set the 10th digit to 1), no Hate\n\n"
-                  "The output would be: CW02305000010\n\n"
-                  "Output Format:\n"
-                  "Always return a 13-character code following this structure.",
+            value=instructions,
             label="Instructions",
-            lines=10,
+            lines=15,
         ),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),