POST
/
v0
/
logs
curl --request POST \
  --url 'https://api.unify.ai/v0/logs' \
  --header "Authorization: Bearer $UNIFY_KEY" \
  --header 'Content-Type: application/json' \
  --data '{
    "project": "eval-project",
    "context": "experiment1/trial1"
}'

{
    "info": "Logs created successfully!",
    "log_event_ids": [
        101,
        102,
        103
    ],
    "row_ids": {
        "name": "row_id",
        "ids": [
            0,
            1,
            2
        ]
    }
}

Creates one or more logs associated to a project. Logs are LLM-call-level data that might depend on other variables.

If a context is specified and it is versioned, all logs will be versioned and mutable. The context version will be incremented automatically when logs are added, updated, or removed.

The context parameter can be:

  • A string: Uses the string as the context name with default values (description=None, is_versioned=False)
  • An object: Uses the object’s name, description, and is_versioned properties

An “explicit_types” dictionary can be passed as part of the entries. If present, any matching key inside this dictionary will override the inferred type of that particular entry. The explicit_types dictionary can also specify if a field is mutable via a ‘mutable’ boolean flag and if a field is unique via a ‘unique’ boolean flag:

{
    "field_name": {
        "type": "str",
        "mutable": false,  # Makes the field immutable
        "unique": true     # Makes the field unique
    }
}

By default, all fields are immmutable unless specified otherwise. Once a field is marked as mutable, only then can it be modified through the update endpoint.

This method returns the ids of the new stored logs.

​
Authorizations

​
Authorization
string
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

​
Body

​
project
string
required

Name of the project the stored entries will be associated to.

​
context
any | string | null

Optional context path to update for the logs. Can use ’/’ for nested contexts (e.g. ‘training/batch1’). Can be a string (which will be interpreted with description=None and is_versioned=False) or a ContextCreateRequest object.

​
params
object | array
default:"{}"

Dictionary containing one or more key:value pairs that will be logged into the platform. Can be either a single dictionary or a list of dictionaries for batch processing. When using lists for both params and entries, their lengths must match. Values must be JSON serializable. If a explicit_types dictionary is present, its values will override the inferred types of the entries. The explicit_types dictionary can also specify if a field is mutable via a ‘mutable’ boolean flag, or unique via a ‘unique’ boolean flag. For enum types, use the EnumType model with ‘values’ list and optional ‘restrict’ flag. Omit ‘values’ to create an open enum (auto-seeding). For contexts with nested unique IDs, parent ID values for the leftmost N-1 unique columns can be supplied as normal param keys. The rightmost column is always auto-incremented. For example, if unique columns are [‘user’, ‘session’, ‘step’], you can provide ‘user’ and ‘session’ values in params, and ‘step’ will be auto-generated.

​
entries
object | array
default:"{}"

Dictionary containing one or more key:value pairs that will be logged into the platform. Can be either a single dictionary or a list of dictionaries for batch processing. When using lists for both params and entries, their lengths must match. Values must be JSON serializable. If a explicit_types dictionary is present, its values will override the inferred types of the entries. The explicit_types dictionary can also specify if a field is mutable via a ‘mutable’ boolean flag, or unique via a ‘unique’ boolean flag. For enum types, use the EnumType model with ‘values’ list and optional ‘restrict’ flag. Omit ‘values’ to create an open enum (auto-seeding). For contexts with nested unique IDs, parent ID values for the leftmost N-1 unique columns can be supplied as normal entry keys. The rightmost column is always auto-incremented. For example, if unique columns are [‘user’, ‘session’, ‘step’], you can provide ‘user’ and ‘session’ values in entries, and ‘step’ will be auto-generated.

curl --request POST \
  --url 'https://api.unify.ai/v0/logs' \
  --header "Authorization: Bearer $UNIFY_KEY" \
  --header 'Content-Type: application/json' \
  --data '{
    "project": "eval-project",
    "context": "experiment1/trial1"
}'

{
    "info": "Logs created successfully!",
    "log_event_ids": [
        101,
        102,
        103
    ],
    "row_ids": {
        "name": "row_id",
        "ids": [
            0,
            1,
            2
        ]
    }
}