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d80db75d4e Merge master into main - use local README 2025-12-09 16:42:09 +08:00
46915964e1 Initial commit: University Playwright Codegen Agent
🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-09 16:38:33 +08:00
32 changed files with 3091 additions and 3 deletions

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# University-Playwright-Codegen-Agent
# University Playwright Codegen Agent
这是一个自动化生成代码的agent给定一个海外大学官网的址,即可生成python脚本爬取这个大学各级学院下的所有硕士项目网址和硕士项目中各导师个人信息的网址
构建于 [Agno](https://docs.agno.com/) 的自动化代码生成代理:输入海外大学官网的根地址,即可生成一份使用 **Playwright** 的 Python 脚本,脚本会抓取各学院/研究生院下的硕士项目网址以及项目中列出的导师Supervisor/Faculty个人信息页面。本项目使用 `uv` 进行依赖管理,`ruff` 做静态检查,`ty` 负责类型检查,并提供了一个基于 Typer 的 CLI
## Features
-**Agno Agent**:利用 `output_schema` 强制结构化输出,里程碑式地生成 `ScriptPlan` 并将其渲染为可执行脚本。
-**Playwright sampling**:计划生成前会用 Playwright 对站点进行轻量抓取,帮助 Agent 找到关键词与导航策略。
-**Deterministic script template**:脚本模板包含 BFS 爬取、关键词过滤、JSON 输出等逻辑,确保满足“硕士项目 + 导师”需求。
-**uv + ruff + ty workflow**:开箱即用的现代 Python 工具链。
## Getting started
1. **创建虚拟环境并安装依赖**
```bash
uv venv --python 3.12
uv pip install -r pyproject.toml
playwright install # 安装浏览器内核
```
2. **配置大模型 API key**
- OpenAI: `export OPENAI_API_KEY=...`
- Anthropic: `export ANTHROPIC_API_KEY=...`
- 可通过环境变量 `CODEGEN_MODEL_PROVIDER` 在 `openai` 与 `anthropic` 之间切换。
3. **运行 CLI 生成脚本**
```bash
uv run university-agent generate \
"https://www.example.edu" \
--campus "Example Campus" \
--language "English" \
--max-depth 2 \
--max-pages 60
```
运行完成后会在 `artifacts/` 下看到生成的 Playwright 脚本,并在终端展示自动规划的关键词与验证步骤。
4. **执行 Ruff & Ty 检查**
```bash
uv run ruff check
uvx ty check
```
## Project structure
```
├── README.md
├── pyproject.toml
├── src/university_agent
│ ├── agent.py # Agno Agent 配置
│ ├── cli.py # Typer CLI
│ ├── config.py # pydantic Settings
│ ├── generator.py # Orchestration 引擎
│ ├── models.py # 数据模型(请求/计划/结果)
│ ├── renderer.py # ScriptPlan -> Playwright script
│ ├── sampler.py # Playwright 采样
│ ├── templates/
│ │ └── playwright_script.py.jinja
│ └── writer.py # 将脚本写入 artifacts/
└── 任务1.txt
```
## Tips
- `university-agent generate --help` 查看所有 CLI 选项,可选择跳过采样或导出规划 JSON。
- 如果 Agno Agent 需使用其他工具,可在 `agent.py` 中自行扩展自定义 `tool`。
- Playwright 采样在某些环境中需要额外的浏览器依赖,请根据官方提示执行 `playwright install`。
Happy building! 🎓🤖

