/venice-chat

name: venice-chat
description: Call POST /chat/completions on Venice. Covers the OpenAI-compatible request shape, Venice-only venice_parameters (web search, scraping, citations, E2EE, characters, thinking control, X search), anon_user_id, multimodal inputs (images/audio/video/files), tool calls, reasoning controls (reasoning_effort, reasoning.enabled), streaming, prompt caching, structured output, per-model caps, and model feature suffixes.

Venice Chat Completions

`POST /api/v1/chat/completions` is Venice's main text endpoint. It's OpenAI-compatible, plus a `venice_parameters` object for Venice-only features. Auth is a Bearer API key or an x402 wallet (`SIGN-IN-WITH-X`); see [`venice-auth`](../venice-auth/SKILL.md).

Use when

• You need LLM text generation, with or without tools, with or without streaming.
• You want multimodal inputs (images, audio, video, documents) to a capable model.
• You want Venice-specific features: web search, web scraping, citations, E2EE, characters, xAI X/Twitter search, thinking control.
• You need prompt caching for large system prompts or long documents.
• You need structured (`json_schema`) output.

For the OpenAI Responses-style shape (typed `output[]` blocks), see [`venice-responses`](../venice-responses/SKILL.md). To pick a model, see [`venice-text-routing`](../venice-text-routing/SKILL.md).

Minimal request

curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "zai-org-glm-5-1",
    "messages": [{"role": "user", "content": "Why is the sky blue?"}]
  }'

OpenAI SDK (Python) — Venice-only fields go in `extra_body`:

import os
from openai import OpenAI
client = OpenAI(api_key=os.environ["VENICE_API_KEY"], base_url="https://api.venice.ai/api/v1")
resp = client.chat.completions.create(
    model="zai-org-glm-5-1",
    messages=[{"role": "user", "content": "Summarize today's AI news."}],
    extra_body={"venice_parameters": {"enable_web_search": "auto", "include_venice_system_prompt": False}},
)

Response shape is the standard OpenAI `chat.completion` object (`id`, `object: "chat.completion"`, `created`, `model`, `choices[].message`, `choices[].finish_reason`, `usage`) plus:

• `cost: {usd, diem}` — the request's cost split by the currency it was charged in (bundled credits count as USD). `0` when the response has no output tokens (those responses are not billed). Omitted if the cost can't be computed, and currently also when the request was charged to earned credits.
• `venice_parameters` — the effective Venice settings, plus `web_search_citations[]` (an empty array when no search ran).
• `usage.prompt_tokens_details.{cached_tokens, cache_creation_input_tokens}` and `usage.completion_tokens_details.reasoning_tokens` when the provider reports them.

`choices[].finish_reason` is one of `stop`, `length`, `tool_calls`, or `content_filter`. `content_filter` is a `200` in which the model refused or the output was cut (e.g. a Claude refusal); it is not a `422`, so check for it before trusting `message.content`. Some providers block mid-stream instead; the stream then ends with an in-band error chunk (`type: "content_filter_error"`, `code: "content_blocked_by_provider"`) followed by `[DONE]`.

`system_fingerprint` is always stripped. With `stream: true`, responses come as SSE `data:` lines in `chat.completion.chunk` format.

The request body

The top-level schema is **strict**: unknown top-level fields return `400`. (A few compatibility aliases are rewritten before validation: `input` → `messages`, `max_output_tokens` → `max_tokens`, `web_search: true|false` → `enable_web_search`, `promptCacheKey` → `prompt_cache_key`.)

Core fields (OpenAI-compatible)

| Field | Notes | |---|---| | `model` | string — model ID, trait (e.g. `default`, `default_code`), or compatibility mapping. Required. Feature suffixes allowed (see below). Lookups also tolerate dots/underscores/spaces (`kimi k2.6` → `kimi-k2-6`) and a `venice-` prefix (for IDEs that hijack `claude-*` names). | | `messages` | array of `system` / `developer` / `user` / `assistant` / `tool` messages. Required, min 1. Assistant messages with neither `content` nor `tool_calls` are silently dropped. | | `temperature` (0–2), `top_p` (0–1), `top_k` (int ≥ 0), `min_p` (0–1), `min_temp`, `max_temp` (0–2) | sampling controls. Some models publish defaults in `model_spec.constraints` | | `repetition_penalty` (≥ 0), `frequency_penalty`, `presence_penalty` (−2..2) | repetition controls | | `max_completion_tokens` / `max_tokens` *(deprecated)* | integers. Output cap including reasoning tokens. Above the model's `model_spec.maxCompletionTokens` → `400` on models with an enforced API cap. `max_tokens ≤ 0` is ignored; `max_tokens` is ignored when `max_completion_tokens` is set | | `n` | number of choices (default `1`; you pay for all choices) | | `seed` | positive integer | | `stop` / `stop_token_ids` | string or 1–4 strings / array of token IDs | | `stream`, `stream_options.include_usage` | SSE streaming (Venice sends the usage chunk even without `include_usage` — see Streaming) | | `response_format` | `{type:"json_schema", json_schema:{name, schema, strict}}` (preferred), `{type:"json_object"}`, or `{type:"text"}` | | `tools`, `tool_choice`, `parallel_tool_calls` | function calling | | `logprobs`, `top_logprobs` (int ≥ 0) | log-probabilities | | `reasoning_effort` / `reasoning.effort` | `none` \| `minimal` \| `low` \| `medium` \| `high` \| `xhigh` \| `max`. `reasoning_effort` wins if both are set | | `reasoning.enabled` | `false` disables reasoning on supported models. Ignored when an effort is set | | `reasoning.summary` | `auto` \| `concise` \| `detailed` | | `prompt_cache_key` | cache-routing hint. If omitted, Venice derives a stable key per API user | | `prompt_cache_retention` | `default` \| `extended` \| `24h`. `extended` and `24h` extend retention to 24 hours on supp