394ac1befa
* Add Anthropic and Grok provider support * feat: Add crucial GPT-5 and reasoning model support for OpenRouter - Add requires_max_completion_tokens() function for GPT-5, o1, o3, Grok-3 series - Add prepare_chat_completion_params() for reasoning model compatibility - Implement max_tokens → max_completion_tokens conversion for reasoning models - Add temperature handling for reasoning models (must be 1.0 default) - Enhanced provider validation and API key security in provider endpoints - Streamlined retry logic (3→2 attempts) for faster issue detection - Add failure tracking and circuit breaker analysis for debugging - Support OpenRouter format detection (openai/gpt-5-nano, openai/o1-mini) - Improved Grok provider empty response handling with structured fallbacks - Enhanced contextual embedding with provider-aware model selection Core provider functionality: - OpenRouter, Grok, Anthropic provider support with full embedding integration - Provider-specific model defaults and validation - Secure API connectivity testing endpoints - Provider context passing for code generation workflows 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * fully working model providers, addressing securtiy and code related concerns, throughly hardening our code * added multiprovider support, embeddings model support, cleaned the pr, need to fix health check, asnyico tasks errors, and contextual embeddings error * fixed contextual embeddings issue * - Added inspect-aware shutdown handling so get_llm_client always closes the underlying AsyncOpenAI / httpx.AsyncClient while the loop is still alive, with defensive logging if shutdown happens late (python/src/server/services/llm_provider_service.py:14, python/src/server/ services/llm_provider_service.py:520). * - Restructured get_llm_client so client creation and usage live in separate try/finally blocks; fallback clients now close without logging spurious Error creating LLM client when downstream code raises (python/src/server/services/llm_provider_service.py:335-556). - Close logic now sanitizes provider names consistently and awaits whichever aclose/close coroutine the SDK exposes, keeping the loop shut down cleanly (python/src/server/services/llm_provider_service.py:530-559). Robust JSON Parsing - Added _extract_json_payload to strip code fences / extra text returned by Ollama before json.loads runs, averting the markdown-induced decode errors you saw in logs (python/src/server/services/storage/code_storage_service.py:40-63). - Swapped the direct parse call for the sanitized payload and emit a debug preview when cleanup alters the content (python/src/server/ services/storage/code_storage_service.py:858-864). * added provider connection support * added provider api key not being configured warning * Updated get_llm_client so missing OpenAI keys automatically fall back to Ollama (matching existing tests) and so unsupported providers still raise the legacy ValueError the suite expects. The fallback now reuses _get_optimal_ollama_instance and rethrows ValueError(OpenAI API key not found and Ollama fallback failed) when it cant connect. Adjusted test_code_extraction_source_id.py to accept the new optional argument on the mocked extractor (and confirm its None when present). * Resolved a few needed code rabbit suggestion - Updated the knowledge API key validation to call create_embedding with the provider argument and removed the hard-coded OpenAI fallback (python/src/server/api_routes/knowledge_api.py). - Broadened embedding provider detection so prefixed OpenRouter/OpenAI model names route through the correct client (python/src/server/ services/embeddings/embedding_service.py, python/src/server/services/llm_provider_service.py). - Removed the duplicate helper definitions from llm_provider_service.py, eliminating the stray docstring that was causing the import-time syntax error. * updated via code rabbit PR review, code rabbit in my IDE found no issues and no nitpicks with the updates! what was done: Credential service now persists the provider under the uppercase key LLM_PROVIDER, matching the read path (no new EMBEDDING_PROVIDER usage introduced). Embedding batch creation stops inserting blank strings, logging failures and skipping invalid items before they ever hit the provider (python/src/server/services/embeddings/embedding_service.py). Contextual embedding prompts use real newline characters everywhereboth when constructing the batch prompt and when parsing the models response (python/src/server/services/embeddings/contextual_embedding_service.py). Embedding provider routing already recognizes OpenRouter-prefixed OpenAI models via is_openai_embedding_model; no further change needed there. Embedding insertion now skips unsupported vector dimensions instead of forcing them into the 1536-column, and the backoff loop uses await asyncio.sleep so we no longer block the event loop (python/src/server/services/storage/code_storage_service.py). RAG settings props were extended to include LLM_INSTANCE_NAME and OLLAMA_EMBEDDING_INSTANCE_NAME, and the debug log no longer prints API-key prefixes (the rest of the TanStack refactor/EMBEDDING_PROVIDER support remains deferred). * test fix * enhanced Openrouters parsing logic to automatically detect reasoning models and parse regardless of json output or not. this commit creates a robust way for archons parsing to work throughly with openrouter automatically, regardless of the model youre using, to ensure proper functionality with out breaking any generation capabilities! --------- Co-authored-by: Chillbruhhh <joshchesser97@gmail.com> Co-authored-by: Claude <noreply@anthropic.com>
759 lines
33 KiB
Python
759 lines
33 KiB
Python
"""
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Crawling Service Module for Archon RAG
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This module combines crawling functionality and orchestration.
