Kapso: long-running agents for AI and Data

from kapso import Kapso, Source, DeployStrategy

kapso = Kapso(kg_index="data/indexes/legal_contracts.index")

# Research the problem space
findings = kapso.research(
    "RLHF and DPO fine-tuning for legal contract analysis",
    mode=["idea", "implementation"],
    depth="deep",
)

# Fold public knowledge into the knowledge graph
kapso.learn_knowledge(
    Source.Repo("https://github.com/huggingface/trl"),
    findings,
    wiki_dir="data/wikis",
)

# Run the campaign
solution = kapso.evolve(
    goal=(
        "Fine-tune Llama-3.1-8B on the CUAD dataset for legal clause risk "
        "classification, target F1 > 0.85 on high-risk clause detection"
    ),
    context=[findings.to_string()],
    output_path="./models/legal_risk_v1",
)

# Bank what the campaign learned, so the next one starts ahead
kapso.learn(solution)

# Ship it
deployed = kapso.deploy(solution, strategy=DeployStrategy.MODAL)