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Venice Ai

by @jonisjongithub

Complete Venice AI platform — text generation, vision/image analysis, web search, X/Twitter search, embeddings, TTS, speech-to-text, image generation, backgr...

Versionv2.1.1
Downloads3,868
Stars⭐ 3
#crypto-defi#image-gen#audio#social-media#legal
TERMINAL
clawhub install venice-ai

📖 About This Skill

name: venice-ai description: Complete Venice AI platform — text generation, vision/image analysis, web search, X/Twitter search, embeddings, TTS, speech-to-text, image generation, background removal, video creation, music generation, upscaling, and AI editing. Private, uncensored AI inference for everything. homepage: https://venice.ai metadata: { "clawdbot": { "emoji": "🏛️", "requires": { "bins": ["python3"], "env": ["VENICE_API_KEY"] }, "primaryEnv": "VENICE_API_KEY", "notes": "Full Venice AI platform — text, vision, images, video, audio, music, embeddings. One skill for everything.", "install": [ { "id": "python-brew", "kind": "brew", "formula": "python", "bins": ["python3"], "label": "Install Python (brew)", }, ], }, }

Venice AI — Complete Platform Skill

What is Venice AI?

Venice AI is 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." The AI answers what you actually ask, whether that's creative fiction, security research, controversial topics, or anything else mainstream AI platforms won't touch.

Why agents should care:

  • Private inference — Models marked "Private" have zero data retention. Process sensitive data without it leaking into training sets.
  • TEE (Trusted Execution Environment) — Hardware-secured inference; Venice's own servers cannot access the computation.
  • E2EE (End-to-End Encryption) — Prompts encrypted client-side before they reach Venice's servers. Maximum privacy.
  • Uncensored responses — No guardrails blocking legitimate use cases.
  • OpenAI-compatible API — Drop-in replacement. Same API format, just change the base URL.
  • 30+ models — From tiny efficient models to Claude Opus 4.6, GPT-5.2, Grok-4, Gemini Pro, and Venice's own uncensored models.
  • Built-in web search — LLMs can search the web (and X/Twitter via Grok) and cite sources in a single API call.
  • Vision/multimodal — Analyze images, audio, and video in chat completions.
  • Image & video generation — Flux, Sora, Runway, WAN models for visual content.
  • Music generation — AI-composed music with optional lyrics support.
  • Background removal — One-click transparent PNG output.

    • This skill gives you the complete Venice platform in one place.

    > ⚠️ API changes: If something doesn't work as expected, check docs.venice.ai — the API specs may have been updated since this skill was written.

    Prerequisites

  • Python 3.10+
  • Venice API key (free tier available at venice.ai/settings/api)

    • Setup

    Get Your API Key

    1. Create account at venice.ai 2. Go to venice.ai/settings/api 3. Click "Create API Key" → copy the key (starts with vn_...)

    Configure

    Option A: Environment variable 

    export VENICE_API_KEY="vn_your_key_here"

    Option B: Clawdbot config (recommended) 

    // ~/.clawdbot/clawdbot.json
{
  skills: {
    entries: {
      "venice-ai": {
        env: { VENICE_API_KEY: "vn_your_key_here" }
      }
    }
  }
}

    Verify

    python3 {baseDir}/scripts/venice.py models --type text

    Scripts Overview

    | Script | Purpose | |--------|---------| | venice.py | Text generation, vision analysis, models, embeddings, TTS, transcription | | venice-image.py | Image generation, background removal | | venice-video.py | Video generation (Sora, WAN, Runway) | | venice-music.py | Music generation (queue-based async) | | venice-upscale.py | Image upscaling | | venice-edit.py | AI image editing, multi-image editing |

    Part 1: Text, Vision & Audio

    Model Discovery & Selection

    Venice has a huge model catalog spanning text, image, video, audio, and embeddings.

