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docs: add Models page and restructure agents docs into directory (#22643)

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Adds a Models page documenting LLM provider and model configuration for
Coder Agents. Moves agents pages into `docs/ai-coder/agents/` directory.
URLs are unchanged.

<img width="1343" height="633" alt="image"
src="https://github.com/user-attachments/assets/e870340b-9ae5-4904-9936-49f51ab0e0c4"
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This commit is contained in:
Matt Vollmer
2026-03-04 21:56:15 -05:00
committed by GitHub
parent 27f0f2962c
commit c0995ed736
8 changed files with 221 additions and 15 deletions
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docs/ai-coder/agents-architecture.md → docs/ai-coder/agents/architecture.md
+1 -1
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@@ -19,7 +19,7 @@ Three components are involved in every agent interaction:
reads and writes files, and executes processes — exactly what occurs when a
developer connects via their IDE.
![Architecture diagram ](../images/guides/ai-agents/agent-loop-detailed.png)
![Architecture diagram ](../../images/guides/ai-agents/agent-loop-detailed.png)
## The same connection your IDE uses
docs/ai-coder/agents.md → docs/ai-coder/agents/index.md
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@@ -9,13 +9,6 @@ Coder Agents is a chat interface and API for delegating development work and res
Coder Agents includes its own self-hosted AI coding
agent that runs the agent loop directly within the Coder control plane.
It is not a wrapper around third-party agent tools like Claude Code
or Codex.
It is a standalone agent written in Go that implements standard
agentic patterns — sub-agent delegation, context compaction, file editing, and
shell execution — and works with any LLM provider you configure.
No specialized software, API keys, or network access is required inside your workspace. The only requirement is network access between the control plane and external LLM providers.
<video autoplay playsinline loop>
@@ -23,7 +16,16 @@ No specialized software, API keys, or network access is required inside your wor
Your browser does not support the video tag.
</video>
## Who is Coder Agents for
## What Coder Agents is and isn't
It is a standalone agent written in Go that implements standard
agentic patterns — sub-agent delegation, context compaction, file editing, and
shell execution — and works with any LLM provider you configure.
It is not a wrapper around third-party agent tools like Claude Code
or Codex.
## Who Coder Agents is for
Coder Agents is designed for organizations that need to self-host their AI
coding workflows and maintain full control over how agents operate. It is a
@@ -49,7 +51,7 @@ other editor to review, refine, and complete work that the agent produces.
## How it works
The agent loop runs inside [the control plane](./agents-architecture.md). When a user
The agent loop runs inside [the control plane](./architecture.md). When a user
submits a prompt, the control plane:
1. Sends the prompt to the configured LLM provider (Anthropic, OpenAI, Google,
@@ -66,7 +68,7 @@ The workspace itself has no knowledge of AI. It is standard compute
infrastructure — there are no LLM API keys, no agent harnesses, and no special
software installed. All intelligence lives in the control plane.
![Architecture diagram showing the control plane in the center, with arrows out to LLM providers and arrows to workspaces](../images/guides/ai-agents/agent-loop.png)
![Architecture diagram showing the control plane in the center, with arrows out to LLM providers and arrows to workspaces](../../images/guides/ai-agents/agent-loop.png)
<small>The agent loop runs in the control plane. It makes outbound requests to LLM
providers and connects to workspaces only when tool execution is needed.</small>
@@ -193,7 +195,7 @@ enterprise LLM proxies, self-hosted model endpoints, and internal gateways.
Administrators can configure multiple providers simultaneously and set a default
model. Developers select from enabled models when starting a chat.
![Screenshot of the provider/model configuration admin panel](../images/guides/ai-agents/llm-providers.png)
![Screenshot of the provider/model configuration admin panel](../../images/guides/ai-agents/llm-providers.png)
<small>The model configuration panel in the Coder dashboard.</small>
@@ -223,7 +225,7 @@ the workspace.
