chore: import upstream snapshot with attribution
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# Crawl4AI Prospect‑Wizard – step‑by‑step guide
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[](https://colab.research.google.com/drive/10nRCwmfxPjVrRUHyJsYlX7BH5bvPoGpx?usp=sharing)
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A three‑stage demo that goes from **LinkedIn scraping** ➜ **LLM reasoning** ➜ **graph visualisation**.
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**Try it in Google Colab!** Click the badge above to run this demo in a cloud environment with zero setup required.
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```
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prospect‑wizard/
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├─ c4ai_discover.py # Stage 1 – scrape companies + people
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├─ c4ai_insights.py # Stage 2 – embeddings, org‑charts, scores
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├─ graph_view_template.html # Stage 3 – graph viewer (static HTML)
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└─ data/ # output lands here (*.jsonl / *.json)
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```
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---
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## 1 Install & boot a LinkedIn profile (one‑time)
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### 1.1 Install dependencies
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```bash
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pip install crawl4ai litellm sentence-transformers pandas rich
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```
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### 1.2 Create / warm a LinkedIn browser profile
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```bash
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crwl profiles
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```
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1. The interactive shell shows **New profile** – hit **enter**.
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2. Choose a name, e.g. `profile_linkedin_uc`.
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3. A Chromium window opens – log in to LinkedIn, solve whatever CAPTCHA, then close.
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> Remember the **profile name**. All future runs take `--profile-name <your_name>`.
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---
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## 2 Discovery – scrape companies & people
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```bash
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python c4ai_discover.py full \
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--query "health insurance management" \
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--geo 102713980 \ # Malaysia geoUrn
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--title-filters "" \ # or "Product,Engineering"
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--max-companies 10 \ # default set small for workshops
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--max-people 20 \ # \^ same
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--profile-name profile_linkedin_uc \
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--outdir ./data \
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--concurrency 2 \
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--log-level debug
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```
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**Outputs** in `./data/`:
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* `companies.jsonl` – one JSON per company
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* `people.jsonl` – one JSON per employee
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🛠️ **Dry‑run:** `C4AI_DEMO_DEBUG=1 python c4ai_discover.py full --query coffee` uses bundled HTML snippets, no network.
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### Handy geoUrn cheatsheet
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| Location | geoUrn |
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|----------|--------|
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| Singapore | **103644278** |
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| Malaysia | **102713980** |
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| United States | **103644922** |
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| United Kingdom | **102221843** |
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| Australia | **101452733** |
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_See more: <https://www.linkedin.com/search/results/companies/?geoUrn=XXX> – the number after `geoUrn=` is what you need._
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---
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## 3 Insights – embeddings, org‑charts, decision makers
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```bash
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python c4ai_insights.py \
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--in ./data \
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--out ./data \
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--embed-model all-MiniLM-L6-v2 \
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--llm-provider gemini/gemini-2.0-flash \
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--llm-api-key "" \
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--top-k 10 \
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--max-llm-tokens 8024 \
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--llm-temperature 1.0 \
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--workers 4
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```
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Emits next to the Stage‑1 files:
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* `company_graph.json` – inter‑company similarity graph
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* `org_chart_<handle>.json` – one per company
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* `decision_makers.csv` – hand‑picked ‘who to pitch’ list
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Flags reference (straight from `build_arg_parser()`):
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| Flag | Default | Purpose |
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|------|---------|---------|
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| `--in` | `.` | Stage‑1 output dir |
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| `--out` | `.` | Destination dir |
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| `--embed_model` | `all-MiniLM-L6-v2` | Sentence‑Transformer model |
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| `--top_k` | `10` | Neighbours per company in graph |
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| `--openai_model` | `gpt-4.1` | LLM for scoring decision makers |
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| `--max_llm_tokens` | `8024` | Token budget per LLM call |
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| `--llm_temperature` | `1.0` | Creativity knob |
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| `--stub` | off | Skip OpenAI and fabricate tiny charts |
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| `--workers` | `4` | Parallel LLM workers |
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---
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## 4 Visualise – interactive graph
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After Stage 2 completes, simply open the HTML viewer from the project root:
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```bash
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open graph_view_template.html # or Live Server / Python -http
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```
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The page fetches `data/company_graph.json` and the `org_chart_*.json` files automatically; keep the `data/` folder beside the HTML file.
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* Left pane → list of companies (clans).
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* Click a node to load its org‑chart on the right.
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* Chat drawer lets you ask follow‑up questions; context is pulled from `people.jsonl`.
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---
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## 5 Common snags
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| Symptom | Fix |
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|---------|-----|
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| Infinite CAPTCHA | Use a residential proxy: `--proxy http://user:pass@ip:port` |
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| 429 Too Many Requests | Lower `--concurrency`, rotate profile, add delay |
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| Blank graph | Check JSON paths, clear `localStorage` in browser |
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---
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### TL;DR
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`crwl profiles` → `c4ai_discover.py` → `c4ai_insights.py` → open `graph_view_template.html`.
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Live long and `import crawl4ai`.
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@@ -0,0 +1,446 @@
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#!/usr/bin/env python3
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"""
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c4ai-discover — Stage‑1 Discovery CLI
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Scrapes LinkedIn company search + their people pages and dumps two newline‑delimited
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JSON files: companies.jsonl and people.jsonl.
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Key design rules
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----------------
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* No BeautifulSoup — Crawl4AI only for network + HTML fetch.
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* JsonCssExtractionStrategy for structured scraping; schema auto‑generated once
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from sample HTML provided by user and then cached under ./schemas/.
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* Defaults are embedded so the file runs inside VS Code debugger without CLI args.
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* If executed as a console script (argv > 1), CLI flags win.
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* Lightweight deps: argparse + Crawl4AI stack.
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Author: Tom @ Kidocode 2025‑04‑26
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"""
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from __future__ import annotations
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import warnings, re
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warnings.filterwarnings(
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"ignore",
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message=r"The pseudo class ':contains' is deprecated, ':-soup-contains' should be used.*",
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category=FutureWarning,
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module=r"soupsieve"
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)
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# ───────────────────────────────────────────────────────────────────────────────
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# Imports
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# ───────────────────────────────────────────────────────────────────────────────
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import argparse
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import random
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import asyncio
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import json
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import logging
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import os
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import pathlib
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import sys
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# 3rd-party rich for pretty logging
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from rich.console import Console
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from rich.logging import RichHandler
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from datetime import datetime, UTC
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from textwrap import dedent
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from types import SimpleNamespace
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from typing import Dict, List, Optional
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from urllib.parse import quote
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from pathlib import Path
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from glob import glob
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from crawl4ai import (
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AsyncWebCrawler,
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BrowserConfig,
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CacheMode,
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CrawlerRunConfig,
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JsonCssExtractionStrategy,
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BrowserProfiler,
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LLMConfig,
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)
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# ───────────────────────────────────────────────────────────────────────────────
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# Constants / paths
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# ───────────────────────────────────────────────────────────────────────────────
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BASE_DIR = pathlib.Path(__file__).resolve().parent
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SCHEMA_DIR = BASE_DIR / "schemas"
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SCHEMA_DIR.mkdir(parents=True, exist_ok=True)
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COMPANY_SCHEMA_PATH = SCHEMA_DIR / "company_card.json"
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PEOPLE_SCHEMA_PATH = SCHEMA_DIR / "people_card.json"
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# ---------- deterministic target JSON examples ----------
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_COMPANY_SCHEMA_EXAMPLE = {
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"handle": "/company/posify/",
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"profile_image": "https://media.licdn.com/dms/image/v2/.../logo.jpg",
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"name": "Management Research Services, Inc. (MRS, Inc)",
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"descriptor": "Insurance • Milwaukee, Wisconsin",
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"about": "Insurance • Milwaukee, Wisconsin",
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"followers": 1000
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}
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_PEOPLE_SCHEMA_EXAMPLE = {
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"profile_url": "https://www.linkedin.com/in/lily-ng/",
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"name": "Lily Ng",
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"headline": "VP Product @ Posify",
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"followers": 890,
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"connection_degree": "2nd",
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"avatar_url": "https://media.licdn.com/dms/image/v2/.../lily.jpg"
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}
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# Provided sample HTML snippets (trimmed) — used exactly once to cold‑generate schema.
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_SAMPLE_COMPANY_HTML = (Path(__file__).resolve().parent / "snippets/company.html").read_text()
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_SAMPLE_PEOPLE_HTML = (Path(__file__).resolve().parent / "snippets/people.html").read_text()
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# --------- tighter schema prompts ----------
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_COMPANY_SCHEMA_QUERY = dedent(
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"""
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Using the supplied <li> company-card HTML, build a JsonCssExtractionStrategy schema that,
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for every card, outputs *exactly* the keys shown in the example JSON below.
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JSON spec:
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• handle – href of the outermost <a> that wraps the logo/title, e.g. "/company/posify/"
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• profile_image – absolute URL of the <img> inside that link
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• name – text of the <a> inside the <span class*='t-16'>
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• descriptor – text line with industry • location
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• about – text of the <div class*='t-normal'> below the name (industry + geo)
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• followers – integer parsed from the <div> containing 'followers'
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IMPORTANT: Do not use the base64 kind of classes to target element. It's not reliable.
