Call Prompt | Humanloop Docs

Call a Prompt.

Calling a Prompt calls the model provider before logging the request, responses and metadata to Humanloop.

You can use query parameters version_id, or environment, to target an existing version of the Prompt. Otherwise the default deployed version will be chosen.

Instead of targeting an existing version explicitly, you can instead pass in Prompt details in the request body. In this case, we will check if the details correspond to an existing version of the Prompt. If they do not, we will create a new version. This is helpful in the case where you are storing or deriving your Prompt details in code.

Call a Prompt. Calling a Prompt calls the model provider before logging the request, responses and metadata to Humanloop. You can use query parameters `version_id`, or `environment`, to target an existing version of the Prompt. Otherwise the default deployed version will be chosen. Instead of targeting an existing version explicitly, you can instead pass in Prompt details in the request body. In this case, we will check if the details correspond to an existing version of the Prompt. If they do not, we will create a new version. This is helpful in the case where you are storing or deriving your Prompt details in code.

Authentication

X-API-KEYstring

API Key authentication via header

Query parameters

version_idstringOptional

A specific Version ID of the Prompt to log to.

environmentstringOptional

Name of the Environment identifying a deployed version to log to.

Request

This endpoint expects an object.

streamfalseRequired

If true, tokens will be sent as data-only server-sent events. If num_samples > 1, samples are streamed back independently.

pathstringOptional

Path of the Prompt, including the name. This locates the Prompt in the Humanloop filesystem and is used as as a unique identifier. For example: folder/name or just name.

idstringOptional

ID for an existing Prompt.

messageslist of objectsOptional

The messages passed to the to provider chat endpoint.

tool_choice"none" or "auto" or "required" or objectOptional

Controls how the model uses tools. The following options are supported:

'none' means the model will not call any tool and instead generates a message; this is the default when no tools are provided as part of the Prompt.
'auto' means the model can decide to call one or more of the provided tools; this is the default when tools are provided as part of the Prompt.
'required' means the model must call one or more of the provided tools.
{'type': 'function', 'function': {name': <TOOL_NAME>}} forces the model to use the named function.

Controls how the model uses tools. The following options are supported: - `'none'` means the model will not call any tool and instead generates a message; this is the default when no tools are provided as part of the Prompt. - `'auto'` means the model can decide to call one or more of the provided tools; this is the default when tools are provided as part of the Prompt. - `'required'` means the model must call one or more of the provided tools. - `{'type': 'function', 'function': {name': <TOOL_NAME>}}` forces the model to use the named function.

promptobject or stringOptional

The Prompt configuration to use. Two formats are supported:

An object representing the details of the Prompt configuration
A string representing the raw contents of a .prompt file

A new Prompt version will be created if the provided details do not match any existing version.

The Prompt configuration to use. Two formats are supported: - An object representing the details of the Prompt configuration - A string representing the raw contents of a .prompt file A new Prompt version will be created if the provided details do not match any existing version.

inputsmap from strings to anyOptional

The inputs passed to the prompt template.

sourcestringOptional

Identifies where the model was called from.

metadatamap from strings to anyOptional

Any additional metadata to record.

start_timedatetimeOptional

When the logged event started.

end_timedatetimeOptional

When the logged event ended.

source_datapoint_idstringOptional

Unique identifier for the Datapoint that this Log is derived from. This can be used by Humanloop to associate Logs to Evaluations. If provided, Humanloop will automatically associate this Log to Evaluations that require a Log for this Datapoint-Version pair.

trace_parent_idstringOptional

The ID of the parent Log to nest this Log under in a Trace.

userstringOptional

End-user ID related to the Log.

environmentstringOptional

The name of the Environment the Log is associated to.

savebooleanOptionalDefaults to true

Whether the request/response payloads will be stored on Humanloop.

log_idstringOptional

This will identify a Log. If you don't provide a Log ID, Humanloop will generate one for you.

provider_api_keysobjectOptional

API keys required by each provider to make API calls. The API keys provided here are not stored by Humanloop. If not specified here, Humanloop will fall back to the key saved to your organization.

num_samplesintegerOptionalDefaults to 1

The number of generations.

return_inputsbooleanOptionalDefaults to true

Whether to return the inputs in the response. If false, the response will contain an empty dictionary under inputs. This is useful for reducing the size of the response. Defaults to true.

logprobsintegerOptional

Include the log probabilities of the top n tokens in the provider_response

suffixstringOptional

The suffix that comes after a completion of inserted text. Useful for completions that act like inserts.