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It handles web crawling operations including single page crawling,
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batch crawling, recursive crawling, and overall orchestration with progress tracking.
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"""
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import asyncio
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import uuid
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from collections.abc import Awaitable, Callable
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from typing import Any, Optional
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from ...config.logfire_config import get_logger, safe_logfire_error, safe_logfire_info
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from ...utils import get_supabase_client
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from ...utils.progress.progress_tracker import ProgressTracker
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# Import strategies
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# Import operations
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from .document_storage_operations import DocumentStorageOperations
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from .helpers.site_config import SiteConfig
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# Import helpers
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from .helpers.url_handler import URLHandler
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from .progress_mapper import ProgressMapper
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from .strategies.batch import BatchCrawlStrategy
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from .strategies.recursive import RecursiveCrawlStrategy
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from .strategies.single_page import SinglePageCrawlStrategy
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from .strategies.sitemap import SitemapCrawlStrategy
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logger = get_logger(__name__)
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# Global registry to track active orchestration services for cancellation support
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_active_orchestrations: dict[str, "CrawlingService"] = {}
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def get_active_orchestration(progress_id: str) -> Optional["CrawlingService"]:
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"""Get an active orchestration service by progress ID."""
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return _active_orchestrations.get(progress_id)
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def register_orchestration(progress_id: str, orchestration: "CrawlingService"):
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"""Register an active orchestration service."""
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_active_orchestrations[progress_id] = orchestration
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def unregister_orchestration(progress_id: str):
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"""Unregister an orchestration service."""
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if progress_id in _active_orchestrations:
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del _active_orchestrations[progress_id]
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class CrawlingService:
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"""
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Service class for web crawling and orchestration operations.
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Combines functionality from both CrawlingService and CrawlOrchestrationService.
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"""
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def __init__(self, crawler=None, supabase_client=None, progress_id=None):
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"""
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Initialize the crawling service.
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Args:
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crawler: The Crawl4AI crawler instance
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supabase_client: The Supabase client for database operations
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progress_id: Optional progress ID for HTTP polling updates
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"""
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self.crawler = crawler
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self.supabase_client = supabase_client or get_supabase_client()
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self.progress_id = progress_id
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self.progress_tracker = None
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# Initialize helpers
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self.url_handler = URLHandler()
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self.site_config = SiteConfig()
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self.markdown_generator = self.site_config.get_markdown_generator()
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self.link_pruning_markdown_generator = self.site_config.get_link_pruning_markdown_generator()
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# Initialize strategies
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self.batch_strategy = BatchCrawlStrategy(crawler, self.link_pruning_markdown_generator)
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self.recursive_strategy = RecursiveCrawlStrategy(crawler, self.link_pruning_markdown_generator)
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self.single_page_strategy = SinglePageCrawlStrategy(crawler, self.markdown_generator)
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self.sitemap_strategy = SitemapCrawlStrategy()
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# Initialize operations
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self.doc_storage_ops = DocumentStorageOperations(self.supabase_client)
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# Track progress state across all stages to prevent UI resets
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self.progress_state = {"progressId": self.progress_id} if self.progress_id else {}
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# Initialize progress mapper to prevent backwards jumps
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self.progress_mapper = ProgressMapper()
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# Cancellation support
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self._cancelled = False
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def set_progress_id(self, progress_id: str):
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"""Set the progress ID for HTTP polling updates."""
