LLM Provider Configuration Guide¶

This guide covers configuring different Large Language Model (LLM) providers with the Mattermost Agents plugin. Each provider has specific configuration requirements and capabilities.

Supported Providers¶

The Mattermost Agents plugin currently supports these LLM providers:

Local models via OpenAI-compatible APIs (Ollama, vLLM, etc.)
OpenAI
Anthropic
AWS Bedrock
Cohere
Mistral
Azure OpenAI

General Configuration Concepts¶

For any LLM provider, you’ll need to configure API authentication (keys, tokens, or other authentication methods), model selection for different use cases, parameters like context length and token limits, and ensure proper connectivity to provider endpoints.

Local Models (OpenAI Compatible)¶

The OpenAI Compatible option allows integration with any OpenAI-compatible LLM provider, such as Ollama:

Configuration¶

Deploy your model, for example, on Ollama
Select OpenAI Compatible in the AI Service dropdown
Enter the URL to your AI service from your Mattermost deployment in the API URL field. Be sure to include the port, and append /v1 to the end of the URL if using Ollama. (e.g., http://localhost:11434/v1 for Ollama, otherwise http://localhost:11434/)
If using Ollama, leave the API Key field blank
Specify your model name in the Default Model field

Configuration Options¶

Setting	Required	Description
API URL	Yes	The endpoint URL for your OpenAI-compatible API
API Key	No	API key if your service requires authentication
Default Model	Yes	The model to use by default
Organization ID	No	Organization ID if your service supports it
Send User ID	No	Whether to send user IDs to the service

Special Considerations¶

Ensure your self-hosted solution has sufficient compute resources and test for compatibility with the Mattermost plugin. Some advanced features may not be available with all compatible providers, so adjust token limits based on your deployment’s capabilities.

OpenAI¶

Authentication¶

Obtain an OpenAI API key, then select OpenAI in the Service dropdown and enter your API key. Specify a model name in the Default Model field that corresponds with the model’s label in the API. If your API key belongs to an OpenAI organization, you can optionally specify your Organization ID.

Configuration Options¶

Setting	Required	Description
API Key	Yes	Your OpenAI API key
Organization ID	No	Your OpenAI organization ID
Default Model	Yes	The model to use by default (see OpenAI’s model documentation)
Send User ID	No	Whether to send user IDs to OpenAI

Anthropic (Claude)¶

Authentication¶

Obtain an Anthropic API key, then select Anthropic in the Service dropdown and enter your API key. Specify a model name in the Default Model field that corresponds with the model’s label in the API.

Configuration Options¶

Setting	Required	Description
API Key	Yes	Your Anthropic API key
Default Model	Yes	The model to use by default (see Anthropic’s model documentation)

AWS Bedrock¶

AWS Bedrock provides access to foundation models from Anthropic (Claude), Amazon (Nova, Titan), and other providers via a unified API. For full setup instructions — including IAM policy configuration and Anthropic-specific Claude requirements — see the AWS Bedrock Setup Guide.

Authentication¶

The plugin uses the AWS SDK default credential chain. For Mattermost servers running on EC2, attach an IAM instance profile to your instance and leave all credential fields blank — the SDK discovers credentials automatically. For non-EC2 deployments, enter an AWS Access Key ID and AWS Secret Access Key, or a short-term Bedrock console API key.

Configuration Options¶

Setting	Required	Description
AWS Region	Yes	AWS region where Bedrock is available (e.g., `us-east-1`, `us-west-2`, `eu-central-1`)
Custom Endpoint URL	No	Optional custom endpoint for VPC endpoints or proxies. Leave blank for standard AWS endpoints.
AWS Access Key ID	No	IAM user access key ID for long-term credentials. Takes precedence over API Key if both are set.
AWS Secret Access Key	No	IAM user secret access key. Required if AWS Access Key ID is provided.
API Key	No	Bedrock console API key (base64 encoded, format: `ABSKQm...`). If IAM credentials above are set, they take precedence.
Default Model	Yes	The Bedrock model ID to use (e.g., `us.anthropic.claude-sonnet-4-6`). See the AWS Bedrock model IDs documentation for the full list of available models and their IDs. Model availability varies by AWS region.

Cohere¶

Authentication¶

Obtain a Cohere API key, then select Cohere in the Service dropdown and enter your API key. Specify a model name in the Default Model field that corresponds with the model’s label in the API.

Configuration Options¶

Setting	Required	Description
API Key	Yes	Your Cohere API key
Default Model	Yes	The model to use by default (see Cohere’s model documentation)

Mistral¶

Authentication¶

Obtain a Mistral API key, then select Mistral in the Service dropdown and enter your API key. Specify a model name in the Default Model field that corresponds with the model’s label in the API.

Configuration Options¶

Setting	Required	Description
API Key	Yes	Your Mistral API key
Default Model	Yes	The model to use by default (see Mistral’s model documentation)

Azure OpenAI¶

Authentication¶

For more details about integrating with Microsoft Azure’s OpenAI services, see the official Azure OpenAI documentation.

Provision sufficient access to Azure OpenAI for your organization and access your Azure portal
If you do not already have one, deploy an Azure AI Hub resource within Azure AI Studio
Once the deployment is complete, navigate to the resource and select Launch Azure AI Studio
In the side navigation pane, select Deployments under Shared resources
Select Deploy model then Deploy base model
Select your desired model and select Confirm
Select Deploy to start your model
In Mattermost, select OpenAI Compatible in the Service dropdown
In the Endpoint panel for your new model deployment, copy the base URI of the Target URI (everything up to and including .com) and paste it in the API URL field in Mattermost
In the Endpoint panel for your new model deployment, copy the Key and paste it in the API Key field in Mattermost
In the Deployment panel for your new model deployment, copy the Model name and paste it in the Default Model field in Mattermost

Configuration Options¶

Setting	Required	Description
API Key	Yes	Your Azure OpenAI API key
API URL	Yes	Your Azure OpenAI endpoint
Default Model	Yes	The model to use by default (see Azure OpenAI’s model documentation)
Send User ID	No	Whether to send user IDs to Azure OpenAI