ostruct-cli 0.3.0

CLI for OpenAI Structured Output

ostruct-cli

Command-line interface for working with OpenAI models and structured output, powered by the openai-structured library.

Features

• Generate structured output from natural language using OpenAI models
• Rich template system for defining output schemas
• Automatic token counting and context window management
• Streaming support for real-time output
• Caching system for cost optimization
• Secure handling of sensitive data

Installation

pip install ostruct-cli

Quick Start

1. Set your OpenAI API key:

export OPENAI_API_KEY=your-api-key

2. Create a task template file task.j2:

Extract information about the person: {{ stdin }}

3. Create a schema file schema.json:

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "The person's full name"
    },
    "age": {
      "type": "integer",
      "description": "The person's age"
    },
    "occupation": {
      "type": "string",
      "description": "The person's job or profession"
    }
  },
  "required": ["name", "age", "occupation"]
}

4. Run the CLI:

echo "John Smith is a 35 year old software engineer" | ostruct --task @task.j2 --schema schema.json

Output:

{
  "name": "John Smith",
  "age": 35,
  "occupation": "software engineer"
}

About Template Files

Template files use the .j2 extension to indicate they contain Jinja2 template syntax. This convention:

• Enables proper syntax highlighting in most editors
• Makes it clear the file contains template logic
• Follows industry standards for Jinja2 templates

While the CLI accepts templates with any extension (when prefixed with @), we recommend using .j2 for better tooling support and clarity.

Debug Options

• --show-model-schema: Display the generated Pydantic model schema
• --debug-validation: Show detailed schema validation debugging
• --verbose-schema: Enable verbose schema debugging output
• --debug-openai-stream: Enable low-level debug output for OpenAI streaming (very verbose)
• --progress-level {none,basic,detailed}: Set progress reporting level (default: basic)

All debug and error logs are written to:

• ~/.ostruct/logs/ostruct.log: General application logs
• ~/.ostruct/logs/openai_stream.log: OpenAI streaming operations logs

For more detailed documentation and examples, visit our documentation.

Development

To contribute or report issues, please visit our GitHub repository.

Development Setup

1. Clone the repository:

git clone https://github.com/yanivgolan/ostruct.git
cd ostruct

2. Install Poetry if you haven't already:

curl -sSL https://install.python-poetry.org | python3 -

3. Install dependencies:

poetry install

4. Install openai-structured in editable mode:

poetry add --editable ../openai-structured  # Adjust path as needed

5. Run tests:

poetry run pytest

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Migration from openai-structured

If you were previously using the CLI bundled with openai-structured (pre-1.0.0), this is its new home. The migration is straightforward:

1. Update openai-structured to version 1.0.0 or later
2. Install ostruct-cli
3. Replace any openai-structured CLI commands with ostruct

The functionality remains the same, just moved to a dedicated package for better maintenance and focus.