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The main div parent contains these li element is "div.search-results-container" you can use this.
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The <ul> parent has "role" equal to "list". Using these two should be enough to target the <li> elements.
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IMPORTANT: Remember there might be multiple <a> tags that start with https://www.linkedin.com/company/[NAME],
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so in case you refer to them for different fields, make sure to be more specific. One has the image, and one
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has the person's name.
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IMPORTANT: Be very smart in selecting the correct and unique way to address the element. You should ensure
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your selector points to a single element and is unique to the place that contains the information.
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"""
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)
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_PEOPLE_SCHEMA_QUERY = dedent(
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"""
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Using the supplied <li> people-card HTML, build a JsonCssExtractionStrategy schema that
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outputs exactly the keys in the example JSON below.
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Fields:
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• profile_url – href of the outermost profile link
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• name – text inside artdeco-entity-lockup__title
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• headline – inner text of artdeco-entity-lockup__subtitle
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• followers – integer parsed from the span inside lt-line-clamp--multi-line
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• connection_degree – '1st', '2nd', etc. from artdeco-entity-lockup__badge
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• avatar_url – src of the <img> within artdeco-entity-lockup__image
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IMPORTANT: Do not use the base64 kind of classes to target element. It's not reliable.
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The main div parent contains these li element is a "div" has these classes "artdeco-card org-people-profile-card__card-spacing org-people__card-margin-bottom".
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"""
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)
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# ---------------------------------------------------------------------------
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# Utility helpers
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# ---------------------------------------------------------------------------
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def _load_or_build_schema(
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path: pathlib.Path,
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sample_html: str,
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query: str,
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example_json: Dict,
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force = False
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) -> Dict:
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"""Load schema from path, else call generate_schema once and persist."""
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if path.exists() and not force:
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return json.loads(path.read_text())
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logging.info("[SCHEMA] Generating schema %s", path.name)
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schema = JsonCssExtractionStrategy.generate_schema(
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html=sample_html,
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llm_config=LLMConfig(
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provider=os.getenv("C4AI_SCHEMA_PROVIDER", "openai/gpt-4o"),
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api_token=os.getenv("OPENAI_API_KEY", "env:OPENAI_API_KEY"),
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),
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query=query,
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target_json_example=json.dumps(example_json, indent=2),
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)
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path.write_text(json.dumps(schema, indent=2))
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return schema
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def _openai_friendly_number(text: str) -> Optional[int]:
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"""Extract first int from text like '1K followers' (returns 1000)."""
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import re
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m = re.search(r"(\d[\d,]*)", text.replace(",", ""))
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if not m:
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return None
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val = int(m.group(1))
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if "k" in text.lower():
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val *= 1000
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if "m" in text.lower():
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val *= 1_000_000
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return val
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# ---------------------------------------------------------------------------
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# Core async workers
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# ---------------------------------------------------------------------------
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async def crawl_company_search(crawler: AsyncWebCrawler, url: str, schema: Dict, limit: int) -> List[Dict]:
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"""Paginate 10-item company search pages until `limit` reached."""
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extraction = JsonCssExtractionStrategy(schema)
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cfg = CrawlerRunConfig(
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extraction_strategy=extraction,
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cache_mode=CacheMode.BYPASS,
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wait_for = ".search-marvel-srp",
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session_id="company_search",
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delay_before_return_html=1,
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magic = True,
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verbose= False,
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)
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companies, page = [], 1
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while len(companies) < max(limit, 10):
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paged_url = f"{url}&page={page}"
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res = await crawler.arun(paged_url, config=cfg)
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batch = json.loads(res[0].extracted_content)
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if not batch:
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break
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for item in batch:
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name = item.get("name", "").strip()
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handle = item.get("handle", "").strip()
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if not handle or not name:
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continue
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descriptor = item.get("descriptor")
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about = item.get("about")
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followers = _openai_friendly_number(str(item.get("followers", "")))
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companies.append(
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{
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"handle": handle,
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"name": name,
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"descriptor": descriptor,
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"about": about,
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"followers": followers,
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"people_url": f"{handle}people/",
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"captured_at": datetime.now(UTC).isoformat(timespec="seconds") + "Z",
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}
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)
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page += 1
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logging.info(
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f"[dim]Page {page}[/] — running total: {len(companies)}/{limit} companies"
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)
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return companies[:max(limit, 10)]
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async def crawl_people_page(
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crawler: AsyncWebCrawler,
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people_url: str,
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schema: Dict,
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limit: int,
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title_kw: str,
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) -> List[Dict]:
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people_u = f"{people_url}?keywords={quote(title_kw)}"
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extraction = JsonCssExtractionStrategy(schema)
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cfg = CrawlerRunConfig(
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extraction_strategy=extraction,
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# scan_full_page=True,
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cache_mode=CacheMode.BYPASS,
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magic=True,
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wait_for=".org-people-profile-card__card-spacing",
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wait_for_images=5000,
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delay_before_return_html=1,
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session_id="people_search",
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)
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res = await crawler.arun(people_u, config=cfg)
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if not res[0].success:
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return []
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raw = json.loads(res[0].extracted_content)
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people = []
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for p in raw[:limit]:
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followers = _openai_friendly_number(str(p.get("followers", "")))
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people.append(
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{
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"profile_url": p.get("profile_url"),
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"name": p.get("name"),
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"headline": p.get("headline"),
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"followers": followers,
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"connection_degree": p.get("connection_degree"),
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"avatar_url": p.get("avatar_url"),
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}
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)
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return people
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# ---------------------------------------------------------------------------
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# CLI + main
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# ---------------------------------------------------------------------------
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def build_arg_parser() -> argparse.ArgumentParser:
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ap = argparse.ArgumentParser("c4ai-discover — Crawl4AI LinkedIn discovery")
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sub = ap.add_subparsers(dest="cmd", required=False, help="run scope")
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def add_flags(parser: argparse.ArgumentParser):
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parser.add_argument("--query", required=False, help="query keyword(s)")
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parser.add_argument("--geo", required=False, type=int, help="LinkedIn geoUrn")
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parser.add_argument("--title-filters", default="Product,Engineering", help="comma list of job keywords")
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parser.add_argument("--max-companies", type=int, default=1000)
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parser.add_argument("--max-people", type=int, default=500)
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parser.add_argument("--profile-name", default=str(pathlib.Path.home() / ".crawl4ai/profiles/profile_linkedin_uc"))
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parser.add_argument("--outdir", default="./output")
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parser.add_argument("--concurrency", type=int, default=4)
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parser.add_argument("--log-level", default="info", choices=["debug", "info", "warn", "error"])
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||||
add_flags(sub.add_parser("full"))
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add_flags(sub.add_parser("companies"))
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add_flags(sub.add_parser("people"))
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||||
# global flags
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||||
ap.add_argument(
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"--debug",
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action="store_true",
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||||
help="Use built-in demo defaults (same as C4AI_DEMO_DEBUG=1)",
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||||
)
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||||
return ap
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||||
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||||
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||||
def detect_debug_defaults(force = False) -> SimpleNamespace:
|
||||
if not force and sys.gettrace() is None and not os.getenv("C4AI_DEMO_DEBUG"):
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||||
return SimpleNamespace()
|
||||
# ----- debug‑friendly defaults -----
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||||
return SimpleNamespace(
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cmd="full",
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||||
query="health insurance management",
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||||
geo=102713980,
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||||
# title_filters="Product,Engineering",
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||||
title_filters="",
|
||||
max_companies=10,
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||||
max_people=5,
|
||||
profile_name="profile_linkedin_uc",
|
||||
outdir="./debug_out",
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||||
concurrency=2,
|
||||
log_level="debug",
|
||||
)
|
||||
|
||||
|
||||
async def async_main(opts):
|
||||
# ─────────── logging setup ───────────
|
||||
console = Console()
|
||||
logging.basicConfig(
|
||||
level=opts.log_level.upper(),
|
||||
format="%(message)s",
|
||||
handlers=[RichHandler(console=console, markup=True, rich_tracebacks=True)],
|
||||
)
|
||||
|
||||
# -------------------------------------------------------------------
|
||||
# Load or build schemas (one‑time LLM call each)
|
||||
# -------------------------------------------------------------------
|
||||
company_schema = _load_or_build_schema(
|
||||
COMPANY_SCHEMA_PATH,
|
||||
_SAMPLE_COMPANY_HTML,
|
||||
_COMPANY_SCHEMA_QUERY,
|
||||
_COMPANY_SCHEMA_EXAMPLE,
|
||||
# True
|
||||
)
|
||||
people_schema = _load_or_build_schema(
|
||||
PEOPLE_SCHEMA_PATH,
|
||||
_SAMPLE_PEOPLE_HTML,
|
||||
_PEOPLE_SCHEMA_QUERY,
|
||||
_PEOPLE_SCHEMA_EXAMPLE,
|
||||
# True
|
||||
)
|
||||
|
||||
outdir = BASE_DIR / pathlib.Path(opts.outdir)
|
||||
outdir.mkdir(parents=True, exist_ok=True)
|
||||
f_companies = (BASE_DIR / outdir / "companies.jsonl").open("a", encoding="utf-8")
|
||||
f_people = (BASE_DIR / outdir / "people.jsonl").open("a", encoding="utf-8")
|
||||
|
||||
# -------------------------------------------------------------------
|
||||
# Prepare crawler with cookie pool rotation
|
||||
# -------------------------------------------------------------------
|
||||
profiler = BrowserProfiler()
|
||||
path = profiler.get_profile_path(opts.profile_name)
|
||||
bc = BrowserConfig(
|
||||
headless=False,
|
||||
verbose=False,
|
||||
user_data_dir=path,
|
||||
use_managed_browser=True,
|
||||
user_agent_mode = "random",
|
||||
user_agent_generator_config= {
|
||||
"platforms": "mobile",
|
||||
"os": "Android"
|
||||
}
|
||||
)
|
||||
crawler = AsyncWebCrawler(config=bc)
|
||||
|
||||
await crawler.start()
