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venice-router威尼斯路由器

Agent Skill

venice-router 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:venice-router(威尼斯路由器)
来源仓库:https://github.com/plusone/venice-router
安装命令:
openclaw skills install venice-router
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install venice-router

简介

venice-router 用于智能路由查询请求至最合适的 AI 模型,兼顾成本与性能优化。

  • 适合在 OpenClaw 中处理复杂或多变语义的任务,自动匹配最低成本的足够能力模型。
  • 通过自然语言输入即可触发路由决策,具体参数与分类逻辑需参考原始仓库说明。
  • 安装前需确认是否允许动态调用外部推理服务,并评估其对网络延迟与计费的影响。
  • 建议在非关键路径先行测试,确保路由策略符合预期且具备回退机制。

SKILL.md

name
venice-router
version
1.5.0
description
Supreme model router for Venice.ai — the privacy-first, uncensored AI platform. Automatically classifies query complexity and routes to the cheapest adequate model. Supports web search, uncensored mode, private-only mode (zero data retention), conversation-aware routing, cost budgets, function calling, thinking/reasoning mode, and 35+ Venice.ai text models. Use when the user wants to chat via Venice.ai, send prompts through Venice, or needs smart model selection to minimize API costs while keeping data private from Big Tech.
homepage
https://venice.ai
source
https://github.com/PlusOne/venice.ai-router-openclaw
user-invocable
true
metadata
openclaw
emoji
🦞🚀
homepage
https://github.com/PlusOne/venice.ai-router-openclaw
os
["linux", "macos"]
requires
bins
["python3"]
env
["VENICE_API_KEY"]
primaryEnv
VENICE_API_KEY
optionalEnv
notes
Python 3.8+ (stdlib only, no pip dependencies). All scripts bundled under scripts/. Source: https://github.com/PlusOne/venice.ai-router-openclaw
cliHelp
python3 venice-router.py --help\
usage
venice-router.py [-h] [--prompt PROMPT] [--tier {cheap,budget,budget-medium,mid,high,premium}] [--model MODEL] [--classify CLASSIFY] [--list-models] [--stream] [--temperature TEMPERATURE] [--max-tokens MAX_TOKENS] [--system SYSTEM] [--prefer-anon] [--uncensored] [--private-only] [--web-search] [--character CHARACTER] [--json] [--thinking] [--conversation CONVERSATION] [--tools TOOLS] [--tool-choice TOOL_CHOICE] [--budget-status] [--session-id SESSION_ID]\
Examples
--prompt \"What is 2+2?\" | --tier mid --prompt \"Explain recursion\" | --stream --prompt \"Write a haiku\" | --web-search --prompt \"Latest AI news\" | --uncensored --prompt \"Creative fiction\" | --private-only --prompt \"Sensitive data\" | --thinking --prompt \"Prove the halting problem\" | --conversation history.json --prompt \"continue\" | --tools tools.json --prompt \"Get weather\" | --budget-status | --classify \"Design a microservices architecture\" | --list-models
install
kind
brew
formula
python
bins
["python3"]
label
Install Python (brew)

Venice.ai Supreme Router

Smart, cost-optimized model routing for Venice.ai — the AI platform for people who don't want Big Tech watching over their shoulder.

Unlike OpenAI, Anthropic, and Google — where every prompt is logged, analyzed, and potentially used to train future models — Venice offers true privacy with zero data retention on private models. Your conversations stay yours. Venice is also uncensored: no content filters, no refusals, no "I can't help with that."

Setup

  1. Get a Venice.ai API key from venice.ai/settings/api
  2. Set the environment variable:
export VENICE_API_KEY="your-key-here"

Or configure in ~/.openclaw/openclaw.json:

{
  "skills": {
    "entries": {
      "venice-router": {
        "enabled": true,
        "apiKey": "YOUR_VENICE_API_KEY"
      }
    }
  }
}

Usage

Route a prompt (auto-selects model)

python3 {baseDir}/scripts/venice-router.py --prompt "What is 2+2?"

