Ollama¶

Structured Output for Open Source and Local LLMs

Instructor has expanded its capabilities for language models. It started with API interactions via the OpenAI SDK, using Pydantic for structured data validation. Now, Instructor supports multiple models and platforms.

The integration of JSON mode improved adaptability to vision models and open source alternatives. This allows support for models from GPT and Mistral to models on Ollama and Hugging Face, using llama-cpp-python.

Instructor now works with cloud-based APIs and local models for structured data extraction. Developers can refer to our guide on Patching for information on using JSON mode with different models.

For learning about Instructor and Pydantic, we offer a course on Steering language models towards structured outputs.

The following sections show examples of Instructor's integration with platforms and local setups for structured outputs in AI projects.

Structured Output for Open Source and Local LLMs

Instructor has expanded its capabilities for language models. It started with API interactions via the OpenAI SDK, using Pydantic for structured data validation. Now, Instructor supports multiple models and platforms.

The integration of JSON mode improved adaptability to vision models and open source alternatives. This allows support for models from GPT and Mistral to models on Ollama and Hugging Face, using llama-cpp-python.

Instructor now works with cloud-based APIs and local models for structured data extraction. Developers can refer to our guide on Patching for information on using JSON mode with different models.

For learning about Instructor and Pydantic, we offer a course on Steering language models towards structured outputs.

The following sections show examples of Instructor's integration with platforms and local setups for structured outputs in AI projects.