|
||||
|
||||
# Single worker for simplicity; concurrency can be scaled by arun_many if needed.
|
||||
# crawler = await next_crawler().start()
|
||||
try:
|
||||
# Build LinkedIn search URL
|
||||
search_url = f'https://www.linkedin.com/search/results/companies/?keywords={quote(opts.query)}&companyHqGeo="{opts.geo}"'
|
||||
logging.info("Seed URL => %s", search_url)
|
||||
|
||||
companies: List[Dict] = []
|
||||
if opts.cmd in ("companies", "full"):
|
||||
companies = await crawl_company_search(
|
||||
crawler, search_url, company_schema, opts.max_companies
|
||||
)
|
||||
for c in companies:
|
||||
f_companies.write(json.dumps(c, ensure_ascii=False) + "\n")
|
||||
logging.info(f"[bold green]✓[/] Companies scraped so far: {len(companies)}")
|
||||
|
||||
if opts.cmd in ("people", "full"):
|
||||
if not companies:
|
||||
# load from previous run
|
||||
src = outdir / "companies.jsonl"
|
||||
if not src.exists():
|
||||
logging.error("companies.jsonl missing — run companies/full first")
|
||||
return 10
|
||||
companies = [json.loads(l) for l in src.read_text().splitlines()]
|
||||
total_people = 0
|
||||
title_kw = " ".join([t.strip() for t in opts.title_filters.split(",") if t.strip()]) if opts.title_filters else ""
|
||||
for comp in companies:
|
||||
people = await crawl_people_page(
|
||||
crawler,
|
||||
comp["people_url"],
|
||||
people_schema,
|
||||
opts.max_people,
|
||||
title_kw,
|
||||
)
|
||||
for p in people:
|
||||
rec = p | {
|
||||
"company_handle": comp["handle"],
|
||||
# "captured_at": datetime.now(UTC).isoformat(timespec="seconds") + "Z",
|
||||
"captured_at": datetime.now(UTC).isoformat(timespec="seconds") + "Z",
|
||||
}
|
||||
f_people.write(json.dumps(rec, ensure_ascii=False) + "\n")
|
||||
total_people += len(people)
|
||||
logging.info(
|
||||
f"{comp['name']} — [cyan]{len(people)}[/] people extracted"
|
||||
)
|
||||
await asyncio.sleep(random.uniform(0.5, 1))
|
||||
logging.info("Total people scraped: %d", total_people)
|
||||
finally:
|
||||
await crawler.close()
|
||||
f_companies.close()
|
||||
f_people.close()
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def main():
|
||||
parser = build_arg_parser()
|
||||
cli_opts = parser.parse_args()
|
||||
|
||||
# decide on debug defaults
|
||||
if cli_opts.debug:
|
||||
opts = detect_debug_defaults(force=True)
|
||||
cli_opts = opts
|
||||
else:
|
||||
env_defaults = detect_debug_defaults()
|
||||
opts = env_defaults if env_defaults else cli_opts
|
||||
|
||||
if not getattr(opts, "cmd", None):
|
||||
opts.cmd = "full"
|
||||
|
||||
exit_code = asyncio.run(async_main(cli_opts))
|
||||
sys.exit(exit_code)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,381 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Stage-2 Insights builder
|
||||
------------------------
|
||||
Reads companies.jsonl & people.jsonl (Stage-1 output) and produces:
|
||||
• company_graph.json
|
||||
• org_chart_<handle>.json (one per company)
|
||||
• decision_makers.csv
|
||||
• graph_view.html (interactive visualisation)
|
||||
|
||||
Run:
|
||||
python c4ai_insights.py --in ./stage1_out --out ./stage2_out
|
||||
|
||||
Author : Tom @ Kidocode, 2025-04-28
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Imports & Third-party
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
import argparse, asyncio, json, pathlib, random
|
||||
from datetime import datetime, UTC
|
||||
from types import SimpleNamespace
|
||||
from pathlib import Path
|
||||
from typing import List, Dict, Any
|
||||
# Pretty CLI UX
|
||||
from rich.console import Console
|
||||
from rich.logging import RichHandler
|
||||
from rich.progress import Progress, SpinnerColumn, BarColumn, TextColumn, TimeElapsedColumn
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
BASE_DIR = pathlib.Path(__file__).resolve().parent
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# 3rd-party deps
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
import numpy as np
|
||||
# from sentence_transformers import SentenceTransformer
|
||||
# from sklearn.metrics.pairwise import cosine_similarity
|
||||
import pandas as pd
|
||||
import hashlib
|
||||
|
||||
from litellm import completion #Support any LLM Provider
|
||||
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Utils
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def load_jsonl(path: Path) -> List[Dict[str, Any]]:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return [json.loads(l) for l in f]
|
||||
|
||||
def dump_json(obj, path: Path):
|
||||
with open(path, "w", encoding="utf-8") as f:
|
||||
json.dump(obj, f, ensure_ascii=False, indent=2)
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Constants
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
BASE_DIR = pathlib.Path(__file__).resolve().parent
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Debug defaults (mirrors Stage-1 trick)
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def dev_defaults() -> SimpleNamespace:
|
||||
return SimpleNamespace(
|
||||
in_dir="./samples",
|
||||
out_dir="./samples/insights",
|
||||
embed_model="all-MiniLM-L6-v2",
|
||||
top_k=10,
|
||||
llm_provider="openai/gpt-4.1",
|
||||
llm_api_key=None,
|
||||
max_llm_tokens=8000,
|
||||
llm_temperature=1.0,
|
||||
stub=False, # Set to True to use a stub for org-chart inference
|
||||
llm_base_url=None, # e.g., "https://api.openai.com/v1" for OpenAI
|
||||
workers=4
|
||||
)
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Graph builders
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def embed_descriptions(companies, model_name:str, opts) -> np.ndarray:
|
||||
from sentence_transformers import SentenceTransformer
|
||||
|
||||
console = Console()
|
||||
console.print(f"Using embedding model: [bold cyan]{model_name}[/]")
|
||||
cache_path = BASE_DIR / Path(opts.out_dir) / "embeds_cache.json"
|
||||
cache = {}
|
||||
if cache_path.exists():
|
||||
with open(cache_path) as f:
|
||||
cache = json.load(f)
|
||||
# flush cache if model differs
|
||||
if cache.get("_model") != model_name:
|
||||
cache = {}
|
||||
|
||||
model = SentenceTransformer(model_name)
|
||||
new_texts, new_indices = [], []
|
||||
vectors = np.zeros((len(companies), 384), dtype=np.float32)
|
||||
|
||||
for idx, comp in enumerate(companies):
|
||||
text = comp.get("about") or comp.get("descriptor","")
|
||||
h = hashlib.sha1(text.encode("utf-8")).hexdigest()
|
||||
cached = cache.get(comp["handle"])
|
||||
if cached and cached["hash"] == h:
|
||||
vectors[idx] = np.array(cached["vector"], dtype=np.float32)
|
||||
else:
|
||||
new_texts.append(text)
|
||||
new_indices.append((idx, comp["handle"], h))
|
||||
|
||||
if new_texts:
|
||||
embeds = model.encode(new_texts, show_progress_bar=False, convert_to_numpy=True)
|
||||
for vec, (idx, handle, h) in zip(embeds, new_indices):
|
||||
vectors[idx] = vec
|
||||
cache[handle] = {"hash": h, "vector": vec.tolist()}
|
||||
cache["_model"] = model_name
|
||||
with open(cache_path, "w") as f:
|
||||
json.dump(cache, f)
|
||||
|
||||
return vectors
|
||||
|
||||
def build_company_graph(companies, embeds:np.ndarray, top_k:int) -> Dict[str,Any]:
|
||||
from sklearn.metrics.pairwise import cosine_similarity
|
||||
sims = cosine_similarity(embeds)
|
||||
nodes, edges = [], []
|
||||
for i,c in enumerate(companies):
|
||||
node = dict(
|
||||
id=c["handle"].strip("/"),
|
||||
name=c["name"],
|
||||
handle=c["handle"],
|
||||
about=c.get("about",""),
|
||||
people_url=c.get("people_url",""),
|
||||
industry=c.get("descriptor","").split("•")[0].strip(),
|
||||
geoUrn=c.get("geoUrn"),
|
||||
followers=c.get("followers",0),
|
||||
# desc_embed=embeds[i].tolist(),
|
||||
desc_embed=[],
|
||||
)
|
||||
nodes.append(node)
|
||||
# pick top-k most similar except itself
|
||||
top_idx = np.argsort(sims[i])[::-1][1:top_k+1]
|
||||
for j in top_idx:
|
||||
tgt = companies[j]
|
||||
weight = float(sims[i,j])
|
||||
if node["industry"] == tgt.get("descriptor","").split("•")[0].strip():
|
||||
weight += 0.10
|
||||
if node["geoUrn"] == tgt.get("geoUrn"):
|
||||
weight += 0.05
|
||||
tgt['followers'] = tgt.get("followers", None) or 1