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#!/usr/bin/env python
"""
Auto-generated by the Agno codegen agent.
Target university: Stanford (https://www.stanford.edu)
Requested caps: depth=2, pages=20
Plan description: Async Playwright scraper targeting Stanford University to collect (1) master's program landing pages and (2) faculty/supervisor profiles linked from those programs. Respects depth=2, pages=20 caps. Starts from the main site, navigates through Academics and school/department portals to locate graduate program listings and associated faculty directories.
Navigation strategy: 1. Seed from https://www.stanford.edu and follow the 'Academics' top-nav link to reach school/department listings. 2. On school pages, look for anchors containing master_program_keywords (href fragments like /programs/, /graduate/, /masters/) and queue them. 3. On each master's program page, extract metadata and scan for faculty_keywords in link text or href (e.g., /people/, /faculty/, /directory/). 4. Follow qualifying faculty links up to the depth cap and record each profile. 5. Use URL deduplication (set of visited URLs) and respect the 20-page cap by counting unique pages fetched. 6. Prioritize links via keyword score so high-relevance pages are visited first if cap is approached.
Verification checklist:
- Assert each JSONL row contains a non-empty 'url' and 'title' field.
- Confirm at least one record has entity_type='master_program' and one has entity_type='faculty'.
- Validate that no URL appears more than once in the output file.
- Check that total scraped pages does not exceed the requested cap of 20.
Playwright snapshot used to guide this plan:
1. Stanford University (https://www.stanford.edu)
Snippet: Skip to content Stanford University Information for: Students Faculty & Staff Families Visitors Alumni Search Academics Research Health Care Campus Life Athletics Admission About News Events Stanford Explore Stanford Main Content A Mission Defined by Possibility At Stanford,
Anchors: Skip to content -> https://www.stanford.edu/#main-content, Stanford University -> https://www.stanford.edu/, Students -> https://www.stanford.edu/student-gateway/, Faculty & Staff -> https://www.stanford.edu/faculty-staff-gateway/, Families -> http://parents.stanford.edu/, Visitors -> https://visit.stanford.edu/
2. Stanford University (https://www.stanford.edu/)
Snippet: Skip to content Stanford University Information for: Students Faculty & Staff Families Visitors Alumni Search Academics Research Health Care Campus Life Athletics Admission About News Events Stanford Explore Stanford Main Content A Mission Defined by Possibility At Stanford,
Anchors: Skip to content -> https://www.stanford.edu/#main-content, Stanford University -> https://www.stanford.edu/, Students -> https://www.stanford.edu/student-gateway/, Faculty & Staff -> https://www.stanford.edu/faculty-staff-gateway/, Families -> http://parents.stanford.edu/, Visitors -> https://visit.stanford.edu/
3. Gateway for Students Stanford University (https://www.stanford.edu/student-gateway/)
Snippet: Skip to content Stanford University Information for: Students Faculty & Staff Families Visitors Alumni Search Academics Research Health Care Campus Life Athletics Admission About News Events Main Content Gateway for Students Gateway for Students Resources, offices and services t
Anchors: Skip to content -> https://www.stanford.edu/student-gateway/#main-content, Stanford University -> https://www.stanford.edu/, Students -> https://www.stanford.edu/student-gateway/, Faculty & Staff -> https://www.stanford.edu/faculty-staff-gateway/, Families -> http://parents.stanford.edu/, Visitors -> https://visit.stanford.edu/
4. Gateway for Faculty & Staff Stanford University (https://www.stanford.edu/faculty-staff-gateway/)
Snippet: Skip to content Stanford University Information for: Students Faculty & Staff Families Visitors Alumni Search Academics Research Health Care Campus Life Athletics Admission About News Events Main Content Gateway for Faculty & Staff Gateway for Faculty & Staff Resources, offices,
Anchors: Skip to content -> https://www.stanford.edu/faculty-staff-gateway/#main-content, Stanford University -> https://www.stanford.edu/, Students -> https://www.stanford.edu/student-gateway/, Faculty & Staff -> https://www.stanford.edu/faculty-staff-gateway/, Families -> http://parents.stanford.edu/, Visitors -> https://visit.stanford.edu/
Snapshot truncated.
Generated at: 2025-12-09T04:03:37.802236+00:00
"""
from __future__ import annotations
import argparse
import asyncio
import json
from collections import deque
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Deque, Iterable, List, Set, Tuple
from urllib.parse import urljoin, urldefrag
from playwright.async_api import async_playwright, Page
PROGRAM_KEYWORDS = ['master', 'graduate program', 'MS degree', 'MA degree', 'graduate studies', 'postgraduate']
FACULTY_KEYWORDS = ['faculty', 'professor', 'advisor', 'researcher', 'people', 'directory']
EXCLUSION_KEYWORDS = ['admission', 'apply', 'tuition', 'financial aid', 'login', 'news', 'events', 'alumni', 'athletics', 'giving', 'donate', 'careers', 'jobs']
METADATA_FIELDS = ['url', 'title', 'entity_type', 'department', 'school', 'description', 'contact_email', 'scraped_at']
EXTRA_NOTES = ["Stanford's seven schools each host their own subdomains (e.g., engineering.stanford.edu, law.stanford.edu); the script should allow cross-subdomain crawling within *.stanford.edu while still counting against the page cap.", "Many program pages load additional content via JavaScript; use page.wait_for_load_state('networkidle') or explicit waits before extracting links.", 'Faculty directories may paginate or use infinite scroll; handle at least the first visible batch given the tight page cap.', 'Respect polite crawling: insert a 1-2 second delay between requests to avoid rate-limiting.']
def normalize_url(base: str, href: str) -> str:
absolute = urljoin(base, href)
cleaned, _ = urldefrag(absolute)
return cleaned
def matches_any(text: str, keywords: Iterable[str]) -> bool:
lowered = text.lower()
return any(keyword.lower() in lowered for keyword in keywords)
@dataclass
class ScrapedLink:
url: str
text: str
source_url: str
bucket: str # either "program" or "faculty"
@dataclass
class ScrapeSettings:
root_url: str
max_depth: int
max_pages: int
headless: bool
output: Path
async def extract_links(page: Page) -> List[Tuple[str, str]]:
anchors: Iterable[dict] = await page.eval_on_selector_all(
"a",
"""elements => elements
.map(el => ({text: (el.textContent || '').trim(), href: el.href}))
.filter(item => item.text && item.href)""",
)
return [(item["href"], item["text"]) for item in anchors]
async def crawl(settings: ScrapeSettings, browser_name: str) -> List[ScrapedLink]:
async with async_playwright() as p:
browser_launcher = getattr(p, browser_name)
browser = await browser_launcher.launch(headless=settings.headless)
context = await browser.new_context()
queue: Deque[Tuple[str, int]] = deque([(settings.root_url, 0)])
visited: Set[str] = set()
results: List[ScrapedLink] = []
try:
while queue and len(visited) < settings.max_pages:
url, depth = queue.popleft()
if url in visited or depth > settings.max_depth:
continue
visited.add(url)
page = await context.new_page()
try:
await page.goto(url, wait_until="domcontentloaded", timeout=20000)
except Exception:
await page.close()
continue
links = await extract_links(page)
for href, text in links:
normalized = normalize_url(url, href)
if matches_any(text, EXCLUSION_KEYWORDS) or matches_any(normalized, EXCLUSION_KEYWORDS):
continue
text_lower = text.lower()
normalized_lower = normalized.lower()
if matches_any(text_lower, PROGRAM_KEYWORDS) or matches_any(normalized_lower, PROGRAM_KEYWORDS):
results.append(
ScrapedLink(
url=normalized,
text=text,
source_url=url,
bucket="program",
)
)
if matches_any(text_lower, FACULTY_KEYWORDS) or matches_any(normalized_lower, FACULTY_KEYWORDS):
results.append(
ScrapedLink(
url=normalized,
text=text,
source_url=url,
bucket="faculty",
)
)
if depth < settings.max_depth:
queue.append((normalized, depth + 1))
await page.close()
finally:
await context.close()
await browser.close()
return results
def serialize(results: List[ScrapedLink], target: Path, root_url: str) -> None:
payload = {
"root_url": root_url,
"program_links": [
{**asdict(link), "bucket": link.bucket} for link in results if link.bucket == "program"
],
"faculty_links": [
{**asdict(link), "bucket": link.bucket} for link in results if link.bucket == "faculty"
],
"notes": EXTRA_NOTES,
"metadata_fields": METADATA_FIELDS,
}
target.parent.mkdir(parents=True, exist_ok=True)
target.write_text(json.dumps(payload, indent=2, ensure_ascii=False), encoding="utf-8")
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(
description="Playwright scraper generated by the Agno agent for https://www.stanford.edu."
)
parser.add_argument(
"--root-url",
default="https://www.stanford.edu",
help="Seed url to start crawling from.",
)
parser.add_argument(
"--max-depth",
type=int,
default=2,
help="Maximum crawl depth.",
)
parser.add_argument(
"--max-pages",
type=int,
default=20,
help="Maximum number of pages to visit.",
)
parser.add_argument(
"--output",
type=Path,
default=Path("stanford-masters-faculty_masters.json"),
help="Where to save the JSON output.",
)
parser.add_argument(
"--headless",
action="store_true",
default=True,
help="Run browser in headless mode (default: True).",
)
parser.add_argument(
"--no-headless",
action="store_false",
dest="headless",
help="Run browser with visible window.",
)
parser.add_argument(
"--browser",
choices=["chromium", "firefox", "webkit"],
default="chromium",
help="Browser engine to launch via Playwright.",
)
return parser.parse_args()
async def main_async() -> None:
args = parse_args()
settings = ScrapeSettings(
root_url=args.root_url,
max_depth=args.max_depth,
max_pages=args.max_pages,
headless=args.headless,
output=args.output,
)
links = await crawl(settings, browser_name=args.browser)
serialize(links, settings.output, settings.root_url)
def main() -> None:
asyncio.run(main_async())
if __name__ == "__main__":
main()

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pyproject.toml Normal file
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[project]
name = "university-agent"
version = "0.1.0"
description = "Agno powered agent that generates Playwright scraping scripts for university program research."
readme = "README.md"
requires-python = ">=3.11"
license = {text = "MIT"}
authors = [
{name = "Codex Agent"}
]
dependencies = [
"agno>=2.3.8",
"typer>=0.12.5",
"pydantic>=2.9",
"pydantic-settings>=2.6",
"jinja2>=3.1",
"playwright>=1.48",
"httpx>=0.28",
"rich>=13.7"
]
[project.optional-dependencies]
dev = [
"ruff>=0.6.9",
"ty>=0.0.1a32"
]
[project.scripts]
university-agent = "university_agent.cli:main"
[build-system]
requires = ["setuptools>=68"]
build-backend = "setuptools.build_meta"
[tool.setuptools]
package-dir = {"" = "src"}
[tool.setuptools.packages.find]
where = ["src"]
[tool.setuptools.package-data]
"university_agent" = ["templates/*.jinja"]
[tool.uv]
managed = true
dev-dependencies = ["ruff>=0.6.9", "ty>=0.0.1a32"]
[tool.ruff]
line-length = 100
target-version = "py311"
[tool.ruff.lint]
select = ["E", "F", "B", "I", "UP", "RUF"]
ignore = ["B008"] # Allow function calls in argument defaults (typer pattern)
[tool.ty.environment]
python-version = "3.12"

