Venice聊天

SKILLAI 工具
AI 工具 未标注权限 许可证不明确
安装这个技能

Venice聊天专用技能,帮助AI Agent高效完成相关任务。

一句话选型结论

按资料字段整理

Venice聊天是AI 工具类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类AI 工具 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_3c6cb52e/venice-chat-gpq9
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

AI 工具
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_3c6cb52e仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791682684
正文体量12.4 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
组合多个 AI 能力

把写作、检索、总结串成一条流程。

搭工作流

把固定流程做成可重复调用的步骤。

做提示词与评测

整理提示词并对比输出效果。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在AI 工具场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
Venice聊天当前 未标注权限 未标注 未标注 未标注 有
执行计划 只读 GitHub 仓库 151.5 万 Codex、Claude、Cursor 有
Playwright MCP 测试 浏览器控制 ClawHub 市场 136.5 万 OpenClaw 有
完成前的验证 未标注权限 GitHub 仓库 131.9 万 Codex、Claude、Cursor 有
子 Agent 驱动开发 只读 GitHub 仓库 131.2 万 Codex、Claude、Cursor 有
前端设计 执行命令 GitHub 仓库 125.6 万 Codex、Claude、Cursor 有

SKILL.md 全文

12.4 KB
模型实际读到的说明书原文,来自技能仓库

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.

Use when

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

For the newer Alpha Responses API, see venice-responses.

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?"}]
  }'

Response shape is the standard OpenAI chat.completion object (id, object: "chat.completion", choices[].message, usage). With stream: true, responses come as SSE data: lines in chat.completion.chunk format.

The request body

Core fields (OpenAI-compatible)

Field Notes
model string — model ID, trait name, or compatibility mapping. Suffixes allowed (see below). Required.
messages array of system / developer / user / assistant / tool messages. Required, min 1.
temperature, top_p, top_k, min_p, min_temp, max_temp sampling controls
repetition_penalty, frequency_penalty, presence_penalty repetition controls
max_tokens (deprecated) / max_completion_tokens upper bound on output tokens
n number of choices (keep 1 to minimize cost)
seed integer for reproducibility
stop / stop_token_ids up to 4 strings, or raw token IDs
stream, stream_options.include_usage SSE streaming + include usage in the final chunk
response_format {type:"json_schema", json_schema:{...}} (preferred), {type:"json_object"}, or {type:"text"}
tools, tool_choice, parallel_tool_calls function calling / built-in tools
logprobs, top_logprobs return token log-probabilities
reasoning.effort / reasoning_effort none | minimal | low | medium | high | xhigh | max
reasoning.summary auto | concise | detailed
prompt_cache_key, prompt_cache_retention (default/extended/24h) prompt caching hints
text.verbosity low/medium/high/auto
metadata key/value strings for tracking
user, store accepted but ignored (OpenAI compat)

venice_parameters (Venice-only)

All optional. Combined with model feature suffixes, these are how you enable Venice features.

Field Type Default Effect
character_slug string — Apply a published Venice character. Slug is the "Public ID" on the character page. See venice-characters.
strip_thinking_response bool false Strip <think>...</think> from the assistant output on reasoning models.
disable_thinking bool false Disable thinking entirely on supported reasoning models and strip tags.
enable_e2ee bool true End-to-end encryption on E2EE-capable models when E2EE headers are present. Set to false to force TEE-only.
enable_web_search "off"/"auto"/"on" "off" Venice server-side web search. Citations arrive in the first streamed chunk or the response.
enable_web_scraping bool false Scrape any URLs found in the last user message (Firecrawl).
enable_web_citations bool false Ask the LLM to cite sources with ^1^ / ^1,3^ superscripts.
include_search_results_in_stream bool false Experimental — emit search results as the first stream chunk.
return_search_results_as_documents bool — Also surface search results as a synthetic tool call venice_web_search_documents (LangChain-friendly).
include_venice_system_prompt bool true Prepend Venice's curated system prompt. Turn off for full control.
enable_x_search bool false xAI native web + X/Twitter search (Grok models with supportsXSearch). Adds ~$0.01/search.

Model feature suffixes

Some venice_parameters can also be expressed as model feature suffixes on the model string — useful when the caller/library (OpenAI SDK, LangChain) can't set venice_parameters. Syntax:

<model-id>:<key>=<value>[&<key>=<value>…]

Values are URL-decoded. Supported keys (exact match):

Key Type Maps to
enable_web_search on / off / auto venice_parameters.enable_web_search
enable_web_citations "true" / "false" venice_parameters.enable_web_citations
enable_web_scraping "true" / "false" venice_parameters.enable_web_scraping
include_venice_system_prompt "true" / "false" venice_parameters.include_venice_system_prompt
include_search_results_in_stream "true" / "false" venice_parameters.include_search_results_in_stream
return_search_results_as_documents "true" / "false" venice_parameters.return_search_results_as_documents
character_slug string venice_parameters.character_slug
strip_thinking_response "true" / "false" venice_parameters.strip_thinking_response
disable_thinking "true" / "false" venice_parameters.disable_thinking

Unknown keys are silently ignored. Examples:

zai-org-glm-5-1:enable_web_search=on
kimi-k2-6:strip_thinking_response=true&enable_web_search=auto
zai-org-glm-5-1:character_slug=alan-watts

Note: enable_e2ee and enable_x_search can only be set via venice_parameters, not as suffixes.

Messages and modalities

messages[].content is either a string or an array of typed parts. Roles: user, assistant, tool, system, developer (reasoning models like o-series / codex).

