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The Chat endpoint is the simplest way to query your Ragen knowledge base. Send a single message, get a single answer — Ragen handles retrieval, reranking, and generation behind the scenes. If you need multi-turn conversation, model selection, or token usage tracking, use Chat Completions instead.

Endpoint

Authentication — include your API key in every request:
API keys are scoped to your organization. Create and manage keys in the Ragen dashboard under Settings → API Keys.
Prefer POST /v1/chat/completions for new integrations. It supports multi-turn conversations, model override, temperature, and usage tracking via the standard OpenAI wire format.

Request parameters

string
required
The assistant (project) ID to query. Find it in the dashboard URL when viewing a project (…/projects/<assistant_id>), via GET /v1/assistants, or under Settings → Assistant settings.
string
required
The user’s message. Must be between 1 and 10,000 characters.
string
Additional page or document context passed directly to the model alongside the retrieved chunks. Maximum 20,000 characters. Useful when building embedded chatbots — pass the current page’s content here so the model can answer questions about it even if it isn’t in the knowledge base.
boolean
default:"false"
When true, the response is returned as a Server-Sent Events stream instead of a single JSON object.
string
OpenAI-style reasoning effort: "low", "medium", or "high". Forwarded to the underlying model; only honored by reasoning-capable models (e.g. GPT-o series). When set, streaming responses additionally emit {"reasoning": "..."} events with the model’s intermediate thinking.

Response

Non-streaming (default)

A JSON object with a single text field:
string
The AI-generated answer grounded in your knowledge base.

Streaming (stream: true)

Returns a text/event-stream response. Two event shapes may appear, followed by a [DONE] sentinel:
The stream always ends with data: [DONE]. Display reasoning chunks separately from the answer or ignore them — most users don’t need to show them.

Examples

Use the official @webamigos/ragen-sdk-ts package for typed responses, streaming iterators, and automatic retries.

Error codes

Example error body:

Rate limits

When rate-limited, use exponential backoff with jitter. Each streaming and non-streaming request counts equally against this budget.

How the endpoint works

When you call POST /v1/chat, Ragen runs a five-step pipeline:
1

Authentication

Your API key is validated and the organization is resolved from it.
2

Assistant resolution

The assistant_id is matched to a project within your organization.
3

RAG retrieval

Relevant document chunks are retrieved from the assistant’s knowledge base via vector search.
4

Reranking

Retrieved chunks are reranked for relevance before being included in the prompt.
5

Generation and response

The language model generates an answer using the retrieved context and your message. The response is returned as JSON or streamed as SSE.