Skip to main content
POST
/
api
/
request-logs
/
list
/
url = "https://api.keywordsai.co/api/request-logs/list/?page=1&sort_by=-id&is_test=false&all_envs=false&fetch_filters=false&page_size=1"


from urllib.parse import urlencode
params = {
    "page": 1,
    "sort_by": "-id",
    "is_test": "false",
    "all_envs": "false",
    "fetch_filters": "false",
    "page_size": 1
}
url = f"https://api.keywordsai.co/api/request-logs/list/?{urlencode(params)}"
headers = {
    "Authorization": f"Api-Key {YOUR_KEYWORDS_AI_API_KEY}",
}
data = {
    "filters": {}
}
response = requests.post(url, headers=headers, json=data)

{
    "results": [
       {
        "unique_id": "xxxxx",
        "organization_key__name": "Keywords AI Default",
        "organization": "Keywords AI",
        "user": "hendrix@keywordsai.co",
        "is_example": false,
        "status": "success",
        "prompt_tokens": 452,
        "completion_tokens": 89,
        "cost": 0.0005869,
        "prompt_messages": [
                {
                    "role": "system",
                    "content": "You are a helpful assistant"
                },
                {
                    "role": "user",
                    "content": "What is Keywords AI?"
                }
        ],
        "completion_message": {
                "role": "assistant",
                "content": "Keywords AI is a unified DevOps platform for AI products."
        },
        "latency": 1.2114145755767822,
        "model": "gpt-3.5-turbo",
        "foundation_model": "gpt-3.5-turbo",
        "provider_id": "openai",
        "tool_choice": null,
        "tools": null,
        "tool_calls": null,
        "timestamp": "2024-06-24T21:33:06.601353Z",
        "failed": false,
        "time_to_first_token": null,
        "routing_time": 0.0,
        "metadata": {
            // any params you want to pass in the request
            },
        "stream": false,
        "status_code": 200,
        "customer_identifier": "123456",
        "customer_email": "",
        "used_custom_credential": false,
       // ... other models ... 
       },
    ]
}
The Logs List endpoint allows you to get the past logs with specified filters.

​
Query params

You can add these params to the URL params. For example: 
"https://api.keywordsai.co/api/request-logs/list/?page=1&sort_by=-id&is_test=false&all_envs=false&fetch_filters=false&page_size=1"
​
start_time
string
required
The start time for filtering logs in ISO 8601 format. If not provided, defaults to 1 hour ago.
{
  "start_time": "2025-08-15T00:00:00" // ISO 8601 format
}
​
end_time
string
required
The end time for filtering logs in ISO 8601 format. If not provided, defaults to current time.
{
  "end_time": "2025-08-16T00:00:00" // ISO 8601 format
}
​
sort_by
string
required
The field to sort by. Default is -id (same as sort by -timestamp, but with better performance). - is for descending order, if not provided, it will be in ascending order.
​
id
string
Sort by the ID of each request.
​
cost
string
Sort by the cost of each request.
​
time_to_first_token
string
TTFT - useful for Voice AI applications
​
latency
string
Generation time of each request.
​
prompt_tokens
string
Input / prompt tokens of each request.
​
completion_tokens
string
Output / completion tokens of each request.
​
all_tokens
string
Total tokens of each request.
{
  "sort_by": "cost" //sort by cost in ascending order.
}
​
all_envs
string
default:"false"
Whether to include logs from all environments. is_test parameter will override this parameter. Options: true, false.
​
is_test
string
default:"false"
Whether the log is a test call or not. This parameter will override the all_envs parameter. Options: true, false.
​
fetch_filters
string
default:"false"
Whether to retrieve the available filtering options. Enabling this could slow down the response time. Options: true, false.
​
page_size
number
default:100
The number of logs to return per page. Maximum is 1000.
​
page
number
default:1
The page number of the current logs.
​
include_fields
string
Comma separated fields to be included in the response logs. This parameter allows you to specify which fields should be returned to improve performance and reduce response size.
include_fields guarantees the listed fields will be present in each log item, but it does not enforce exclusivity. The API may still return additional fields required for the endpoint (e.g., identifiers, pagination-related fields, or internal metadata).
include_fields=custom_identifier,customer_identifier,id,latency

​
POST params

You can add these params to the body: 
url = "https://api.keywordsai.co/api/request-logs/list/"
headers = {
    "Authorization": f"Api-Key {YOUR_KEYWORDS_AI_API_KEY}",
}
data = {
    "filters":    {
      "cost": {
        "operator": "gt",
        "value": [0.01]
      },
    }
}
response = requests.post(url, headers=headers, json=data)
​
filters
object
default:{}
The filters be applied to the logs. For available options in the response body, use the fetch_filters parameter.
If you want to filter your custom properties, you should add metadata__+ your custom property name. For example, if you want to filter your custom property my_custom_property, you should add metadata__my_custom_property to the filters.
  {
    "name_of_metric": {
      "operator": "gt",
      "value": [100]
    },
  }
​
operator
string
required
Default is "" (equal).
​
string
Equal
{
  "name_of_metric": {
    "operator": "", // equal
    "value": [100]
  },
}
​
iexact
string
case insensitive equal
​
lt
string
Less than
​
lte
string
Less than or equal
​
gt
string
Greater than
​
gte
string
Greater than or equal
​
contains
string
Contains
​
endswith
string
Ends with
​
startswith
string
Starts with
​
in
string
Can be used in arrays or text
​
isnull
string
Check if the field is null
​
icontains
string
Case insensitive contains
​
not
string
Not equal
url = "https://api.keywordsai.co/api/request-logs/list/?page=1&sort_by=-id&is_test=false&all_envs=false&fetch_filters=false&page_size=1"


from urllib.parse import urlencode
params = {
    "page": 1,
    "sort_by": "-id",
    "is_test": "false",
    "all_envs": "false",
    "fetch_filters": "false",
    "page_size": 1
}
url = f"https://api.keywordsai.co/api/request-logs/list/?{urlencode(params)}"
headers = {
    "Authorization": f"Api-Key {YOUR_KEYWORDS_AI_API_KEY}",
}
data = {
    "filters": {}
}
response = requests.post(url, headers=headers, json=data)

{
    "results": [
       {
        "unique_id": "xxxxx",
        "organization_key__name": "Keywords AI Default",
        "organization": "Keywords AI",
        "user": "hendrix@keywordsai.co",
        "is_example": false,
        "status": "success",
        "prompt_tokens": 452,
        "completion_tokens": 89,
        "cost": 0.0005869,
        "prompt_messages": [
                {
                    "role": "system",
                    "content": "You are a helpful assistant"
                },
                {
                    "role": "user",
                    "content": "What is Keywords AI?"
                }
        ],
        "completion_message": {
                "role": "assistant",
                "content": "Keywords AI is a unified DevOps platform for AI products."
        },
        "latency": 1.2114145755767822,
        "model": "gpt-3.5-turbo",
        "foundation_model": "gpt-3.5-turbo",
        "provider_id": "openai",
        "tool_choice": null,
        "tools": null,
        "tool_calls": null,
        "timestamp": "2024-06-24T21:33:06.601353Z",
        "failed": false,
        "time_to_first_token": null,
        "routing_time": 0.0,
        "metadata": {
            // any params you want to pass in the request
            },
        "stream": false,
        "status_code": 200,
        "customer_identifier": "123456",
        "customer_email": "",
        "used_custom_credential": false,
       // ... other models ... 
       },
    ]
}