Force a specific tier

python3 {baseDir}/scripts/venice-router.py --tier cheap --prompt "Tell me a joke"
python3 {baseDir}/scripts/venice-router.py --tier budget-medium --prompt "Write a Python function"
python3 {baseDir}/scripts/venice-router.py --tier mid --prompt "Explain quantum computing"
python3 {baseDir}/scripts/venice-router.py --tier premium --prompt "Write a distributed systems architecture"

Stream output

python3 {baseDir}/scripts/venice-router.py --stream --prompt "Write a poem about lobsters"

Web search (LLM searches the web and cites sources)

python3 {baseDir}/scripts/venice-router.py --web-search --prompt "Latest news on AI regulation"

Uncensored mode (prefer models with no content filters)

python3 {baseDir}/scripts/venice-router.py --uncensored --prompt "Write edgy creative fiction"

Private-only mode (zero data retention, no Big Tech proxying)

python3 {baseDir}/scripts/venice-router.py --private-only --prompt "Analyze this confidential contract"

Conversation-aware routing (multi-turn context)

# Save conversation history as JSON, then route follow-ups with context
python3 {baseDir}/scripts/venice-router.py --conversation history.json --prompt "Can you add tests too?"

The router analyzes conversation history to keep context: trivial follow-ups ("thanks") go cheap, while follow-ups in complex code discussions stay at the right tier.

Function calling (tool use)

# Define tools in a JSON file (OpenAI tools format)
python3 {baseDir}/scripts/venice-router.py --tools tools.json --prompt "What's the weather in NYC?"
python3 {baseDir}/scripts/venice-router.py --tools tools.json --tool-choice auto --prompt "Search for latest AI news"

Tool definitions use the standard OpenAI format. The router auto-bumps to mid tier minimum for function calling since it requires capable models.

Cost budget tracking

# Show current spending
python3 {baseDir}/scripts/venice-router.py --budget-status

# Track per-session costs
python3 {baseDir}/scripts/venice-router.py --session-id my-project --prompt "help me code"

Set VENICE_DAILY_BUDGET and/or VENICE_SESSION_BUDGET to enforce spending limits. The router auto-downgrades tiers as you approach budget limits.

Classify only (no API call)

python3 {baseDir}/scripts/venice-router.py --classify "Explain the Riemann hypothesis"

List available models and tiers

python3 {baseDir}/scripts/venice-router.py --list-models

Override model directly

python3 {baseDir}/scripts/venice-router.py --model deepseek-v3.2 --prompt "Hello"

Tiers

TierModelsCost (input/output per 1M tokens)Best For
cheapVenice Small (qwen3-4b), GLM 4.7 Flash, GPT OSS 120B, Llama 3.2 3B$0.05–$0.15 / $0.15–$0.60Simple Q&A, greetings, math, lookups
budgetQwen 3 235B, Venice Uncensored, GLM 4.7 Flash Heretic$0.14–$0.20 / $0.75–$0.90Moderate questions, summaries, translations
budget-mediumGrok Code Fast, DeepSeek V3.2, MiniMax M2.1$0.25–$0.40 / $1.00–$1.87Moderate-to-complex tasks, code snippets, structured output
midDeepSeek V3.2, MiniMax M2.1/M2.5, Qwen3 Thinking 235B, Venice Medium, Llama 3.3 70B$0.25–$0.70 / $1.00–$3.50Code generation, analysis, longer writing, reasoning
highGLM 5, Kimi K2 Thinking, Kimi K2.5, Grok 4.1 Fast, Hermes 3 405B, Gemini 3 Flash$0.50–$1.10 / $1.25–$3.75Complex reasoning, multi-step tasks, code review
premiumGPT-5.2, GPT-5.2 Codex, Gemini 3 Pro, Gemini 3.1 Pro (1M ctx), Claude Opus/Sonnet 4.5/4.6$2.19–$6.00 / $15.00–$30.00Expert-level analysis, architecture, research papers

