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updated docs with responses API options

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docs/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/index.md
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@ -25,21 +25,26 @@ Select the model to use to generate the completion.
n8n dynamically loads models from OpenAI, and you'll only see the models available to your account.
### Use Responses API
OpenAI provides two endpoints for generating output from a model:
- **Chat Completions**: The Chat Completions API endpoint generates a model response from a list of messages that comprise a conversation. The API requires the user to handle conversation state manually, for example by adding a [Simple Memory](docs/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.memorybufferwindow/index.md) subnode. For new projects, OpenAI recommends to use the Responses API.
- **Responses**: The Responses API is an agentic loop, allowing the model to call multiple built-in tools within the span of one API request. It also supports persistent conversations by passing a `conversation_id`.
Toggle to **Use Responses API** if you want the model to generate output using the Responses API. Otherwise, the OpenAI Chat Model node will default to using the Chat Completions API.
Refer to the OpenAI documentation for a [comparison of the Chat Completions and Responses APIs](https://platform.openai.com/docs/guides/migrate-to-responses).
### Built-in Tools
The OpenAI Responses API provides a range of [built-in tools](https://platform.openai.com/docs/guides/tools) to enrich the model's response:
The OpenAI Responses API provides a range of [built-in tools](https://platform.openai.com/docs/guides/tools) to enrich the model's response. Toggle to **Use Responses API** if you want the model to have access to the following built-in tools:
- **Web Search**: Allows models to search the web for the latest information before generating a response.
- **MCP Servers**: Allows models to connect to remote MCP servers. Find out more about using remote MCP servers as tools [here](https://platform.openai.com/docs/guides/tools-connectors-mcp).
- **File Search**: Allow models to search your knowledgebase from previously uploaded files for relevant information before generating a response. Refer to the [OpenAI documentation](https://platform.openai.com/docs/guides/tools-file-search) for more information.
- **Code Interpreter**: Allows models to write and run Python code in a sandboxed environment.
## Node options
Use these options to further refine the node's behavior.
### Base URL
Enter a URL here to override the default URL for the API.
Use these options to further refine the node's behavior. The following options are available whether you use the Responses API to generate model output or not.
### Frequency Penalty
@ -49,10 +54,6 @@ Use this option to control the chances of the model repeating itself. Higher val
Enter the maximum number of tokens used, which sets the completion length.
### Response Format
Choose **Text** or **JSON**. **JSON** ensures the model returns valid JSON.
### Presence Penalty
Use this option to control the chances of the model talking about new topics. Higher values increase the chance of the model talking about new topics.
@ -73,6 +74,9 @@ Enter the maximum number of times to retry a request.
Use this option to set the probability the completion should use. Use a lower value to ignore less probable options.
## Additional node options (Responses API only)
The following, additional options are available when toggling to **Use Responses API**.
### Conversation ID
The conversation that this response belongs to. Input items and output items from this response are automatically added to this conversation after this response completes.
@ -95,10 +99,7 @@ Define an integer between 0 and 20 specifying the number of most likely tokens t
Choose a response format: Text, JSON Schema, or JSON Object. Use of JSON Schema is recommended, if you want to receive data in JSON format.
### Prompt
Configure the prompt filled with a unique ID, its version, and substitutable variables.
### Reasoning Effort
Control the reasoning level of AI results: Low, Medium, or High.
Configure the prompt filled with a unique ID, its version, and substitutable variables. Prompts are configured via the OpenAI dashboard.
## Templates and examples