## Comparison to Coder Tasks
Coder Agents is a new approach that differs from
[Coder Tasks](./tasks.md) in several ways:
[Coder Tasks](../tasks.md) in several ways:
| Aspect | Coder Agents | Coder Tasks |
|---------------------|--------------------------------------|----------------------------------------------------------------|
docs/ai-coder/agents/models.md
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@@ -0,0 +1,199 @@
# Models
Administrators configure LLM providers and models from the Coder dashboard.
These are deployment-wide settings — developers do not manage API keys or
provider configuration. They select from the set of models that an administrator
has enabled.
## Providers
Each LLM provider has a type, an API key, and an optional base URL override.
Coder supports the following provider types:
| Provider | Description |
|-------------------|------------------------------------------|
| Anthropic | Claude models via Anthropic API |
| OpenAI | GPT and o-series models via OpenAI API |
| Google | Gemini models via Google AI API |
| Azure OpenAI | OpenAI models hosted on Azure |
| AWS Bedrock | Models available through AWS Bedrock |
| OpenAI Compatible | Any endpoint implementing the OpenAI API |
| OpenRouter | Multi-model routing via OpenRouter |
| Vercel AI Gateway | Models via Vercel AI SDK |
The **OpenAI Compatible** type is a catch-all for any service that exposes an
OpenAI-compatible chat completions endpoint. Use it to connect to self-hosted
models, internal gateways, or third-party proxies like LiteLLM.
### Add a provider
1. Navigate to the **Agents** page in the Coder dashboard.
1. Click **Admin** in the top bar to open the configuration dialog.
1. Select the **Providers** tab.
1. Click the provider you want to configure.
1. Enter the **API key** for the provider.
1. Optionally set a **Base URL** to override the default endpoint. This is
useful for enterprise proxies, regional endpoints, or self-hosted models.
1. Click **Save**.
![Screenshot of the providers list in the admin dialog](../../images/guides/ai-agents/models-providers.png)
<small>The providers list shows all supported providers and their configuration
status.</small>
![Screenshot of the add provider form](../../images/guides/ai-agents/models-add-provider.png)
<small>Adding a provider requires an API key. The base URL is optional.</small>
### Provider API keys and security
Provider API keys are stored encrypted in the Coder database. They are never
exposed to workspaces, developers, or the browser after initial entry. The
dashboard shows only whether a key is set, not the key itself.
Because the agent loop runs in the control plane, workspaces never need direct
access to LLM providers. See
[Architecture](./architecture.md#no-api-keys-in-workspaces) for details
on this security model.
## Models
Each model belongs to a provider and has its own configuration for context limits,
generation parameters, and provider-specific options.
### Add a model
1. Open the **Admin** dialog and select the **Models** tab.
1. Click **Add** and select the provider for the new model.
1. Enter the **Model Identifier** — the exact model string your provider
expects (e.g., `claude-opus-4-6`, `gpt-5.3-codex`).
1. Set a **Display Name** so developers see a human-readable label in the model
selector.
1. Set the **Context Limit** — the maximum number of tokens in the model's
context window (e.g., `200000` for Claude Sonnet).
1. Configure any provider-specific options (see below).
1. Click **Save**.
![Screenshot of the models list in the admin dialog](../../images/guides/ai-agents/models-list.png)
<small>The models list shows all configured models grouped by provider.</small>
![Screenshot of the add model form](../../images/guides/ai-agents/models-add-model.png)
<small>Adding a model requires a model identifier, display name, and context
limit. Provider-specific options appear dynamically based on the selected
provider.</small>
### Set a default model
Click the **star icon** next to a model in the models list to make it the
default. The default model is pre-selected when developers start a new chat.
Only one model can be the default at a time.
## Model options
Every model has a set of general options and provider-specific options.
The admin UI generates these fields automatically from the provider's
configuration schema, so the available options always match the provider type.