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self.progress_id = progress_id
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if self.progress_id:
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self.progress_state = {"progressId": self.progress_id}
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# Initialize progress tracker for HTTP polling
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self.progress_tracker = ProgressTracker(progress_id, operation_type="crawl")
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def cancel(self):
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"""Cancel the crawl operation."""
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self._cancelled = True
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safe_logfire_info(f"Crawl operation cancelled | progress_id={self.progress_id}")
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def is_cancelled(self) -> bool:
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"""Check if the crawl operation has been cancelled."""
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return self._cancelled
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def _check_cancellation(self):
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"""Check if cancelled and raise an exception if so."""
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if self._cancelled:
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raise asyncio.CancelledError("Crawl operation was cancelled by user")
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async def _create_crawl_progress_callback(
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self, base_status: str
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) -> Callable[[str, int, str], Awaitable[None]]:
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"""Create a progress callback for crawling operations.
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Args:
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base_status: The base status to use for progress updates
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Returns:
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Async callback function with signature (status: str, progress: int, message: str, **kwargs) -> None
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"""
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async def callback(status: str, progress: int, message: str, **kwargs):
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if self.progress_tracker:
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# Debug log what we're receiving
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safe_logfire_info(
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f"Progress callback received | status={status} | progress={progress} | "
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f"total_pages={kwargs.get('total_pages', 'N/A')} | processed_pages={kwargs.get('processed_pages', 'N/A')} | "
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f"kwargs_keys={list(kwargs.keys())}"
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)
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# Map the progress to the overall progress range
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mapped_progress = self.progress_mapper.map_progress(base_status, progress)
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# Update progress via tracker (stores in memory for HTTP polling)
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await self.progress_tracker.update(
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status=base_status,
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progress=mapped_progress,
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log=message,
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**kwargs
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)
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safe_logfire_info(
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f"Updated crawl progress | progress_id={self.progress_id} | status={base_status} | "
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f"raw_progress={progress} | mapped_progress={mapped_progress} | "
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f"total_pages={kwargs.get('total_pages', 'N/A')} | processed_pages={kwargs.get('processed_pages', 'N/A')}"
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)
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return callback
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async def _handle_progress_update(self, task_id: str, update: dict[str, Any]) -> None:
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"""
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Handle progress updates from background task.
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Args:
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task_id: The task ID for the progress update
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update: Dictionary containing progress update data
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"""
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if self.progress_tracker:
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# Update progress via tracker for HTTP polling
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await self.progress_tracker.update(
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status=update.get("status", "processing"),
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progress=update.get("progress", update.get("percentage", 0)), # Support both for compatibility
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log=update.get("log", "Processing..."),
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**{k: v for k, v in update.items() if k not in ["status", "progress", "percentage", "log"]}
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)
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# Simple delegation methods for backward compatibility
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async def crawl_single_page(self, url: str, retry_count: int = 3) -> dict[str, Any]:
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"""Crawl a single web page."""
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return await self.single_page_strategy.crawl_single_page(
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url,
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self.url_handler.transform_github_url,
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self.site_config.is_documentation_site,
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retry_count,
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)
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async def crawl_markdown_file(
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self, url: str, progress_callback: Callable[[str, int, str], Awaitable[None]] | None = None
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) -> list[dict[str, Any]]:
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"""Crawl a .txt or markdown file."""
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return await self.single_page_strategy.crawl_markdown_file(
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url,
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self.url_handler.transform_github_url,
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progress_callback,
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)
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def parse_sitemap(self, sitemap_url: str) -> list[str]:
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"""Parse a sitemap and extract URLs."""
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return self.sitemap_strategy.parse_sitemap(sitemap_url, self._check_cancellation)
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async def crawl_batch_with_progress(
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self,
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urls: list[str],
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max_concurrent: int | None = None,
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progress_callback: Callable[[str, int, str], Awaitable[None]] | None = None,
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) -> list[dict[str, Any]]:
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"""Batch crawl multiple URLs in parallel."""
