Update single log

PATCH /api/request-logs/{unique_id}/

Python

import requests

unique_id = "log_abc123..."  # Replace with actual log ID
url = f"https://api.keywordsai.co/api/request-logs/{unique_id}/"

headers = {
    "Authorization": f"Bearer {YOUR_KEYWORDS_AI_API_KEY}",
    "Content-Type": "application/json"
}

data = {
    "metadata": {
        "user_feedback": "helpful",
        "quality_rating": 5
    },
    "custom_identifier": "ticket_12345"
}

response = requests.patch(url, headers=headers, json=data)
print(response.json())

200 OK

{
  "id": "log_abc123...",
  "unique_id": "log_abc123...",
  "organization_id": "org_xyz789",
  "environment": "prod",
  "timestamp": "2025-12-26T10:30:00Z",
  "start_time": "2025-12-26T10:29:58Z",
  "log_type": "chat",
  "model": "gpt-4o-mini",
  "cost": 0.000705,
  "latency": 1.234,
  "status": "success",
  "custom_identifier": "ticket_12345",
  "metadata": {
    "user_feedback": "helpful",
    "quality_rating": 5,
    "previous_metadata_key": "previous_value"
  },
  "input": "[{\"role\":\"user\",\"content\":\"Hello\"}]",
  "output": "{\"role\":\"assistant\",\"content\":\"Hi there!\"}",
  // ... rest of log fields
}

The Update Log endpoint allows you to modify specific fields of a single log. This is useful for adding annotations, updating metadata, or correcting information.

For updating multiple logs at once, use the Batch Update endpoint.

Updatable fields

The following fields can be updated:

• metadata - Custom metadata properties
• custom_identifier - Custom identifier
• blurred - Privacy flag to blur log content

Core log data is immutable

Fields like input, output, log_type, model, usage, cost, latency, and other telemetry fields cannot be modified to maintain data integrity.

Path parameters

unique_id · string · required

The unique ID of the log to update. You can get this from the List Logs endpoint.

Body parameters

metadata · object

Update the log’s metadata with custom properties. This can be used for tagging, categorization, or adding context.

Example

{
  "metadata": {
    "user_feedback": "helpful",
    "quality_rating": 5,
    "reviewed": true,
    "reviewer": "[e-mail]"
  }
}

custom_identifier · string

Update the log’s custom identifier. Useful for linking logs to external systems.

Example

{
  "custom_identifier": "ticket_12345_resolved"
}

blurred · boolean

Set whether the log content should be blurred for privacy reasons.

Example

{
  "blurred": true
}

Response

Returns the complete updated log object (same structure as the Get Log endpoint).

Python

import requests

unique_id = "log_abc123..."  # Replace with actual log ID
url = f"https://api.keywordsai.co/api/request-logs/{unique_id}/"

headers = {
    "Authorization": f"Bearer {YOUR_KEYWORDS_AI_API_KEY}",
    "Content-Type": "application/json"
}

data = {
    "metadata": {
        "user_feedback": "helpful",
        "quality_rating": 5
    },
    "custom_identifier": "ticket_12345"
}

response = requests.patch(url, headers=headers, json=data)
print(response.json())

200 OK

{
  "id": "log_abc123...",
  "unique_id": "log_abc123...",
  "organization_id": "org_xyz789",
  "environment": "prod",
  "timestamp": "2025-12-26T10:30:00Z",
  "start_time": "2025-12-26T10:29:58Z",
  "log_type": "chat",
  "model": "gpt-4o-mini",
  "cost": 0.000705,
  "latency": 1.234,
  "status": "success",
  "custom_identifier": "ticket_12345",
  "metadata": {
    "user_feedback": "helpful",
    "quality_rating": 5,
    "previous_metadata_key": "previous_value"
  },
  "input": "[{\"role\":\"user\",\"content\":\"Hello\"}]",
  "output": "{\"role\":\"assistant\",\"content\":\"Hi there!\"}",
  // ... rest of log fields
}

