265 lines
8.9 KiB
Markdown
265 lines
8.9 KiB
Markdown
---
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summary: "Use Venice AI privacy-focused models in Clawdbot"
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read_when:
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- You want privacy-focused inference in Clawdbot
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- You want Venice AI setup guidance
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---
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# Venice AI (Venius highlight)
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**Venius** is our highlight Venice setup for privacy-first inference with optional anonymized access to proprietary models.
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Venice AI provides privacy-focused AI inference with support for uncensored models and access to major proprietary models through their anonymized proxy. All inference is private by default—no training on your data, no logging.
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## Why Venice in Clawdbot
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- **Private inference** for open-source models (no logging).
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- **Uncensored models** when you need them.
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- **Anonymized access** to proprietary models (Opus/GPT/Gemini) when quality matters.
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- OpenAI-compatible `/v1` endpoints.
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## Privacy Modes
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Venice offers two privacy levels — understanding this is key to choosing your model:
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| Mode | Description | Models |
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|------|-------------|--------|
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| **Private** | Fully private. Prompts/responses are **never stored or logged**. Ephemeral. | Llama, Qwen, DeepSeek, Venice Uncensored, etc. |
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| **Anonymized** | Proxied through Venice with metadata stripped. The underlying provider (OpenAI, Anthropic) sees anonymized requests. | Claude, GPT, Gemini, Grok, Kimi, MiniMax |
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## Features
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- **Privacy-focused**: Choose between "private" (fully private) and "anonymized" (proxied) modes
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- **Uncensored models**: Access to models without content restrictions
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- **Major model access**: Use Claude, GPT-5.2, Gemini, Grok via Venice's anonymized proxy
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- **OpenAI-compatible API**: Standard `/v1` endpoints for easy integration
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- **Streaming**: ✅ Supported on all models
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- **Function calling**: ✅ Supported on select models (check model capabilities)
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- **Vision**: ✅ Supported on models with vision capability
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- **No hard rate limits**: Fair-use throttling may apply for extreme usage
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## Setup
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### 1. Get API Key
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1. Sign up at [venice.ai](https://venice.ai)
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2. Go to **Settings → API Keys → Create new key**
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3. Copy your API key (format: `vapi_xxxxxxxxxxxx`)
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### 2. Configure Clawdbot
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**Option A: Environment Variable**
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```bash
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export VENICE_API_KEY="vapi_xxxxxxxxxxxx"
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```
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**Option B: Interactive Setup (Recommended)**
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```bash
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clawdbot onboard --auth-choice venice-api-key
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```
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This will:
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1. Prompt for your API key (or use existing `VENICE_API_KEY`)
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2. Show all available Venice models
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3. Let you pick your default model
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4. Configure the provider automatically
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**Option C: Non-interactive**
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```bash
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clawdbot onboard --non-interactive \
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--auth-choice venice-api-key \
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--venice-api-key "vapi_xxxxxxxxxxxx"
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```
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### 3. Verify Setup
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```bash
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clawdbot chat --model venice/llama-3.3-70b "Hello, are you working?"
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```
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## Model Selection
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After setup, Clawdbot shows all available Venice models. Pick based on your needs:
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- **Default (our pick)**: `venice/llama-3.3-70b` for private, balanced performance.
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- **Best overall quality**: `venice/claude-opus-45` for hard jobs (Opus remains the strongest).
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- **Privacy**: Choose "private" models for fully private inference.
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- **Capability**: Choose "anonymized" models to access Claude, GPT, Gemini via Venice's proxy.
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Change your default model anytime:
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```bash
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clawdbot models set venice/claude-opus-45
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clawdbot models set venice/llama-3.3-70b
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```
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List all available models:
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```bash
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clawdbot models list | grep venice
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```
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## Configure via `clawdbot configure`
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1. Run `clawdbot configure`
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2. Select **Model/auth**
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3. Choose **Venice AI**
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## Which Model Should I Use?
