From a3bc37dcc47874d4dea8dee4f89501611f859cd1 Mon Sep 17 00:00:00 2001 From: Celina Hanouti Date: Tue, 5 Aug 2025 18:10:07 +0100 Subject: [PATCH 1/2] fix-snippets --- docs/inference-providers/guides/gpt-oss.md | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/docs/inference-providers/guides/gpt-oss.md b/docs/inference-providers/guides/gpt-oss.md index 7f0df6c911..93a1c49d4b 100644 --- a/docs/inference-providers/guides/gpt-oss.md +++ b/docs/inference-providers/guides/gpt-oss.md @@ -43,7 +43,7 @@ Getting started with GPT OSS models on Inference Providers is simple and straigh Here's a basic example using [gpt-oss-120b](https://hf.co/openai/gpt-oss-120b) through the fast Cerebras provider: - + ```python @@ -64,6 +64,7 @@ print(response.choices[0].message.content) ``` + ```ts @@ -86,7 +87,7 @@ console.log(response.choices[0].message.content); You can also give the model access to tools. Below, we define a `get_current_weather` function and let the model decide whether to call it: - + ```python @@ -131,6 +132,7 @@ print(response.choices[0].message) ``` + ```ts @@ -178,7 +180,7 @@ console.log(response.choices[0].message); For structured tasks like data extraction, you can force the model to return a valid JSON object using the `response_format` parameter. We use the Fireworks AI provider. - + ```python @@ -301,7 +303,7 @@ The implementation is based on the open-source [huggingface/responses.js](https: Unlike traditional text streaming, the Responses API uses a system of semantic events for streaming. This means the stream is not just raw text, but a series of structured event objects. Each event has a type, so you can listen for the specific events you care about, such as content being added (`output_text.delta`) or the message being completed (`completed). The example below shows how to iterate through these events and print the content as it arrives. - + ```python @@ -327,6 +329,7 @@ for event in stream: ``` + ```ts @@ -357,7 +360,7 @@ for await (const event of stream) { You can extend the model with tools to access external data. The example below defines a get_current_weather function that the model can choose to call. - + ```python @@ -399,6 +402,7 @@ print(response) ``` + ```ts @@ -445,7 +449,7 @@ console.log(response); The API's most advanced feature is Remote MCP calls, which allow the model to delegate tasks to external services. Calling a remote MCP server with the Responses API is straightforward. For example, here's how you can use the DeepWiki MCP server to ask questions about nearly any public GitHub repository. - + ```python @@ -474,6 +478,7 @@ print(response) ``` + ```ts @@ -508,7 +513,7 @@ console.log(response); You can also control the model's "thinking" time with the `reasoning` parameter. The following example nudges the model to spend a medium amount of effort on the answer. - + ```python From f98db3b66f2fd69479f355bffc7f34a40de7ede9 Mon Sep 17 00:00:00 2001 From: Celina Hanouti Date: Tue, 5 Aug 2025 18:12:43 +0100 Subject: [PATCH 2/2] nit --- docs/inference-providers/guides/gpt-oss.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/inference-providers/guides/gpt-oss.md b/docs/inference-providers/guides/gpt-oss.md index 93a1c49d4b..25d48b43fa 100644 --- a/docs/inference-providers/guides/gpt-oss.md +++ b/docs/inference-providers/guides/gpt-oss.md @@ -513,7 +513,7 @@ console.log(response); You can also control the model's "thinking" time with the `reasoning` parameter. The following example nudges the model to spend a medium amount of effort on the answer. - ```python