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Async Operations

structx provides asynchronous versions of all extraction methods for better performance in async environments.

Basic Async Extraction

import asyncio

async def extract_data():
    result = await extractor.extract_async(
        data="scripts/example_input/free-consultancy-agreement.docx",
        query="extract the main parties and the effective date"
    )
    return result

# Run the async function
result = asyncio.run(extract_data())

Async Methods

For each synchronous method, there is an async counterpart:

Synchronous Method Asynchronous Method
extract extract_async
extract_queries extract_queries_async
get_schema get_schema_async

Parallel Processing

Process multiple documents in parallel:

Async Processing Flow

View Async Processing Flow Diagram 
graph TB
    A[Multiple Files] --> B[Create Async Tasks]
    B --> C[Parallel Execution]

    C --> D1[File 1 Processing]
    C --> D2[File 2 Processing]
    C --> D3[File 3 Processing]
    C --> D4[File N Processing]

    D1 --> E1[Result 1]
    D2 --> E2[Result 2]
    D3 --> E3[Result 3]
    D4 --> E4[Result N]

    E1 --> F[Gather Results]
    E2 --> F
    E3 --> F
    E4 --> F

    F --> G[Combined Output]

    subgraph "Concurrent Execution"
        D1
        D2
        D3
        D4
    end
import asyncio

async def process_documents(docs):
    tasks = []
    for doc_path, query in docs.items():
        task = extractor.extract_async(
            data=doc_path,
            query=query
        )
        tasks.append(task)

    results = await asyncio.gather(*tasks)
    return results

documents = {
    "scripts/example_input/free-consultancy-agreement.docx": "extract parties and governing law",
    "scripts/example_input/S0305SampleInvoice.pdf": "extract invoice number and total amount"
}
results = asyncio.run(process_documents(documents))

Combining with Other Async Operations

import asyncio
import aiofiles

async def read_and_extract(file_path, query):
    # Asynchronously read a file
    async with aiofiles.open(file_path, mode='r') as f:
        content = await f.read()

    # Extract information from the content
    result = await extractor.extract_async(
        data=content,
        query=query
    )

    return result

result = asyncio.run(read_and_extract("path/to/your/document.txt", "extract key details"))

Async Multiple Queries

import asyncio

async def process_multiple_queries():
    queries = [
        "extract all clauses related to payment",
        "extract termination conditions",
        "summarize the scope of services"
    ]

    results = await extractor.extract_queries_async(
        data="scripts/example_input/free-consultancy-agreement.docx",
        queries=queries
    )

    return results

results = asyncio.run(process_multiple_queries())

Best Practices

  1. Use in Async Environments: Only use async methods in async environments
  2. Limit Concurrency: Be mindful of API rate limits when processing in parallel
  3. Handle Errors: Use try/except with async operations
  4. Close Resources: Ensure proper cleanup of resources in async contexts

Next Steps