Create Skills

# Upload a local skill folder directly (zips and creates in one step)
vlmrun skills upload ./my-skill

# Override name/description from SKILL.md frontmatter
vlmrun skills upload ./my-skill --name "invoice-extraction" --description "Extract structured data from invoices"

from vlmrun.client import VLMRun
from pathlib import Path

client = VLMRun(api_key="<VLMRUN_API_KEY>")

# One-step: zip, upload, and create a skill from a local directory
skill = client.skills.create_from_directory(
    directory=Path("./my-skill"),
)
print(f"Created skill: {skill.skill_name} (type={skill.type})")

# Override name/description from SKILL.md frontmatter
skill = client.skills.create_from_directory(
    directory=Path("./my-skill"),
    name="invoice-extraction",
    description="Extract structured data from invoices",
)

# From a text prompt
vlmrun skills create --prompt "Extract invoice_id, date, and total_amount from invoices."

# With a JSON schema file
vlmrun skills create --prompt "Extract invoice data" --schema schema.json

from vlmrun.client import VLMRun

client = VLMRun(api_key="<VLMRUN_API_KEY>")

skill = client.skills.create(
    prompt="Extract invoice_id, date, and total_amount from invoices.",
    json_schema={
        "type": "object",
        "properties": {
            "invoice_id": {"type": "string"},
            "invoice_date": {"type": "string", "format": "date"},
            "total_amount": {"type": "number"}
        },
        "required": ["invoice_id", "invoice_date", "total_amount"]
    }
)
print(f"Created skill: {skill.id} ({skill.name})")

vlmrun skills create --session-id "<session-id>"

from vlmrun.client import VLMRun

client = VLMRun(api_key="<VLMRUN_API_KEY>")

skill = client.skills.create(session_id="<session-id>")
print(f"Created skill: {skill.id} ({skill.name})")