Traigent

Debug and troubleshoot Traigent optimization issues. Use when encountering CostLimitExceeded, ConfigurationError, OptimizationStateError, ModuleNotFoundError, or when optimization produces unexpected results. Covers mock mode, logging configuration, and common error resolution.

Configure the @traigent.optimize() decorator with evaluation, injection, and execution options. Use when setting up eval_dataset, choosing injection_mode, configuring execution_mode, defining objectives, using EvaluationOptions/InjectionOptions/ExecutionOptions, or integrating custom evaluators.

Run Traigent optimization: async/sync execution, algorithm selection, cost limits, stop conditions, and parallel trials. Use when calling func.optimize() or optimize_sync(), choosing algorithms (grid/random — locally; bayesian/optuna/tpe run in the Traigent cloud), setting max_trials or cost_limit, configuring parallel execution, or handling CostLimitExceeded.

Install and set up the Traigent SDK for LLM optimization. Use when the user wants to install traigent, set up their first optimization, create an eval dataset, or get started with @traigent.optimize. Covers pip install, environment variables, mock mode, and running a first optimization.

Analyze Traigent optimization results: best config, trial comparison, convergence, cost, and applying results to production. Use when reading results.best_config, comparing trials, checking stop_reason, calling apply_best_config(), accessing total_cost or total_tokens, or understanding why optimization stopped.

Integrate Traigent with LangChain, LiteLLM, DSPy, and other AI frameworks. Use when importing langchain/litellm/dspy alongside traigent, setting up multi-provider model testing, using auto_override_frameworks, or asking about framework-specific adapter patterns.

Define tuned variables and configuration spaces for Traigent optimization. Use when setting up parameter search spaces, choosing models/temperatures/prompts to optimize, using Range/IntRange/Choices/LogRange types, adding constraints between parameters, or using factory presets like Range.temperature().