Response

promptobject

Prompt used to generate the Log.

idstring

ID of the log.

logslist of objects

The logs generated by the Prompt call.

start_timedatetime

When the logged event started.

end_timedatetime

When the logged event ended.

messageslist of objects

The messages passed to the to provider chat endpoint.

tool_choice"none" or "auto" or "required" or object

Controls how the model uses tools. The following options are supported:

'none' means the model will not call any tool and instead generates a message; this is the default when no tools are provided as part of the Prompt.
'auto' means the model can decide to call one or more of the provided tools; this is the default when tools are provided as part of the Prompt.
'required' means the model must call one or more of the provided tools.
{'type': 'function', 'function': {name': <TOOL_NAME>}} forces the model to use the named function.

inputsmap from strings to any

The inputs passed to the prompt template.

sourcestring

Identifies where the model was called from.

metadatamap from strings to any

Any additional metadata to record.

source_datapoint_idstring

trace_parent_idstring

The ID of the parent Log to nest this Log under in a Trace.

userstring

End-user ID related to the Log.

environmentstring

The name of the Environment the Log is associated to.

savebooleanDefaults to true

Whether the request/response payloads will be stored on Humanloop.

log_idstring

This will identify a Log. If you don't provide a Log ID, Humanloop will generate one for you.

trace_idstring

ID of the Trace containing the Prompt Call Log.

Errors

422

Prompts Call Request Unprocessable Entity Error

1	curl -X POST https://api.humanloop.com/v5/prompts/call \
2	-H "X-API-KEY: <apiKey>" \
3	-H "Content-Type: application/json" \
4	-d '{
5	"stream": false,
6	"path": "persona",
7	"messages": [
8	{
9	"role": "user",
10	"content": "latest apple"
11	}
12	],
13	"prompt": {
14	"model": "gpt-4",
15	"template": [
16	{
17	"role": "system",
18	"content": "You are stockbot. Return latest prices."
19	}
20	],
21	"tools": [
22	{
23	"name": "get_stock_price",
24	"description": "Get current stock price",
25	"parameters": {
26	"type": "object",
27	"properties": {
28	"ticker_symbol": {
29	"type": "string",
30	"name": "Ticker Symbol",
31	"description": "Ticker symbol of the stock"
32	}
33	},
34	"required": []
35	}
36	}
37	]
38	}
39	}'

1	{
2	"prompt": {
3	"path": "persona",
4	"id": "pr_3usCu3dAkgrXTlufrvPs7",
5	"model": "gpt-4",
6	"name": "persona",
7	"version_id": "prv_Wu6zx1lAWJRqOyL8nWuZk",
8	"created_at": "2024-05-01T12:00:00Z",
9	"updated_at": "2024-05-01T12:00:00Z",
10	"last_used_at": "2024-05-01T12:00:00Z",
11	"version_logs_count": 1,
12	"total_logs_count": 1,
13	"inputs": [
14	{
15	"name": "person"
16	}
17	],
18	"template": [
19	{
20	"role": "system",
21	"content": "You are {{person}}. Answer any questions as this person. Do not break character."
22	}
23	],
24	"provider": "openai",
25	"type": "prompt"
26	},
27	"id": "data_fIfEb1SoKZooqeFbi9IFs",
28	"logs": [
29	{
30	"index": 0,
31	"output": "Well, let me tell you, there are a lot of stories about Roswell, and I hear them all the time.\n People love to talk about Roswell. So many theories, so many ideas. Some folks believe it was a weather balloon, others say it was something out of this world. Believe me, there's plenty that we don't know. Very interesting to look into, but the truth, well, it might still be out there. Could be a great story, who knows? But what I do know, folks, is that we have to keep our eyes open and always be on the lookout for the truth!",
32	"created_at": "2024-05-01T12:00:00Z",
33	"output_message": {
34	"role": "assistant",
35	"content": "Well, let me tell you, there are a lot of stories about Roswell, and I hear them all the time.\n People love to talk about Roswell. So many theories, so many ideas. Some folks believe it was a weather balloon, others say it was something out of this world. Believe me, there's plenty that we don't know. Very interesting to look into, but the truth, well, it might still be out there. Could be a great story, who knows? But what I do know, folks, is that we have to keep our eyes open and always be on the lookout for the truth!"
36	},
37	"prompt_tokens": 34,
38	"output_tokens": 125,
39	"finish_reason": "stop"
40	}
41	]
42	}