Overview
Mistral AI is a generative AI platform offering large language models for chat completions, code generation, embeddings, moderation, and more. The Ballerina ballerinax/mistral connector (v1.0.1) provides programmatic access to the full Mistral REST API, enabling you to integrate chat completions, fill-in-the-middle code generation, OCR, embeddings, fine-tuning, batch processing, and model management into your Ballerina integration flows.
Key features
- Chat completions with tool use, JSON mode, and configurable sampling parameters
- Fill-in-the-middle (FIM) code completion for code generation tasks
- Text embedding generation for semantic search and similarity applications
- OCR (optical character recognition) for extracting text from documents and images
- Content moderation and classification for text and chat inputs
- Fine-tuning job management: create, monitor, cancel, and start training jobs
- Batch job processing for large-scale asynchronous API requests
- Model and file management: list, retrieve, upload, download, and delete resources
Actions
Actions are operations you invoke on Mistral AI from your integration: generating chat completions, creating embeddings, managing models, running fine-tuning jobs, and more. The Mistral connector exposes all actions through a single client:
| Client | Actions |
|---|---|
Client | Chat completions, FIM, embeddings, OCR, moderation, agents, models, files, fine-tuning, batch jobs |
See the Action Reference for the full list of operations, parameters, and sample code for each client.
Documentation
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Setup Guide: This guide walks you through creating a Mistral AI account and obtaining the API key required to use the Mistral connector.
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Action Reference: Full reference for all clients: operations, parameters, return types, and sample code.
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Example: Learn how to build and configure an integration using the Mistral connector, including connection setup, operation configuration, and execution flow.
How to contribute
As an open source project, WSO2 welcomes contributions from the community.
To contribute to the code for this connector, please create a pull request in the following repository.
Check the issue tracker for open issues that interest you. We look forward to receiving your contributions.