be63c98db3
Implements comprehensive hooks functionality allowing users to provide custom Python functions as strings that execute at specific points in the crawling pipeline. Key Features: - Support for all 8 crawl4ai hook points: • on_browser_created: Initialize browser settings • on_page_context_created: Configure page context • before_goto: Pre-navigation setup • after_goto: Post-navigation processing • on_user_agent_updated: User agent modification handling • on_execution_started: Crawl execution initialization • before_retrieve_html: Pre-extraction processing • before_return_html: Final HTML processing Implementation Details: - Created UserHookManager for validation, compilation, and safe execution - Added IsolatedHookWrapper for error isolation and timeout protection - AST-based validation ensures code structure correctness - Sandboxed execution with restricted builtins for security - Configurable timeout (1-120 seconds) prevents infinite loops - Comprehensive error handling ensures hooks don't crash main process - Execution tracking with detailed statistics and logging API Changes: - Added HookConfig schema with code and timeout fields - Extended CrawlRequest with optional hooks parameter - Added /hooks/info endpoint for hook discovery - Updated /crawl and /crawl/stream endpoints to support hooks Safety Features: - Malformed hooks return clear validation errors - Hook errors are isolated and reported without stopping crawl - Execution statistics track success/failure/timeout rates - All hook results are JSON-serializable Testing: - Comprehensive test suite covering all 8 hooks - Error handling and timeout scenarios validated - Authentication, performance, and content extraction examples - 100% success rate in production testing Documentation: - Added extensive hooks section to docker-deployment.md - Security warnings about user-provided code risks - Real-world examples using httpbin.org, GitHub, BBC - Best practices and troubleshooting guide ref #1377
86 lines
2.6 KiB
Python
86 lines
2.6 KiB
Python
from typing import List, Optional, Dict
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from enum import Enum
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from pydantic import BaseModel, Field
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from utils import FilterType
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class CrawlRequest(BaseModel):
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urls: List[str] = Field(min_length=1, max_length=100)
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browser_config: Optional[Dict] = Field(default_factory=dict)
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crawler_config: Optional[Dict] = Field(default_factory=dict)
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class HookConfig(BaseModel):
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"""Configuration for user-provided hooks"""
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code: Dict[str, str] = Field(
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default_factory=dict,
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description="Map of hook points to Python code strings"
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)
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timeout: int = Field(
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default=30,
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ge=1,
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le=120,
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description="Timeout in seconds for each hook execution"
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)
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class Config:
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schema_extra = {
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"example": {
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"code": {
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"on_page_context_created": """
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async def hook(page, context, **kwargs):
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# Block images to speed up crawling
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await context.route("**/*.{png,jpg,jpeg,gif}", lambda route: route.abort())
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return page
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""",
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"before_retrieve_html": """
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async def hook(page, context, **kwargs):
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# Scroll to load lazy content
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await page.evaluate("window.scrollTo(0, document.body.scrollHeight)")
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await page.wait_for_timeout(2000)
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return page
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"""
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},
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"timeout": 30
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}
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}
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class CrawlRequestWithHooks(CrawlRequest):
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"""Extended crawl request with hooks support"""
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hooks: Optional[HookConfig] = Field(
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default=None,
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description="Optional user-provided hook functions"
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)
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class MarkdownRequest(BaseModel):
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"""Request body for the /md endpoint."""
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url: str = Field(..., description="Absolute http/https URL to fetch")
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f: FilterType = Field(FilterType.FIT, description="Content‑filter strategy: fit, raw, bm25, or llm")
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q: Optional[str] = Field(None, description="Query string used by BM25/LLM filters")
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c: Optional[str] = Field("0", description="Cache‑bust / revision counter")
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provider: Optional[str] = Field(None, description="LLM provider override (e.g., 'anthropic/claude-3-opus')")
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class RawCode(BaseModel):
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code: str
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class HTMLRequest(BaseModel):
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url: str
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class ScreenshotRequest(BaseModel):
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url: str
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screenshot_wait_for: Optional[float] = 2
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output_path: Optional[str] = None
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class PDFRequest(BaseModel):
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url: str
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output_path: Optional[str] = None
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class JSEndpointRequest(BaseModel):
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url: str
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scripts: List[str] = Field(
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...,
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description="List of separated JavaScript snippets to execute"
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) |