Generate Chat Completion - BlinkOps Documentation

Generate a chat completion from a model using a conversation history.

External DocumentationTo learn more, visit the LiteLLM documentation.

Basic Parameters

Parameter	Description
Completions Number	The number of completions to generate.
Frequency Penalty	Penalize new tokens based on their existing frequency. Accept values from `-2.0` to `2.0`.
Include Log Probabilities	Select to include the log probabilities for the most likely tokens.
Include Top Log Probabilities	The number of log probabilities to return for the most likely tokens at each generation step. Accepts an integer value between `0` and `5`. This parameter is only available when `logprobs` is set to `true`.
Logit Bias	A JSON object mapping token IDs to bias values. This modifies the probability of generating specific tokens. Example: `{ “2683”: -100, “7211”: 5 }`
Max Completion Tokens	The maximum number of tokens to generate in the completion. This includes visible output tokens and reasoning tokens. Note: This parameter can’t be used along with `Max Tokens`.
Max Tokens	The maximum number of tokens to generate in the completion. Note: This parameter can’t be used along with `Max Completion Tokens`.
Messages	The list of messages in the conversation. Example: `[ { “role”: “system”, “content”: “You are a helpful assistant that answers questions about programming.” }, { “role”: “user”, “content”: “Can you explain what a JSON map is?” } ]`
Model ID	The ID of the model to get chat completions with.
Parallel Tool Calls	Select to allow the model to call multiple tools in parallel. Note: To set this parameter to `True`, the parameter `Tools` must be set.
Presence Penalty	Penalize tokens based on whether they appear in the text so far. Valid range is `-2.0` - `2.0`.
Provider	Select a provider of the chat model, this will allow to have access to the corresponding parameters.
Response Format	The format that the model must output. Set to `{ "type": "json_object" }` to enable JSON mode, which guarantees the model generates valid JSON. Important Note: When using JSON mode, you must also instruct the model to produce JSON via a system or user message. Without this, the model may generate whitespace indefinitely until reaching the token limit.
Safety Identifier	A unique ID to help track and manage safety-related requests.
Seed	A seed to make the generated output more deterministic.
Stop Tokens	A comma-separated list of tokens that will stop the generation. Example: `\n`, `END`, `---`
Temperature	The degree of randomness to use in the generation. Valid range is `0.0` - `2.0`.
Tool Choice	Control which function is called by the model. This parameter accepts either a string or an object. The optional values for string are: * `auto` * `required` * `none` Object Example: `{ “type”: “function”, “function”: { “name”: “get_weather” } }`
Tools	A list of JSON objects representing tools that the model can use. Example: [ { “type”: “function”, “function”: { “name”: “get_weather”, “description”: “Fetches the current weather for a given location.”, “parameters”: { “type”: “object”, “properties”: { “location”: { “type”: “string”, “description”: “The city or location to get the weather for.” }, “date”: { “type”: “string”, “description”: “The date for which to get the weather (YYYY-MM-DD).” } }, “required”: [“location”] } } } ]
Top P	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with `Top P` probability mass.
User ID	The ID of the user to associate with the request.

Advanced Parameters

Parameter	Description
API Base	The API endpoint you want to call the model with.
API Version	The API version for the call. This is an Azure specific parameter.
Additional Parameters	A JSON object for additional body parameters. Values specified in this parameter will override equivalent parameters. For example: `{ “first_key”: 12345, “second_key”: “some_value” }` The object must follow the vendor’s structure as defined in the API documentation.
Fallbacks	A List of JSON objects representing fallback models to use in case the primary model fails. Example: `[ { “openai/*”: [ “gpt-4o-mini” ] } ]`
Metadata	Additional metadata to send with the request for logging. Example: `{ “request_id”: “req-8f21c9a2”, “tenant_id”: “acme-prod”, “workflow”: “blink-workflow”, “feature”: “docs-helper”, “trace_id”: “trace-91b7e3”, “user_id”: “user-1234”, “debug”: true }`
Num Retries	The number of times to retry the request in case of `APIError`, `TimeoutError` or `ServiceUnavailableError`.

Example Output

{
	"id": "chatcmpl-CzHVeyzZj09MzGSXlmesrcTztrr66",
	"created": 1768721350,
	"model": "gpt-4o-mini-2024-07-18",
	"object": "chat.completion",
	"system_fingerprint": "fp_29330a9688",
	"choices": [
		{
			"finish_reason": "stop",
			"index": 0,
			"message": {
				"content": "The current weather in New York City is cloudy, with a temperature of 12°C.",
				"role": "assistant"
			},
			"logprobs": {
				"content": [
					{
						"token": "The",
						"bytes": [
							84
						],
						"logprob": -0.001632451661862433,
						"top_logprobs": [
							{
								"token": "The",
								"bytes": [
									84
								],
								"logprob": -0.001632451661862433
							},
							{
								"token": "In",
								"bytes": [
									73
								],
								"logprob": -7.001632213592529
							},
							{
								"token": "Currently",
								"bytes": [
									67
								],
								"logprob": -7.376632213592529
							}
						]
					}
				]
			}
		}
	]
}

Workflow Library Example

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​Basic Parameters

​Advanced Parameters

​Example Output

​Workflow Library Example

Basic Parameters

Advanced Parameters

Example Output

Workflow Library Example