TouAI

Complete Examples

Use these end-to-end snippets as starting points for real applications and automation workflows.

RAG Pipeline

from touai import TouAI
 
with TouAI() as client:
    conn = client.context_hub.connections.create(
        name="Analytics DB",
        connector_type="postgresql",
        credentials={"host": "db.example.com", "database": "analytics", "...": "..."},
        auto_sync=True,
    )
 
    client.context_hub.sync.wait_until_ready(conn.connection_id, timeout=300)
 
    results = client.context_hub.search(
        "What were our top-performing products in Q1?",
        connection_ids=[conn.connection_id],
        top_k=10,
        rerank=True,
    )
 
    for r in results.results:
        print(f"[{r.similarity:.2f}] {r.content[:150]}")

Document Processing Pipeline

from touai import TouAI
 
with TouAI() as client:
    job = client.unstructured.jobs.create(
        source={"source_type": "url", "url": "https://example.com/report.pdf"},
        options={"chunking": {"enabled": True}},
    )
 
    result = client.unstructured.jobs.wait_until_complete(job.job_id)
    print(f"Processed: {result.status}")
 
    research = client.deep_research.research(
        "Summarize the key findings from the processed document",
        mode="pro",
    )
    print(research.content)

Web Intelligence Gathering

from touai import TouAI
 
with TouAI() as client:
    crawl = client.data_search.deep_crawl_and_wait(
        "https://docs.example.com",
        max_depth=3,
        max_pages=100,
        timeout=300,
    )
    print(f"Crawled {len(crawl.pages)} pages")
 
    for event in client.deep_research.research_stream(
        "What are the main features documented on this site?",
        mode="pro",
    ):
        if event.type == "complete":
            print(event.data.get("content"))

These examples are intended to be copied and adapted. Start with the simplest one that matches your workflow, then add auth, retries, and persistence for your production environment.

Type Reference