Function calling (also called tool calling) lets LLMs respond with structured function names and arguments that you can execute in your application. It enables models to interact with external systems, retrieve real-time data, and power agentic AI workflows. Pass function descriptions to theDocumentation Index
Fetch the complete documentation index at: https://docs.together.ai/llms.txt
Use this file to discover all available pages before exploring further.
tools parameter, and the model returns tool_calls when it determines a function should be used. You then execute these functions and optionally pass the results back to the model for further processing.
Patterns
Function calling fits a handful of common shapes. Pick the one that matches what you’re building, then follow the link for runnable Python, TypeScript, and cURL examples.| Pattern | Description | Use cases | Page |
|---|---|---|---|
| Simple | One function, one call | Basic utilities, simple queries | Call functions |
| Multiple | Choose from many functions | Many tools, model has to choose | Call functions |
| Parallel | Same function, multiple calls in one turn | Complex prompts, batched lookups | Parallel calls |
| Parallel multiple | Multiple functions, parallel calls | Single requests that need many tools | Parallel calls |
| Multi-step | Sequential function calling in one turn | Data-processing workflows | Agentic patterns |
| Multi-turn | Conversational context plus functions | Agents with humans in the loop | Agentic patterns |
| Vision | Tool use with image inputs | Extract structured data from images | Vision-language function calling |
Supported models
For the current list of models that support function calling, see the serverless and dedicated endpoint model catalogs.Next steps
- Call functions: one tool call per response (simple and multiple).
- Call functions in parallel: multiple tool calls in one response.
- Agentic patterns: multi-step and multi-turn loops.
- Vision-language function calling: combine image understanding with tool use on VLMs.