## Prerequisites Before you get started, you need: 1. An API key for your access method: a Poolside Platform API key, an API key for your organization’s Poolside deployment, or an OpenRouter API key. To get a key and send it with Bearer authentication, see [Authenticate API requests](https://docs.poolside.ai/api/overview#authenticate-api-requests). 2. `curl` or another tool that can make API requests. ## List available models Most API requests require you to pass a model `id`. To get all available models and their `ids`: - Poolside Platform - Poolside deployment - OpenRouter List models ``` curl --request GET \ --url https://inference.poolside.ai/v1/models \ --header 'Accept: application/json, application/problem+json' \ --header 'Authorization: Bearer ' ``` Response example ``` { "data": [ { "id": "poolside/laguna-s-2.1", "created": 1751637312, "owned_by": "system", "object": "model" } ], "object": "list" } ``` In this case, the response includes one model with the `id` `poolside/laguna-s-2.1`. This request does not require an API key. The response is not limited to Poolside models, so this example pipes the output to `jq` to filter for Poolside model `id` values: List models ``` curl --silent --request GET \ --url https://openrouter.ai/api/v1/models | jq '[.data[] | select(.id | startswith("poolside/")) | {id, name}]' ``` Response example ``` [ { "id": "poolside/laguna-s-2.1", "name": "Poolside: Laguna S 2.1" }, { "id": "poolside/laguna-s-2.1:free", "name": "Poolside: Laguna S 2.1 (free)" } ] ``` OpenRouter may offer free and paid Poolside models. To see current availability in the browser, see [Poolside models on OpenRouter](https://openrouter.ai/poolside). ## Send a chat prompt To generate completions from a model, you need the model `id` and your prompt formatted as `content` inside `messages` with the `user` role: Send chat prompt ``` curl --request POST \ --url https://inference.poolside.ai/v1/chat/completions \ --header 'Accept: application/json, application/problem+json' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer ' \ --data '{ "messages": [ { "content": "Explain cURL", "role": "user" } ], "model": "poolside/laguna-s-2.1" }' ``` Response example ``` { "model": "poolside/laguna-s-2.1", "created": 1751993576, "object": "chat.completion", "choices": [ { "index": 0, "message": { "content": "cURL is a powerful command-line tool used for transferring data to or from a server, supporting various protocols such as HTTP, HTTPS, FTP, and more. It's widely used for testing APIs, downloading files, and automating HTTP requests. cURL allows you to specify headers, methods (GET, POST, PUT, DELETE, etc.), and data payloads, making it versatile for a range of web-related tasks.\n", "role": "assistant" }, "finish_reason": "stop" } ], "usage": { "completion_tokens": 88, "prompt_tokens": 447, "total_tokens": 535 } } ``` ## Turn off thinking through the Poolside API Some Poolside models support per-request thinking control through Poolside API chat template settings. To turn off thinking, set `chat_template_kwargs.enable_thinking` to `false`: Turn off thinking ``` curl --request POST \ --url https://inference.poolside.ai/v1/chat/completions \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer ' \ --data '{ "model": "poolside/laguna-s-2.1", "messages": [ { "role": "user", "content": "What are channels in Go?" } ], "chat_template_kwargs": { "enable_thinking": false } }' ``` OpenAI-compatible tool calling behavior can vary by model and serving configuration. If you need to force a specific function call with `tool_choice`, such as `"required"` or a named function, try turning off thinking first by setting `chat_template_kwargs.enable_thinking` to `false`. ## Control reasoning through OpenRouter To control reasoning effort through OpenRouter-compatible models, include a `reasoning` object: ``` { "model": "", "messages": [ { "content": "Explain cURL", "role": "user" } ], "reasoning": { "effort": "max" } } ``` OpenRouter’s generic effort values are `max`, `xhigh`, `high`, `medium`, `low`, `minimal`, and `none`, but provider and model support varies. ## Stream responses For example, if you want to receive your response as a series of completion chunks returned as server-sent events, set `stream` to `true`. This is useful for real-time applications. Stream chat prompt ``` curl --request POST \ --url https://inference.poolside.ai/v1/chat/completions \ --header 'Accept: application/json, application/problem+json' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer ' \ --data '{ "messages": [ { "content": "Explain cURL", "role": "user" } ], "model": "poolside/laguna-s-2.1", "stream": true }' ``` Response example ``` data: {"model":"poolside/laguna-s-2.1","created":1754035552,"object":"chat.completion.chunk","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":""}]} data: {"model":"poolside/laguna-s-2.1","created":1754035552,"object":"chat.completion.chunk","choices":[{"index":0,"delta":{"content":"cURL","role":"assistant"},"finish_reason":""}]} ... ``` ## Send a chat prompt with extra context Optionally, you can add more context to a query. This is useful when you want to give the model information it does not have. Ask without context ``` curl --request POST \ --url https://inference.poolside.ai/v1/chat/completions \ --header 'Accept: application/json, application/problem+json' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer ' \ --data '{ "messages": [ { "content": "What is my name?", "role": "user" } ], "model": "poolside/laguna-s-2.1" }' ``` Ask with context ``` curl --request POST \ --url https://inference.poolside.ai/v1/chat/completions \ --header 'Accept: application/json, application/problem+json' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer ' \ --data '{ "messages": [ { "content": "path:/Users/name/Desktop/userinfo content:My name is Jason. Question: What is my name?", "role": "user" } ], "model": "poolside/laguna-s-2.1" }' ``` In the previous snippet, the message provides context about the user’s name. If you run this example, the response takes this information into account. Response example ``` { "model": "poolside/laguna-s-2.1", "created": 1751993576, "object": "chat.completion", "choices": [ { "index": 0, "message": { "content": "Based on the provided context, your name is Jason.", "role": "assistant" }, "finish_reason": "stop" } ], "usage": { "completion_tokens": 15, "prompt_tokens": 693, "total_tokens": 708 } } ``` ## Extend models with tools You can extend your model’s capabilities by providing tools (functions) that the model can call during conversations. Define a tool ``` curl --request POST \ --url https://inference.poolside.ai/v1/chat/completions \ --header 'Accept: application/json, application/problem+json' \ --header 'Content-Type: application/json' \ --header 'Authorization: Bearer ' \ --data '{ "model": "poolside/laguna-s-2.1", "messages": [ { "role": "user", "content": "what is the weather forecast for San Francisco" } ], "tools": [ { "type": "function", "function": { "name": "get_forecast", "description": "Get weather forecast for a city", "parameters": { "type": "object", "properties": { "city": { "type": "string", "description": "City name" } }, "required": [ "city" ], "additionalProperties": false } } } ] }' ``` When the model needs to use a tool, it responds with a `tool_calls` array in the model response message.