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return await self.batch_strategy.crawl_batch_with_progress(
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urls,
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self.url_handler.transform_github_url,
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self.site_config.is_documentation_site,
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max_concurrent,
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progress_callback,
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self._check_cancellation, # Pass cancellation check
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)
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async def crawl_recursive_with_progress(
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self,
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start_urls: list[str],
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max_depth: int = 3,
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max_concurrent: int | None = None,
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progress_callback: Callable[[str, int, str], Awaitable[None]] | None = None,
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) -> list[dict[str, Any]]:
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"""Recursively crawl internal links from start URLs."""
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return await self.recursive_strategy.crawl_recursive_with_progress(
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start_urls,
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self.url_handler.transform_github_url,
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self.site_config.is_documentation_site,
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max_depth,
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max_concurrent,
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progress_callback,
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self._check_cancellation, # Pass cancellation check
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)
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# Orchestration methods
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async def orchestrate_crawl(self, request: dict[str, Any]) -> dict[str, Any]:
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"""
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Main orchestration method - non-blocking using asyncio.create_task.
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Args:
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request: The crawl request containing url, knowledge_type, tags, max_depth, etc.
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Returns:
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Dict containing task_id, status, and the asyncio task reference
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"""
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url = str(request.get("url", ""))
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safe_logfire_info(f"Starting background crawl orchestration | url={url}")
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# Create task ID
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task_id = self.progress_id or str(uuid.uuid4())
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# Register this orchestration service for cancellation support
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if self.progress_id:
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register_orchestration(self.progress_id, self)
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# Start the crawl as an async task in the main event loop
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# Store the task reference for proper cancellation
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crawl_task = asyncio.create_task(self._async_orchestrate_crawl(request, task_id))
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# Set a name for the task to help with debugging
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if self.progress_id:
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crawl_task.set_name(f"crawl_{self.progress_id}")
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# Return immediately with task reference
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return {
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"task_id": task_id,
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"status": "started",
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"message": f"Crawl operation started for {url}",
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"progress_id": self.progress_id,
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"task": crawl_task, # Return the actual task for proper cancellation
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}
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async def _async_orchestrate_crawl(self, request: dict[str, Any], task_id: str):
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"""
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Async orchestration that runs in the main event loop.
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"""
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last_heartbeat = asyncio.get_event_loop().time()
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heartbeat_interval = 30.0 # Send heartbeat every 30 seconds
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async def send_heartbeat_if_needed():
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"""Send heartbeat to keep connection alive"""
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nonlocal last_heartbeat
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current_time = asyncio.get_event_loop().time()
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if current_time - last_heartbeat >= heartbeat_interval:
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await self._handle_progress_update(
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task_id,
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{
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"status": self.progress_mapper.get_current_stage(),
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"progress": self.progress_mapper.get_current_progress(),
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"heartbeat": True,
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"log": "Background task still running...",
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"message": "Processing...",
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},
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)
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last_heartbeat = current_time
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try:
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url = str(request.get("url", ""))
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safe_logfire_info(f"Starting async crawl orchestration | url={url} | task_id={task_id}")
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# Start the progress tracker if available
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if self.progress_tracker:
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await self.progress_tracker.start({
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"url": url,
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"status": "starting",
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"progress": 0,
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"log": f"Starting crawl of {url}"
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})
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# Generate unique source_id and display name from the original URL
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original_source_id = self.url_handler.generate_unique_source_id(url)
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source_display_name = self.url_handler.extract_display_name(url)
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safe_logfire_info(
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f"Generated unique source_id '{original_source_id}' and display name '{source_display_name}' from URL '{url}'"
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)
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# Helper to update progress with mapper
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async def update_mapped_progress(
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stage: str, stage_progress: int, message: str, **kwargs
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):
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overall_progress = self.progress_mapper.map_progress(stage, stage_progress)
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await self._handle_progress_update(
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task_id,
