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LLM HTML Extractor Symfony Bundle

A powerful Symfony bundle for extracting structured data from HTML using LLM (Large Language Model) providers with a plugin architecture.

Features

• LLM-Based Extraction: Uses LLM providers (starting with Jina Reader) to extract structured data from HTML
• Type-Safe DTOs: Define extraction schemas using PHP attributes on your DTOs
• Hybrid Extraction: Easily combine LLM extraction with code-based extraction - use AI for complex fields and DomCrawler/XPath for simple structured data
• Extensible: Plugin architecture allows custom extractors for specific use cases
• Cacheable: Built-in caching support for LLM responses
• Logging: Optional logging for LLM requests/responses and cache operations
• Configurable: Flexible configuration for different LLM providers and caching strategies

Installation

Configuration

Create or update config/packages/llm_html_extractor.yaml:

Alternatively, you can use an existing HTTP client service:

Using a Custom LLM Client

To use your own LLM client implementation, just set the client parameter to your service ID:

Your custom client must implement LlmHtmlExtractor\SymfonyBundle\Client\LlmClientInterface. The bundle will validate this during container compilation and throw a clear error if the interface is not implemented.

Logging

The bundle provides comprehensive logging for debugging and monitoring:

• Request/Response Logging: When logs.enabled: true, all LLM requests and responses are logged at info level
• Cache Operations: Cache hits and misses are logged when both caching and logging are enabled
• Error Logging: Failed LLM requests are logged at error level with exception details

The decorators are applied in this order:

1. Base LLM Client (e.g., JinaReaderLlmClient)
2. LoggingLlmClient (if logs enabled) - logs requests/responses
3. CacheableLlmClient (if cache enabled) - logs cache hits/misses

This means logged requests show the actual LLM calls (cache misses), not cached responses.

Usage

1. Define Your Extraction DTO

2. Use the Extraction Handler

3. Create Custom Extractors (Optional)

For specific extraction needs, implement the FromHtmlExtractorInterface:

Supported LLM Providers

Currently supported:

• Jina Reader (jinaai/readerlm-v2, jinaai/readerlm-v1.5)
  • Uses vLLM OpenAI API standard endpoint (/openai/v1/chat/completions)
  • Tested with Runpod serverless deployments
  • Compatible with any vLLM deployment following the OpenAI API standard

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.