Text + image (image_url)

{
  "model": "zai-org-glm-5-1",
  "messages": [{
    "role": "user",
    "content": [
      {"type": "text", "text": "What's in this image?"},
      {"type": "image_url", "image_url": {"url": "https://example.com/cat.jpg"}}
    ]
  }]
}
  • url accepts a public URL or data:image/png;base64,....
  • Models with model_spec.capabilities.supportsMultipleImages: true preserve images across the whole conversation; single-image vision models only keep images from the last user message. Check model_spec.capabilities.maxImages for the per-request cap.

Audio input (input_audio)

{
  "role": "user",
  "content": [
    {"type": "text", "text": "Transcribe this clip."},
    {"type": "input_audio", "input_audio": {"data": "<base64>", "format": "wav"}}
  ]
}

Formats: wav, mp3, aiff, aac, ogg, flac, m4a, pcm16, pcm24. Audio URLs are not supported — always inline base64.

Video input (video_url)

{
  "role": "user",
  "content": [
    {"type": "text", "text": "Summarize this."},
    {"type": "video_url", "video_url": {"url": "https://www.youtube.com/watch?v=..."}}
  ]
}

Accepts public URLs (including YouTube for some providers) or data:video/mp4;base64,.... Supported formats: mp4, mpeg, mov, webm.

Prompt caching (cache_control)

Any text / image_url / input_audio / video_url part can carry:

{"cache_control": {"type": "ephemeral", "ttl": "1h"}}

Combine with prompt_cache_key and prompt_cache_retention: "24h" on the root request for predictable cache routing. Cache read / write pricing is model-specific — check model_spec.pricing on /models.

Tools & function calling

Function tools

{
  "tools": [{
    "type": "function",
    "function": {
      "name": "get_weather",
      "description": "Get current weather for a city",
      "parameters": {
        "type": "object",
        "properties": {"city": {"type": "string"}},
        "required": ["city"]
      },
      "strict": true
    }
  }],
  "tool_choice": "auto"
}
  • tool_choice can also be "required", "none", or {"type":"function","function":{"name":"get_weather"}}.
  • parallel_tool_calls: true (default) lets the model emit multiple calls at once.
  • Respond by appending {"role":"tool","tool_call_id":"...","content":"..."} before the next call.

Built-in tools

"tools": [{"type": "web_search"}, {"type": "x_search"}]

Equivalent to toggling venice_parameters.enable_web_search / enable_x_search. x_search requires a model with supportsXSearch.

Reasoning models

On thinking models (GLM 5.1, Kimi K2.6, Claude Opus 4.7, GPT-5.4 Pro, …):

{
  "model": "zai-org-glm-5-1",
  "reasoning": {"effort": "medium", "summary": "auto"},
  "venice_parameters": {"strip_thinking_response": false},
  "messages": [...]
}
  • reasoning_effort is the OpenAI-compatible flat variant (takes precedence over reasoning.effort).
  • Reasoning models may return reasoning_content or structured reasoning_details[] on the assistant message. Pass reasoning_details back verbatim in the next turn — it encodes thought signatures for providers like Claude Opus 4.7 and GPT-5.4 Pro.
  • Use venice_parameters.disable_thinking: true to skip thinking entirely on supported models.

Structured output (response_format)

{
  "response_format": {
    "type": "json_schema",
    "json_schema": {
      "type": "object",
      "properties": {"name": {"type": "string"}, "age": {"type": "number"}},
      "required": ["name", "age"]
    }
  }
}

Prefer json_schema over the legacy json_object. Plain text is the default ({"type": "text"}).

E2EE (end-to-end encryption)

For models advertising supportsE2EE:

  1. Perform an HPKE / Noise handshake with Venice (see docs.venice.ai/e2ee).
  2. Send encrypted payload with the required E2EE request headers.
  3. Leave venice_parameters.enable_e2ee at default true, or set false to fall back to TEE-only.

E2EE is not supported on /responses — use /chat/completions for encrypted inference.

Streaming

{"stream": true, "stream_options": {"include_usage": true}}
  • Response is text/event-stream. Each event is data: {...chunk...}\n\n, terminated by data: [DONE].
  • include_usage: true adds a final chunk with token counts.
  • With venice_parameters.include_search_results_in_stream: true, the first chunk carries venice_search_results.

Web-search answers

When enable_web_search is "auto" or "on", the response includes venice_parameters.web_search_citations[] where each entry has url, title, content (snippet), and date. Turn on enable_web_citations to have the model insert ^1^ superscripts inline.

Error handling specifics

  • 402 — insufficient balance. Bearer: INSUFFICIENT_BALANCE. x402: PAYMENT_REQUIRED with structured topUpInstructions and siwxChallenge.
  • 422 — prompt violates Venice or provider content policy. May include suggested_prompt.
  • 413 — payload too large (mostly vision/audio).
  • 429 — rate limit. See /api_keys/rate_limits and venice-errors.

Common gotchas

  • max_tokens is deprecated — prefer max_completion_tokens.
  • Image URLs must be publicly reachable from Venice's network. Localhost / signed S3 URLs without public access fail.
  • Audio inputs cannot be URLs — always base64.
  • Single-image vision models drop older images on each turn; chain them into the last user message.
  • For multi-turn with tools on Claude Opus 4.7, GPT-5.4 Pro, and similar, always round-trip reasoning_details unchanged.
  • parallel_tool_calls: true means you MUST be prepared to execute several tools in parallel before sending a single tool-role reply chain.
  • character_slug replaces the default Venice system prompt. Combine with include_venice_system_prompt: false for total control.

常见问题

5 问
答案由本站依据条目字段整理
Venice聊天怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_3c6cb52e/venice-chat-gpq9。安装方式为未标注。装完刷新技能列表或重开客户端。

Venice聊天支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

Venice聊天权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

Venice聊天收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

Venice聊天用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。