Analysis Capability

AnalysisCapability adds search, citations, and sandboxed Python computation over the document corpus. Use it for counts, aggregation, comparison, structural traversal, and section-scoped reading.

It is deferred by default, keeping its substantial instructions and tool schemas out of context until the model chooses to load it.

The default request limit is 30 model requests per question. Override it with create_capability(request_limit=...), or set request_limit=None to disable it. As with the RAG capability, create_capability(vision=...) overrides the image-attachment gate, defaulting to the configured analysis model's vision flag. At the limit, only analysis tools are removed and the model gets one more turn to answer from gathered evidence. Other agent and capability tools remain available, and the budget resets for every agent run.

Tools

The sandbox exposes documents under /documents/{document_id}/ with metadata.json, content.txt, items.jsonl, and toc.json.

Compose with RAG

from pydantic_ai import Agent
from haiku.rag.capabilities.analysis import create_capability as analysis
from haiku.rag.capabilities.rag import create_capability as rag

agent = Agent(
    "openai:gpt-5",
    capabilities=[
        rag(db_path="my.lancedb"),
        analysis(db_path="my.lancedb"),
    ],
)

For the high-level convenience API:

from haiku.rag.client import HaikuRAG

async with HaikuRAG("my.lancedb") as client:
    result = await client.analyze("Which quarter had the highest revenue?")
    print(result.answer)

State

When dependencies expose a state dictionary, AnalysisState is stored under "analysis". It contains the document filter, code execution log, searches, and citations. Per-run searches and executions reset automatically; the filter and citation index persist.

The capability lazily opens both LanceDB and the sandbox only after it is loaded and a tool requires them. Resources close at the end of the agent run.