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Key Features

< 1 min read

FlashLearn is built to simplify and accelerate complex LLM workflows. Key features include:

  • Easy Orchestration of Agent LLMs
    Simple fit/predict flow. Seamlessly integrate and coordinate multiple language model agents, enabling you to design and execute multi-step workflows with minimal hassle.

  • Fast Parallel Execution (up to 1,000 calls/min)
    Efficiently process large batches of tasks concurrently. FlashLearn’s built-in parallel execution capability enables high-throughput processing, making it ideal for scaling operations.

  • Support for Multiple Clients
    Whether you’re using LiteLLM, Ollama, OpenAI, DeepSeek, or any other OpenAI-compatible service, FlashLearn provides a uniform interface, allowing you to switch or combine clients effortlessly.

  • Built-in JSON Output and Structured Task Management
    All outputs are maintained in a structured, JSON format. This consistency enables easy auditing, debugging, and integration with downstream applications, ensuring every piece of data adheres to a standard schema.

These features make FlashLearn a robust and flexible library for transforming data, performing classification, and building custom multi-step LLM pipelines.