Routing Strategy

The router classifies each prompt using keyword + heuristic analysis:

  1. Length — longer prompts suggest more complex tasks
  2. Keywords — domain-specific terms (e.g., "architecture", "optimize", "prove") signal complexity
  3. Code markers — presence of code blocks, function names, or technical syntax
  4. Instruction depth — multi-step instructions, comparisons, or "explain in detail" bump the tier
  5. Conversational simplicity — greetings, yes/no, small talk stay on the cheapest tier
  6. Conversation history — when --conversation is provided, analyzes full chat context: code in history boosts tier, trivial follow-ups ("thanks") downgrade, tool calls in history signal complexity
  7. Function calling--tools auto-bumps to at least mid tier (capable models required)
  8. Thinking/reasoning mode--thinking prefers chain-of-thought reasoning models (Qwen3 Thinking, Kimi K2) and bumps to at least mid tier
  9. Budget constraints — progressive tier downgrade as spending approaches daily/session limits (95% → cheap, 80% → budget, 60% → mid, 40% → high)

The classifier errs on the side of cheaper models — it only escalates when there's strong signal for complexity.

Environment Variables

VariableDescriptionDefault
VENICE_API_KEYVenice.ai API key (required)
VENICE_DEFAULT_TIERMinimum floor tier — auto-classification never goes below this. Valid: cheap, budget, budget-medium, mid, high, premiumbudget
VENICE_MAX_TIERMaximum tier to ever use (cost cap)premium
VENICE_TEMPERATUREDefault temperature0.7
VENICE_MAX_TOKENSDefault max tokens4096
VENICE_STREAMEnable streaming by defaultfalse
VENICE_UNCENSOREDAlways prefer uncensored modelsfalse
VENICE_PRIVATE_ONLYOnly use private models (zero data retention)false
VENICE_WEB_SEARCHEnable web search by default ($10/1K calls)false
VENICE_THINKINGAlways prefer thinking/reasoning modelsfalse
VENICE_DAILY_BUDGETMax daily spend in USD (0 = unlimited)0
VENICE_SESSION_BUDGETMax per-session spend in USD (0 = unlimited)0

Why Venice.ai?

  • 🔒 Private inference — Models marked "Private" have zero data retention. Your data never trains anyone's model.
  • 🔓 Uncensored — No guardrails blocking legitimate use cases. No refusals, no filters.
  • 🔌 OpenAI-compatible — Same API format, just change the base URL. Drop-in replacement.
  • 📦 30+ models — From tiny efficient models ($0.05/M) to Claude Opus 4.6 and GPT-5.2.
  • 🌐 Built-in web search — LLMs can search the web and cite sources in a single API call.

Tips

  • Use --classify to preview which tier a prompt would hit before spending tokens
  • Set VENICE_MAX_TIER=mid to cap costs and never hit premium models
  • Use --uncensored for creative, security research, or other content mainstream AI won't touch
  • Use --private-only when processing sensitive/confidential data — zero retention guaranteed
  • Use --web-search when you need up-to-date information with cited sources
  • Use --conversation with a JSON message history for smarter multi-turn routing
  • Use --tools to enable function calling — the router auto-bumps to capable models
  • Set VENICE_DAILY_BUDGET=1.00 to cap daily spend at $1 — the router auto-downgrades tiers as you approach the limit
  • Use --budget-status to see a detailed breakdown of your spending by tier
  • Use --thinking for math proofs, logic puzzles, and multi-step reasoning — routes to Qwen3 Thinking or Kimi K2 models
  • The router prefers private (self-hosted) Venice models over anonymized ones when available at the same tier
  • When --uncensored is active, the router auto-bumps to the nearest tier with uncensored models
  • Combine with OpenClaw WebChat for a seamless chat experience routed through Venice.ai

适合场景

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03

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能力 5

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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