Large language models (LLMs) have revolutionized natural language processing by generating impressive text based on massive pretraining and strategic alignment with user preferences during post training. However, their inherent limitation is that—while they excel at generating human-like language—they lack the ability to access or update real-world information on demand. This is where function (or tool) calling comes into play. By enabling LLMs to invoke external functions or APIs, we can dynamically extend their capabilities, making them not only great conversationalists but also powerful, interactive agents.
We are thrilled to announce that Fireworks AI API now supports function calling on top of the latest generation DeepSeek V3 model.
Function calling refers to the process by which an LLM detects that a user request requires external data or action and then produces a structured output (typically in JSON) that specifies which function to call along with the necessary arguments. For example, instead of simply generating text to answer “What is the weather in London?” an LLM equipped with function calling can output a JSON object that triggers a weather API call. Once the external tool returns the relevant data, the LLM integrates this information into its final response.
This paradigm is sometimes also called tool calling, and it fundamentally transforms LLMs from static knowledge generators into dynamic, interactive agents capable of real‐world tasks.
At its core, function calling involves the following key steps:
The ability to call functions extends LLMs’ applicability into numerous domains:
We are excited to announce that the Fireworks AI API now offers function calling capabilities integrated with the latest DeepSeek v3 model. This enhancement enables developers to create applications where the model can interact with external functions or APIs, thereby extending its capabilities beyond static responses.
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DeepSeek has never released a complete official template for tool formatting in the DeepSeek v3 model. We did our best to deduce it from info available in the community. We will keep updating the template as new information appears.
One issue we discovered during testing is that the model is not great at multi-turn function calling. It performs best in scenarios where a single user message triggers (potentially multiple) function call(s).
The function calling feature is currently enabled on the Serverless offering only for now. If you want it activated for your On Demand or Reserved instances, please reach out to us.
Find the detailed documentation for function calling here.
Try out DeepSeek models on Fireworks AI Model Library