    Browse Models

    # List all text models
python3 {baseDir}/scripts/venice.py models --type text
    List image models
    
python3 {baseDir}/scripts/venice.py models --type image
    List all model types
    
python3 {baseDir}/scripts/venice.py models --type text,image,video,audio,embedding
    Get details on a specific model
    
python3 {baseDir}/scripts/venice.py models --filter grok

    Model Selection Guide

    | Need | Recommended Model | Why | |------|------------------|-----| | Cheapest text | qwen3-4b | Tiny, fast, efficient | | Best uncensored | venice-uncensored | Venice's own uncensored model | | Best private + smart | deepseek-v3.2 | Great reasoning, efficient | | Vision/multimodal | qwen3-vl-235b-a22b | Analyze images, video, audio | | Best coding | qwen3-coder-480b-a35b-instruct | Massive coder model | | Frontier fast | grok-41-fast | Fast, 262K context | | X/Twitter search | grok-4-20-beta or grok-41-fast | Grok models + --x-search | | Frontier max quality | claude-opus-4-6 | Best overall quality | | Reasoning | kimi-k2-5 | Strong chain-of-thought | | Web search | Any model + --web-search | Built-in web search |

    Text Generation (Chat Completions)

    Basic Generation

    # Simple prompt
python3 {baseDir}/scripts/venice.py chat "What is the meaning of life?"
    Choose a model
    
python3 {baseDir}/scripts/venice.py chat "Explain quantum computing" --model deepseek-v3.2
    System prompt
    
python3 {baseDir}/scripts/venice.py chat "Review this code" --system "You are a senior engineer."
    Read from stdin
    
echo "Summarize this" | python3 {baseDir}/scripts/venice.py chat --model qwen3-4b
    Stream output
    
python3 {baseDir}/scripts/venice.py chat "Write a story" --stream

    Web Search Integration

    # Auto web search (model decides when to search)
python3 {baseDir}/scripts/venice.py chat "What happened in tech news today?" --web-search auto
    Force web search with citations
    
python3 {baseDir}/scripts/venice.py chat "Current Bitcoin price" --web-search on --web-citations
    Web scraping (extracts content from URLs in prompt)
    
python3 {baseDir}/scripts/venice.py chat "Summarize: https://example.com/article" --web-scrape

    X/Twitter Search (via Grok)

    Use Grok models to search X (Twitter) for real-time posts and discussions: 
    # Search X for latest AI news
python3 {baseDir}/scripts/venice.py chat "latest AI news from X today" \
  --model grok-41-fast --x-search
    Combine X search with web search
    
python3 {baseDir}/scripts/venice.py chat "What are people saying about OpenAI?" \
  --model grok-4-20-beta --x-search --web-search auto

    Note: --x-search only works with Grok models (grok-*). It sets enable_x_search: true in venice_parameters, which routes search through xAI's infrastructure.

    Uncensored Mode

    # Use Venice's own uncensored model
python3 {baseDir}/scripts/venice.py chat "Your question" --model venice-uncensored
    Disable Venice system prompts for raw model output
    
python3 {baseDir}/scripts/venice.py chat "Your prompt" --no-venice-system-prompt

    Reasoning Models

    Venice supports extended reasoning/thinking modes with fine-grained effort control:

    # Use a reasoning model with effort control
python3 {baseDir}/scripts/venice.py chat "Solve this math problem..." \
  --model kimi-k2-5 --reasoning-effort high
    Minimal reasoning (faster, cheaper)
    
python3 {baseDir}/scripts/venice.py chat "Simple question" \
  --model qwen3-4b --reasoning-effort minimal
    Maximum reasoning (slowest, most thorough)
    
python3 {baseDir}/scripts/venice.py chat "Complex analysis" \
  --model claude-opus-4-6 --reasoning-effort max
    Strip thinking from output (result only)
    
python3 {baseDir}/scripts/venice.py chat "Debug this code" --model qwen3-4b --strip-thinking
    Disable reasoning entirely
    
python3 {baseDir}/scripts/venice.py chat "Quick answer" --model qwen3-4b --disable-thinking

    Reasoning effort values (not all models support all levels): | Value | Description | |-------|-------------| | none | No reasoning (fastest) | | minimal | Very brief thinking | | low | Light reasoning | | medium | Balanced (often default) | | high | Thorough reasoning | | xhigh | Extended reasoning | | max | Maximum reasoning budget |