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{
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"status": stage,
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"progress": overall_progress,
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"log": message,
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"message": message,
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**kwargs,
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},
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)
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# Initial progress
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await update_mapped_progress(
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"starting", 100, f"Starting crawl of {url}", current_url=url
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)
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# Check for cancellation before proceeding
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self._check_cancellation()
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# Analyzing stage - report initial page count (at least 1)
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await update_mapped_progress(
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"analyzing", 50, f"Analyzing URL type for {url}",
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total_pages=1, # We know we have at least the start URL
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processed_pages=0
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)
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# Detect URL type and perform crawl
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crawl_results, crawl_type = await self._crawl_by_url_type(url, request)
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# Update progress tracker with crawl type
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if self.progress_tracker and crawl_type:
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# Use mapper to get correct progress value
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mapped_progress = self.progress_mapper.map_progress("crawling", 100) # 100% of crawling stage
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await self.progress_tracker.update(
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status="crawling",
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progress=mapped_progress,
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log=f"Processing {crawl_type} content",
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crawl_type=crawl_type
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)
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# Check for cancellation after crawling
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self._check_cancellation()
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# Send heartbeat after potentially long crawl operation
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await send_heartbeat_if_needed()
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if not crawl_results:
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raise ValueError("No content was crawled from the provided URL")
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# Processing stage
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await update_mapped_progress("processing", 50, "Processing crawled content")
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# Check for cancellation before document processing
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self._check_cancellation()
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# Calculate total work units for accurate progress tracking
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total_pages = len(crawl_results)
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# Process and store documents using document storage operations
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last_logged_progress = 0
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async def doc_storage_callback(
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status: str, progress: int, message: str, **kwargs
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):
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nonlocal last_logged_progress
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# Log only significant progress milestones (every 5%) or status changes
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should_log_debug = (
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status != "document_storage" or # Status changes
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progress == 100 or # Completion
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progress == 0 or # Start
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abs(progress - last_logged_progress) >= 5 # 5% progress changes
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)
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if should_log_debug:
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safe_logfire_info(
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f"Document storage progress: {progress}% | status={status} | "
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f"message={message[:50]}..." + ("..." if len(message) > 50 else "")
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)
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last_logged_progress = progress
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if self.progress_tracker:
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# Use ProgressMapper to ensure progress never goes backwards
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mapped_progress = self.progress_mapper.map_progress("document_storage", progress)
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# Update progress state via tracker
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await self.progress_tracker.update(
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status="document_storage",
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progress=mapped_progress,
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log=message,
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total_pages=total_pages,
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**kwargs
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)
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storage_results = await self.doc_storage_ops.process_and_store_documents(
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crawl_results,
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request,
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crawl_type,
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original_source_id,
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doc_storage_callback,
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self._check_cancellation,
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source_url=url,
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source_display_name=source_display_name,
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)
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|
|
# Update progress tracker with source_id now that it's created
|
|
if self.progress_tracker and storage_results.get("source_id"):
|
|
# Update the tracker to include source_id for frontend matching
|
|
# Use update method to maintain timestamps and invariants
|
|
await self.progress_tracker.update(
|
|
status=self.progress_tracker.state.get("status", "document_storage"),
|
|
progress=self.progress_tracker.state.get("progress", 0),
|
|
log=self.progress_tracker.state.get("log", "Processing documents"),
|
|
source_id=storage_results["source_id"]
|
|
)
|
|
safe_logfire_info(
|
|
f"Updated progress tracker with source_id | progress_id={self.progress_id} | source_id={storage_results['source_id']}"
|
|
)
|
|
|
|
# Check for cancellation after document storage
|
|
self._check_cancellation()
|
|
|
|
# Send heartbeat after document storage
|
|
await send_heartbeat_if_needed()
|
|
|
|
# CRITICAL: Verify that chunks were actually stored
|
|
actual_chunks_stored = storage_results.get("chunks_stored", 0)
|
|
if storage_results["chunk_count"] > 0 and actual_chunks_stored == 0:
|
|
# We processed chunks but none were stored - this is a failure
|
|
error_msg = (
|
|
f"Failed to store documents: {storage_results['chunk_count']} chunks processed but 0 stored "
|
|
f"| url={url} | progress_id={self.progress_id}"
|
|
)
|
|
safe_logfire_error(error_msg)
|
|
raise ValueError(error_msg)
|
|
|
|
# Extract code examples if requested
|
|
code_examples_count = 0
|
|
if request.get("extract_code_examples", True) and actual_chunks_stored > 0:
|
|
# Check for cancellation before starting code extraction
|
|
self._check_cancellation()
|
|
|
|
await update_mapped_progress("code_extraction", 0, "Starting code extraction...")