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| Use Case | Recommended Model | Why |
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|----------|-------------------|-----|
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| **General chat** | `llama-3.3-70b` | Good all-around, fully private |
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| **Best overall quality** | `claude-opus-45` | Opus remains the strongest for hard tasks |
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| **Privacy + Claude quality** | `claude-opus-45` | Best reasoning via anonymized proxy |
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| **Coding** | `qwen3-coder-480b-a35b-instruct` | Code-optimized, 262k context |
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| **Vision tasks** | `qwen3-vl-235b-a22b` | Best private vision model |
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| **Uncensored** | `venice-uncensored` | No content restrictions |
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| **Fast + cheap** | `qwen3-4b` | Lightweight, still capable |
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| **Complex reasoning** | `deepseek-v3.2` | Strong reasoning, private |
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## Available Models (25 Total)
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### Private Models (15) — Fully Private, No Logging
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| Model ID | Name | Context (tokens) | Features |
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|----------|------|------------------|----------|
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| `llama-3.3-70b` | Llama 3.3 70B | 131k | General |
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| `llama-3.2-3b` | Llama 3.2 3B | 131k | Fast, lightweight |
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| `hermes-3-llama-3.1-405b` | Hermes 3 Llama 3.1 405B | 131k | Complex tasks |
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| `qwen3-235b-a22b-thinking-2507` | Qwen3 235B Thinking | 131k | Reasoning |
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| `qwen3-235b-a22b-instruct-2507` | Qwen3 235B Instruct | 131k | General |
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| `qwen3-coder-480b-a35b-instruct` | Qwen3 Coder 480B | 262k | Code |
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| `qwen3-next-80b` | Qwen3 Next 80B | 262k | General |
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| `qwen3-vl-235b-a22b` | Qwen3 VL 235B | 262k | Vision |
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| `qwen3-4b` | Venice Small (Qwen3 4B) | 32k | Fast, reasoning |
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| `deepseek-v3.2` | DeepSeek V3.2 | 163k | Reasoning |
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| `venice-uncensored` | Venice Uncensored | 32k | Uncensored |
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| `mistral-31-24b` | Venice Medium (Mistral) | 131k | Vision |
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| `google-gemma-3-27b-it` | Gemma 3 27B Instruct | 202k | Vision |
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| `openai-gpt-oss-120b` | OpenAI GPT OSS 120B | 131k | General |
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| `zai-org-glm-4.7` | GLM 4.7 | 202k | Reasoning, multilingual |
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### Anonymized Models (10) — Via Venice Proxy
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| Model ID | Original | Context (tokens) | Features |
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|----------|----------|------------------|----------|
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| `claude-opus-45` | Claude Opus 4.5 | 202k | Reasoning, vision |
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| `claude-sonnet-45` | Claude Sonnet 4.5 | 202k | Reasoning, vision |
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| `openai-gpt-52` | GPT-5.2 | 262k | Reasoning |
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| `openai-gpt-52-codex` | GPT-5.2 Codex | 262k | Reasoning, vision |
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| `gemini-3-pro-preview` | Gemini 3 Pro | 202k | Reasoning, vision |
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| `gemini-3-flash-preview` | Gemini 3 Flash | 262k | Reasoning, vision |
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| `grok-41-fast` | Grok 4.1 Fast | 262k | Reasoning, vision |
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| `grok-code-fast-1` | Grok Code Fast 1 | 262k | Reasoning, code |
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| `kimi-k2-thinking` | Kimi K2 Thinking | 262k | Reasoning |
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| `minimax-m21` | MiniMax M2.1 | 202k | Reasoning |
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## Model Discovery
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Clawdbot automatically discovers models from the Venice API when `VENICE_API_KEY` is set. If the API is unreachable, it falls back to a static catalog.
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The `/models` endpoint is public (no auth needed for listing), but inference requires a valid API key.
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## Streaming & Tool Support
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| Feature | Support |
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|---------|---------|
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| **Streaming** | ✅ All models |
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| **Function calling** | ✅ Most models (check `supportsFunctionCalling` in API) |
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| **Vision/Images** | ✅ Models marked with "Vision" feature |
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| **JSON mode** | ✅ Supported via `response_format` |
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## Pricing
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Venice uses a credit-based system. Check [venice.ai/pricing](https://venice.ai/pricing) for current rates:
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- **Private models**: Generally lower cost
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- **Anonymized models**: Similar to direct API pricing + small Venice fee
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## Comparison: Venice vs Direct API
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| Aspect | Venice (Anonymized) | Direct API |
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|--------|---------------------|------------|
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| **Privacy** | Metadata stripped, anonymized | Your account linked |
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| **Latency** | +10-50ms (proxy) | Direct |
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| **Features** | Most features supported | Full features |
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| **Billing** | Venice credits | Provider billing |
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## Usage Examples
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```bash
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# Use default private model
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clawdbot chat --model venice/llama-3.3-70b
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# Use Claude via Venice (anonymized)
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clawdbot chat --model venice/claude-opus-45
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# Use uncensored model
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clawdbot chat --model venice/venice-uncensored
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# Use vision model with image
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clawdbot chat --model venice/qwen3-vl-235b-a22b
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# Use coding model
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clawdbot chat --model venice/qwen3-coder-480b-a35b-instruct
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```
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## Troubleshooting
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### API key not recognized
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```bash
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echo $VENICE_API_KEY
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clawdbot models list | grep venice
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```
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Ensure the key starts with `vapi_`.
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### Model not available
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The Venice model catalog updates dynamically. Run `clawdbot models list` to see currently available models. Some models may be temporarily offline.
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### Connection issues
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Venice API is at `https://api.venice.ai/api/v1`. Ensure your network allows HTTPS connections.
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## Config file example
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```json5
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{
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env: { VENICE_API_KEY: "vapi_..." },
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agents: { defaults: { model: { primary: "venice/llama-3.3-70b" } } },
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models: {
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mode: "merge",
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providers: {
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venice: {
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baseUrl: "https://api.venice.ai/api/v1",
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apiKey: "${VENICE_API_KEY}",
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api: "openai-completions",
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models: [
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{
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id: "llama-3.3-70b",
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name: "Llama 3.3 70B",
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reasoning: false,
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input: ["text"],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: 131072,
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maxTokens: 8192
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}
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]
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}
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}
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}
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}
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```
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## Links
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- [Venice AI](https://venice.ai)
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- [API Documentation](https://docs.venice.ai)
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- [Pricing](https://venice.ai/pricing)
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- [Status](https://status.venice.ai)
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