    Privacy: E2EE Mode

    For maximum privacy, use End-to-End Encryption with supported models: 
    # Enable E2EE (prompts encrypted client-side before reaching Venice)
python3 {baseDir}/scripts/venice.py chat "sensitive analysis" \
  --model some-e2ee-model --enable-e2ee

    Privacy tiers on Venice:

  • Standard — Anonymized inference, no persistent logs
  • Private inference — Hardware-isolated, zero retention
  • TEE (Trusted Execution Environment) — Hardware-secured; Venice servers cannot access computation
  • E2EE (End-to-End Encryption) — Prompts encrypted client-side; Venice has zero visibility

    • Advanced Options

    # Temperature and token control
python3 {baseDir}/scripts/venice.py chat "Be creative" --temperature 1.2 --max-tokens 4000
    JSON output mode
    
python3 {baseDir}/scripts/venice.py chat "List 5 colors as JSON" --json
    Prompt caching (for repeated context — up to 90% cost savings)
    
python3 {baseDir}/scripts/venice.py chat "Question" --cache-key my-session-123
    Show usage stats and balance
    
python3 {baseDir}/scripts/venice.py chat "Hello" --show-usage
    Use a Venice character
    
python3 {baseDir}/scripts/venice.py chat "Tell me about yourself" --character venice-default

    Vision / Image Analysis

    Analyze images using multimodal vision models. Supports local files, URLs, and data URLs.

    # Analyze a local image
python3 {baseDir}/scripts/venice.py analyze photo.jpg "What's in this image?"
    Analyze with default prompt (describe in detail)
    
python3 {baseDir}/scripts/venice.py analyze photo.jpg
    Analyze from URL
    
python3 {baseDir}/scripts/venice.py analyze "https://example.com/image.jpg" "Describe the scene"
    Choose vision model
    
python3 {baseDir}/scripts/venice.py analyze diagram.png "Explain this diagram" \
  --model qwen3-vl-235b-a22b
    Stream the analysis
    
python3 {baseDir}/scripts/venice.py analyze photo.jpg "Identify all objects" --stream
    Count tokens used
    
python3 {baseDir}/scripts/venice.py analyze photo.jpg "Analyze this" --show-usage

    Vision-capable models: qwen3-vl-235b-a22b, claude-opus-4-6, gpt-5.2, and others — check --list-models for current availability.

    Supported image formats: JPEG, PNG, WebP, GIF, BMP

    Embeddings

    Generate vector embeddings for semantic search, RAG, and recommendations:

    # Single text
python3 {baseDir}/scripts/venice.py embed "Venice is a private AI platform"
    Multiple texts (batch)
    
python3 {baseDir}/scripts/venice.py embed "first text" "second text" "third text"
    From file (one text per line)
    
python3 {baseDir}/scripts/venice.py embed --file texts.txt
    Output as JSON
    
python3 {baseDir}/scripts/venice.py embed "some text" --output json

    Model: text-embedding-bge-m3 (private, $0.15/M tokens)

    Text-to-Speech (TTS)

    Convert text to speech with 60+ multilingual voices:

    # Default voice
python3 {baseDir}/scripts/venice.py tts "Hello, welcome to Venice AI"
    Choose a voice
    
python3 {baseDir}/scripts/venice.py tts "Exciting news!" --voice af_nova
    List available voices
    
python3 {baseDir}/scripts/venice.py tts --list-voices
    Custom output path
    
python3 {baseDir}/scripts/venice.py tts "Some text" --output /tmp/speech.mp3
    Adjust speed
    
python3 {baseDir}/scripts/venice.py tts "Speaking slowly" --speed 0.8

    Popular voices: af_sky, af_nova, am_liam, bf_emma, zf_xiaobei (Chinese), jm_kumo (Japanese)

    Model: tts-kokoro (private, $3.50/M characters)

    Speech-to-Text (Transcription)

    Transcribe audio files to text:

    # Transcribe a file
python3 {baseDir}/scripts/venice.py transcribe audio.wav
    With timestamps
    
python3 {baseDir}/scripts/venice.py transcribe recording.mp3 --timestamps
    From URL
    
python3 {baseDir}/scripts/venice.py transcribe --url https://example.com/audio.wav

