jae
19b25341bd
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Skills included: - venice-chat: Chat with Venice LLM models, vision, reasoning - venice-chat-benchmark: Benchmark chat models with infographics - venice-image-gen: Generate images via Venice API - venice-list-image-models: List available image models - venice-list-text-models: List available text models - venice-list-video-models: List available video models - venice-tts: Text-to-speech via Venice API - venice-video-generate: Generate videos from text/images - venice-video-queue: Queue video generation jobs - venice-video-quote: Get video generation cost quotes - venice-video-retrieve: Retrieve completed videos All rebranded from Agent Zero paths to Agent JAE (~/.jae/agent/skills/). Requires VENICE_API_KEY environment variable.
293 lines
9.4 KiB
Python
293 lines
9.4 KiB
Python
"""List Venice.ai Video Models
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This instrument fetches and displays all available video generation models from Venice.ai API
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with comprehensive specifications for each model including:
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- Supported durations
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- Valid resolutions
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- Aspect ratios (if configurable)
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- Audio capabilities (generation, input, configurable)
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- Video input support
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- Beta/offline status
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This information is CRITICAL for video generation - each model has different valid
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parameter combinations that must be respected.
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Usage:
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python list_video_models.py # List all models
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python list_video_models.py --detailed # Show full specs for each model
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python list_video_models.py --model <id> # Show specs for specific model
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python list_video_models.py --json # Output as JSON
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"""
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import os
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import sys
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import json
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import requests
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from typing import Optional
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from dataclasses import dataclass, field, asdict
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@dataclass
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class VideoModelSpec:
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"""Complete specification for a video generation model."""
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id: str
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name: str
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model_type: str # text-to-video, image-to-video, video
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# Generation constraints
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durations: list = field(default_factory=list)
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resolutions: list = field(default_factory=list)
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aspect_ratios: list = field(default_factory=list)
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# Audio capabilities
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audio: bool = False
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audio_configurable: bool = False
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audio_input: bool = False
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# Input requirements
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video_input: bool = False
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requires_image: bool = False
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# Status
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beta: bool = False
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offline: bool = False
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privacy: str = "anonymized"
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VENICE_API_URL = "https://api.venice.ai/api/v1/models"
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VENICE_API_KEY = os.getenv("VENICE_API_KEY")
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def fetch_video_models():
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"""Fetch all video models from Venice.ai API."""
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if not VENICE_API_KEY:
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raise ValueError("VENICE_API_KEY environment variable not set")
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headers = {
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"Authorization": f"Bearer {VENICE_API_KEY}",
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"Content-Type": "application/json"
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}
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response = requests.get(VENICE_API_URL, headers=headers, params={"type": "video"}, timeout=30)
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response.raise_for_status()
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data = response.json()
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models = []
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for item in data.get("data", []):
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spec = item.get("model_spec", {})
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constraints = spec.get("constraints", {})
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model_type = constraints.get("model_type", "unknown")
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models.append(VideoModelSpec(
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id=item.get("id", ""),
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name=spec.get("name", item.get("id", "Unknown")),
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model_type=model_type,
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durations=constraints.get("durations", []),
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resolutions=constraints.get("resolutions", []),
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aspect_ratios=constraints.get("aspect_ratios", []),
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audio=constraints.get("audio", False),
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audio_configurable=constraints.get("audio_configurable", False),
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audio_input=constraints.get("audio_input", False),
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video_input=constraints.get("video_input", False),
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requires_image=(model_type == "image-to-video"),
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beta=spec.get("beta", False),
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offline=spec.get("offline", False),
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privacy=spec.get("privacy", "anonymized")
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))
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return models
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def format_summary_table(models):
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"""Format models as summary table grouped by type."""
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lines = []
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by_type = {}
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for m in models:
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by_type.setdefault(m.model_type, []).append(m)
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for mtype in ["text-to-video", "image-to-video", "video"]:
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if mtype not in by_type:
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continue
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type_models = by_type[mtype]
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lines.append("")
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lines.append("=" * 115)
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lines.append(f" {mtype.upper()} MODELS ({len(type_models)})")
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lines.append("=" * 115)
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lines.append("")
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lines.append(f" {'Model ID':<40} {'Durations':<25} {'Res':<12} {'Audio':<12} {'Audio In'}")
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lines.append(f" {'-'*40} {'-'*25} {'-'*12} {'-'*12} {'-'*10}")
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for m in sorted(type_models, key=lambda x: x.name):
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durations = ", ".join(m.durations) if m.durations else "N/A"
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resolutions = ", ".join(m.resolutions) if m.resolutions else "default"
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audio = "Yes" if m.audio else "No"
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if m.audio_configurable:
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audio += " (cfg)"
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audio_in = "Yes" if m.audio_input else "No"
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status = ""
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if m.beta:
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status = " [BETA]"
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if m.offline:
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status = " [OFFLINE]"
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lines.append(f" {m.id:<40} {durations:<25} {resolutions:<12} {audio:<12} {audio_in}{status}")
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return "\n".join(lines)
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def format_detailed_spec(model):
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"""Format detailed specs for a single model."""