|
||||
node["followers"] = node.get("followers", None) or 1
|
||||
follower_ratio = min(node["followers"], tgt.get("followers",1)) / max(node["followers"] or 1, tgt.get("followers",1))
|
||||
weight += 0.05 * follower_ratio
|
||||
edges.append(dict(
|
||||
source=node["id"],
|
||||
target=tgt["handle"].strip("/"),
|
||||
weight=round(weight,4),
|
||||
drivers=dict(
|
||||
embed_sim=round(float(sims[i,j]),4),
|
||||
industry_match=0.10 if node["industry"] == tgt.get("descriptor","").split("•")[0].strip() else 0,
|
||||
geo_overlap=0.05 if node["geoUrn"] == tgt.get("geoUrn") else 0,
|
||||
)
|
||||
))
|
||||
# return {"nodes":nodes,"edges":edges,"meta":{"generated_at":datetime.now(UTC).isoformat()}}
|
||||
return {"nodes":nodes,"edges":edges,"meta":{"generated_at":datetime.now(UTC).isoformat()}}
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Org-chart via LLM
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
async def infer_org_chart_llm(company, people, llm_provider:str, api_key:str, max_tokens:int, temperature:float, stub:bool=False, base_url:str=None):
|
||||
if stub:
|
||||
# Tiny fake org-chart when debugging offline
|
||||
chief = random.choice(people)
|
||||
nodes = [{
|
||||
"id": chief["profile_url"],
|
||||
"name": chief["name"],
|
||||
"title": chief["headline"],
|
||||
"dept": chief["headline"].split()[:1][0],
|
||||
"yoe_total": 8,
|
||||
"yoe_current": 2,
|
||||
"seniority_score": 0.8,
|
||||
"decision_score": 0.9,
|
||||
"avatar_url": chief.get("avatar_url")
|
||||
}]
|
||||
return {"nodes":nodes,"edges":[],"meta":{"debug_stub":True,"generated_at":datetime.now(UTC).isoformat()}}
|
||||
|
||||
prompt = [
|
||||
{"role":"system","content":"You are an expert B2B org-chart reasoner."},
|
||||
{"role":"user","content":f"""Here is the company description:
|
||||
|
||||
<company>
|
||||
{json.dumps(company, ensure_ascii=False)}
|
||||
</company>
|
||||
|
||||
Here is a JSON list of employees:
|
||||
<employees>
|
||||
{json.dumps(people, ensure_ascii=False)}
|
||||
</employees>
|
||||
|
||||
1) Build a reporting tree (manager -> direct reports)
|
||||
2) For each person output a decision_score 0-1 for buying new software
|
||||
|
||||
Return JSON: {{ "nodes":[{{id,name,title,dept,yoe_total,yoe_current,seniority_score,decision_score,avatar_url,profile_url}}], "edges":[{{source,target,type,confidence}}] }}
|
||||
"""}
|
||||
]
|
||||
resp = completion(
|
||||
model=llm_provider,
|
||||
messages=prompt,
|
||||
max_tokens=max_tokens,
|
||||
temperature=temperature,
|
||||
response_format={"type":"json_object"},
|
||||
api_key=api_key,
|
||||
base_url=base_url
|
||||
)
|
||||
chart = json.loads(resp.choices[0].message.content)
|
||||
chart["meta"] = dict(
|
||||
model=llm_provider,
|
||||
generated_at=datetime.now(UTC).isoformat()
|
||||
)
|
||||
return chart
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# CSV flatten
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def export_decision_makers(charts_dir:Path, csv_path:Path, threshold:float=0.5):
|
||||
rows=[]
|
||||
for p in charts_dir.glob("org_chart_*.json"):
|
||||
data=json.loads(p.read_text())
|
||||
comp = p.stem.split("org_chart_")[1]
|
||||
for n in data.get("nodes",[]):
|
||||
if n.get("decision_score",0)>=threshold:
|
||||
rows.append(dict(
|
||||
company=comp,
|
||||
person=n["name"],
|
||||
title=n["title"],
|
||||
decision_score=n["decision_score"],
|
||||
profile_url=n["id"]
|
||||
))
|
||||
pd.DataFrame(rows).to_csv(csv_path,index=False)
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# HTML rendering
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def render_html(out:Path, template_dir:Path):
|
||||
# From template folder cp graph_view.html and ai.js in out folder
|
||||
import shutil
|
||||
shutil.copy(template_dir/"graph_view_template.html", out / "graph_view.html")
|
||||
shutil.copy(template_dir/"ai.js", out)
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Main async pipeline
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
async def run(opts):
|
||||
# ── silence SDK noise ──────────────────────────────────────────────────────
|
||||
# for noisy in ("openai", "httpx", "httpcore"):
|
||||
# lg = logging.getLogger(noisy)
|
||||
# lg.setLevel(logging.WARNING) # or ERROR if you want total silence
|
||||
# lg.propagate = False # optional: stop them reaching root
|
||||
|
||||
# ────────────── logging bootstrap ──────────────
|
||||
console = Console()
|
||||
# logging.basicConfig(
|
||||
# level="INFO",
|
||||
# format="%(message)s",
|
||||
# handlers=[RichHandler(console=console, markup=True, rich_tracebacks=True)],
|
||||
# )
|
||||
|
||||
in_dir = BASE_DIR / Path(opts.in_dir)
|
||||
out_dir = BASE_DIR / Path(opts.out_dir)
|
||||
out_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
companies = load_jsonl(in_dir/"companies.jsonl")
|
||||
people = load_jsonl(in_dir/"people.jsonl")
|
||||
|
||||
console.print(f"[bold cyan]Loaded[/] {len(companies)} companies, {len(people)} people")
|
||||
|
||||
console.print("[bold]⇢[/] Embedding company descriptions…")
|
||||
embeds = embed_descriptions(companies, opts.embed_model, opts)
|
||||
|
||||
console.print("[bold]⇢[/] Building similarity graph")
|
||||
company_graph = build_company_graph(companies, embeds, opts.top_k)
|
||||
dump_json(company_graph, out_dir/"company_graph.json")
|
||||
|
||||
# Filter companies that need processing
|
||||
to_process = []
|
||||
for comp in companies:
|
||||
handle = comp["handle"].strip("/").replace("/","_")
|
||||
out_file = out_dir/f"org_chart_{handle}.json"
|
||||
if out_file.exists():
|
||||
console.print(f"[green]✓[/] Skipping existing {comp['name']}")
|
||||
continue
|
||||
to_process.append(comp)
|
||||
|
||||
|
||||
if not to_process:
|
||||
console.print("[yellow]All companies already processed[/]")
|
||||
else:
|
||||
workers = getattr(opts, 'workers', 1)
|
||||
parallel = workers > 1
|
||||
|
||||
console.print(f"[bold]⇢[/] Inferring org-charts via LLM {f'(parallel={workers} workers)' if parallel else ''}")
|
||||
|
||||
with Progress(
|
||||
SpinnerColumn(),
|
||||
BarColumn(),
|
||||
TextColumn("[progress.description]{task.description}"),
|
||||
TimeElapsedColumn(),
|
||||
console=console,
|
||||
) as progress:
|
||||
task = progress.add_task("Org charts", total=len(to_process))
|
||||
|
||||
async def process_one(comp):
|
||||
handle = comp["handle"].strip("/").replace("/","_")
|
||||
persons = [p for p in people if p["company_handle"].strip("/") == comp["handle"].strip("/")]
|
||||
chart = await infer_org_chart_llm(
|
||||
comp, persons,
|
||||
llm_provider=opts.llm_provider,
|
||||
api_key=opts.llm_api_key or None,
|
||||
max_tokens=opts.max_llm_tokens,
|
||||
temperature=opts.llm_temperature,
|
||||
stub=opts.stub or False,
|
||||
base_url=opts.llm_base_url or None
|
||||
)
|
||||
chart["meta"]["company"] = comp["name"]
|
||||
|
||||
# Save the result immediately
|
||||
dump_json(chart, out_dir/f"org_chart_{handle}.json")
|
||||
|
||||
progress.update(task, advance=1, description=f"{comp['name']} ({len(persons)} ppl)")
|
||||
|
||||
# Create tasks for all companies
|
||||
tasks = [process_one(comp) for comp in to_process]
|
||||
|
||||
# Process in batches based on worker count
|
||||
semaphore = asyncio.Semaphore(workers)
|
||||
|
||||
async def bounded_process(coro):
|
||||
async with semaphore:
|
||||
return await coro
|
||||
|
||||
# Run with concurrency control
|
||||
await asyncio.gather(*(bounded_process(task) for task in tasks))
|
||||
|
||||
console.print("[bold]⇢[/] Flattening decision-makers CSV")
|
||||
export_decision_makers(out_dir, out_dir/"decision_makers.csv")
|
||||
|
||||
render_html(out_dir, template_dir=BASE_DIR/"templates")
|
||||
console.print(f"[bold green]✓[/] Stage-2 artefacts written to {out_dir}")
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# CLI
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def build_arg_parser():
|
||||
p = argparse.ArgumentParser(description="Build graphs & visualisation from Stage-1 output")
|
||||
p.add_argument("--in", dest="in_dir", required=False, help="Stage-1 output dir", default=".")