|
|
|
|
# Create progress callback for code extraction
|
|
async def code_progress_callback(data: dict):
|
|
if self.progress_tracker:
|
|
# Use ProgressMapper to ensure progress never goes backwards
|
|
raw_progress = data.get("progress", data.get("percentage", 0))
|
|
mapped_progress = self.progress_mapper.map_progress("code_extraction", raw_progress)
|
|
|
|
# Update progress state via tracker
|
|
await self.progress_tracker.update(
|
|
status=data.get("status", "code_extraction"),
|
|
progress=mapped_progress,
|
|
log=data.get("log", "Extracting code examples..."),
|
|
total_pages=total_pages, # Include total context
|
|
**{k: v for k, v in data.items() if k not in ["status", "progress", "percentage", "log"]}
|
|
)
|
|
|
|
try:
|
|
# Extract provider from request or use credential service default
|
|
provider = request.get("provider")
|
|
if not provider:
|
|
try:
|
|
from ..credential_service import credential_service
|
|
provider_config = await credential_service.get_active_provider("llm")
|
|
provider = provider_config.get("provider", "openai")
|
|
except Exception as e:
|
|
logger.warning(f"Failed to get provider from credential service: {e}, defaulting to openai")
|
|
provider = "openai"
|
|
|
|
code_examples_count = await self.doc_storage_ops.extract_and_store_code_examples(
|
|
crawl_results,
|
|
storage_results["url_to_full_document"],
|
|
storage_results["source_id"],
|
|
code_progress_callback,
|
|
self._check_cancellation,
|
|
provider,
|
|
)
|
|
except RuntimeError as e:
|
|
# Code extraction failed, continue crawl with warning
|
|
logger.error("Code extraction failed, continuing crawl without code examples", exc_info=True)
|
|
safe_logfire_error(f"Code extraction failed | error={e}")
|
|
code_examples_count = 0
|
|
|
|
# Report code extraction failure to progress tracker
|
|
if self.progress_tracker:
|
|
await self.progress_tracker.update(
|
|
status="code_extraction",
|
|
progress=self.progress_mapper.map_progress("code_extraction", 100),
|
|
log=f"Code extraction failed: {str(e)}. Continuing crawl without code examples.",
|
|
total_pages=total_pages,
|
|
)
|
|
|
|
# Check for cancellation after code extraction
|
|
self._check_cancellation()
|
|
|
|
# Send heartbeat after code extraction
|
|
await send_heartbeat_if_needed()
|
|
|
|
# Finalization
|
|
await update_mapped_progress(
|
|
"finalization",
|
|
50,
|
|
"Finalizing crawl results...",
|
|
chunks_stored=actual_chunks_stored,
|
|
code_examples_found=code_examples_count,
|
|
)
|
|
|
|
# Complete - send both the progress update and completion event
|
|
await update_mapped_progress(
|
|
"completed",
|
|
100,
|
|
f"Crawl completed: {actual_chunks_stored} chunks, {code_examples_count} code examples",
|
|
chunks_stored=actual_chunks_stored,
|
|
code_examples_found=code_examples_count,
|
|
processed_pages=len(crawl_results),
|
|
total_pages=len(crawl_results),
|
|
)
|
|
|
|
# Mark crawl as completed
|
|
if self.progress_tracker:
|
|
await self.progress_tracker.complete({
|
|
"chunks_stored": actual_chunks_stored,
|
|
"code_examples_found": code_examples_count,
|
|
"processed_pages": len(crawl_results),
|
|
"total_pages": len(crawl_results),
|
|
"sourceId": storage_results.get("source_id", ""),