    Supported formats: WAV, FLAC, MP3, M4A, AAC, MP4

    Model: nvidia/parakeet-tdt-0.6b-v3 (private, $0.0001/audio second)

    Check Balance

    python3 {baseDir}/scripts/venice.py balance

    Part 2: Images & Video

    Pricing Overview

    | Feature | Cost | |---------|------| | Image generation | ~$0.01-0.03 per image | | Background removal | ~$0.02 | | Image upscale | ~$0.02-0.04 | | Image edit (single) | ~$0.04 | | Image multi-edit | ~$0.04-0.08 | | Video (WAN) | ~$0.10-0.50 | | Video (Sora) | ~$0.50-2.00 | | Video (Runway) | ~$0.20-1.00 | | Music generation | varies by model/duration |

    Use --quote with video/music commands to check pricing before generation.

    Image Generation

    # Basic generation
python3 {baseDir}/scripts/venice-image.py --prompt "a serene canal in Venice at sunset"
    Multiple images
    
python3 {baseDir}/scripts/venice-image.py --prompt "cyberpunk city" --count 4
    Custom dimensions
    
python3 {baseDir}/scripts/venice-image.py --prompt "portrait" --width 768 --height 1024
    List available models and styles
    
python3 {baseDir}/scripts/venice-image.py --list-models
python3 {baseDir}/scripts/venice-image.py --list-styles
    Use specific model and style
    
python3 {baseDir}/scripts/venice-image.py --prompt "fantasy" --model flux-2-pro \
  --style-preset "Cinematic"
    Reproducible results with seed
    
python3 {baseDir}/scripts/venice-image.py --prompt "abstract" --seed 12345
    PNG format with no watermark
    
python3 {baseDir}/scripts/venice-image.py --prompt "product shot" \
  --format png --hide-watermark

    Key flags: --prompt, --model (default: flux-2-max), --count, --width, --height, --format (webp/png/jpeg), --resolution (1K/2K/4K), --aspect-ratio, --negative-prompt, --style-preset, --cfg-scale (0-20), --seed, --safe-mode, --hide-watermark, --embed-exif, --steps

    Background Removal

    Remove the background from any image, producing a transparent PNG:

    # From local file
python3 {baseDir}/scripts/venice-image.py --background-remove photo.jpg
    Specify output path
    
python3 {baseDir}/scripts/venice-image.py --background-remove photo.jpg --output cutout.png
    From URL
    
python3 {baseDir}/scripts/venice-image.py --background-remove \
  "https://example.com/product.jpg" --output product-transparent.png

    The output is always a PNG with a transparent background (alpha channel). Works best with clear subject/background separation.

    Image Upscale

    # 2x upscale
python3 {baseDir}/scripts/venice-upscale.py photo.jpg --scale 2
    4x with AI enhancement
    
python3 {baseDir}/scripts/venice-upscale.py photo.jpg --scale 4 --enhance
    Enhanced with custom prompt
    
python3 {baseDir}/scripts/venice-upscale.py photo.jpg --enhance --enhance-prompt "sharpen details"
    From URL
    
python3 {baseDir}/scripts/venice-upscale.py --url "https://example.com/image.jpg" --scale 2

    Key flags: --scale (1-4, default: 2), --enhance (AI enhancement), --enhance-prompt, --enhance-creativity (0.0-1.0), --url, --output

    Image Edit (AI-powered)

    Single Image Edit

    AI-powered editing where the model interprets your prompt to modify the image:

    # Add elements
python3 {baseDir}/scripts/venice-edit.py photo.jpg --prompt "add sunglasses"
    Modify scene
    
python3 {baseDir}/scripts/venice-edit.py photo.jpg --prompt "change the sky to sunset"
    Remove objects
    
python3 {baseDir}/scripts/venice-edit.py photo.jpg --prompt "remove the person in background"
    From URL
    
python3 {baseDir}/scripts/venice-edit.py --url "https://example.com/image.jpg" \
  --prompt "colorize this black and white photo"
    Specify output location
    
python3 {baseDir}/scripts/venice-edit.py photo.jpg --prompt "add snow" --output result.png

    Multi-Image Edit (up to 3 images)

    Compose or blend multiple images together using advanced edit models:

