Update app.py

app.py

@@ -1,25 +1,48 @@
-import requests
 import gradio as gr
+from transformers import pipeline
 
-# The model endpoint on Hugging Face
-API_URL = "https://api-inference.huggingface.co/models/neovalle/H4rmoniousBreeze"
+# Load the Flan-T5-Large model and tokenizer via a pipeline.
+# If you're on a GPU Space, device=0 will place it on GPU.
+# If you're on CPU only, leave device=-1.
+model_name = "google/flan-t5-large"
+pipe = pipeline("text2text-generation", model=model_name, device=-1)
 
-def query_model(prompt):
-    # If your model is public, you may not need an API token.
-    # If it’s private, you'll need:
-    # headers = {"Authorization": "Bearer hf_..."} 
-    # and pass them in your requests.post(...) call.
-    payload = {"inputs": prompt}
-    response = requests.post(API_URL, json=payload)
-    return response.json()
+def judge_ecolinguistics(pairs_text):
+    """
+    Takes a multiline string of question–answer pairs and returns a model-generated
+    scoring from 1 to 10 for each pair, along with a brief explanation.
+    """
+    # Construct a single prompt that instructs the model to score each Q&A pair.
+    prompt = f"""
+You are an ecolinguistics judge. You evaluate answers based on how thoroughly
+they address ecological concerns, clarity of expression, and factual correctness.
 
+Below is a set of question–answer pairs:
+
+{pairs_text}
+
+Please provide, for each pair, a single numerical score from 1 to 10 and a brief explanation.
+"""
+    # Use the pipeline to generate a response.
+    response = pipe(prompt, max_length=512, truncation=True)[0]["generated_text"]
+    return response
+
+# Build the Gradio interface.
 demo = gr.Interface(
-    fn=query_model,
-    inputs="text",
+    fn=judge_ecolinguistics,
+    inputs=gr.Textbox(
+        lines=10,
+        label="Enter Your Question–Answer Pairs",
+        placeholder="Example:\nQ1: What is an ecological niche?\nA1: It is the role a species plays in its environment.\n\nQ2: How does deforestation affect the climate?\nA2: It can reduce carbon sequestration and disrupt rainfall patterns.\n"
+    ),
     outputs="text",
-    title="H4rmoniousBreeze",
-    description="Score narratives"
+    title="Ecolinguistics Q&A Scorer (Flan-T5-Large)",
+    description=(
+        "Paste multiple question–answer pairs. The model will assign a score from 1–10 "
+        "to each answer, considering ecological relevance and clarity. "
+        "It will also provide a brief rationale for its scoring."
+    )
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()