### General options
These options apply to all providers:
| Option | Description |
|-----------------------|--------------------------------------------------------------------------------------------------|
| Model Identifier | The API model string sent to the provider (e.g., `claude-opus-4-6`). |
| Display Name | The label shown to developers in the model selector. |
| Context Limit | Maximum tokens in the context window. Used to determine when context compaction triggers. |
| Compression Threshold | Percentage (0–100) of context usage at which the agent compresses older messages into a summary. |
| Max Output Tokens | Maximum tokens generated per model response. |
| Temperature | Controls randomness. Lower values produce more deterministic output. |
| Top P | Nucleus sampling threshold. |
| Top K | Limits token selection to the top K candidates. |
| Presence Penalty | Penalizes tokens that have already appeared in the conversation. |
| Frequency Penalty | Penalizes tokens proportional to how often they have appeared. |
### Provider-specific options
Each provider type exposes additional options relevant to its models. These
fields appear dynamically in the admin UI when you select a provider.
#### Anthropic
| Option | Description |
|------------------------|---------------------------------------------------------|
| Thinking Budget Tokens | Maximum tokens allocated for extended thinking. |
| Effort | Thinking effort level (`low`, `medium`, `high`, `max`). |
#### OpenAI
| Option | Description |
|-----------------------|-----------------------------------------------------------------------|
| Reasoning Effort | How much effort the model spends reasoning (`low`, `medium`, `high`). |
| Max Completion Tokens | Cap on completion tokens for reasoning models. |
| Parallel Tool Calls | Whether the model can call multiple tools at once. |
#### Google
| Option | Description |
|------------------|-----------------------------------------------------|
| Thinking Budget | Maximum tokens for the model's internal reasoning. |
| Include Thoughts | Whether to include thinking traces in the response. |
| Safety Settings | Content safety thresholds by category. |
#### OpenRouter
| Option | Description |
|-------------------|---------------------------------------------------|
| Reasoning Enabled | Enable extended reasoning mode. |
| Reasoning Effort | Reasoning effort level (`low`, `medium`, `high`). |
| Provider Order | Preferred provider routing order. |
| Allow Fallbacks | Whether to fall back to alternative providers. |
#### Vercel AI Gateway
| Option | Description |
|-------------------|-----------------------------------------------|
| Reasoning Enabled | Enable extended reasoning mode. |
| Reasoning Effort | Reasoning effort level. |
| Provider Options | Routing preferences for underlying providers. |
> [!NOTE]
> Azure OpenAI uses the same options as OpenAI. AWS Bedrock uses the same
> options as Anthropic.
## How developers select models
Developers see a model selector dropdown when starting or continuing a chat on
the Agents page. The selector shows only models from providers that have valid
API keys configured. Models are grouped by provider if multiple providers are
active.
The model selector uses the following precedence to pre-select a model:
1. **Last used model** — stored in the browser's local storage.
1. **Admin-designated default** — the model marked with the star icon.
1. **First available model** — if no default is set and no history exists.
Developers cannot add their own providers, models, or API keys. If no models
are configured, the chat interface displays a message directing developers to
contact an administrator.
## Using an LLM proxy
Organizations that route LLM traffic through a centralized proxy — such as
Coder's AI Bridge or third parties like LiteLLM — can point any provider's **Base URL** at their proxy endpoint.
For example, to route all OpenAI traffic through Coder's AI Bridge:
1. Add or edit the **OpenAI** provider.
1. Set the **Base URL** to your AI Bridge endpoint
(e.g., `https://example.coder.com/api/v2/aibridge/openai/v1`).
1. Enter the API key your proxy expects.
Alternatively, use the **OpenAI Compatible** provider type if your proxy serves
multiple model families through a single OpenAI-compatible endpoint.
This lets you keep existing proxy-level features like per-user budgets, rate
limiting, and audit logging while using Coder Agents as the developer interface.
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docs/manifest.json
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@@ -1185,12 +1185,17 @@
{
"title": "Coder Agents",
"description": "Self-hosted agent by Coder",
"path": "./ai-coder/agents.md",
"path": "./ai-coder/agents/index.md",
"children": [
{
"title": "Architecture",
"description": "How the agent in the control plane communicates with workspaces",
"path": "./ai-coder/agents-architecture.md"
"path": "./ai-coder/agents/architecture.md"
},
{
"title": "Models",
"description": "Configure LLM providers and models for Coder Agents",
"path": "./ai-coder/agents/models.md"
}
]
}