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Metadata-Version: 2.4
Name: university-agent
Version: 0.1.0
Summary: Agno powered agent that generates Playwright scraping scripts for university program research.
Author: Codex Agent
License: MIT
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: agno>=2.3.8
Requires-Dist: typer>=0.12.5
Requires-Dist: pydantic>=2.9
Requires-Dist: pydantic-settings>=2.6
Requires-Dist: jinja2>=3.1
Requires-Dist: playwright>=1.48
Requires-Dist: httpx>=0.28
Requires-Dist: rich>=13.7
Provides-Extra: dev
Requires-Dist: ruff>=0.6.9; extra == "dev"
Requires-Dist: ty>=0.0.1a32; extra == "dev"
# University Playwright Codegen Agent
构建于 [Agno](https://docs.agno.com/) 的自动化代码生成代理:输入海外大学官网的根地址,即可生成一份使用 **Playwright** 的 Python 脚本,脚本会抓取各学院/研究生院下的硕士项目网址以及项目中列出的导师Supervisor/Faculty个人信息页面。本项目使用 `uv` 进行依赖管理,`ruff` 做静态检查,`ty` 负责类型检查,并提供了一个基于 Typer 的 CLI。
## Features
- ✅ **Agno Agent**:利用 `output_schema` 强制结构化输出,里程碑式地生成 `ScriptPlan` 并将其渲染为可执行脚本。
- ✅ **Playwright sampling**:计划生成前会用 Playwright 对站点进行轻量抓取,帮助 Agent 找到关键词与导航策略。
- ✅ **Deterministic script template**:脚本模板包含 BFS 爬取、关键词过滤、JSON 输出等逻辑,确保满足“硕士项目 + 导师”需求。
- ✅ **uv + ruff + ty workflow**:开箱即用的现代 Python 工具链。
## Getting started
1. **创建虚拟环境并安装依赖**
```bash
uv venv --python 3.12
uv pip install -r pyproject.toml
playwright install # 安装浏览器内核
```
2. **配置大模型 API key**
- OpenAI: `export OPENAI_API_KEY=...`
- Anthropic: `export ANTHROPIC_API_KEY=...`
- 可通过环境变量 `CODEGEN_MODEL_PROVIDER` 在 `openai` 与 `anthropic` 之间切换。
3. **运行 CLI 生成脚本**
```bash
uv run university-agent generate \
"https://www.example.edu" \
--campus "Example Campus" \
--language "English" \
--max-depth 2 \
--max-pages 60
```
运行完成后会在 `artifacts/` 下看到生成的 Playwright 脚本,并在终端展示自动规划的关键词与验证步骤。
4. **执行 Ruff & Ty 检查**
```bash
uv run ruff check
uvx ty check
```
## Project structure
```
├── README.md
├── pyproject.toml
├── src/university_agent
│ ├── agent.py # Agno Agent 配置
│ ├── cli.py # Typer CLI
│ ├── config.py # pydantic Settings
│ ├── generator.py # Orchestration 引擎
│ ├── models.py # 数据模型(请求/计划/结果)
│ ├── renderer.py # ScriptPlan -> Playwright script
│ ├── sampler.py # Playwright 采样
│ ├── templates/
│ │ └── playwright_script.py.jinja
│ └── writer.py # 将脚本写入 artifacts/
└── 任务1.txt
```
## Tips
- `university-agent generate --help` 查看所有 CLI 选项,可选择跳过采样或导出规划 JSON。
- 如果 Agno Agent 需使用其他工具,可在 `agent.py` 中自行扩展自定义 `tool`。
- Playwright 采样在某些环境中需要额外的浏览器依赖,请根据官方提示执行 `playwright install`。
Happy building! 🎓🤖

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README.md
pyproject.toml
src/university_agent/__init__.py
src/university_agent/agent.py
src/university_agent/cli.py
src/university_agent/config.py
src/university_agent/generator.py
src/university_agent/models.py
src/university_agent/renderer.py
src/university_agent/sampler.py
src/university_agent/writer.py
src/university_agent.egg-info/PKG-INFO
src/university_agent.egg-info/SOURCES.txt
src/university_agent.egg-info/dependency_links.txt
src/university_agent.egg-info/entry_points.txt
src/university_agent.egg-info/requires.txt
src/university_agent.egg-info/top_level.txt
src/university_agent/templates/playwright_script.py.jinja

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[console_scripts]
university-agent = university_agent.cli:main

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agno>=2.3.8
typer>=0.12.5
pydantic>=2.9
pydantic-settings>=2.6
jinja2>=3.1
playwright>=1.48
httpx>=0.28
rich>=13.7
[dev]
ruff>=0.6.9
ty>=0.0.1a32

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university_agent

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"""Top-level package for the university code generation agent."""
from .agent import ScriptAgent
from .config import Settings
from .generator import GenerationEngine
from .models import GenerationRequest, GenerationResult, ScriptPlan
__all__ = [
"GenerationEngine",
"GenerationRequest",
"GenerationResult",
"ScriptAgent",
"ScriptPlan",
"Settings",
]

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from __future__ import annotations
import json
from textwrap import dedent
from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.models.openai import OpenAIChat
from agno.run.agent import RunOutput
from .config import Settings
from .models import GenerationRequest, ScriptPlan, SiteSummary
BASE_INSTRUCTIONS = dedent(
"""
You are a senior automation engineer specializing in web scraping for academic research.
Your task is to generate production-grade Playwright scraping plans that collect:
1. **Master's program pages**: Landing pages for graduate/master's degree programs.
- Look for URLs containing: /programs/, /graduate/, /masters/, /degrees/, /academics/
- Keywords in text: "Master of", "M.S.", "M.A.", "graduate program", "postgraduate"
2. **Individual faculty/supervisor profile pages**: Personal pages of professors and researchers.
- IMPORTANT: We need INDIVIDUAL profile pages, NOT directory listings or department pages.
- Profile URL patterns: /people/firstname-lastname, /~username, /profile/, /faculty/name
- The goal is to find pages like "Dr. John Smith" not "Faculty Directory"
Key requirements:
- Prioritize crawling faculty/people directory pages to find individual profiles
- Use specific keywords that distinguish individual profiles from listing pages
- Include URL patterns that indicate personal pages (e.g., /people/*, /profile/*, /~*)
- Exclude general navigation pages (admissions, news, events, careers, login)
Output must follow the ScriptPlan schema exactly with specific, actionable keywords.
"""
).strip()
PROMPT_TEMPLATE = dedent(
"""
## University context
- Target url: {target_url}
- Campus or nickname: {campus}
- Assumed language: {language}
- Crawl caps requested by user: depth={depth}, pages={pages}
- Custom notes: {notes}
## Browser snapshot (Playwright)
{snapshot}
## Your task
Produce a ScriptPlan with these requirements:
1. **script_name**: Use `{default_script}` or infer a better name.
2. **master_program_keywords** (6-8 keywords): Terms that identify master's program pages.
- Include both URL fragments (e.g., "/graduate/", "/masters/") and text patterns
- Be specific to this university's naming conventions based on the snapshot
3. **faculty_keywords** (6-8 keywords): Terms that identify INDIVIDUAL faculty profile pages.
- Focus on patterns that indicate a PERSON's page, not a directory
- Include: professor names patterns, "/people/", "/profile/", "Dr.", "Professor"
- Look at the snapshot to identify how this university structures faculty URLs
4. **exclusion_keywords** (8-12 keywords): Aggressively exclude non-relevant pages.
- Include: admissions, apply, tuition, news, events, careers, jobs, login, donate, alumni
- Add university-specific noise pages you spot in the snapshot
5. **navigation_strategy**: Describe how to efficiently find individual profiles.
- Identify the path from homepage -> department -> faculty directory -> individual profiles
- Note any subdomains (e.g., cs.university.edu, engineering.university.edu)
6. **verification_steps**: How to verify the results are correct.
7. **extra_notes**: Important observations about the site structure.
Respond with valid JSON only.
"""
).strip()
class ScriptAgent:
"""Thin wrapper around Agno's Agent configured for our structured planning task."""
def __init__(self, settings: Settings):
self.settings = settings
self._agent = Agent(
name="UniversityScriptSmith",
description="Produces structured plans for Playwright-based scrapers.",
instructions=[BASE_INSTRUCTIONS],
model=self._resolve_model(),
output_schema=ScriptPlan,
reasoning=settings.reasoning_enabled,
reasoning_max_steps=settings.reasoning_max_steps,
add_history_to_context=False,
markdown=False,
)
def _resolve_model(self):
provider = self.settings.model_provider.lower()
if provider == "anthropic":
return Claude(id=self.settings.anthropic_model)
if provider == "openai":
return OpenAIChat(id=self.settings.openai_model)
raise ValueError(f"Unsupported provider: {provider}")
def build_plan(self, request: GenerationRequest, summary: SiteSummary | None) -> ScriptPlan:
"""Call the Agno agent and coerce the structured response into our Pydantic model."""
snapshot = summary.to_prompt_section() if summary else "No snapshot available."
prompt = PROMPT_TEMPLATE.format(
target_url=request.target_url,
campus=request.campus_name or "unspecified",
language=request.assumed_language or "unspecified",
depth=request.max_depth,
pages=request.max_pages,
notes=request.notes or "n/a",
snapshot=snapshot,
default_script=self.settings.default_script_name,
)
run_response = self._agent.run(prompt)
plan = self._coerce_plan(run_response)
if not plan.project_slug:
fallback = (request.campus_name or "university").replace(" ", "-").lower()
plan.project_slug = fallback
if not plan.script_name:
plan.script_name = self.settings.default_script_name
return plan
@staticmethod
def _coerce_plan(run_response: RunOutput) -> ScriptPlan:
content = run_response.content
if isinstance(content, ScriptPlan):
return content
if isinstance(content, dict):
return ScriptPlan.model_validate(content)
if isinstance(content, str):
try:
payload = json.loads(content)
except json.JSONDecodeError as exc:
raise ValueError("Agent returned a non-JSON payload.") from exc
return ScriptPlan.model_validate(payload)
raise ValueError("Agent response did not match the ScriptPlan schema.")

