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🚀 EDDI 6.5.0

19 LLM providers, knowledge bases that crawl your site and read your files, and conversations that follow compatible agent versionsWhat's new

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Mistral AIOpen weights

Mistral Small 4

An open-weight mixture-of-experts model (about 6B active parameters) that combines instruct, reasoning and coding, with image input.

Strengths

  • Instruct, reasoning and coding in one model
  • Reasoning that can be switched on
  • Image input
  • Apache 2.0 license

Best For

  • Cost-sensitive agents
  • General chat with optional reasoning
  • Image understanding

Run It in EDDI

The fastest route is the Manager: open the agent wizard or the Platform Operator and pick the provider and model. To configure it yourself, follow these steps for the provider you want.

Mistral AI · type: "mistral"

Model ids: mistral-small-latest, mistral-small-2603

1. Store the credential

Add the provider's API key to the Secrets Vault in the Manager, or with PUT /secretstore/secrets/default/mistral-key, under the name used below. Configurations reference it as ${vault:…}, so the key never appears in plain text.

${vault:mistral-key}

2. Configure the LLM task

Use this as the langchain.json of the agent's workflow, or paste the parameters into the LLM editor in the Manager.

{
  "tasks": [
    {
      "actions": [
        "send_message"
      ],
      "id": "chat",
      "type": "mistral",
      "parameters": {
        "apiKey": "${vault:mistral-key}",
        "modelName": "mistral-small-latest",
        "systemMessage": "You are a helpful assistant",
        "addToOutput": "true"
      }
    }
  ]
}

Or create the whole agent in one call

setup_agent writes the rules, LLM configuration and workflow, then deploys the agent. Call it over MCP or POST /administration/agents/setup.

setup_agent(
  agentName: "My mistral-small-latest agent",
  systemPrompt: "You are a helpful assistant.",
  provider: "mistral",
  model: "mistral-small-latest",
  apiKey: "${vault:mistral-key}"
)

Notes for EDDI

  • A good first tier in a model cascade: fast and inexpensive, escalating to a larger model only when confidence is low.

Related Models

Sources

The facts on this page come from the vendor's documentation, checked on 2026-09-30. Models change quickly, so confirm limits with the vendor before you rely on them. Prices are not listed here: see the vendor's pricing page.

Vendor documentation ↗ · Pricing ↗