|
||||
p.add_argument("--out", dest="out_dir", required=False, help="Destination dir", default=".")
|
||||
p.add_argument("--embed-model", default="all-MiniLM-L6-v2")
|
||||
p.add_argument("--top-k", type=int, default=10, help="Top-k neighbours per company")
|
||||
p.add_argument("--llm-provider", default="openai/gpt-4.1",
|
||||
help="LLM model to use in format 'provider/model_name' (e.g., 'anthropic/claude-3')")
|
||||
p.add_argument("--llm-api-key", help="API key for LLM provider (defaults to env vars)")
|
||||
p.add_argument("--llm-base-url", help="Base URL for LLM API endpoint")
|
||||
p.add_argument("--max-llm-tokens", type=int, default=8024)
|
||||
p.add_argument("--llm-temperature", type=float, default=1.0)
|
||||
p.add_argument("--stub", action="store_true", help="Skip OpenAI call and generate tiny fake org charts")
|
||||
p.add_argument("--workers", type=int, default=4, help="Number of parallel workers for LLM inference")
|
||||
return p
|
||||
|
||||
def main():
|
||||
dbg = dev_defaults()
|
||||
opts = dbg if True else build_arg_parser().parse_args()
|
||||
# opts = build_arg_parser().parse_args()
|
||||
asyncio.run(run(opts))
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,9 @@
|
||||
{"handle": "https://www.linkedin.com/company/healthpartnersng/", "name": "Health Partners HMO", "descriptor": "Hospitals and Health Care • Ikoyi, LAGOS", "about": "Healthpartners Ltd is a leading HMO in Nigeria providing affordablehealthinsuranceandhealthmanagementservices for companies and individuals in Nigeria. We have several individual and group plans that meets yourhealthmanagementneeds. Call us now at 0807-460-9165, 0807-714-0759 or email...", "followers": null, "people_url": "https://www.linkedin.com/company/healthpartnersng/people/", "captured_at": "2025-04-29T10:46:08Z"}
|
||||
{"handle": "https://www.linkedin.com/company/health-insurance-management-services-organization/", "name": "Health & Insurance Management Services Organization", "descriptor": "Non-profit Organizations • Mbeya", "about": "Health&InsuranceManagementServices Organization (HIMSO) was established and registered in 2012 as a Non- Government Organization (NGO) with the aim...", "followers": 35, "people_url": "https://www.linkedin.com/company/health-insurance-management-services-organization/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
{"handle": "https://www.linkedin.com/company/national-health-insurance-management-authority/", "name": "National Health Insurance Management Authority", "descriptor": "Insurance • Lusaka, Lusaka", "about": "The NationalHealthInsuranceManagementAuthority (NHIMA) is established pursuant to section 4 of the NationalHealthInsurance(NHI) Act No. 2 of 2018. The compulsory NationalHealthInsurancescheme seeks to provide for a sound and reliable healthcare financing for Zambian households and the entirehealthsector...", "followers": null, "people_url": "https://www.linkedin.com/company/national-health-insurance-management-authority/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
{"handle": "https://www.linkedin.com/company/health-alliance-plan/", "name": "Health Alliance Plan", "descriptor": "Hospitals and Health Care • Detroit, MI", "about": "...organizations to enhance the lives of those we touch. We offer six distincthealthinsurancelines: • Group Insured Commercial • Individual • Medicare • Medicaid • Self-Funded • Network Leasing HAP also provides: • Award-winning wellness programs • Community outreach • Digitalhealthtools • Diseasemanagement...", "followers": null, "people_url": "https://www.linkedin.com/company/health-alliance-plan/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
{"handle": "https://www.linkedin.com/company/insurance-recruiting-solutions/", "name": "Insurance Recruiting Solutions", "descriptor": "Insurance • Waukee, Iowa", "about": "InsuranceRecruiting Solutions provides staffing and recruiting services exclusively to theinsuranceindustry. We are committed to providing highly personalized recruiting services, tailored to each candidate and employer. With years ofinsuranceindustry experience, we speak your language. As a leading national...", "followers": null, "people_url": "https://www.linkedin.com/company/insurance-recruiting-solutions/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
{"handle": "https://www.linkedin.com/company/healthplanofsanmateo/", "name": "Health Plan of San Mateo (HPSM)", "descriptor": "Hospitals and Health Care • South San Francisco, California", "about": "TheHealthPlan of San Mateo (HPSM) is a local non-profithealthcare plan that offershealthcoverage and a provider network to San Mateo County's under-insured population. We currently serve more than 145,000 County residents.", "followers": null, "people_url": "https://www.linkedin.com/company/healthplanofsanmateo/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
{"handle": "https://www.linkedin.com/company/insurance-management-group_2/", "name": "Insurance Management Group", "descriptor": "Insurance • Marion, Indiana", "about": "InsuranceManagementGroup is an all-riskinsuranceagency with over 140 years of experience, specializing in Home, Auto, BusinessInsurance, Individual Life &Health, and Employee Benefits. We represent highly rated and financially soundinsurancecarriers, to ensure that our clients are getting the best coverage...", "followers": null, "people_url": "https://www.linkedin.com/company/insurance-management-group_2/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
{"handle": "https://www.linkedin.com/company/carecard-health-insurance-management-co/", "name": "CareCard Health Insurance Management Co", "descriptor": "Insurance • Damascus", "about": "CareCard offers Business Process Outsourcing (BPO) services toInsurance, Self Funded and Retireehealthplan market. CareCard provides operational outsourcing...", "followers": 187, "people_url": "https://www.linkedin.com/company/carecard-health-insurance-management-co/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
{"handle": "https://www.linkedin.com/company/healthcluster/", "name": "Health Cluster", "descriptor": "Technology, Information and Internet • Dubai", "about": "..., knowledge and interaction. The company has solutions and products inHealthTech, eHealth, DigitalHealth, Revenue CycleManagement– RCM Solutions, AI & ML, Internet...", "followers": null, "people_url": "https://www.linkedin.com/company/healthcluster/people/", "captured_at": "2025-04-29T13:15:04Z"}
|
||||
@@ -0,0 +1,108 @@
|
||||
{"profile_url": null, "name": "Yahya Ipuge", "headline": "Senior Health Specialist, Independent Consultant, Certified Board Director, Board Chair in NGO and Private Entities", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/C4E03AQFuqPObSyLPMQ/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1517757008397?e=1751500800&v=beta&t=zaHc2CY7AJ-eX1MCSvazp8ny37iBAu3YsyaZjwq6gB0", "company_handle": "https://www.linkedin.com/company/health-insurance-management-services-organization/", "captured_at": "2025-04-29T13:15:33Z"}
|
||||
{"profile_url": null, "name": "LinkedIn Member", "headline": "Field officer at Health and Insurance Management Services Organization", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/C5103AQEVmdDwTIhsjQ/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1540989154156?e=1751500800&v=beta&t=7N0baJNfZ26dbrNNbv2055sbGlacQUwQu07wUTN0whs", "company_handle": "https://www.linkedin.com/company/health-insurance-management-services-organization/", "captured_at": "2025-04-29T13:15:33Z"}
|
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Medical Practitioner @ Health & Insurance | Master's Degree in Infection Control", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/D4D03AQHjMXy7dSmmLg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1725975429410?e=1751500800&v=beta&t=lDIL2KhDw471XYvtCrRfkHAnG3Q-npDJnwDdK0sYvpA", "company_handle": "https://www.linkedin.com/company/health-insurance-management-services-organization/", "captured_at": "2025-04-29T13:15:34Z"}
|
||||
{"profile_url": null, "name": "LinkedIn Member", "headline": "--", "followers": null, "connection_degree": null, "avatar_url": "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7", "company_handle": "https://www.linkedin.com/company/health-insurance-management-services-organization/", "captured_at": "2025-04-29T13:15:38Z"}