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from __future__ import annotations
import json
from pathlib import Path
import typer
from rich.console import Console
from rich.table import Table
from .config import Settings
from .generator import GenerationEngine
from .models import GenerationRequest
app = typer.Typer(help="Generate Playwright scraping scripts for overseas universities.")
def _print_plan(result) -> None:
console = Console()
table = Table(title="Script Plan", show_lines=False)
table.add_column("Key", style="cyan", no_wrap=True)
table.add_column("Value", style="white")
plan = result.plan
table.add_row("Script name", plan.script_name)
table.add_row("Project slug", plan.project_slug)
table.add_row("Master keywords", ", ".join(plan.master_program_keywords))
table.add_row("Faculty keywords", ", ".join(plan.faculty_keywords))
table.add_row("Exclude keywords", ", ".join(plan.exclusion_keywords) or "n/a")
table.add_row("Metadata fields", ", ".join(plan.metadata_fields))
table.add_row("Navigation strategy", plan.navigation_strategy)
table.add_row("Verification steps", "\n".join(plan.verification_steps) or "n/a")
if plan.extra_notes:
table.add_row("Extra notes", "\n".join(plan.extra_notes))
console.print(table)
@app.command()
def generate(
url: str = typer.Argument(..., help="Root URL of the university site."),
campus: str | None = typer.Option(None, "--campus", help="Campus or locale nickname."),
language: str | None = typer.Option(None, "--language", help="Primary site language."),
notes: str | None = typer.Option(None, "--notes", help="Extra requirements for the script."),
max_depth: int = typer.Option(2, "--max-depth", min=1, max=5, help="Depth limit for crawling."),
max_pages: int = typer.Option(
40, "--max-pages", min=10, max=200, help="Page budget for the generated script."
),
no_snapshot: bool = typer.Option(
False, "--no-snapshot", help="Skip the Playwright site sampling step."
),
export_plan: Path | None = typer.Option(
None, "--export-plan", help="Optional path to persist the structured plan as JSON."
),
) -> None:
"""Generate a tailored Playwright script for the provided university website."""
settings = Settings()
engine = GenerationEngine(settings)
request = GenerationRequest(
target_url=url,
campus_name=campus,
assumed_language=language,
notes=notes,
max_depth=max_depth,
max_pages=max_pages,
)
result = engine.generate(request, capture_snapshot=not no_snapshot)
console = Console()
console.print(f"[green]Script saved to[/green] {result.script_path}")
_print_plan(result)
if export_plan:
export_plan.parent.mkdir(parents=True, exist_ok=True)
export_plan.write_text(
json.dumps(result.plan.model_dump(mode="json"), indent=2),
encoding="utf-8",
)
console.print(f"[blue]Plan exported to[/blue] {export_plan}")
def main():
app()
if __name__ == "__main__":
main()

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from __future__ import annotations
from pathlib import Path
from typing import Literal
from pydantic import Field
from pydantic_settings import BaseSettings
class Settings(BaseSettings):
"""Runtime configuration for the code-generation agent."""
model_provider: Literal["anthropic", "openai"] = Field(
default="anthropic",
description="LLM provider consumed through the Agno SDK.",
)
anthropic_model: str = Field(
default="claude-opus-4-5-20251101",
description="Default Anthropic model identifier.",
)
openai_model: str = Field(
default="o4-mini",
description="Default OpenAI model identifier.",
)
reasoning_enabled: bool = Field(
default=True,
description="Enable multi-step reasoning for higher-fidelity plans.",
)
reasoning_max_steps: int = Field(
default=12,
ge=1,
le=20,
description="Cap on how many explicit reasoning turns the agent can request.",
)
sample_pages: int = Field(
default=4,
ge=1,
le=25,
description="How many unique pages Playwright should snapshot before planning.",
)
sample_depth: int = Field(
default=2,
ge=1,
le=5,
description="Maximum depth of the limited site crawl performed for context.",
)
playwright_browser: Literal["chromium", "firefox", "webkit"] = Field(
default="chromium",
description="Browser engine used by the Playwright-powered sampler.",
)
playwright_headless: bool = Field(
default=True, description="Run Playwright in headless mode when sampling."
)
navigation_timeout_ms: int = Field(
default=20000,
ge=5000,
le=60000,
description="Timeout applied to each Playwright navigation call.",
)
output_dir: Path = Field(
default=Path("artifacts"),
description="Directory where generated scripts will be stored.",
)
default_script_name: str = Field(
default="university_playwright_scraper.py",
description="Fallback script name when the agent omits a filename.",
)
class Config:
env_prefix = "CODEGEN_"
env_file = ".env"
case_sensitive = False

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from __future__ import annotations
from rich.console import Console
from rich.text import Text
from .agent import ScriptAgent
from .config import Settings
from .models import GenerationRequest, GenerationResult, SiteSummary
from .renderer import ScriptRenderer
from .sampler import SiteSampler
from .writer import ScriptWriter
class GenerationEngine:
"""High-level orchestration that stitches together the sampler, agent, and renderer."""
def __init__(self, settings: Settings | None = None):
self.settings = settings or Settings()
self.console = Console()
self.sampler = SiteSampler(self.settings)
self.agent = ScriptAgent(self.settings)
self.renderer = ScriptRenderer()
self.writer = ScriptWriter(self.settings)
def _maybe_snapshot(self, request: GenerationRequest, capture: bool) -> SiteSummary | None:
if not capture:
return None
try:
self.console.log(
f"[cyan]Sampling[/cyan] {request.target_url} "
f"(pages={self.settings.sample_pages}, depth={self.settings.sample_depth})"
)
return self.sampler.snapshot(
request.target_url,
max_pages=self.settings.sample_pages,
max_depth=self.settings.sample_depth,
)
except RuntimeError as exc:
self.console.log(
Text("Playwright sampling failed. Continuing without snapshot.", style="yellow")
)
self.console.log(str(exc))
return None
def generate(
self, request: GenerationRequest, *, capture_snapshot: bool = True
) -> GenerationResult:
summary = self._maybe_snapshot(request, capture=capture_snapshot)
plan = self.agent.build_plan(request, summary)
script_body = self.renderer.render(plan, request, summary)
artifact = self.writer.write(plan, script_body)
return GenerationResult(
plan=plan,
request=request,
summary=summary,
script_path=artifact,
)

