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app.py

@@ -1,64 +1,19 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 
-"""
-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
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+model = "VerifiedPrompts/CNTXT-Filter-Prompt-Opt"
+classifier = pipeline("text-classification", model=model)
 
+def classify(prompt):
+    result = classifier(prompt)[0]
+    return f"{result['label']} (score: {round(result['score'], 3)})"
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        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"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+demo = gr.Interface(
+    fn=classify,
+    inputs="textbox",
+    outputs="text",
+    title="Prompt Context Classifier",
+    description="Classifies prompts as clear, vague, or missing structural context."
 )
 
-
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()

requirements.txt

@@ -1 +1,11 @@
-huggingface_hub==0.25.2
+{\rtf1\ansi\ansicpg1252\cocoartf2822
+\cocoatextscaling0\cocoaplatform0{\fonttbl\f0\fswiss\fcharset0 Helvetica;}
+{\colortbl;\red255\green255\blue255;}
+{\*\expandedcolortbl;;}
+\paperw11900\paperh16840\margl1440\margr1440\vieww11520\viewh8400\viewkind0
+\pard\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\pardirnatural\partightenfactor0
+
+\f0\fs24 \cf0 transformers\
+torch\
+gradio\
+}