FrootAI Python SDK

Direct Python APIs for FrootAI knowledge, Solution Plays, FAI Protocol wiring, evaluation, and trusted federation.

Python product page · Setup guide · PyPI · API docs

Choose SDK or Python MCP

The SDK is Python-standard-library based with zero runtime dependencies. Bundled knowledge and search work offline. Federation is lazy, but the current default client is deliberately transport-pending: applications must inject a supported transport before making live federation calls.

Five steps to first value

1. Install and verify

python -m pip install --upgrade frootai
frootai --version

Requirements: Python 3.10 or newer. Published classifiers cover Python 3.10–3.13.

2. Search bundled knowledge

from frootai import FrootAI

fai = FrootAI()

for result in fai.search("secure enterprise RAG", max_results=3):
    print(result["id"], result["title"], result["score"])

module = fai.get_module("R2")
print(module["title"] if module else "Module not found")

Knowledge, glossary, Play metadata, and the BM25 search index are packaged with the wheel. No API key is required for these operations.

3. Inspect a Solution Play and cost direction

from frootai import FrootAI, SolutionPlay

fai = FrootAI()
play = SolutionPlay.get("01")
if play:
    print(play.name, play.complexity)

estimate = fai.estimate_cost("01-enterprise-rag", scale="prod")
print(estimate)

Cost output is directional reference data, not a cloud bill or deployment quote. Confirm region, SKU, traffic, retention, and current provider pricing before committing spend.

4. Wire and validate the FAI Protocol

from frootai import FrootAI

fai = FrootAI()
manifest = fai.wire_play("01")
validation = fai.validate_manifest(manifest)

print(validation)

# Preview before creating a project structure
preview = fai.scaffold_play("01", project_name="customer-rag", dry_run=True)
print(preview)

The manifest connects knowledge, WAF context, agents, instructions, skills, hooks, and guardrails. Validation reports structure and references; it does not deploy infrastructure.

5. Evaluate quality or connect trusted tools

from frootai import Evaluator

scores = {
    "groundedness": 4.6,
    "relevance": 4.2,
    "coherence": 4.4,
    "fluency": 4.5,
}

evaluator = Evaluator()
print(evaluator.summary(scores))
print("passed:", evaluator.all_passed(scores))

Federation is optional and asynchronous. The current SDK exposes the client contract but does not silently start a kernel transport:

from frootai.federation import create_federation_client

# `transport` implements: async call({"method": str, "params": mapping})
mcp = create_federation_client(
    transport=your_transport,
    federation={
        "pre_attach": ["azure"],
        "trust_file": "/etc/frootai/trust.json",
        "idle_disconnect_minutes": 30,
    },
)

async def inspect_azure() -> None:
    handle = await mcp.attach({"name": "azure", "trustOverride": True})
    tools = await mcp.list_tools(handle)
    print([tool["qualifiedName"] for tool in tools])
    await mcp.detach(handle)

Without an injected transport, federation calls fail explicitly with kernel_connection_pending (or remote_mode_pending for the reserved remote mode). Review publisher evidence, credentials, tool annotations, and permissions before overriding a trust decision.

API map

from frootai import SolutionPlay

all_plays = SolutionPlay.all()
ready_plays = SolutionPlay.ready()
rag_plays = SolutionPlay.search("RAG")
play = SolutionPlay.get("01")

from frootai import resolve_primitive, fetch_primitive

resolved = resolve_primitive("fai-rag-architect", lean_mode=True)
content = fetch_primitive("fai-rag-architect", lean_mode=True)

from frootai.ab_testing import PromptExperiment, PromptVariant

experiment = PromptExperiment(
    name="rag-prompt",
    variants=[
        PromptVariant("control", "Answer with citations."),
        PromptVariant("concise", "Answer briefly and cite sources."),
    ],
)

results = experiment.run(
    test_queries=["What is hybrid search?"],
    model_fn=your_model_callback,
    scorer_fn=your_scorer_callback,
)
print(experiment.summary(results))

result = await mcp.chain([
    {"tool": "azure.subscription_list", "args": {"tier": "verified"}},
    {
        "tool": "azure.resource_list",
        "mapPrev": lambda previous: {"subscription": previous["id"]},
    },
])

Command-line reference

Operating boundaries

Verify and develop

cd python-sdk
python -m pip install --upgrade build pytest
python -m pytest tests -v
python -m build

Related packages

License

MIT © 2026 FrootAI.