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from __future__ import annotations
from pathlib import Path
from pydantic import BaseModel, ConfigDict, Field, HttpUrl, field_validator
class GenerationRequest(BaseModel):
"""User intent passed to the agent when creating a scraper."""
target_url: HttpUrl | str
campus_name: str | None = Field(
default=None,
description="Optional human readable name for the campus or region.",
)
assumed_language: str | None = Field(
default=None,
description="Language hint to bias prompts and keyword selection.",
)
notes: str | None = Field(
default=None, description="Any speciality requirements for the scraper."
)
max_depth: int = Field(
default=2, ge=1, le=5, description="Maximum crawl depth for generated script."
)
max_pages: int = Field(
default=32,
ge=5,
le=200,
description="Safety cap for how many pages the script should traverse.",
)
class AnchorSample(BaseModel):
text: str
href: str
class SiteSample(BaseModel):
"""Summarised snapshot of a single page captured through Playwright."""
url: HttpUrl | str
title: str
snippet: str
anchors: list[AnchorSample] = Field(default_factory=list)
class SiteSummary(BaseModel):
target_url: HttpUrl | str
pages: list[SiteSample] = Field(default_factory=list)
truncated: bool = False
def to_prompt_section(self) -> str:
"""Render the summary as a markdown friendly text block."""
if not self.pages:
return "No browser snapshot was captured."
parts: list[str] = []
for idx, sample in enumerate(self.pages, start=1):
anchors = ", ".join(
f"{a.text.strip()[:64]} -> {a.href}" for a in sample.anchors[:6]
)
parts.append(
f"{idx}. {sample.title.strip()} ({sample.url})\n"
f" Snippet: {sample.snippet.strip()[:280]}\n"
f" Anchors: {anchors if anchors else 'n/a'}"
)
note = "\nSnapshot truncated." if self.truncated else ""
return "\n".join(parts) + note
class ScriptPlan(BaseModel):
"""Structured artifact we expect from the Agno agent."""
script_name: str = Field(
default="university_playwright_scraper.py",
description="Filename for the generated script.",
)
project_slug: str = Field(
description="A short kebab-case slug describing the university target."
)
description: str
master_program_keywords: list[str]
faculty_keywords: list[str]
exclusion_keywords: list[str] = Field(
default_factory=lambda: [
"admissions", "apply", "tuition", "financial aid", "login",
"news", "events", "alumni", "athletics", "giving", "donate",
"careers", "jobs", "contact", "sitemap"
]
)
metadata_fields: list[str] = Field(
default_factory=lambda: [
"url", "title", "entity_type", "department", "email", "scraped_at"
]
)
navigation_strategy: str
output_format: str = Field(
default="jsonl", description="Format used by the generated script."
)
verification_steps: list[str] = Field(default_factory=list)
extra_notes: list[str] = Field(default_factory=list)
model_config = ConfigDict(validate_assignment=True)
@field_validator("script_name")
@classmethod
def ensure_python_extension(cls, value: str) -> str:
if not value.endswith(".py"):
return f"{value}.py"
return value
@field_validator("project_slug")
@classmethod
def enforce_slug(cls, value: str) -> str:
return value.strip().replace(" ", "-").lower()
class GeneratedScript(BaseModel):
plan: ScriptPlan
request: GenerationRequest
summary: SiteSummary | None = None
script_body: str
artifact_path: Path
class GenerationResult(BaseModel):
plan: ScriptPlan
request: GenerationRequest
summary: SiteSummary | None = None
script_path: Path

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from __future__ import annotations
from datetime import UTC, datetime
from importlib import resources
from textwrap import dedent
from jinja2 import BaseLoader, Environment
from .models import GenerationRequest, ScriptPlan, SiteSummary
class ScriptRenderer:
"""Render a deterministic Python script using a Jinja template."""
def __init__(self) -> None:
template_text = resources.files("university_agent.templates").joinpath(
"playwright_script.py.jinja"
).read_text(encoding="utf-8")
self._env = Environment(
loader=BaseLoader(), trim_blocks=True, lstrip_blocks=True, autoescape=False
)
self._template = self._env.from_string(template_text)
def render(
self, plan: ScriptPlan, request: GenerationRequest, summary: SiteSummary | None
) -> str:
generated_at = datetime.now(tz=UTC).isoformat()
summary_text = summary.to_prompt_section() if summary else "No snapshot."
return self._template.render(
plan=plan,
request=request,
summary_text=summary_text,
generated_at=generated_at,
header=dedent(
f"""
Auto-generated by the Agno codegen agent.
Target university: {request.campus_name or 'unspecified'} ({request.target_url})
Requested caps: depth={request.max_depth}, pages={request.max_pages}
"""
).strip(),
)

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from __future__ import annotations
import asyncio
from collections import deque
from collections.abc import Iterable
from dataclasses import dataclass
from urllib.parse import urldefrag, urljoin
from pydantic import HttpUrl
from .config import Settings
from .models import AnchorSample, SiteSample, SiteSummary
def _normalize_url(base: str, raw: str) -> str:
absolute = urljoin(base, raw)
cleaned, _ = urldefrag(absolute)
return cleaned
@dataclass
class SiteSampler:
"""Lightweight Playwright-powered crawler used to prime the agent."""
settings: Settings
async def _gather(self, target: HttpUrl | str, max_pages: int, max_depth: int) -> SiteSummary:
try:
from playwright.async_api import async_playwright
except ImportError as exc:
raise RuntimeError(
"Playwright is required for sampling but is not installed. "
"Install it with `uv pip install playwright` and `playwright install`."
) from exc
summary = SiteSummary(target_url=target)
visited: set[str] = set()
queue: deque[tuple[str, int]] = deque([(str(target), 0)])
async with async_playwright() as p:
browser_launcher = getattr(p, self.settings.playwright_browser)
browser = await browser_launcher.launch(headless=self.settings.playwright_headless)
context = await browser.new_context()
try:
while queue and len(summary.pages) < max_pages:
url, depth = queue.popleft()
if url in visited or depth > max_depth:
continue
visited.add(url)
page = await context.new_page()
try:
timeout = self.settings.navigation_timeout_ms
await page.goto(url, wait_until="domcontentloaded", timeout=timeout)
except Exception:
await page.close()
continue
title = await page.title()
text_timeout = self.settings.navigation_timeout_ms // 2
snippet = await page.inner_text("body", timeout=text_timeout)
snippet = snippet.replace("\n", " ").strip()
snippet = snippet[:500]
anchors_raw: Iterable[dict] = await page.eval_on_selector_all(
"a",
"""elements => elements
.map(el => ({text: (el.textContent || '').trim(), href: el.href}))
.filter(item => item.href && item.text)""",
)
anchors: list[AnchorSample] = []
for anchor in anchors_raw:
if len(anchors) >= 12:
break
anchors.append(AnchorSample(text=anchor["text"][:80], href=anchor["href"]))
if depth < max_depth:
queue.append((_normalize_url(url, anchor["href"]), depth + 1))
summary.pages.append(
SiteSample(
url=url,
title=title or url,
snippet=snippet or "n/a",
anchors=anchors,
)
)
await page.close()
finally:
await context.close()
await browser.close()
summary.truncated = len(summary.pages) >= max_pages and bool(queue)
return summary
def snapshot(self, target: HttpUrl | str, *, max_pages: int, max_depth: int) -> SiteSummary:
"""Collect a synchronous snapshot by spinning up an event loop if needed."""
async def runner() -> SiteSummary:
return await self._gather(target, max_pages=max_pages, max_depth=max_depth)
try:
asyncio.get_running_loop()
except RuntimeError:
return asyncio.run(runner())
raise RuntimeError(
"The Playwright sampler cannot run inside an active asyncio loop. "
"Call the private `_gather` coroutine directly if you need async integration."
)