Use Cases

Add user feedback

# Add thumbs up/down feedback to a log
import requests

def add_feedback(log_id, is_positive, api_key):
    url = f"https://api.keywordsai.co/api/request-logs/{log_id}/"
    
    response = requests.patch(
        url,
        headers={"Authorization": f"Bearer {api_key}"},
        json={
            "metadata": {
                "user_feedback": "positive" if is_positive else "negative",
                "feedback_timestamp": datetime.now().isoformat()
            }
        }
    )
    return response.json()

# Usage
add_feedback("log_abc123", True, YOUR_API_KEY)

Link log to support ticket

# Update log with support ticket information
import requests

def link_to_ticket(log_id, ticket_id, ticket_status, api_key):
    url = f"https://api.keywordsai.co/api/request-logs/{log_id}/"
    
    response = requests.patch(
        url,
        headers={"Authorization": f"Bearer {api_key}"},
        json={
            "custom_identifier": ticket_id,
            "metadata": {
                "ticket_status": ticket_status,
                "linked_at": datetime.now().isoformat()
            }
        }
    )
    return response.json()

# Usage
link_to_ticket("log_abc123", "TICKET-5678", "resolved", YOUR_API_KEY)

Mark logs for review

# Flag logs that need human review
import requests

def mark_for_review(log_id, reason, priority, api_key):
    url = f"https://api.keywordsai.co/api/request-logs/{log_id}/"
    
    response = requests.patch(
        url,
        headers={"Authorization": f"Bearer {api_key}"},
        json={
            "metadata": {
                "needs_review": True,
                "review_reason": reason,
                "review_priority": priority,
                "flagged_at": datetime.now().isoformat()
            }
        }
    )
    return response.json()

# Usage
mark_for_review(
    "log_abc123",
    "Potential PII in response",
    "high",
    YOUR_API_KEY
)

Blur sensitive logs

# Blur logs containing sensitive information
import requests

def blur_log(log_id, reason, api_key):
    url = f"https://api.keywordsai.co/api/request-logs/{log_id}/"
    
    response = requests.patch(
        url,
        headers={"Authorization": f"Bearer {api_key}"},
        json={
            "blurred": True,
            "metadata": {
                "blur_reason": reason,
                "blurred_at": datetime.now().isoformat()
            }
        }
    )
    return response.json()

# Usage
blur_log("log_abc123", "Contains PII", YOUR_API_KEY)

Tag logs with experiments

# Tag logs with A/B test or experiment information
import requests

def tag_experiment(log_id, experiment_name, variant, api_key):
    url = f"https://api.keywordsai.co/api/request-logs/{log_id}/"
    
    response = requests.patch(
        url,
        headers={"Authorization": f"Bearer {api_key}"},
        json={
            "metadata": {
                "experiment": experiment_name,
                "variant": variant,
                "experiment_tagged_at": datetime.now().isoformat()
            }
        }
    )
    return response.json()

# Usage
tag_experiment(
    "log_abc123",
    "prompt_optimization_v2",
    "variant_b",
    YOUR_API_KEY
)

Metadata Best Practices

Organizing metadata

1. Use consistent keys: Establish naming conventions across your organization
2. Add timestamps: Include _at or _timestamp fields for tracking when metadata was added
3. Namespace related fields: Use prefixes like review_, feedback_, experiment_ to group related fields
4. Keep it queryable: Use simple data types (strings, numbers, booleans) for fields you’ll filter on
5. Document your schema: Maintain documentation of your metadata structure

Error Responses

404 Not Found

{
  "detail": "Log not found"
}

400 Bad Request

{
  "error": "Cannot update immutable field",
  "detail": "The field 'cost' cannot be modified"
}

Related Endpoints

• Batch Update Logs - Update multiple logs at once
• Get Log - View log details before updating
• List Logs - Find logs to update using filters