    # Combine 2 images
python3 {baseDir}/scripts/venice-edit.py --multi-edit base.jpg overlay.png \
  --prompt "merge these images seamlessly"
    Layer 3 images with model selection
    
python3 {baseDir}/scripts/venice-edit.py --multi-edit bg.jpg subject.png detail.png \
  --prompt "compose these layers into one image" --model flux-2-max-edit
    Mix local file and URL
    
python3 {baseDir}/scripts/venice-edit.py --multi-edit local.jpg "https://example.com/img.png" \
  --prompt "blend these two photos" --output blended.png

    Multi-edit models: flux-2-max-edit (default), qwen-edit, gpt-image-1-5-edit

    Note: The standard edit endpoint uses Qwen-Image which has some content restrictions. Multi-edit uses Flux-based models.

    Video Generation

    # Get price quote first
python3 {baseDir}/scripts/venice-video.py --quote --model wan-2.6-image-to-video --duration 10s
    Image-to-video (WAN - default)
    
python3 {baseDir}/scripts/venice-video.py --image photo.jpg --prompt "camera pans slowly" \
  --duration 10s
    Image-to-video (Sora)
    
python3 {baseDir}/scripts/venice-video.py --image photo.jpg --prompt "cinematic" \
  --model sora-2-image-to-video --duration 8s --aspect-ratio 16:9 --skip-audio-param
    Video-to-video (Runway Gen4)
    
python3 {baseDir}/scripts/venice-video.py --video input.mp4 --prompt "anime style" \
  --model runway-gen4-turbo-v2v
    List models with available durations
    
python3 {baseDir}/scripts/venice-video.py --list-models

    Key flags: --image or --video, --prompt, --model (default: wan-2.6-image-to-video), --duration, --resolution (480p/720p/1080p), --aspect-ratio, --audio/--no-audio, --quote, --timeout

    Models:

  • WAN — Image-to-video, configurable audio, 5s-21s
  • Sora — Requires --aspect-ratio, use --skip-audio-param
  • Runway — Video-to-video transformation

    • Part 3: Music Generation

    Music Generation (AI Composed)

    Venice supports AI music generation via a queue-based async API (similar to video generation). Music is generated server-side and polled for completion.

    # Get price quote first
python3 {baseDir}/scripts/venice-music.py --quote --model elevenlabs-music --duration 60
    Generate instrumental music
    
python3 {baseDir}/scripts/venice-music.py --prompt "epic orchestral battle theme" --instrumental
    Generate music with lyrics
    
python3 {baseDir}/scripts/venice-music.py \
  --prompt "upbeat pop summer song" \
  --lyrics "Verse 1: Walking down the beach / feeling the heat..."
    Control duration
    
python3 {baseDir}/scripts/venice-music.py --prompt "ambient piano meditation" --duration 30
    Specify output location
    
python3 {baseDir}/scripts/venice-music.py --prompt "jazz café background" \
  --output ~/Music/venice-jazz.mp3
    List available audio models
    
python3 {baseDir}/scripts/venice-music.py --list-models
    Don't delete from server after download (useful for re-downloading)
    
python3 {baseDir}/scripts/venice-music.py --prompt "..." --no-delete
    Clean up server-side media after downloading with --no-delete
    
python3 {baseDir}/scripts/venice-music.py --complete QUEUE_ID

    Parameters: | Flag | Description | |------|-------------| | --prompt | Music description (style, mood, genre, instruments) | | --model | Model ID (default: elevenlabs-music) | | --duration | Duration in seconds | | --lyrics | Optional lyrics text for vocal generation | | --instrumental | Force instrumental (no vocals) | | --voice | Voice selection for vocal tracks | | --language | Language code (e.g., en, es, fr) | | --quote | Get price estimate without generating | | --timeout | Max wait time in seconds (default: 300) | | --poll-interval | Status check interval (default: 10s) |

    Prompt tips for music:

  • Be specific: genre, tempo, instruments, mood
  • e.g., "chill lo-fi hip hop with piano and rain ambiance, 85 BPM"
  • e.g., "cinematic orchestral swell, strings and brass, dramatic tension"
  • e.g., "acoustic folk guitar, warm and intimate, fingerpicking style"

    • Tips & Ideas

    🔍 Web Search + LLM = Research Assistant

    Use --web-search on --web-citations to build a research workflow. Venice searches the web, synthesizes results, and cites sources — all in one API call.