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#!/usr/bin/env python
"""
{{ header }}
Plan description: {{ plan.description }}
Navigation strategy: {{ plan.navigation_strategy }}
Verification checklist:
{% for step in plan.verification_steps -%}
- {{ step }}
{% endfor -%}
Playwright snapshot used to guide this plan:
{{ summary_text }}
Generated at: {{ generated_at }}
"""
from __future__ import annotations
import argparse
import asyncio
import json
import time
from collections import deque
from dataclasses import asdict, dataclass, field
from datetime import datetime, timezone
from pathlib import Path
from typing import Deque, Iterable, List, Set, Tuple
from urllib.parse import urljoin, urldefrag, urlparse
from playwright.async_api import async_playwright, Page, Response
PROGRAM_KEYWORDS = {{ plan.master_program_keywords }}
FACULTY_KEYWORDS = {{ plan.faculty_keywords }}
EXCLUSION_KEYWORDS = {{ plan.exclusion_keywords }}
METADATA_FIELDS = {{ plan.metadata_fields }}
EXTRA_NOTES = {{ plan.extra_notes }}
# URL patterns that indicate individual profile pages
PROFILE_URL_PATTERNS = [
"/people/", "/person/", "/profile/", "/profiles/",
"/faculty/", "/staff/", "/directory/",
"/~", # Unix-style personal pages
"/bio/", "/about/",
]
# URL patterns that indicate listing/directory pages (should be crawled deeper)
DIRECTORY_URL_PATTERNS = [
"/faculty", "/people", "/directory", "/staff",
"/team", "/members", "/researchers",
]
def normalize_url(base: str, href: str) -> str:
"""Normalize URL by resolving relative paths and removing fragments."""
absolute = urljoin(base, href)
cleaned, _ = urldefrag(absolute)
# Remove trailing slash for consistency
return cleaned.rstrip("/")
def matches_any(text: str, keywords: Iterable[str]) -> bool:
"""Check if text contains any of the keywords (case-insensitive)."""
lowered = text.lower()
return any(keyword.lower() in lowered for keyword in keywords)
def is_same_domain(url1: str, url2: str) -> bool:
"""Check if two URLs belong to the same root domain."""
domain1 = urlparse(url1).netloc.replace("www.", "")
domain2 = urlparse(url2).netloc.replace("www.", "")
# Allow subdomains of the same root domain
parts1 = domain1.split(".")
parts2 = domain2.split(".")
if len(parts1) >= 2 and len(parts2) >= 2:
return parts1[-2:] == parts2[-2:]
return domain1 == domain2
def is_profile_url(url: str) -> bool:
"""Check if URL pattern suggests an individual profile page."""
url_lower = url.lower()
return any(pattern in url_lower for pattern in PROFILE_URL_PATTERNS)
def is_directory_url(url: str) -> bool:
"""Check if URL pattern suggests a directory/listing page."""
url_lower = url.lower()
return any(pattern in url_lower for pattern in DIRECTORY_URL_PATTERNS)
@dataclass
class ScrapedLink:
url: str
title: str
text: str
source_url: str
bucket: str # "program" or "faculty"
is_verified: bool = False
http_status: int = 0
is_profile_page: bool = False
scraped_at: str = field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
@dataclass
class ScrapeSettings:
root_url: str
max_depth: int
max_pages: int
headless: bool
output: Path
verify_links: bool = True
request_delay: float = 1.0 # Polite crawling delay
async def extract_links(page: Page) -> List[Tuple[str, str]]:
"""Extract all anchor links from the page."""
anchors: Iterable[dict] = await page.eval_on_selector_all(
"a",
"""elements => elements
.map(el => ({text: (el.textContent || '').trim(), href: el.href}))
.filter(item => item.text && item.href && item.href.startsWith('http'))""",
)
return [(item["href"], item["text"]) for item in anchors]
async def get_page_title(page: Page) -> str:
"""Get the page title safely."""
try:
return await page.title() or ""
except Exception:
return ""
async def verify_link(context, url: str, timeout: int = 10000) -> Tuple[bool, int, str]:
"""
Verify a link by making a HEAD-like request.
Returns: (is_valid, status_code, page_title)
"""
page = await context.new_page()
try:
response: Response = await page.goto(url, wait_until="domcontentloaded", timeout=timeout)
if response:
status = response.status
title = await get_page_title(page)
is_valid = 200 <= status < 400
return is_valid, status, title
return False, 0, ""
except Exception:
return False, 0, ""
finally:
await page.close()
async def crawl(settings: ScrapeSettings, browser_name: str) -> List[ScrapedLink]:
"""
Crawl the website using BFS, collecting program and faculty links.
Features:
- URL deduplication
- Link verification
- Profile page detection
- Polite crawling with delays
"""
async with async_playwright() as p:
browser_launcher = getattr(p, browser_name)
browser = await browser_launcher.launch(headless=settings.headless)
context = await browser.new_context()
# Priority queue: (priority, url, depth) - lower priority = processed first
# Directory pages get priority 0, others get priority 1
queue: Deque[Tuple[int, str, int]] = deque([(0, settings.root_url, 0)])
visited: Set[str] = set()
found_urls: Set[str] = set() # For deduplication of results
results: List[ScrapedLink] = []
print(f"Starting crawl from: {settings.root_url}")
print(f"Max depth: {settings.max_depth}, Max pages: {settings.max_pages}")
try:
while queue and len(visited) < settings.max_pages:
# Sort queue by priority (directory pages first)
queue = deque(sorted(queue, key=lambda x: x[0]))
priority, url, depth = queue.popleft()
normalized_url = normalize_url(settings.root_url, url)
if normalized_url in visited or depth > settings.max_depth:
continue
# Only crawl same-domain URLs
if not is_same_domain(settings.root_url, normalized_url):
continue
visited.add(normalized_url)
print(f"[{len(visited)}/{settings.max_pages}] Depth {depth}: {normalized_url[:80]}...")
page = await context.new_page()
try:
response = await page.goto(
normalized_url, wait_until="domcontentloaded", timeout=20000
)
if not response or response.status >= 400:
await page.close()
continue
except Exception as e:
print(f" Error: {e}")
await page.close()
continue
page_title = await get_page_title(page)
links = await extract_links(page)
for href, text in links:
normalized_href = normalize_url(normalized_url, href)
# Skip if already found or is excluded
if normalized_href in found_urls:
continue
if matches_any(text, EXCLUSION_KEYWORDS) or matches_any(normalized_href, EXCLUSION_KEYWORDS):
continue
text_lower = text.lower()
href_lower = normalized_href.lower()
is_profile = is_profile_url(normalized_href)
# Check for program links
if matches_any(text_lower, PROGRAM_KEYWORDS) or matches_any(href_lower, PROGRAM_KEYWORDS):
found_urls.add(normalized_href)
results.append(
ScrapedLink(
url=normalized_href,
title="",
text=text[:200],
source_url=normalized_url,
bucket="program",
is_profile_page=False,
)
)
# Check for faculty links
if matches_any(text_lower, FACULTY_KEYWORDS) or matches_any(href_lower, FACULTY_KEYWORDS):
found_urls.add(normalized_href)
results.append(
ScrapedLink(
url=normalized_href,
title="",
text=text[:200],
source_url=normalized_url,
bucket="faculty",
is_profile_page=is_profile,
)
)
# Queue for further crawling
if depth < settings.max_depth and is_same_domain(settings.root_url, normalized_href):
# Prioritize directory pages
link_priority = 0 if is_directory_url(normalized_href) else 1
queue.append((link_priority, normalized_href, depth + 1))
await page.close()
# Polite delay between requests
await asyncio.sleep(settings.request_delay)
finally:
await context.close()
await browser.close()
# Verify links if enabled
if settings.verify_links and results:
print(f"\nVerifying {len(results)} links...")
browser = await browser_launcher.launch(headless=True)
context = await browser.new_context()
verified_results = []
for i, link in enumerate(results):
if link.url in [r.url for r in verified_results]:
continue # Skip duplicates
print(f" [{i+1}/{len(results)}] Verifying: {link.url[:60]}...")
is_valid, status, title = await verify_link(context, link.url)
link.is_verified = True
link.http_status = status
link.title = title or link.text
if is_valid:
verified_results.append(link)
else:
print(f" Invalid (HTTP {status})")
await asyncio.sleep(0.5) # Delay between verifications
await context.close()
await browser.close()
results = verified_results
return results
def deduplicate_results(results: List[ScrapedLink]) -> List[ScrapedLink]:
"""Remove duplicate URLs, keeping the first occurrence."""
seen: Set[str] = set()
unique = []
for link in results:
if link.url not in seen:
seen.add(link.url)
unique.append(link)
return unique
def serialize(results: List[ScrapedLink], target: Path, root_url: str) -> None:
"""Save results to JSON file with statistics."""
results = deduplicate_results(results)
program_links = [link for link in results if link.bucket == "program"]
faculty_links = [link for link in results if link.bucket == "faculty"]
profile_pages = [link for link in faculty_links if link.is_profile_page]
payload = {
"root_url": root_url,
"generated_at": datetime.now(timezone.utc).isoformat(),
"statistics": {
"total_links": len(results),
"program_links": len(program_links),
"faculty_links": len(faculty_links),
"profile_pages": len(profile_pages),
"verified_links": len([r for r in results if r.is_verified and r.http_status == 200]),
},
"program_links": [asdict(link) for link in program_links],
"faculty_links": [asdict(link) for link in faculty_links],
"notes": EXTRA_NOTES,
"metadata_fields": METADATA_FIELDS,
}
target.parent.mkdir(parents=True, exist_ok=True)
target.write_text(json.dumps(payload, indent=2, ensure_ascii=False), encoding="utf-8")
print(f"\nResults saved to: {target}")
print(f" Total links: {len(results)}")
print(f" Program links: {len(program_links)}")
print(f" Faculty links: {len(faculty_links)}")
print(f" Profile pages: {len(profile_pages)}")
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(
description="Playwright scraper generated by the Agno agent for {{ request.target_url }}."
)
parser.add_argument(
"--root-url",
default="{{ request.target_url }}",
help="Seed url to start crawling from.",
)
parser.add_argument(
"--max-depth",
type=int,
default={{ request.max_depth }},
help="Maximum crawl depth.",
)
parser.add_argument(
"--max-pages",
type=int,
default={{ request.max_pages }},
help="Maximum number of pages to visit.",
)
parser.add_argument(
"--output",
type=Path,
default=Path("{{ plan.project_slug }}_results.json"),
help="Where to save the JSON output.",
)
parser.add_argument(
"--headless",
action="store_true",
default=True,
help="Run browser in headless mode (default: True).",
)
parser.add_argument(
"--no-headless",
action="store_false",
dest="headless",
help="Run browser with visible window.",
)
parser.add_argument(
"--browser",
choices=["chromium", "firefox", "webkit"],
default="chromium",
help="Browser engine to launch via Playwright.",
)
parser.add_argument(
"--no-verify",
action="store_true",
default=False,
help="Skip link verification step.",
)
parser.add_argument(
"--delay",
type=float,
default=1.0,
help="Delay between requests in seconds (polite crawling).",
)
return parser.parse_args()
async def main_async() -> None:
args = parse_args()
settings = ScrapeSettings(
root_url=args.root_url,
max_depth=args.max_depth,
max_pages=args.max_pages,
headless=args.headless,
output=args.output,
verify_links=not args.no_verify,
request_delay=args.delay,
)
links = await crawl(settings, browser_name=args.browser)
serialize(links, settings.output, settings.root_url)
def main() -> None:
asyncio.run(main_async())
if __name__ == "__main__":
main()