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lines = []
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lines.append("")
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lines.append("=" * 75)
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lines.append(f" {model.name}")
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lines.append(f" ID: {model.id}")
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lines.append("=" * 75)
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lines.append("")
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lines.append(f" Type: {model.model_type}")
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status = []
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if model.beta:
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status.append("BETA")
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if model.offline:
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status.append("OFFLINE")
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if status:
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lines.append(f" Status: {', '.join(status)}")
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lines.append("")
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lines.append(" GENERATION PARAMETERS:")
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lines.append(" " + "-" * 40)
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if model.durations:
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lines.append(f" duration: {' | '.join(model.durations)}")
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else:
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lines.append(f" duration: (not configurable)")
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if model.resolutions:
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lines.append(f" resolution: {' | '.join(model.resolutions)}")
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else:
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lines.append(f" resolution: (model default)")
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if model.aspect_ratios:
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lines.append(f" aspect_ratio: {' | '.join(model.aspect_ratios)}")
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else:
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lines.append(f" aspect_ratio: (NOT SUPPORTED - do not include in request)")
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lines.append("")
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lines.append(" AUDIO CAPABILITIES:")
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lines.append(" " + "-" * 40)
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lines.append(f" audio: {'Yes - generates audio' if model.audio else 'No'}")
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lines.append(f" audio_configurable: {'Yes - can toggle on/off' if model.audio_configurable else 'No'}")
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lines.append(f" audio_input: {'Yes - accepts audio' if model.audio_input else 'No'}")
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lines.append("")
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lines.append(" INPUT REQUIREMENTS:")
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lines.append(" " + "-" * 40)
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if model.model_type == "text-to-video":
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lines.append(f" prompt: Required (text description)")
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lines.append(f" image_url: Not used")
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elif model.model_type == "image-to-video":
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lines.append(f" prompt: Required (text description)")
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lines.append(f" image_url: REQUIRED (base64 data URL or HTTP URL)")
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elif model.model_type == "video":
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lines.append(f" prompt: Required (text description)")
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lines.append(f" video_url: {'Required' if model.video_input else 'Optional'}")
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return "\n".join(lines)
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def format_generation_example(model):
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"""Generate example API call for this model."""
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example = {
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"model": model.id,
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"prompt": "Your detailed prompt here"
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}
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if model.durations:
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example["duration"] = model.durations[0]
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if model.resolutions:
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example["resolution"] = model.resolutions[0]
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if model.aspect_ratios:
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example["aspect_ratio"] = model.aspect_ratios[0]
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if model.audio_configurable:
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example["audio"] = True
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if model.model_type == "image-to-video":
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example["image_url"] = "data:image/jpeg;base64,... OR https://..."
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return json.dumps(example, indent=2)
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def output_json(models):
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"""Output all models as JSON."""
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return json.dumps([asdict(m) for m in models], indent=2)
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def main():
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args = sys.argv[1:]
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print("Fetching Venice.ai video models...")
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print()
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try:
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models = fetch_video_models()
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if "--json" in args:
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print(output_json(models))
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return
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if "--model" in args:
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idx = args.index("--model")
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if idx + 1 < len(args):
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model_id = args[idx + 1]
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matching = [m for m in models if m.id == model_id or model_id in m.id]
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if matching:
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for m in matching:
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print(format_detailed_spec(m))
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print("\n EXAMPLE API REQUEST:")
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print(" " + "-" * 40)
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for line in format_generation_example(m).split("\n"):
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print(f" {line}")
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else:
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print(f"No model found matching: {model_id}")
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return
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if "--detailed" in args:
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for m in models:
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print(format_detailed_spec(m))
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return
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print(f"Total video models available: {len(models)}")
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print(format_summary_table(models))
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print()
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print("=" * 100)
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print(" USAGE")
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print("=" * 100)
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print("""
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--model <id> Show detailed specs for a specific model
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--detailed Show specs for all models
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--json Output as JSON
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CRITICAL FOR VIDEO GENERATION:
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* Each model has specific valid durations - use ONLY listed values
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* aspect_ratio: ONLY include if model lists them (otherwise causes 400 errors)
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* audio: check audio_configurable before including
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* image-to-video models REQUIRE image_url parameter
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""")
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except Exception as e:
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print(f"Error: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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if __name__ == "__main__":
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main()
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