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Getting Started with Ollama REST APIs
- This article provides a detailed guide on working with Ollama's REST APIs, specifically focusing on the /api/generate endpoint for AI model responses.
- The /api/generate endpoint offers standard and advanced parameters for customization, supporting features like suffix, images, format selection, and more.
- An example request to generate a joke using the llama3.2 model is demonstrated, showing how the response is streamed as incremental JSON objects.
- The response culminates in delivering the full joke 'Why don't eggs tell jokes? Because they'd crack each other up!' as concatenated pieces.
- Key fields in the response JSON include model, created_at timestamp, response content, and indicators like done status and done_reason for completion.
- The article explains the streaming nature of the API in generating responses piece by piece and concludes with how to receive the response as a single JSON object.
- Additionally, it delves into the /api/chat endpoint usage for generating conversation responses, detailing the parameters and an example request.
- The response format, timing information, and key elements like the response message, done status, and token statistics are highlighted for understanding the chat API.
- Lastly, the article covers how to request responses in JSON format using the /api/generate endpoint and receiving the complete joke response in one JSON object.
- Overall, this guide provides insights into leveraging Ollama's REST APIs effectively for generating AI responses and controlling response delivery.
- Source: https://github.com/ollama/ollama/blob/main/docs/api.md
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