View File

@ -0,0 +1,20 @@
from __future__ import annotations
from pathlib import Path
from .config import Settings
from .models import ScriptPlan
class ScriptWriter:
"""Persist generated scripts to disk."""
def __init__(self, settings: Settings):
self.settings = settings
def write(self, plan: ScriptPlan, script_body: str) -> Path:
filename = plan.script_name or self.settings.default_script_name
destination = self.settings.output_dir / filename
destination.parent.mkdir(parents=True, exist_ok=True)
destination.write_text(script_body, encoding="utf-8")
return destination

View File

@ -0,0 +1,689 @@
{
"root_url": "https://www.stanford.edu",
"program_links": [
{
"url": "http://facts.stanford.edu/academics/undergraduate",
"text": "Facts about the Undergraduate Program",
"source_url": "https://www.stanford.edu/academics/",
"bucket": "program"
},
{
"url": "http://facts.stanford.edu/academics/graduate-profile",
"text": "Facts about Graduate Studies",
"source_url": "https://www.stanford.edu/academics/",
"bucket": "program"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/directors-graduate-studies",
"text": "Directors of Graduate Studies",
"source_url": "https://vpge.stanford.edu/",
"bucket": "program"
},
{
"url": "https://humsci.stanford.edu/prospective-students/guide-getting-grad-school/funding-graduate-studies",
"text": "Funding Graduate Studies",
"source_url": "http://humsci.stanford.edu/",
"bucket": "program"
},
{
"url": "https://engineering.stanford.edu/students-academics/student-success-and-engagement/undergraduate-programs",
"text": "Undergraduate Programs",
"source_url": "http://engineering.stanford.edu/",
"bucket": "program"
},
{
"url": "https://engineering.stanford.edu/prospective-graduate-programs",
"text": "Prospective Graduate Programs",
"source_url": "http://engineering.stanford.edu/",
"bucket": "program"
},
{
"url": "https://engineering.stanford.edu/students-academics/student-success-and-engagement/graduate-programs",
"text": "Graduate Programs",
"source_url": "http://engineering.stanford.edu/",
"bucket": "program"
},
{
"url": "https://engineering.stanford.edu/students-academics/student-success-and-engagement/funding-and-financial-aid/funding-your-masters",
"text": "Funding Your Masters Degree",
"source_url": "http://engineering.stanford.edu/",
"bucket": "program"
}
],
"faculty_links": [
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/student-gateway/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/student-gateway/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/student-gateway/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Skip to content",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://facultyaffairs.stanford.edu/",
"text": "Faculty Affairs",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://facultysenate.stanford.edu/",
"text": "Faculty Senate",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://fsh.stanford.edu/",
"text": "Faculty Housing",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://facultydevelopment.stanford.edu/",
"text": "Faculty Development & Engagement",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://fingate.stanford.edu/faculty/",
"text": "Faculty Financial Activities",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://facultyclub.stanford.edu/",
"text": "Faculty Club",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://helpcenter.stanford.edu/",
"text": "Faculty/Staff Help Center",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "http://fingate.stanford.edu/faculty/",
"text": "Faculty Financial Activities",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/faculty-staff-gateway/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/academics/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/academics/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/academics/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/research/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/research/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/research/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/health-care/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/health-care/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/health-care/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/campus-life/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/campus-life/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/campus-life/",
"bucket": "faculty"
},
{
"url": "https://www.stanford.edu/faculty-staff-gateway/",
"text": "Faculty & Staff",
"source_url": "https://www.stanford.edu/about/",
"bucket": "faculty"
},
{
"url": "https://facts.stanford.edu/academics/faculty/",
"text": "Pulitzer Prizes, National Medals, and MacArthur Fellows",
"source_url": "https://www.stanford.edu/about/",
"bucket": "faculty"
},
{
"url": "https://stanfordwho.stanford.edu/",
"text": "Directory",
"source_url": "https://www.stanford.edu/about/",
"bucket": "faculty"
},
{
"url": "https://openfacultypositions.stanford.edu/",
"text": "Faculty Positions",
"source_url": "https://www.stanford.edu/about/",
"bucket": "faculty"
},
{
"url": "https://undergrad.stanford.edu/programs/bhc/faculty",
"text": "For Faculty",
"source_url": "https://undergrad.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpuefacstaff.sites.stanford.edu/",
"text": "For Faculty / Staff",
"source_url": "https://undergrad.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpuefacstaff.stanford.edu/",
"text": "For Faculty / Staff",
"source_url": "https://undergrad.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff",
"text": "Guidance for Faculty & Staff",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/advising-initiative",
"text": "Advising Initiative",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/advising-initiative/programs-faculty",
"text": "Programs for Faculty",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/advising-initiative/promising-practices-stanford",
"text": "Promising Practices at Stanford",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/advising-initiative/resources-stanford-beyond",
"text": "Resources at Stanford & Beyond",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/vpge-fellowship-policies",
"text": "VPGE Fellowship Policies",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/vpge-fellowship-policies/gfs-entry-information",
"text": "GFS Entry Information",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/directors-graduate-studies",
"text": "Directors of Graduate Studies",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/graduate-student-data",
"text": "Graduate Student Data",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/vpge-fellowship-policies",
"text": "VPGE Fellowship Policies",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/guidance-faculty-staff/vpge-fellowship-policies/gfs-entry-information",
"text": "GFS Entry Information",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/fellowships-funding/current-vpge-fellows/graduate-fellowships-faculty-advisory-committee",
"text": "Graduate Fellowships Faculty Advisory Committee",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/about-vpge/faculty-advisory-committee",
"text": "Faculty Advisory Committee",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/about-vpge/student-postdoc-advisory-committee",
"text": "Student & Postdoc Advisory Committee",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/information-faculty-staff",
"text": "Faculty & Staff",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://vpge.stanford.edu/gateways/information-faculty-staff",
