FlashLearn

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FlashLearn is an open-source AI Agents & Automation tool that simplifies the integration of Agent LLMs into workflows and ETL pipelines. It provides a simple interface for data transformations, classifications, summarizations, and custom multi-step tasks.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is FlashLearn?

FlashLearn is an open-source tool designed to integrate Large Language Models (LLMs) into existing workflows and ETL pipelines with ease. It offers a simple interface and orchestration capabilities, supporting up to 1000 calls per minute for tasks like data transformations, classifications, summarizations, rewriting, and custom multi-step processes. The tool leverages a compact JSON definition for each step and task, ensuring pipelines are easy to understand and maintain. FlashLearn supports various LLM providers including LiteLLM, Ollama, OpenAI, DeepSeek, and other OpenAI-compatible clients, making it highly flexible. It operates on a 'fit/predict' pattern, allowing users to define and run custom 'skills' for structured outputs, and provides cost estimation for tasks.

Best used for

Ideal for developers and data scientists who need to integrate LLMs into existing ETL pipelines, automate data classification, and perform multi-step data transformations. Especially valuable for creating custom AI agents with structured JSON outputs and managing concurrent LLM calls efficiently.

Common actions

integrate LLMs

automate data tasks

classify text

summarize content

transform data

github copilot"AI Agents"face swappingcollaborationautomated workflowdeepfakeworkflowsopen-sourcelow-code/no-code

Capabilities

Key features

Integrate LLMs into pipelines
JSON-driven workflows
Built-in concurrency support
Supports multiple LLM providers
Learn and save custom skills
Estimate task costs
Structured JSON outputs

Target Audience

developerdata scientiststartup founder

Integrations

openailitellmollamadeepseek

Pricing & Plans

Open Source

Free

FAQs

What LLM providers does FlashLearn support?

FlashLearn supports a variety of LLM providers, including LiteLLM, Ollama, OpenAI, DeepSeek, and any other OpenAI-compatible clients. This flexibility allows users to integrate their preferred language models into their pipelines.

How does FlashLearn handle parallel processing of tasks?

FlashLearn includes built-in concurrency support, allowing it to process tasks in parallel. The `run_tasks_in_parallel` function organizes concurrent requests to the LLM, enabling high-throughput processing of up to 999 tasks per minute on a local machine.

Can I define custom LLM 'skills' with FlashLearn?

Yes, FlashLearn allows users to define and 'learn' custom skills, similar to a fit/predict pattern in ML. These skills are represented as compact JSON objects, containing instructions and optional function definitions for strict LLM output validation. They can be saved, loaded, and reused across systems.

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