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Modern applications often require structured data, but most information on the web exists in unstructured formats such as HTML pages. SiteScriber is an API-driven solution that transforms any website into a structured, queryable API. Built using FastAPI, Firecrawl, and LangChain, the system extracts website content, structures it into JSON, and refines responses using large language models. This approach enables reliable data extraction workflows for analysis, automation, and downstream system integration.
SiteScriber introduces a FastAPI-based service that converts websites into structured APIs on demand. The system uses Firecrawl to crawl and extract website content, including dynamic pages, and LangChain with OpenAI models to refine and structure the extracted data. Users can define custom schemas to control output structure, and the API returns both raw extracted data and refined, human-readable responses in JSON format.
Users send a POST request to the /extract endpoint with a website URL, extraction prompt, and optional schema.
Firecrawl crawls the target website and extracts relevant content, including dynamic elements.
If a schema is provided, extracted content is organized into structured fields.
LangChain processes extracted data using OpenAI models to generate refined responses based on the user prompt.
The API returns a JSON response containing both raw extracted data and the refined answer.
FastAPI automatically exposes Swagger and ReDoc interfaces for testing and validation.

Architectural Diagram - SiteScriber for Converting Websites into Structured APIs
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Transforms website content into structured API responses accessible via a single endpoint
Allows users to define custom output structures for consistent and predictable data formats
Handles both static and JavaScript-rendered websites during crawling
Returns raw extracted content along with refined and contextualized responses
Uses user-defined prompts to control how extracted data is interpreted and summarized
Enables extracted data to be reused across analytics, databases, and automation workflows
Provides REST API endpoints and automatic interactive documentation
Extracts content from static and dynamic websites
Orchestrates prompt-driven refinement and data processing workflows
Interprets, summarizes, and refines extracted website content
Validates request payloads and response structures
Enables high-performance API execution and local development
Manages API keys and runtime configuration securely
SiteScriber demonstrates how websites can be transformed into structured, API-accessible data sources using modern AI and crawling technologies. By combining robust content extraction with schema-based structuring and prompt-driven refinement, the solution simplifies data ingestion from unstructured web sources. The architecture provides a practical foundation for building scalable data pipelines and automation workflows driven by real-world web content.

Teams exploring structured data extraction and website-to-API workflows can use approaches like SiteScriber to simplify content ingestion and improve downstream data usability. Learn more about practical GenAI-driven data automation patterns at GenAIProtos.