| |
| |
| |
|
|
| import os |
| import json |
| from typing import Dict |
|
|
| import gradio as gr |
| import pandas as pd |
| from groq import Groq |
|
|
| |
| 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" |
| "}" |
| ) |
|
|
| |
| def get_groq_api_key(secret_name: str = "SCAN") -> 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) |
|
|
| |
| 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 |
|
|
| |
| if __name__ == "__main__": |
| api_key = get_groq_api_key("SCAN") |
| client = make_groq_client(api_key) |
| app = build_app(client) |
| app.launch() |
|
|
