praisonai-train Package

Train agents or fine-tune LLMs without installing the full PraisonAI wrapper. The praisonai-train PyPI package (import: praisonai_train) is Tier 2c — it sits on top of praisonaiagents and gives you the train CLI group and a standalone praisonai-train console script.

Quick Start

Agent Training

Improve an agent iteratively — no ML dependencies required.

from praisonaiagents import Agent

agent = Agent(instructions="You are a helpful assistant.")

pip install praisonai-train

praisonai-train agents --input "What is Python?"

LLM Fine-tuning

Add the [llm] extra to pull the Unsloth/torch stack.

pip install "praisonai-train[llm]"

praisonai-train llm dataset.json \
    --model unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit

When to Use `praisonai-train` vs `praisonai train`

Install the standalone package when you only need training; use the wrapper’s praisonai train when you already run the full stack. Both entry points expose the same commands: every praisonai train <sub> also runs as praisonai-train <sub>.

CLI Subcommands

Five subcommands cover fine-tuning and agent training.

Subcommand	Purpose
`praisonai-train llm DATASET`	Fine-tune an LLM via Unsloth
`praisonai-train agents [AGENT_FILE]`	Iteratively train an agent
`praisonai-train list`	List training sessions
`praisonai-train show SESSION_ID`	Show a session’s iterations and best score
`praisonai-train apply SESSION_ID`	Apply learned suggestions to an agent

See Train CLI for full flags.

Common Patterns

Train, review, apply

Run a training session, inspect the iterations, then bake the best one into your agent.

praisonai-train agents --input "Explain AI" --human
praisonai-train list
praisonai-train show train-abc123 --iterations
praisonai-train apply train-abc123 --run "Explain AI"

Apply in Python

Apply a session’s suggestions to an agent directly.

from praisonaiagents import Agent
from praisonai_train.train.agents import apply_training

agent = Agent(instructions="You are a helpful assistant.")
apply_training(agent, session_id="train-abc123")

Best Practices

Install the base package for agent training

pip install praisonai-train pulls only praisonaiagents — enough for agents, list, show, and apply. Add [llm] only when you need Unsloth fine-tuning.

Use the standalone script when you don't want the wrapper

The praisonai-train console script exposes the full train group without installing praisonai. Ideal for lightweight training-only environments.

Old imports keep working

Existing praisonai.train.*, praisonai.train_vision, and praisonai.upload_vision imports still resolve to the same module objects in praisonai_train. Nothing to migrate.

Backward-compatible: if you already have the wrapper installed, praisonai.train.* imports and the setup-conda-env entry point continue to work unchanged.

Train

Training overview and fine-tuning setup.

Train CLI

Full flag reference for the five subcommands.

Installation Extras

The train install matrix.

Package Tiers

How the five packages stack.

Package Tier Architecture

Clarify Tool

​Quick Start

​When to Use praisonai-train vs praisonai train

​CLI Subcommands

​Common Patterns

​Train, review, apply

​Apply in Python

​Best Practices

​Related

Train

Train CLI

Installation Extras

Package Tiers

Quick Start

When to Use `praisonai-train` vs `praisonai train`

CLI Subcommands

Common Patterns

Train, review, apply

Apply in Python

Best Practices

Related