/api/assistant/chats/{id}/messages

Send a turn and stream the character reply

auth: API keybase https://app.nz

Request

curl -sX POST https://app.nz/api/assistant/chats/{id}/messages \
  -H "Authorization: Bearer pk_live_..." \
  -H "Content-Type: application/json" \
  -d '{}'

Character chat API

Start chats with any character by url_name or id, pin a model for that chat, and stream replies over the same server-sent-events shape as the OpenAI-compatible gateway. User-created characters can include long-form text or Markdown documents; app.nz strips image links, chunks the text, stores it in the character vector-search boundary, and retrieves relevant excerpts for each turn.

Character and chat bodies

name*stringPOST /api/characters display name.

system_promptstringOptional persona prompt; generated from name/description/greeting if omitted.

documentsarrayOptional long-form docs: [{ "name": "lore.md", "content": "# Markdown..." }]. Alias: knowledge_docs.

character_url_name*stringPOST /api/assistant/chats target character slug.

modelstringModel or route for this chat, e.g. app/auto or app/auto-fast.

content*stringMessage text for POST /messages.

Create a documented character and talk to it with a model

# Create a character with long-form Markdown knowledge.
curl -sX POST https://app.nz/api/characters \
  -H "Authorization: Bearer pk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "name": "GPU Brain Operator",
    "description": "Helps operate the gpu-brain search stack.",
    "voice": "Kore",
    "documents": [{
      "name": "runbook.md",
      "content": "# Runbook\nUse gobed for low-latency KNN over text chunks. Never ingest image links."
    }]
  }'

# Start a chat with a given model.
CHAT=$(curl -sX POST https://app.nz/api/assistant/chats \
  -H "Authorization: Bearer pk_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "character_url_name": "gpu-brain-operator",
    "model": "app/auto-fast",
    "reasoning_effort": "auto"
  }' | jq -r .chat.id)

# Send a message. The response is text/event-stream; relevant doc excerpts are
# retrieved server-side before the model call.
curl -N -sX POST https://app.nz/api/assistant/chats/$CHAT/messages \
  -H "Authorization: Bearer pk_live_..." \
  -H "Content-Type: application/json" \
  -d '{"content":"What should I check if KNN search looks stale?"}'