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{"profile_url": null, "name": "Fadhy Mtanga", "headline": "Executive Director at Health & Insurance Management Services Organization (HIMSO) Author | Creative Writer | Social Scientist", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D4E03AQEloEreyg3qVQ/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1704391866585?e=1751500800&v=beta&t=86am-v3cjBPBldLTwgt8-AY-YbxFY6QZQzObwLTtMEA", "company_handle": "https://www.linkedin.com/company/health-insurance-management-services-organization/", "captured_at": "2025-04-29T13:15:38Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Business Administrator at Consultancy Business investments", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/D4D03AQEuKXJmknr2YA/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1714545221728?e=1751500800&v=beta&t=zJG-rDZgYJJ0eROibf-Wag-v_JecCghwU3ul4TaH2Eg", "company_handle": "https://www.linkedin.com/company/national-health-insurance-management-authority/", "captured_at": "2025-04-29T13:15:48Z"}
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{"profile_url": null, "name": "Tamani Phiri", "headline": "Corporate Business Strategy | Thought Leadership | Corporate Governance", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D4D03AQF4mFx8jY2n-w/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1730302954035?e=1751500800&v=beta&t=i4QIrHA6A9eLtKolwTRNhuoiaTad28sf5KHxAFuXG-w", "company_handle": "https://www.linkedin.com/company/national-health-insurance-management-authority/", "captured_at": "2025-04-29T13:15:48Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Member Service Assistant @ National Health Insurance Management Authority (NHIMA) | Clinical Officer | Health Insurance & Public Health | Claims Processing & Customer Support | Data & Policy Analyst", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/D4D03AQGob13KyxrB0g/profile-displayphoto-shrink_100_100/B4DZYCgreeHIAU-/0/1743798848889?e=1751500800&v=beta&t=uXxTsMLi5s7hr8FBEzVTDw7V3eJ85kpTaIC7i_5fM-Y", "company_handle": "https://www.linkedin.com/company/national-health-insurance-management-authority/", "captured_at": "2025-04-29T13:15:48Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Economist/ Development Analyst/ Planner/ Customer Care", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/D4E03AQFEc3EgfdpZeg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1727782989867?e=1751500800&v=beta&t=dWjKzSu5FDRgmxAVret9jQPhWF2VjcrnmEpR2LDMC1Q", "company_handle": "https://www.linkedin.com/company/national-health-insurance-management-authority/", "captured_at": "2025-04-29T13:15:48Z"}
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{"profile_url": null, "name": "Samantha Ngandwe", "headline": "Quality Assurance and Accreditation Officer at National Health Insurance Management Authority", "followers": 382, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D4D03AQHyOjyoz7d95g/profile-displayphoto-shrink_100_100/B4DZYvvhP5GwAY-/0/1744557712084?e=1751500800&v=beta&t=DLYRpz20zmwUWx1UY1Dn-ykvgWBnwn8XHWLaDMf199M", "company_handle": "https://www.linkedin.com/company/national-health-insurance-management-authority/", "captured_at": "2025-04-29T13:15:48Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Dental Surgery Assistant at Health Promotion Board", "followers": null, "connection_degree": null, "avatar_url": "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7", "company_handle": "https://www.linkedin.com/company/health-alliance-plan/", "captured_at": "2025-04-29T13:16:11Z"}
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{"profile_url": null, "name": "Liz England Tucker", "headline": "Medical Performance Optimization", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D5603AQFY6yx360QunQ/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1713831102587?e=1751500800&v=beta&t=u-C8Ozpl_ITkTpdgt5QD-C5_Qt7MA0DagLRmiuGKngQ", "company_handle": "https://www.linkedin.com/company/health-alliance-plan/", "captured_at": "2025-04-29T13:16:11Z"}
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{"profile_url": null, "name": "Merrill Hausenfluck", "headline": "Chief Financial Officer", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D4E03AQGKxDKRJM_BCg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1696292650180?e=1751500800&v=beta&t=NbUVC-QP-XL3frBpQcn3GtGrZ04Fl0xdko4V-mHxPag", "company_handle": "https://www.linkedin.com/company/health-alliance-plan/", "captured_at": "2025-04-29T13:16:11Z"}
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{"profile_url": null, "name": "Mike Treash", "headline": "Senior Vice President and Chief Operating Officer at Health Alliance Plan", "followers": 2000, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D5603AQH_c6tIq929gw/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1720478900599?e=1751500800&v=beta&t=l9RLnLDKBBJjJQTsFMJMa_1MpWCKcV4AUa3dcjGnSXQ", "company_handle": "https://www.linkedin.com/company/health-alliance-plan/", "captured_at": "2025-04-29T13:16:11Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Manager at Health Alliance Plan", "followers": null, "connection_degree": null, "avatar_url": "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7", "company_handle": "https://www.linkedin.com/company/health-alliance-plan/", "captured_at": "2025-04-29T13:16:11Z"}
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{"profile_url": null, "name": "Scot Dickerson", "headline": "Insurance Industry Specialist, Insurance Recruiter, Talent Acquisition, Talent Sourcing, Hiring Consultant, Career Consultant, Staffing, Executive Recruiter at Insurance Recruiting Solutions #insurancejobs #insurance", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D5603AQGLFvtPPU3HEw/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1724950672124?e=1751500800&v=beta&t=uT4SFSMF32O1d50Z0dbnd6zRRKdABHxSGlOZdxWdXBM", "company_handle": "https://www.linkedin.com/company/insurance-recruiting-solutions/", "captured_at": "2025-04-29T13:16:24Z"}
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{"profile_url": null, "name": "Steele Dickerson", "headline": "Insurance Recruiting Solutions", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D5603AQEyICWaE_PvXA/profile-displayphoto-shrink_100_100/B56ZQuDHyZH0Ac-/0/1735939358232?e=1751500800&v=beta&t=9FdnWHrjnPQ7LQ5FdwC7sY8sS6hm-R4zfWO5Vmwm46w", "company_handle": "https://www.linkedin.com/company/insurance-recruiting-solutions/", "captured_at": "2025-04-29T13:16:24Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "All Lines Claims Adjuster / General Lines Agent (Property & Casualty : Life, Accident, Health & HMO)", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/D5603AQFTjkb7SxTWWg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1725920318474?e=1751500800&v=beta&t=BGEzQg1c2l8qxuy2iKJ896nElsiYcaWnhkf-mqc-KhY", "company_handle": "https://www.linkedin.com/company/insurance-recruiting-solutions/", "captured_at": "2025-04-29T13:16:24Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Clinical Pharmacy Manager at Health Plan of San Mateo (HPSM)", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/C5603AQEPO0pZOxznoA/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1551565536585?e=1751500800&v=beta&t=qwMGzWX_Zefkciq8h2m9daLMflT0WoDr5F1R5pXvyM4", "company_handle": "https://www.linkedin.com/company/healthplanofsanmateo/", "captured_at": "2025-04-29T13:16:40Z"}
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{"profile_url": null, "name": "Tamana M.", "headline": "MPH Candidate at Brown University | Data Coordinator", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D5603AQEY3iDtFmpzlg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1714197678074?e=1751500800&v=beta&t=IsVT0uC7A-T-Tp22gZFDG9wiT7LMB5GmhccuI8f9c-I", "company_handle": "https://www.linkedin.com/company/healthplanofsanmateo/", "captured_at": "2025-04-29T13:16:40Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Program Manager", "followers": null, "connection_degree": null, "avatar_url": "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7", "company_handle": "https://www.linkedin.com/company/healthplanofsanmateo/", "captured_at": "2025-04-29T13:16:40Z"}
