Create app.py

app.py

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+# app.py — CSS LexiScan for Hugging Face Spaces
+# Fully self-contained: précis + vocabulary extraction + Gradio UI
+
+import os
+import json
+from typing import Dict
+
+import gradio as gr
+import pandas as pd
+from groq import Groq
+
+# === Prompt Templates ===
+SYSTEM_PROMPT = (
+    "You are a helpful, concise assistant specialized in creating high-quality précis "
+    "and teaching vocabulary for CSS aspirants. Always output valid JSON with keys 'precis' and 'difficult_words'."
+)
+
+USER_PROMPT_TEMPLATE = (
+    "Here is a passage delimited by triple backticks.\n"
+    "Task:\n"
+    "1) Produce a concise précis (≤30% of original length).\n"
+    "2) Identify up to 7 difficult/uncommon words, each with word, part_of_speech, meaning (1–2 sentences), example sentence.\n"
+    "Rules:\n"
+    "- Return ONLY valid JSON.\n"
+    "- Avoid repetition.\n"
+    "Passage:\n```{passage}```"
+)
+
+FEW_SHOT = (
+    "Example input: 'The rapid expansion of renewable energy sources has altered global energy markets.'\n"
+    "Example output (JSON):\n"
+    "{\n"
+    "  \"precis\": \"Renewable energy growth is reshaping global markets.\",\n"
+    "  \"difficult_words\": [\n"
+    "    {\"word\": \"renewable\", \"part_of_speech\": \"adjective\", \"meaning\": \"Able to be replenished naturally without being exhausted.\", \"example\": \"Wind and sunlight are renewable sources of power.\"}\n"
+    "  ]\n"
+    "}"
+)
+
+# === Helper Functions ===
+def get_groq_api_key(secret_name: str = "GROQ_API_KEY") -> str:
+    key = os.environ.get(secret_name)
+    if not key:
+        raise ValueError(f"No Groq API key found. Set it in HF Secrets as '{secret_name}'.")
+    return key
+
+def make_groq_client(api_key: str):
+    return Groq(api_key=api_key)
+
+def truncate(text: str, max_len: int) -> str:
+    text = text.strip()
+    return text if len(text) <= max_len else text[:max_len-1] + "…"
+
+def extract_json(text: str) -> str:
+    start = text.find("{")
+    end = text.rfind("}")
+    if start == -1 or end == -1 or end <= start:
+        raise ValueError("No JSON found in model response.")
+    return text[start:end+1]
+
+def post_process(parsed: Dict) -> Dict:
+    precis = parsed.get("precis", "").strip()
+    difficult = parsed.get("difficult_words", [])
+    seen = set()
+    cleaned = []
+    for item in difficult:
+        word = item.get("word", "").strip()
+        if not word or word.lower() in seen:
+            continue
+        seen.add(word.lower())
+        cleaned.append({
+            "word": word,
+            "part_of_speech": item.get("part_of_speech", "").strip(),
+            "meaning": truncate(item.get("meaning", ""), 200),
+            "example": truncate(item.get("example", ""), 200)
+        })
+    return {"precis": truncate(precis, 2000), "difficult_words": cleaned}
+
+def generate_precis_and_vocab(client: Groq, passage: str, model: str = "llama-3.3-70b-versatile") -> Dict:
+    passage = passage.strip()
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {"role": "system", "content": SYSTEM_PROMPT},
+            {"role": "user", "content": FEW_SHOT},
+            {"role": "user", "content": USER_PROMPT_TEMPLATE.format(passage=passage)}
+        ],
+        model=model,
+        temperature=0.2,
+        max_tokens=800
+    )
+    raw_output = chat_completion.choices[0].message.content
+    json_text = extract_json(raw_output)
+    parsed = json.loads(json_text)
+    return post_process(parsed)
+
+# === Gradio UI ===
+def build_app(client: Groq):
+    def process_text(passage: str):
+        if not passage.strip():
+            return "Please enter a passage.", None
+        try:
+            parsed = generate_precis_and_vocab(client, passage)
+        except Exception as e:
+            return f"Error: {e}", None
+        precis = parsed.get("precis", "")
+        df = pd.DataFrame(parsed.get("difficult_words", []))
+        return precis, df
+
+    with gr.Blocks() as demo:
+        gr.Markdown("# 📝 CSS LexiScan — Précis & Vocabulary Assistant")
+        passage_input = gr.Textbox(lines=10, label="Paste your passage here:")
+        generate_btn = gr.Button("Generate Précis & Vocabulary")
+        precis_output = gr.Textbox(lines=5, label="Generated Précis")
+        vocab_output = gr.Dataframe(headers=["word", "part_of_speech", "meaning", "example"], label="Difficult Words")
+        generate_btn.click(fn=process_text, inputs=passage_input, outputs=[precis_output, vocab_output])
+    return demo
+
+# === Main ===
+if __name__ == "__main__":
+    api_key = get_groq_api_key()
+    client = make_groq_client(api_key)
+    app = build_app(client)
+    app.launch()  # HF Spaces will automatically host this