    🐦 X/Twitter Search via Grok

    With Grok models and --x-search, you get real-time access to X posts and discussions. Great for trend monitoring, social listening, and news research.

    🔓 Uncensored Creative Content

    Venice's uncensored models work for both text AND images. No guardrails blocking legitimate creative use cases.

    🔒 Maximum Privacy with TEE/E2EE

    When processing sensitive data:
  • Use models with private inference for zero data retention
  • Use TEE models when you need hardware-level isolation
  • Use --enable-e2ee for encrypted prompt delivery

    • 🎯 Prompt Caching for Agents

    If you're running an agent loop that sends the same system prompt repeatedly, use --cache-key to get up to 90% cost savings.

    👁️ Vision Pipeline

    # Analyze → describe → generate matching image
python3 scripts/venice.py analyze original.jpg "describe the style and composition" > desc.txt
python3 scripts/venice-image.py --prompt "$(cat desc.txt)" --model flux-2-max

    🎤 Audio Pipeline

    Combine TTS and transcription: generate spoken content with tts, process audio with transcribe. Both are private inference.

    🎬 Video Workflow

    1. Generate or find a base image 2. Use --quote to estimate video cost 3. Generate with appropriate duration/model 4. Videos take 1-5 minutes depending on settings

    🎵 Music + Video

    # Generate background music, then use it for video
python3 scripts/venice-music.py --prompt "cinematic adventure theme" --output bgm.mp3
python3 scripts/venice-video.py --image scene.jpg --prompt "epic journey" --audio-url bgm.mp3

    🖼️ Image Cleanup Pipeline

    # Generate → remove background → use in video
python3 scripts/venice-image.py --prompt "product on white background" --format png
python3 scripts/venice-image.py --background-remove output.png --output product-clean.png

    Troubleshooting

    | Problem | Solution | |---------|----------| | VENICE_API_KEY not set | Set env var or configure in ~/.clawdbot/clawdbot.json | | Invalid API key | Verify at venice.ai/settings/api | | Model not found | Run --list-models to see available; use --no-validate for new models | | Rate limited | Check --show-usage output | | Video stuck | Videos can take 1-5 min; use --timeout 600 for long ones | | Vision not working | Ensure you're using a vision-capable model (e.g., qwen3-vl-235b-a22b) | | --x-search no effect | Only works with Grok models (grok-*) | | Music timeout | Music can take 2-5 min; increase --timeout | | Background removal quality | Works best with clear subject/background contrast |

    Resources

  • API Docs: docs.venice.ai
  • Status: veniceai-status.com
  • Discord: discord.gg/askvenice
  • API Key: venice.ai/settings/api

    • ⚙️ Configuration

    Get Your API Key

    1. Create account at venice.ai 2. Go to venice.ai/settings/api 3. Click "Create API Key" → copy the key (starts with vn_...)

    Configure

    Option A: Environment variable 

    export VENICE_API_KEY="vn_your_key_here"

    Option B: Clawdbot config (recommended) 

    // ~/.clawdbot/clawdbot.json
{
  skills: {
    entries: {
      "venice-ai": {
        env: { VENICE_API_KEY: "vn_your_key_here" }
      }
    }
  }
}

    Verify

    python3 {baseDir}/scripts/venice.py models --type text

    📋 Tips & Best Practices

    | Problem | Solution | |---------|----------| | VENICE_API_KEY not set | Set env var or configure in ~/.clawdbot/clawdbot.json | | Invalid API key | Verify at venice.ai/settings/api | | Model not found | Run --list-models to see available; use --no-validate for new models | | Rate limited | Check --show-usage output | | Video stuck | Videos can take 1-5 min; use --timeout 600 for long ones | | Vision not working | Ensure you're using a vision-capable model (e.g., qwen3-vl-235b-a22b) | | --x-search no effect | Only works with Grok models (grok-*) | | Music timeout | Music can take 2-5 min; increase --timeout | | Background removal quality | Works best with clear subject/background contrast |