Run your first Kapso campaign in under ten minutes

kapso doctor evolve

solution.goal              # the goal you gave it
solution.code_path         # directory holding the winning code
solution.final_score       # score of the delivered solution
solution.succeeded         # whether the goal was met
solution.experiment_logs   # one summary per experiment
solution.final_feedback    # the last feedback, including the stop decision
solution.metadata          # cost, iteration count, final evaluation
solution.explain()         # all of the above as readable text

cd ./iris_solution
git branch -a

  generic_exp_0
  generic_exp_1
* generic_exp_2
  main

from kapso import Kapso, DeployStrategy

deployed = kapso.deploy(solution, strategy=DeployStrategy.LOCAL)
result = deployed.run({"data_path": "./test.csv"})
deployed.stop()

findings = kapso.research(
    "QLoRA fine-tuning memory optimizations",
    mode=["idea", "implementation"],
    depth="deep",
)

solution = kapso.evolve(
    goal="Fine-tune Llama-3.1-8B with QLoRA, target eval loss < 0.5",
    context=[findings.to_string()],
    output_path="./qlora_v1",
)

kapso = Kapso()
kapso.index_kg(
    wiki_dir="data/wikis",
    save_to="data/indexes/finetuning.index",
)

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