Venice.Ai Router Openclaw

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.

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

Tier	Models	Cost (input/output per 1M tokens)	Best For
cheap	Venice Small (qwen3-4b), GLM 4.7 Flash, GPT OSS 120B, Llama 3.2 3B	$0.05–$0.15 / $0.15–$0.60	Simple Q&A, greetings, math, lookups
budget	Qwen 3 235B, Venice Uncensored, GLM 4.7 Flash Heretic	$0.14–$0.20 / $0.75–$0.90	Moderate questions, summaries, translations
budget-medium	Grok Code Fast, DeepSeek V3.2, MiniMax M2.1	$0.25–$0.40 / $1.00–$1.87	Moderate-to-complex tasks, code snippets, structured output
mid	DeepSeek V3.2, MiniMax M2.1/M2.5, Qwen3 Thinking 235B, Venice Medium, Llama 3.3 70B	$0.25–$0.70 / $1.00–$3.50	Code generation, analysis, longer writing, reasoning
high	GLM 5, Kimi K2 Thinking, Kimi K2.5, Grok 4.1 Fast, Hermes 3 405B, Gemini 3 Flash	$0.50–$1.10 / $1.25–$3.75	Complex reasoning, multi-step tasks, code review
premium	GPT-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–$30.00	Expert-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

Variable	Description	Default
VENICE_API_KEY	Venice.ai API key (required)	—
VENICE_DEFAULT_TIER	Minimum floor tier — auto-classification never goes below this. Valid: cheap, budget, budget-medium, mid, high, premium	budget
VENICE_MAX_TIER	Maximum tier to ever use (cost cap)	premium
VENICE_TEMPERATURE	Default temperature	0.7
VENICE_MAX_TOKENS	Default max tokens	4096
VENICE_STREAM	Enable streaming by default	false
VENICE_UNCENSORED	Always prefer uncensored models	false
VENICE_PRIVATE_ONLY	Only use private models (zero data retention)	false
VENICE_WEB_SEARCH	Enable web search by default ($10/1K calls)	false
VENICE_THINKING	Always prefer thinking/reasoning models	false
VENICE_DAILY_BUDGET	Max daily spend in USD (0 = unlimited)	0
VENICE_SESSION_BUDGET	Max 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