|
|
"log": "Crawl completed successfully!",
|
|
})
|
|
|
|
# Unregister after successful completion
|
|
if self.progress_id:
|
|
unregister_orchestration(self.progress_id)
|
|
safe_logfire_info(
|
|
f"Unregistered orchestration service after completion | progress_id={self.progress_id}"
|
|
)
|
|
|
|
except asyncio.CancelledError:
|
|
safe_logfire_info(f"Crawl operation cancelled | progress_id={self.progress_id}")
|
|
# Use ProgressMapper to get proper progress value for cancelled state
|
|
cancelled_progress = self.progress_mapper.map_progress("cancelled", 0)
|
|
await self._handle_progress_update(
|
|
task_id,
|
|
{
|
|
"status": "cancelled",
|
|
"progress": cancelled_progress,
|
|
"log": "Crawl operation was cancelled by user",
|
|
},
|
|
)
|
|
# Unregister on cancellation
|
|
if self.progress_id:
|
|
unregister_orchestration(self.progress_id)
|
|
safe_logfire_info(
|
|
f"Unregistered orchestration service on cancellation | progress_id={self.progress_id}"
|
|
)
|
|
except Exception as e:
|
|
# Log full stack trace for debugging
|
|
logger.error("Async crawl orchestration failed", exc_info=True)
|
|
safe_logfire_error(f"Async crawl orchestration failed | error={str(e)}")
|
|
error_message = f"Crawl failed: {str(e)}"
|
|
# Use ProgressMapper to get proper progress value for error state
|
|
error_progress = self.progress_mapper.map_progress("error", 0)
|
|
await self._handle_progress_update(
|
|
task_id, {
|
|
"status": "error",
|
|
"progress": error_progress,
|
|
"log": error_message,
|
|
"error": str(e)
|
|
}
|
|
)
|
|
# Mark error in progress tracker with standardized schema
|
|
if self.progress_tracker:
|
|
await self.progress_tracker.error(error_message)
|
|
# Unregister on error
|
|
if self.progress_id:
|
|
unregister_orchestration(self.progress_id)
|
|
safe_logfire_info(
|
|
f"Unregistered orchestration service on error | progress_id={self.progress_id}"
|
|
)
|
|
|
|
def _is_self_link(self, link: str, base_url: str) -> bool:
|
|
"""
|
|
Check if a link is a self-referential link to the base URL.
|
|
Handles query parameters, fragments, trailing slashes, and normalizes
|
|
scheme/host/ports for accurate comparison.
|
|
|
|
Args:
|
|
link: The link to check
|
|
base_url: The base URL to compare against
|
|
|
|
Returns:
|
|
True if the link is self-referential, False otherwise
|
|
"""
|
|
try:
|
|
from urllib.parse import urlparse
|
|
|
|
def _core(u: str) -> str:
|
|
p = urlparse(u)
|
|
scheme = (p.scheme or "http").lower()
|
|
host = (p.hostname or "").lower()
|
|
port = p.port
|
|
if (scheme == "http" and port in (None, 80)) or (scheme == "https" and port in (None, 443)):
|
|
port_part = ""
|
|
else:
|
|
port_part = f":{port}" if port else ""
|
|
path = p.path.rstrip("/")
|
|
return f"{scheme}://{host}{port_part}{path}"
|
|
|
|
return _core(link) == _core(base_url)
|
|
except Exception as e:
|
|
logger.warning(f"Error checking if link is self-referential: {e}", exc_info=True)
|
|
# Fallback to simple string comparison
|
|
return link.rstrip('/') == base_url.rstrip('/')
|
|
|
|
async def _crawl_by_url_type(self, url: str, request: dict[str, Any]) -> tuple:
|
|
"""
|
|
Detect URL type and perform appropriate crawling.