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{"profile_url": null, "name": "Mackenzie Baysinger Moniz, MSW", "headline": "Program Manager at Health Plan of San Mateo", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/D5603AQHAd3A4zLyuWA/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1675716742150?e=1751500800&v=beta&t=ot3fMyJFnHwwNfKJiA_YxZp6MOK_iVGtSCUgVNq867g", "company_handle": "https://www.linkedin.com/company/healthplanofsanmateo/", "captured_at": "2025-04-29T13:16:40Z"}
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{"profile_url": null, "name": "John O.", "headline": "Healthcare Delivery Strategy Execution", "followers": null, "connection_degree": "· 3rd", "avatar_url": "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7", "company_handle": "https://www.linkedin.com/company/healthplanofsanmateo/", "captured_at": "2025-04-29T13:16:40Z"}
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{"profile_url": null, "name": "Daniel McQuilkin", "headline": "Senior Vice President", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/C4E03AQFkScOqwhxvfQ/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1521406683682?e=1751500800&v=beta&t=iohhak3lrV1gpmA6dnoCxTRJidskfgmZUXKbNQbkxjs", "company_handle": "https://www.linkedin.com/company/insurance-management-group_2/", "captured_at": "2025-04-29T13:17:05Z"}
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{"profile_url": null, "name": "LinkedIn Member", "headline": "Music Professional at Health Options Worldwide", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/C5103AQGF-Dp6v6nkGw/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1585401654822?e=1751500800&v=beta&t=7yeO-dGz1p_B66cJVSlTSdAYJLMFFwxPIhwwcR8uWWo", "company_handle": "https://www.linkedin.com/company/health-options-worldwide/", "captured_at": "2025-04-30T07:45:13+00:00Z"}
|
||||
{"profile_url": null, "name": "LinkedIn Member", "headline": "Trainer/instructor at Health Options Worldwide", "followers": null, "connection_degree": null, "avatar_url": "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7", "company_handle": "https://www.linkedin.com/company/health-options-worldwide/", "captured_at": "2025-04-30T07:45:13+00:00Z"}
|
||||
{"profile_url": null, "name": "Michael Akpoarebe-Isaac", "headline": "Chief Operating officer, Health Partners HMO", "followers": null, "connection_degree": "· 3rd", "avatar_url": "https://media.licdn.com/dms/image/v2/C4E03AQE7KNFaLMyqYg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1602714385413?e=1751500800&v=beta&t=In5GaREqoXtO3sPCx9ZJJBwIPY4008ii13RPRl0w0Fw", "company_handle": "https://www.linkedin.com/company/healthpartnersng/", "captured_at": "2025-04-30T07:45:19+00:00Z"}
|
||||
{"profile_url": null, "name": "LinkedIn Member", "headline": "REGISTERED NURSE/CLAIMS SUPERVISOR/HEALTH EDUCATOR/ CASE MANAGER/ Lekki.", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/D4E35AQEEqf5i5pD76g/profile-framedphoto-shrink_100_100/profile-framedphoto-shrink_100_100/0/1724219552412?e=1746604800&v=beta&t=h0kqmp2KnpqQxsCCwyy7NpA8CAkSQ6qgbsZ0p0H7mXM", "company_handle": "https://www.linkedin.com/company/healthpartnersng/", "captured_at": "2025-04-30T07:45:19+00:00Z"}
|
||||
{"profile_url": null, "name": "LinkedIn Member", "headline": "Data Analyst|Dedicated Retention Officer Boosting Customer Loyalty| Business Developer/ Event planner", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/D4D35AQHIgeS1H7w65w/profile-framedphoto-shrink_100_100/B4DZV1QfcCGcAk-/0/1741429012517?e=1746604800&v=beta&t=zZi8WjnLpDrQD271jAId2mnfld_hO538QrN1-q2G4Zw", "company_handle": "https://www.linkedin.com/company/healthpartnersng/", "captured_at": "2025-04-30T07:45:19+00:00Z"}
|
||||
{"profile_url": null, "name": "LinkedIn Member", "headline": "Former Group managing director at Health Partners Ltd", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/C4E03AQHPQPvIQbPQPg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1583328612508?e=1751500800&v=beta&t=LpynArccJCWrdWMSBvYLH4SI5G-xae7ECoWUUAl_CeU", "company_handle": "https://www.linkedin.com/company/healthpartnersng/", "captured_at": "2025-04-30T07:45:19+00:00Z"}
|
||||
{"profile_url": null, "name": "LinkedIn Member", "headline": "HEAD, FINCON, @ HEALTH PARTNERS (HMO) LTD", "followers": null, "connection_degree": null, "avatar_url": "https://media.licdn.com/dms/image/v2/C4D03AQG8XOvnazEibQ/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1518882054975?e=1751500800&v=beta&t=5gT6GAWGTqYfpvkjOk0ArvV73I_KspkWXgoG-VhoStg", "company_handle": "https://www.linkedin.com/company/healthpartnersng/", "captured_at": "2025-04-30T07:45:19+00:00Z"}
|
||||
@@ -0,0 +1,51 @@
|
||||
{
|
||||
"name": "LinkedIn Company Search Result Card",
|
||||
"baseSelector": "div[data-chameleon-result-urn][data-view-name=\"search-entity-result-universal-template\"]",
|
||||
"baseFields": [
|
||||
{
|
||||
"name": "chameleon_result_urn",
|
||||
"type": "attribute",
|
||||
"attribute": "data-chameleon-result-urn"
|
||||
},
|
||||
{
|
||||
"name": "view_name",
|
||||
"type": "attribute",
|
||||
"attribute": "data-view-name"
|
||||
}
|
||||
],
|
||||
"fields": [
|
||||
{
|
||||
"name": "handle",
|
||||
"selector": "div.mb1 div.display-flex span a[data-test-app-aware-link]",
|
||||
"type": "attribute",
|
||||
"attribute": "href"
|
||||
},
|
||||
{
|
||||
"name": "profile_image",
|
||||
"selector": "div.ivm-image-view-model img",
|
||||
"type": "attribute",
|
||||
"attribute": "src"
|
||||
},
|
||||
{
|
||||
"name": "name",
|
||||
"selector": "div.mb1 div.display-flex span a[data-test-app-aware-link]",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "descriptor",
|
||||
"selector": "div.mb1 > div[class*=\"t-14 t-black\"]",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "about",
|
||||
"selector": "p.entity-result__summary--2-lines",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "followers",
|
||||
"selector": "div.mb1 > div:nth-of-type(3)",
|
||||
"type": "regex",
|
||||
"pattern": "(\\d+[KM]?) followers"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,41 @@
|
||||
{
|
||||
"name": "LinkedIn People Profile Card",
|
||||
"baseSelector": "li.org-people-profile-card__profile-card-spacing",
|
||||
"baseFields": [],
|
||||
"fields": [
|
||||
{
|
||||
"name": "profile_url",
|
||||
"selector": "div.artdeco-entity-lockup__title a[data-test-app-aware-link]",
|
||||
"type": "attribute",
|
||||
"attribute": "href"
|
||||
},
|
||||
{
|
||||
"name": "avatar_url",
|
||||
"selector": "div.artdeco-entity-lockup__image img",
|
||||
"type": "attribute",
|
||||
"attribute": "src"
|
||||
},
|
||||
{
|
||||
"name": "name",
|
||||
"selector": "div.artdeco-entity-lockup__title a div.lt-line-clamp--single-line",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "headline",
|
||||
"selector": "div.artdeco-entity-lockup__subtitle div.lt-line-clamp--multi-line",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "followers",
|
||||
"selector": "span.text-align-center span.lt-line-clamp--multi-line",
|
||||
"type": "regex",
|
||||
"pattern": "(\\d+)"
|
||||
},
|
||||
{
|
||||
"name": "connection_degree",
|
||||
"selector": "span.artdeco-entity-lockup__degree",
|
||||
"type": "regex",
|
||||
"pattern": "(\\d+\\w+)"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,138 @@
|
||||
<li class="kZRArQqqhjjrHYceWaFbyEGWHRZbtqjTMawKA">
|
||||
<!----><!---->
|
||||
|
||||
|
||||
|
||||
<div class="xAuWirHJDUTuhkfOpmJApZWziplUyPIc" data-chameleon-result-urn="urn:li:company:2095237"
|
||||
data-view-name="search-entity-result-universal-template">
|
||||
|
||||
|
||||
|
||||
|
||||
<div class="linked-area flex-1
|
||||
cursor-pointer">
|
||||
|
||||
<div class="qMGLeKnJyQnibGOueKodvnfLgWpsuA">
|
||||
<div class="cBPGFfFovHsbNhBFmECDIsPgMWmtMozOUfIAbs">
|
||||
<div class="display-flex align-items-center">
|
||||
<!---->
|
||||
|
||||
<a class="sDWEFrcVubKuUVGggeBOYqLlgYgPbojOc scale-down " aria-hidden="true" tabindex="-1"
|
||||
href="https://www.linkedin.com/company/health-insurance/" data-test-app-aware-link="">
|
||||
|
||||
<div class="ivm-image-view-model ">
|
||||
|
||||
