Add Gradio web search application and update README with usage instructions
Browse files- README.md +28 -1
- app.py +104 -0
- requirements.txt +4 -0
README.md
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---
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# Gradio News‑to‑Context Service
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## Prerequisites
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`$ pip install gradio httpx trafilatura python-dateutil`
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## Environment
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`export SERPER_API_KEY="YOUR‑KEY‑HERE"`
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## How it works – design notes
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| Step | Technique | Why it matters |
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|---|---|---|
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| API search | Serper’s Google‑News JSON is fast, cost‑effective and immune to Google’s bot‑blocking. | |
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| Concurrency | `httpx.AsyncClient` + `asyncio.gather` gets 10 articles in < 2 s on typical broadband. | |
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| Extraction | Trafilatura consistently tops accuracy charts for main‑content extraction and needs no browser or heavy ML models. | |
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| Date parsing | `python‑dateutil` converts fuzzy strings (“16 hours ago”) into ISO YYYY‑MM‑DD so the LLM sees absolute dates. | |
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| LLM‑friendly output | Markdown headings and horizontal rules make chunk boundaries explicit; hyperlinks preserved for optional citation. | |
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## Extending in production
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* **Caching** – add `aiocache` or Redis to avoid re‑fetching identical URLs within TTL.
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* **Long‑content trimming** – if each article can exceed your LLM’s context window, pipe `body` through a sentence‑ranker or GPT‑based summariser before concatenation.
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* **Paywalls / PDFs** – guard `extract_main_text` with fallback libraries (e.g. `readability‑lxml` or `pymupdf`) for unusual formats.
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* **Rate‑limiting** – Serper free tier allows 100 req/day; wrap the call with exponential‑backoff on HTTP 429.
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Drop this file into any Python‑3.10+ environment, set `SERPER_API_KEY`, pip install the three libraries, and you have a ready‑to‑embed “query‑» context” micro‑service for your LLM pipeline.
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app.py
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"""
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Web Search - Feed LLMs with fresh sources
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==========================================
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Prerequisites
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-------------
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$ pip install gradio httpx trafilatura python-dateutil
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Environment
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-----------
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export SERPER_API_KEY="YOUR‑KEY‑HERE"
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"""
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import os, json, asyncio, httpx, trafilatura, gradio as gr
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from dateutil import parser as dateparser
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from pathlib import Path
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SERPER_API_KEY = os.getenv("SERPER_API_KEY")
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SERPER_ENDPOINT = "https://google.serper.dev/news"
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HEADERS = {"X-API-KEY": SERPER_API_KEY, "Content-Type": "application/json"}
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### 1 ─ Serper call -------------------------------------------------------------
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async def get_serper_news(query: str, num: int = 10) -> list[dict]:
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payload = {"q": query, "type": "news", "num": num, "page": 1}
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async with httpx.AsyncClient(timeout=15) as client:
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resp = await client.post(SERPER_ENDPOINT, headers=HEADERS, json=payload)
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resp.raise_for_status()
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return resp.json()["news"]
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### 2 ─ Concurrent HTML downloads ----------------------------------------------
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async def fetch_html_many(urls: list[str]) -> list[str]:
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async with httpx.AsyncClient(timeout=20, follow_redirects=True) as client:
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tasks = [client.get(u) for u in urls]
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responses = await asyncio.gather(*tasks, return_exceptions=True)
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html_pages = []
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for r in responses:
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if isinstance(r, Exception):
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html_pages.append("") # keep positions aligned
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else:
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html_pages.append(r.text)
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return html_pages
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### 3 ─ Main‑content extraction -------------------------------------------------
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def extract_main_text(html: str) -> str:
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if not html:
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return ""
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# Trafilatura auto‑detects language, removes boilerplate & returns plain text.
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return (
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trafilatura.extract(html, include_formatting=False, include_comments=False)
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or ""
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)
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### 4 ─ Orchestration -----------------------------------------------------------
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async def build_context(query: str, k: int = 10) -> str:
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news_items = await get_serper_news(query, num=k)
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urls = [n["link"] for n in news_items]
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raw_pages = await fetch_html_many(urls)
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chunks = []
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for meta, html in zip(news_items, raw_pages):
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body = extract_main_text(html)
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if not body:
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continue # skip if extraction failed
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# Normalise Serper’s relative date (“21 hours ago”) to ISO date
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try:
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date_iso = dateparser.parse(meta.get("date", ""), fuzzy=True).strftime(
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"%Y-%m-%d"
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)
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except Exception:
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date_iso = meta.get("date", "")
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chunk = (
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f"## {meta['title']}\n"
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f"**Source:** {meta['source']} "
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f"**Date:** {date_iso}\n"
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f"{meta['link']}\n\n"
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f"{body.strip()}\n"
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)
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chunks.append(chunk)
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return "\n---\n".join(chunks) or "No extractable content found."
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### 5 ─ Gradio user interface ---------------------------------------------------
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async def handler(user_query: str, k: int) -> str:
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if not SERPER_API_KEY:
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return "✖️ SERPER_API_KEY is not set."
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return await build_context(user_query, k)
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with gr.Blocks(title="WebSearch") as demo:
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gr.Markdown("# 🔍 Web Search\n" "Feed LLMs with fresh sources.")
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query = gr.Textbox(label="Query", placeholder='e.g. "apple inc"')
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top_k = gr.Slider(1, 20, value=10, label="How many results?")
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out = gr.Textbox(label="Extracted Context", lines=25)
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run = gr.Button("Fetch")
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run.click(handler, inputs=[query, top_k], outputs=out)
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if __name__ == "__main__":
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# Launch in shareable mode when running on Colab/VMs; edit as you wish.
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demo.launch()
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requirements.txt
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gradio
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httpx
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trafilatura
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python-dateutil
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