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Documentation Index

Fetch the complete documentation index at: https://docs.dottxt.ai/llms.txt

Use this file to discover all available pages before exploring further.

Get from zero to your first validated JSON object in about five minutes. Request API access here.

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dottxt CLI

The fastest way to see structured output using the dottxt CLI: 
pip install dottxt
export DOTTXT_API_KEY="your-api-key"

cat > contact.schema.json <<'JSON'
{
  "type": "object",
  "properties": {
    "name": { "type": "string", "minLength": 1 },
    "email": { "type": "string", "pattern": "^[^@]+@[^@]+$" },
    "role": { "type": "string" }
  },
  "required": ["name", "email"],
  "additionalProperties": false
}
JSON

dottxt generate \
  --model openai/gpt-oss-20b \
  --schema contact.schema.json \
  "Extract: John Smith <john@acme.com>, VP Engineering"
Ready to wire it into code? Follow the steps below.

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1. Install

pip install dottxt

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2. Set your API key

export DOTTXT_API_KEY="your-api-key"

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3. Run your first extraction

from pydantic import BaseModel, Field

from dottxt import DotTxt


class Contact(BaseModel):
    name: str = Field(min_length=1)
    email: str = Field(pattern=r"^[^@]+@[^@]+$")
    role: str | None = None


client = DotTxt()

result = client.generate(
    model="openai/gpt-oss-20b",
    input="Extract: John Smith <john@acme.com>, VP Engineering",
    response_format=Contact,
)

print(result.model_dump())
Expected output: 
{
  "name": "John Smith",
  "email": "john@acme.com",
  "role": "VP Engineering"
}

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4. Next steps