Generate & Edit

from vlmrun.client import VLMRun

# Initialize the VLMRun client
client = VLMRun(api_key="<VLMRUN_API_KEY>")

# Generate the video
response = client.agent.completions.create(
    model="vlmrun-orion-1:auto",
    messages=[
        {
            "role": "user",
            "content": "Generate a video of a serene mountain landscape with flowing clouds, cinematic wide shot, golden hour lighting, 4K, 20 seconds"
        }
    ]
)

print(response.choices[0].message.content)
# >>> {"url": "https://.../video.mp4"}

from vlmrun.client import VLMRun
from pydantic import BaseModel, Field

# Define the response schema
class VideoGenerationResponse(BaseModel):
  url: str = Field(..., description="The URL of the generated video")

# Initialize the VLMRun client
client = VLMRun(api_key="<VLMRUN_API_KEY>")

# Generate the video with structured output
response = client.agent.completions.create(
    model="vlmrun-orion-1:auto",
    messages=[
        {
            "role": "user",
            "content": "Generate a video of a serene mountain landscape with flowing clouds, cinematic wide shot, golden hour lighting, 4K, 20 seconds"
        }
    ],
    response_format={"type": "json_schema", "schema": VideoGenerationResponse.model_json_schema()}
)

# Validate the response
result = VideoGenerationResponse.model_validate_json(response.choices[0].message.content)
# >>> VideoGenerationResponse(url="https://.../video.mp4")

import { VlmRun } from "vlmrun";

const client = new VlmRun({
  apiKey: "<VLMRUN_API_KEY>",
  baseURL: "https://api.vlm.run/v1"
});

const response = await client.agent.completions.create({
  model: "vlmrun-orion-1:auto",
  messages: [
    {
      role: "user",
      content: "Generate a video of a serene mountain landscape with flowing clouds, cinematic wide shot, golden hour lighting, 4K, 20 seconds"
    }
  ]
});

console.log(response.choices[0].message.content);

import { VlmRun } from "vlmrun";
import { z } from "zod";
import { zodToJsonSchema } from "zod-to-json-schema";

// Define the response schema with Zod
const VideoGenerationResponseSchema = z.object({
  url: z.string().describe("The URL of the generated video")
});

// Initialize the VLMRun client
const client = new VlmRun({
  apiKey: "<VLMRUN_API_KEY>",
  baseURL: "https://api.vlm.run/v1"
});

// Generate the video with structured output
const response = await client.agent.completions.create({
  model: "vlmrun-orion-1:auto",
  messages: [
    {
      role: "user",
      content: "Generate a video of a serene mountain landscape with flowing clouds, cinematic wide shot, golden hour lighting, 4K, 20 seconds"
    }
  ],
  response_format: {
    type: "json_schema",
    schema: zodToJsonSchema(VideoGenerationResponseSchema)
  }
});

const result = VideoGenerationResponseSchema.parse(JSON.parse(response.choices[0].message.content));