|
|
|
|
Returns:
|
|
Tuple of (crawl_results, crawl_type)
|
|
"""
|
|
crawl_results = []
|
|
crawl_type = None
|
|
|
|
# Helper to update progress with mapper
|
|
async def update_crawl_progress(stage_progress: int, message: str, **kwargs):
|
|
if self.progress_tracker:
|
|
mapped_progress = self.progress_mapper.map_progress("crawling", stage_progress)
|
|
await self.progress_tracker.update(
|
|
status="crawling",
|
|
progress=mapped_progress,
|
|
log=message,
|
|
current_url=url,
|
|
**kwargs
|
|
)
|
|
|
|
if self.url_handler.is_txt(url) or self.url_handler.is_markdown(url):
|
|
# Handle text files
|
|
crawl_type = "llms-txt" if "llms" in url.lower() else "text_file"
|
|
await update_crawl_progress(
|
|
50, # 50% of crawling stage
|
|
"Detected text file, fetching content...",
|
|
crawl_type=crawl_type
|
|
)
|
|
crawl_results = await self.crawl_markdown_file(
|
|
url,
|
|
progress_callback=await self._create_crawl_progress_callback("crawling"),
|
|
)
|
|
# Check if this is a link collection file and extract links
|
|
if crawl_results and len(crawl_results) > 0:
|
|
content = crawl_results[0].get('markdown', '')
|
|
if self.url_handler.is_link_collection_file(url, content):
|
|
# Extract links from the content
|
|
extracted_links = self.url_handler.extract_markdown_links(content, url)
|
|
|
|
# Filter out self-referential links to avoid redundant crawling
|
|
if extracted_links:
|
|
original_count = len(extracted_links)
|
|
extracted_links = [
|
|
link for link in extracted_links
|
|
if not self._is_self_link(link, url)
|
|
]
|
|
self_filtered_count = original_count - len(extracted_links)
|
|
if self_filtered_count > 0:
|
|
logger.info(f"Filtered out {self_filtered_count} self-referential links from {original_count} extracted links")
|
|
|
|
# Filter out binary files (PDFs, images, archives, etc.) to avoid wasteful crawling
|
|
if extracted_links:
|
|
original_count = len(extracted_links)
|
|
extracted_links = [link for link in extracted_links if not self.url_handler.is_binary_file(link)]
|
|
filtered_count = original_count - len(extracted_links)
|
|
if filtered_count > 0:
|
|
logger.info(f"Filtered out {filtered_count} binary files from {original_count} extracted links")
|
|
|
|
if extracted_links:
|
|
# Crawl the extracted links using batch crawling
|
|
logger.info(f"Crawling {len(extracted_links)} extracted links from {url}")
|
|
batch_results = await self.crawl_batch_with_progress(
|
|
extracted_links,
|
|
max_concurrent=request.get('max_concurrent'), # None -> use DB settings
|
|
progress_callback=await self._create_crawl_progress_callback("crawling"),
|
|
)
|
|
|
|
# Combine original text file results with batch results
|
|
crawl_results.extend(batch_results)
|
|
crawl_type = "link_collection_with_crawled_links"
|
|
|
|
logger.info(f"Link collection crawling completed: {len(crawl_results)} total results (1 text file + {len(batch_results)} extracted links)")
|
|
else:
|
|
logger.info(f"No valid links found in link collection file: {url}")
|
|
logger.info(f"Text file crawling completed: {len(crawl_results)} results")
|
|
|
|
elif self.url_handler.is_sitemap(url):
|
|
# Handle sitemaps
|
|
crawl_type = "sitemap"
|
|
await update_crawl_progress(
|
|
50, # 50% of crawling stage
|
|
"Detected sitemap, parsing URLs...",
|
|
crawl_type=crawl_type
|
|
)
|
|
sitemap_urls = self.parse_sitemap(url)
|
|
|
|
if sitemap_urls:
|
|
# Update progress before starting batch crawl
|
|
await update_crawl_progress(
|
|
75, # 75% of crawling stage
|
|
f"Starting batch crawl of {len(sitemap_urls)} URLs...",
|
|
crawl_type=crawl_type
|
|
)
|
|
|
|
crawl_results = await self.crawl_batch_with_progress(
|
|
sitemap_urls,
|
|
progress_callback=await self._create_crawl_progress_callback("crawling"),
|
|
)
|
|
|
|
else:
|
|
# Handle regular webpages with recursive crawling
|
|
crawl_type = "normal"
|
|
await update_crawl_progress(
|
|
50, # 50% of crawling stage
|
|
f"Starting recursive crawl with max depth {request.get('max_depth', 1)}...",
|
|
crawl_type=crawl_type
|
|
)
|
|
|
|
max_depth = request.get("max_depth", 1)
|
|
# Let the strategy handle concurrency from settings
|
|
# This will use CRAWL_MAX_CONCURRENT from database (default: 10)
|
|
|
|
crawl_results = await self.crawl_recursive_with_progress(
|
|
[url],
|
|
max_depth=max_depth,
|
|
max_concurrent=None, # Let strategy use settings
|
|
progress_callback=await self._create_crawl_progress_callback("crawling"),
|
|
)
|
|
|
|
return crawl_results, crawl_type
|
|
|
|
|
|
# Alias for backward compatibility
|
|
CrawlOrchestrationService = CrawlingService
|