> ## Documentation Index
> Fetch the complete documentation index at: https://docs.valarhq.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# API Support Matrix
> What each Valar inference API accepts today.
Valar gives you four endpoints. Three are inference surfaces shaped after APIs you already know, and one batches work asynchronously:
| API | Endpoint | Maturity |
| --------------------------- | --------------------------- | -------------------------------------------- |
| OpenAI **Responses** | `POST /v1/responses` | Stable |
| OpenAI **Chat Completions** | `POST /v1/chat/completions` | Stable |
| Anthropic **Messages** | `POST /v1/messages` | Stable |
| **Batch** | `POST /v1/batches` | Private Preview |
The same [models](/models) and [completion windows](/completion-windows) work across all three inference surfaces. The Batch API layers on top: it wraps a large set of [Responses API](#responses-api) calls into one asynchronous job.
## Behavior shared across every API
Before the per-API detail, a few rules hold no matter which surface you call:
* **Streaming is available on Chat Completions and Messages.** Pass `stream: true` and you get Server-Sent Events (`chat.completion.chunk` on Chat Completions, Anthropic-style events on Messages); add `stream_options.include_usage` on Chat Completions for a closing usage chunk. The Responses API rejects `stream: true`. For long jobs, use `background: true` on the Responses API and poll or wait on [webhooks](/webhooks).
* **Completion windows steer scheduling and price.** Set `metadata.completion_window` (or the `X-Valar-Completion-Window` header) to `"asap"` (the **Now** tier), `"priority"`, `"standard"`, or `"flex"` (background only). See [Completion windows](/completion-windows) and [Pricing](/pricing).
* **Webhooks fire on completion.** Set `metadata.completion_webhook` to receive a POST when processing finishes. See [Webhooks](/webhooks).
* **Responses are always stored.** `store: false` is unsupported.
## Inference APIs
Each accordion below lists what the API accepts and what it rejects. Open the one that matches the SDK you're using.
This is the surface we recommend reaching for first.
**Supported**
| Feature | Details |
| ------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Core parameters** | `model`, `input` (string or message array), `max_output_tokens`, `temperature`, `top_p`, `user`, `prompt_cache_key` |
| **Structured outputs** | `text.format` with `type: "text"` or `type: "json_schema"` |
| **Reasoning** | `reasoning.effort` (`none` / `minimal` / `low` / `medium` / `high` / `xhigh`), `reasoning.generate_summary` (`auto` / `concise` / `detailed`) |
| **Function tools** | `tools` with `type: "function"` - client-side function calling with `name`, `description`, `parameters`, `strict` |
| **Custom tools** | `tools` with `type: "custom"` |
| **Tool choice** | `tool_choice`: `"none"`, `"auto"`, `"required"`, or a specific function/custom tool |
| **Background mode** | `background: true` returns `202` immediately; poll with `GET /v1/responses/{id}` |
| **Prompt cache routing** | `prompt_cache_key` is an optional routing hint for requests that share a large prompt prefix |
| **Image input** | `input_image` content blocks on [multimodal models](/models). Non-multimodal models accept text only. |
| **Output logprobs** | `include: ["message.output_text.logprobs"]` returns one logprob per output token (best effort; omitted for models served via a proxy that does not return logprobs). |
**Not yet supported**
| Feature | Notes |
| ------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Streaming** | `stream: true` is rejected. Every response comes back as one JSON object. |
| **Instructions** | `instructions` is unsupported. Put system messages straight into `input`. |
| **Conversation chaining** | `previous_response_id` and `conversation` are unsupported. Resend the full input on each call. |
| **Prompt templates** | The `prompt` parameter is unsupported. |
| **Server-side tools** | `web_search`, `file_search`, `code_interpreter`, `computer_use`, `mcp`, `image_generation`, `shell`, `apply_patch` are unsupported. |
| **Multimodal input** | Audio and file input blocks are unsupported. Image input works on multimodal models (see above). |
| **Include** | Accepted for compatibility when passed as an array of strings. A request is rejected if it includes `reasoning.encrypted_content`, `web_search_call.action.sources`, `code_interpreter_call.outputs`, `computer_call_output.output.image_url`, or `file_search_call.results`. |
| **Truncation** | `"disabled"` is the only accepted value; custom truncation strategies are unsupported. |
| **Parallel tool calls** | `parallel_tool_calls` is unsupported. |
| **json\_object format** | `text.format.type: "json_object"` is unsupported. Reach for `"json_schema"` instead. |
| **Service tier** | `"auto"` is the only accepted value. Use `metadata.completion_window` to govern response timing instead. |
| **Delete / cancel** | `DELETE /v1/responses/{id}` and the cancel endpoints are not implemented. |
This surface streams `chat.completion.chunk` events.