<div class="ivm-view-attr__img-wrapper
|
||||
|
||||
">
|
||||
<!---->
|
||||
<!----> <img width="48"
|
||||
src="https://media.licdn.com/dms/image/v2/C560BAQEXIoLSJbShlw/company-logo_100_100/company-logo_100_100/0/1662748332921/health_insurance_logo?e=1753920000&v=beta&t=p2ZNMYNsC9KSlp-sIqMYuc88avBTjKF4CqDobq1Xr2M"
|
||||
loading="lazy" height="48" alt="Health Insurance" id="ember28"
|
||||
class="ivm-view-attr__img--centered EntityPhoto-square-3 evi-image lazy-image ember-view">
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
</a>
|
||||
|
||||
|
||||
</div>
|
||||
</div>
|
||||
<div
|
||||
class="BNxZPngZfeRnDrIUbICgBZvQjRvMAUnwCHuDrmRg yNRlrJOHDflDBnYPLbVmiAkUsCUZKUznmAc pt3 pb3 t-12 t-black--light">
|
||||
<div class="mb1">
|
||||
|
||||
<div class="t-roman t-sans">
|
||||
|
||||
|
||||
|
||||
<div class="display-flex">
|
||||
<span
|
||||
class="kmApjJVnFerynwITxTBSCqzqgoHwVfkiA HHGiVqODTCkszDUDWwPGPJGUPfAeRpygAKwwLePrQ ">
|
||||
<span class="OjTMoZLoiuspGuWWptwqxZRcMcHZBoSDxfig
|
||||
t-16">
|
||||
<a class="sDWEFrcVubKuUVGggeBOYqLlgYgPbojOc "
|
||||
href="https://www.linkedin.com/company/health-insurance/"
|
||||
data-test-app-aware-link="">
|
||||
<!---->Health Insurance<!---->
|
||||
<!----> </a>
|
||||
<!----> </span>
|
||||
</span>
|
||||
<!---->
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
<div class="kFTZPhxHBbvnnRxiRPmTxafKGLUNSiaeInag
|
||||
t-14 t-black t-normal">
|
||||
<!---->Insurance ⢠Cardiff, CA<!---->
|
||||
</div>
|
||||
|
||||
<div class="FlWUwyrEUZpkVCgzGTDwUHTLntfZNseavlY
|
||||
t-14 t-normal">
|
||||
<!---->3K followers<!---->
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
<!---->
|
||||
<p class="JBUEKeXhPyClEtYwdsASPYsZsCkTvUBqsDUs
|
||||
entity-result__summary--2-lines
|
||||
t-12 t-black--light
|
||||
">
|
||||
<!---->Your<span class="white-space-pre"> </span><strong><!---->health<!----></strong><span
|
||||
class="white-space-pre"> </span><!----><!----><strong><!---->insurance<!----></strong><span
|
||||
class="white-space-pre"> </span>expert for all stages of your life; Medicare, Individuals,
|
||||
Families, Small Groups, CoveredCA.<!---->
|
||||
</p>
|
||||
|
||||
<!---->
|
||||
</div>
|
||||
<div class="JZcKRppsWfaxfMaqtvfVwEeAtzNwryBOMdo yNRlrJOHDflDBnYPLbVmiAkUsCUZKUznmAc">
|
||||
<!---->
|
||||
|
||||
|
||||
<div>
|
||||
|
||||
|
||||
|
||||
|
||||
<button aria-label="Follow Health Insurance" id="ember49"
|
||||
class="artdeco-button artdeco-button--2 artdeco-button--secondary ember-view"
|
||||
type="button"><!---->
|
||||
<span class="artdeco-button__text">
|
||||
Follow
|
||||
</span></button>
|
||||
|
||||
|
||||
|
||||
<!---->
|
||||
<!---->
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
</li>
|
||||
@@ -0,0 +1,93 @@
|
||||
<li class="grid grid__col--lg-8 block org-people-profile-card__profile-card-spacing">
|
||||
<div>
|
||||
|
||||
|
||||
<section class="artdeco-card full-width IxXiAcHfbZpayHVZUYdQwfYOkMbOirmr">
|
||||
<!---->
|
||||
|
||||
<img width="210" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7"
|
||||
ariarole="presentation" loading="lazy" height="210" alt="" id="ember102"
|
||||
class="evi-image lazy-image ghost-default ember-view org-people-profile-card__cover-photo org-people-profile-card__cover-photo--people">
|
||||
|
||||
<div class="org-people-profile-card__profile-info">
|
||||
<div id="ember103"
|
||||
class="artdeco-entity-lockup artdeco-entity-lockup--stacked-center artdeco-entity-lockup--size-7 ember-view">
|
||||
<div id="ember104"
|
||||
class="artdeco-entity-lockup__image artdeco-entity-lockup__image--type-circle ember-view"
|
||||
type="circle">
|
||||
|
||||
<a class="sDWEFrcVubKuUVGggeBOYqLlgYgPbojOc " id="org-people-profile-card__profile-image-0"
|
||||
href="https://www.linkedin.com/in/ericweberhcbd?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAABVh2MBFoyTaAxDqYQQcW8oGxVsqsKioHw"
|
||||
data-test-app-aware-link="">
|
||||
<img width="104"
|
||||
src="https://media.licdn.com/dms/image/v2/C4D03AQHNP9KoXtSrkg/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1573501774845?e=1753920000&v=beta&t=JYsY56biGUmDzbYj2ORZMcd1dSm2IRWCA-IM3KNFLw8"
|
||||
loading="lazy" height="104" alt="Eric Weber" id="ember105"
|
||||
class="evi-image lazy-image ember-view">
|
||||
</a>
|
||||
|
||||
|
||||
</div>
|
||||
<div id="ember106" class="artdeco-entity-lockup__content ember-view">
|
||||
<div id="ember107" class="artdeco-entity-lockup__title ember-view">
|
||||
<a class="sDWEFrcVubKuUVGggeBOYqLlgYgPbojOc link-without-visited-state"
|
||||
aria-label="View Eric Weberâs profile"
|
||||
href="https://www.linkedin.com/in/ericweberhcbd?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAABVh2MBFoyTaAxDqYQQcW8oGxVsqsKioHw"
|
||||
data-test-app-aware-link="">
|
||||
<div id="ember109" class="ember-view lt-line-clamp lt-line-clamp--single-line rMKrzkehlCEvJWoQjDQJFaHmBFAYQLMGrNY
|
||||
t-black" style="">
|
||||
Eric Weber
|
||||
|
||||
<!---->
|
||||
</div>
|
||||
|
||||
</a>
|
||||
|
||||
</div>
|
||||
<div id="ember110" class="artdeco-entity-lockup__badge ember-view"> <span class="a11y-text">3rd+
|
||||
degree connection</span>
|
||||
<span class="artdeco-entity-lockup__degree" aria-hidden="true">
|
||||
· 3rd
|
||||
</span>
|
||||
<!----><!---->
|
||||
</div>
|
||||
<div id="ember111" class="artdeco-entity-lockup__subtitle ember-view">
|
||||
<div class="t-14 t-black--light t-normal">
|
||||
<div id="ember113" class="ember-view lt-line-clamp lt-line-clamp--multi-line"
|
||||
style="-webkit-line-clamp: 2">
|
||||
HIPN Executive Editor | Healthcare BizDev CEO â Health Insurance Plan News.
|
||||
|
||||
<!---->
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
<div id="ember114" class="artdeco-entity-lockup__caption ember-view"></div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<span class="text-align-center">
|
||||
<span id="ember116"
|
||||
class="ember-view lt-line-clamp lt-line-clamp--multi-line t-12 t-black--light mt2"
|
||||
style="-webkit-line-clamp: 3">
|
||||
10K followers
|
||||
|
||||
<!----> </span>
|
||||
|
||||
</span>
|
||||
</div>
|
||||
|
||||
<footer class="ph3 pb3">
|
||||
<button aria-label="Follow Eric Weber" id="ember117"
|
||||
class="artdeco-button artdeco-button--2 artdeco-button--secondary ember-view full-width"
|
||||
type="button"><!---->
|
||||
<span class="artdeco-button__text">
|
||||
Follow
|
||||
</span></button>
|
||||
</footer>
|
||||
|
||||
</section>
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
</li>
|
||||
@@ -0,0 +1,50 @@
|
||||
// ==== File: ai.js ====
|
||||
|
||||
class ApiHandler {
|
||||
constructor(apiKey = null) {
|
||||
this.apiKey = apiKey || localStorage.getItem("openai_api_key") || "";
|
||||
console.log("ApiHandler ready");
|
||||
}
|
||||
|
||||
setApiKey(k) {
|
||||
this.apiKey = k.trim();
|
||||
if (this.apiKey) localStorage.setItem("openai_api_key", this.apiKey);
|
||||
}
|
||||
|
||||
async *chatStream(messages, {model = "gpt-4o", temperature = 0.7} = {}) {
|
||||
if (!this.apiKey) throw new Error("OpenAI API key missing");
|
||||
const payload = {model, messages, stream: true, max_tokens: 1024};
|
||||
const controller = new AbortController();
|
||||
|
||||
const res = await fetch("https://api.openai.com/v1/chat/completions", {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${this.apiKey}`,
|
||||
},
|
||||
body: JSON.stringify(payload),
|
||||
signal: controller.signal,
|
||||
});
|
||||
if (!res.ok) throw new Error(`OpenAI: ${res.statusText}`);
|
||||
const reader = res.body.getReader();
|
||||
const dec = new TextDecoder();
|
||||
|
||||
let buf = "";
|
||||
while (true) {
|
||||
const {done, value} = await reader.read();
|
||||
if (done) break;
|
||||
buf += dec.decode(value, {stream: true});
|
||||
for (const line of buf.split("\n")) {
|
||||
if (!line.startsWith("data: ")) continue;
|
||||
if (line.includes("[DONE]")) return;
|
||||
const json = JSON.parse(line.slice(6));
|
||||
const delta = json.choices?.[0]?.delta?.content;
|
||||
if (delta) yield delta;
|
||||
}
|
||||
buf = buf.endsWith("\n") ? "" : buf; // keep partial line
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
window.API = new ApiHandler();
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user