"text": "Faculty & Staff",
"source_url": "https://vpge.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://humsci.stanford.edu/prospective-students/guide-getting-grad-school/interviewing-and-talking-prospective-faculty",
"text": "Interviewing and Talking with Prospective Faculty",
"source_url": "http://humsci.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://humsci.stanford.edu/sites/default/files/styles/fixed_height_2x/public/history_itm.png?itok=YBm3Ma2D",
"text": "View Professor Caroline Winterer discusses an archival book with students",
"source_url": "http://humsci.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://humsci.stanford.edu/sites/default/files/styles/fixed_height_2x/public/1-2025-white-plaza-observation-3.jpg?itok=6QlEgl-7",
"text": "View A photo of first year student Serena Young as she sits inside the White Plaza pavilion, observing people",
"source_url": "http://humsci.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/students-academics/student-success-and-engagement/graduate-programs/deans-graduate-student",
"text": "Deans Graduate Student Advisory Council",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research",
"text": "Faculty & Research",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty",
"text": "Faculty",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty/emeritus",
"text": "Emeritus Faculty",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty/memoriam",
"text": "In Memoriam",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments",
"text": "Departments",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/aeronautics-astronautics",
"text": "Aeronautics & Astronautics",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/bioengineering",
"text": "Bioengineering",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/chemical-engineering",
"text": "Chemical Engineering",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/civil-environmental-engineering",
"text": "Civil & Environmental Engineering",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/computer-science",
"text": "Computer Science",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/electrical-engineering",
"text": "Electrical Engineering",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/management-science-engineering",
"text": "Management Science & Engineering",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/materials-science-engineering",
"text": "Materials Science & Engineering",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/departments/mechanical-engineering",
"text": "Mechanical Engineering",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/institutes-labs-and-centers",
"text": "Institutes, Labs and Centers",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards",
"text": "Faculty Awards",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2025-26",
"text": "Faculty Awards 2025-2026",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2024-25",
"text": "Faculty Awards 2024-2025",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2023-24",
"text": "Faculty Awards 2023-2024",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2022-2023",
"text": "Faculty Awards 2022-2023",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2021-2022",
"text": "Faculty Awards 2021-2022",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2020-2021",
"text": "Faculty Awards 2020-2021",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2019-2020",
"text": "Faculty Awards 2019-2020",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2018-2019",
"text": "Faculty Awards 2018-2019",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2016-2017",
"text": "Faculty Awards 2016-2017",
"source_url": "http://engineering.stanford.edu/",
"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2015-2016",
"text": "Faculty Awards 2015-2016",
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{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2014-2015",
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"bucket": "faculty"
},
{
"url": "https://engineering.stanford.edu/faculty-research/faculty-awards/faculty-awards-2012-2013",
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"text": "faculty",
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],
"notes": [
"Stanford's seven schools each host their own subdomains (e.g., engineering.stanford.edu, law.stanford.edu); the script should allow cross-subdomain crawling within *.stanford.edu while still counting against the page cap.",
"Many program pages load additional content via JavaScript; use page.wait_for_load_state('networkidle') or explicit waits before extracting links.",
"Faculty directories may paginate or use infinite scroll; handle at least the first visible batch given the tight page cap.",
"Respect polite crawling: insert a 1-2 second delay between requests to avoid rate-limiting."
],
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}

48
test_run.py Normal file
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@ -0,0 +1,48 @@
#!/usr/bin/env python
"""Quick test script to run the agent."""
import os
# Load environment variables from User scope
import ctypes
from ctypes import wintypes
def get_user_env(name):
"""Get user environment variable on Windows."""
try:
import winreg
with winreg.OpenKey(winreg.HKEY_CURRENT_USER, r"Environment") as key:
return winreg.QueryValueEx(key, name)[0]
except Exception:
return os.environ.get(name)
# Set environment variables
api_key = get_user_env("ANTHROPIC_API_KEY")
base_url = get_user_env("ANTHROPIC_BASE_URL")
if api_key:
os.environ["ANTHROPIC_API_KEY"] = api_key
if base_url:
os.environ["ANTHROPIC_BASE_URL"] = base_url
print(f"API Key set: {bool(api_key)}")
print(f"Base URL: {base_url}")
# Run the agent
from university_agent import GenerationEngine, GenerationRequest, Settings
settings = Settings()
print(f"Using model: {settings.anthropic_model}")
engine = GenerationEngine(settings)
request = GenerationRequest(
target_url="https://www.stanford.edu",
campus_name="Stanford",
assumed_language="English",
max_depth=3, # Increased depth to reach individual profiles
max_pages=30, # More pages to explore
)
print("Starting generation...")
result = engine.generate(request, capture_snapshot=True)
print(f"Script saved to: {result.script_path}")
print(f"Project slug: {result.plan.project_slug}")

762
uv.lock generated Normal file
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{ name = "ty" },
]
[package.dev-dependencies]
dev = [
{ name = "ruff" },
{ name = "ty" },
]
[package.metadata]
requires-dist = [
{ name = "agno", specifier = ">=2.3.8" },
{ name = "httpx", specifier = ">=0.28" },
{ name = "jinja2", specifier = ">=3.1" },
{ name = "playwright", specifier = ">=1.48" },
{ name = "pydantic", specifier = ">=2.9" },
{ name = "pydantic-settings", specifier = ">=2.6" },
{ name = "rich", specifier = ">=13.7" },
{ name = "ruff", marker = "extra == 'dev'", specifier = ">=0.6.9" },
{ name = "ty", marker = "extra == 'dev'", specifier = ">=0.0.1a32" },
{ name = "typer", specifier = ">=0.12.5" },
]
provides-extras = ["dev"]
[package.metadata.requires-dev]
dev = [
{ name = "ruff", specifier = ">=0.6.9" },
{ name = "ty", specifier = ">=0.0.1a32" },
]

4
任务1.txt Normal file
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构建一个自动化生成代码的agent给定一个海外大学官网的网址生成一套或者说一个python脚本能够爬取这个大学各级学院下的所有硕士项目的网址 和 硕士项目中各导师个人信息的网址
agent系统使用 https://docs.agno.com/
然后其中的浏览器自动化使用playwright
使用的python工具库是uv、ruff、ty使用这三个构建项目。