**Supported**
| Feature | Details |
| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Core parameters** | `model`, `messages`, `max_completion_tokens`, `temperature`, `top_p`, `user` |
| **Message roles** | `system`, `user`, `assistant`, `tool`, `function` (deprecated), `developer` |
| **Structured outputs** | `response_format` with `type: "text"`, `"json_object"`, or `"json_schema"` |
| **Reasoning** | `reasoning_effort` (`none` / `minimal` / `low` / `medium` / `high` / `xhigh`) |
| **Function tools** | `tools` with `type: "function"` - standard `{type, function: {name, description, parameters, strict}}` format |
| **Custom tools** | `tools` with `type: "custom"` |
| **Tool choice** | `tool_choice`: `"none"`, `"auto"`, `"required"`, or a specific function/custom tool |
| **Parallel tool calls** | `parallel_tool_calls` is passed through |
| **Metadata** | `metadata` with string key-value pairs, including `completion_window` and `completion_webhook` |
| **Streaming** | `stream: true` returns Server-Sent Events (`chat.completion.chunk`); `stream_options.include_usage` adds a final usage chunk. Reasoning is streamed as `reasoning_content` deltas and tool calls are emitted atomically. |
| **Image input** | `image_url` content parts on [multimodal models](/models). Non-multimodal models accept text only. |
**Not yet supported**
| Feature | Notes |
| ---------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| **Multiple choices** | `n` is required to be `1`. |
| **Multimodal content** | Audio (`input_audio`) content parts are unsupported. Image (`image_url`) input works on multimodal models (see above). |
| **Sampling controls** | `frequency_penalty`, `presence_penalty`, `logit_bias`, `stop`, `seed`, `top_logprobs`, `logprobs`, `verbosity` are unsupported. |
| **Audio modality** | Neither `audio` nor `modalities: ["audio"]` is supported. |
| **Predicted output** | `prediction` is unsupported. |
| **Web search** | `web_search_options` is unsupported. |
| **Service tier** | `"auto"` is the only accepted value. |
| **CRUD endpoints** | The `GET`, `POST`, and `DELETE` operations on stored completions are not implemented. |
| **Deprecated fields** | `max_tokens`, `functions`, and `function_call` are rejected; switch to their modern replacements. |
**What comes back**
* A response always carries exactly one choice (`n=1`).
* `finish_reason` is either `"stop"` or `"tool_calls"` - values such as `"length"` and `"content_filter"` are never returned.
* Neither `system_fingerprint` nor `service_tier` appears in responses.
* `logprobs` is always `null`.
Valar's Anthropic-compatible surface. The [Anthropic Python SDK](/anthropic-sdk) and the Claude Agent SDK work against it with a base URL and key change.
**Supported**
| Feature | Details |
| ---------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Core parameters** | `model`, `max_tokens` (required), `messages`, `system` (string or content blocks) |
| **Sampling** | `temperature` (0–1), `top_p` (0–1), `top_k` |
| **Streaming** | `stream: true` returns Anthropic SSE events (`message_start`, `content_block_delta`, `message_delta`, `message_stop`) |
| **Extended thinking** | `thinking` with `type: "enabled"` and `budget_tokens`, or `output_config.effort` (`low` / `medium` / `high` / `xhigh` / `max`) |
| **Structured outputs** | `output_config.format` with `type: "json_schema"` (translated to the Responses API's `text.format`); see [Structured outputs](/structured-outputs) |
| **Function tools** | `tools` with `name`, `description`, `input_schema`; `tool_choice` (`auto` / `any` / `{type:"tool",name}`) |
| **Tool-result blocks** | `tool_result` content blocks in subsequent `user` messages |
| **Stop sequences** | `stop_sequences` |
| **Image input** | `image` content blocks on [multimodal models](/models). Non-multimodal models accept text only. |
| **Metadata** | `metadata` with string key-value pairs, including `completion_window` and `completion_webhook` |
| **Completion window header** | `X-Valar-Completion-Window` (`asap` / `priority` / `standard` / `flex`) as a fallback when `metadata.completion_window` is absent |
| **Count tokens** | `POST /v1/messages/count_tokens` returns an estimated token count |
**Not yet supported**
| Feature | Notes |
| ---------------------- | ---------------------------------------------------------------------------------------------------------- |
| **Multimodal content** | Document (`document`) content blocks are unsupported. Image input works on multimodal models (see above). |
| **Service tier** | `service_tier` is unsupported. Use `metadata.completion_window` or the `X-Valar-Completion-Window` header. |
| **Inference geo** | `inference_geo` is unsupported. |
| **Batches** | `POST /v1/messages/batches` and its related endpoints are not implemented. |
**What comes back**
* `stop_reason` is `end_turn`, `tool_use`, or `max_tokens`. (A run halted on a `stop_sequences` match comes back as `end_turn`, not `stop_sequence`.)
* The response content is one or more blocks: `text`, `thinking`, and `tool_use`.
* `usage` includes `input_tokens`, `output_tokens`, `cache_read_input_tokens`, and `cache_creation_input_tokens`.
**Authenticating with the Anthropic SDK**
Valar accepts both `Authorization: Bearer ` (the OpenAI convention) and the Anthropic `x-api-key: ` header. With the Anthropic SDK, either `auth_token` or `api_key` works:
```python theme={"system"}
from anthropic import Anthropic
client = Anthropic(
auth_token="YOUR_VALAR_API_KEY", # sends Authorization: Bearer
base_url="https://api.valarhq.ai", # no /v1 — the SDK appends it
)
```
The `anthropic-version` header is neither required nor inspected, and errors come back in the OpenAI-style error envelope format. See [Anthropic SDK & Claude Agent SDK](/anthropic-sdk) for end-to-end examples.
## Batch API
The Batch API runs large volumes of [Responses API](#responses-api) requests asynchronously. Every entry targets `/v1/responses` - you can't batch `/v1/chat/completions` or `/v1/messages` today. One `POST /v1/batches` call takes up to 100,000 requests; you then poll `GET /v1/batches/{id}` for status and fetch each result by its `custom_id`.
For the end-to-end workflow, see [Sending Requests at Scale](/requests_at_scale); for the request and response schemas, see the [Batch API reference](/api-reference/batches-api/create-a-batch).