README.md•3.68 kB
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*Simple data retrieval for AI with unmatched control, precision, and speed.*
[](https://github.com/kruskal-labs/toolfront/actions/workflows/test.yml)
[](https://pypi.org/project/toolfront/)
[](https://discord.gg/rRyM7zkZTf)
[](https://x.com/toolfront)
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---
**Documentation: [docs.toolfront.ai](http://docs.toolfront.ai/)**
---
## Installation
Install with `pip` or your favorite PyPI package manager.
```bash
pip install toolfront
```
## Example 1: Text2SQL with ChatGPT
```python
from toolfront import Database
db = Database("postgres://user:pass@localhost:5432/mydb")
context = "We're an e-commerce company. Sales data is in the `cust_orders` table."
# Returns a string
answer = db.ask("What's our best-selling product?", model="openai:gpt-4o", context=context)
# >>> "Wireless Headphones Pro"
```
> **Note**: For databases, install with PyPI extras, e.g.: `pip install "toolfront[postgres]"`. See the [documentation](http://docs.toolfront.ai/) for the complete list of 10+ databases.
## Example 2: API retrieval with Claude
```python
from toolfront import API
api = API("http://localhost:8000/openapi.json")
# Returns a list of integers
answer: list[int] = api.ask("Get the last 5 order IDs for user_id=42", model="anthropic:claude-3-5-sonnet")
# >>> [1001, 998, 987, 976, 965]
```
> **Note**: ToolFront supports any API with an OpenAPI (formerly Swagger) specification. Most common APIs like Slack, Discord, and GitHub have OpenAPI specs. See the [documentation](http://docs.toolfront.ai/) for more details.
## Example 3: Document information extraction with Gemini
```python
from toolfront import Document
from pydantic import BaseModel, Field
class CompanyReport(BaseModel):
company_name: str = Field(..., description="Name of the company")
revenue: int | float = Field(..., description="Annual revenue in USD")
is_profitable: bool = Field(..., description="Whether the company is profitable")
doc = Document("/path/annual_report.pdf")
# Returns a structured Pydantic object
answer: CompanyReport = doc.ask("Extract the key company information from this report", model="google:gemini-pro")
# >>> CompanyReport(company_name="TechCorp Inc.", revenue=2500000, is_profitable=True)
```
> **Note**: ToolFront supports OpenAI, Anthropic, Google, xAI, and 14+ AI model providers. See the [documentation](http://docs.toolfront.ai/) for the complete list.
## Example 4: Snowflake MCP Server
```json
{
"mcpServers": {
"toolfront": {
"command": "uvx",
"args": [
"toolfront[snowflake]",
"snowflake://user:pass@account/warehouse/database"
]
}
}
}
```
## Community & Contributing
- **Discord**: Join our [community server](https://discord.gg/rRyM7zkZTf) for real-time help and discussions
- **X**: Follow us [@toolfront](https://x.com/toolfront) for updates and news
- **Issues**: Report bugs or request features on [GitHub Issues](https://github.com/kruskal-labs/toolfront/issues)
## License
This project is licensed under the terms of the MIT license.