> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dataframer.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Create red team spec
> Create a new red team specification
## What is Red Teaming?
Red teaming generates adversarial prompts designed to test your LLM application's safety guardrails. Given a description of your application and its domain, it identifies potential undesirable behaviors and creates prompts that attempt to trigger them.
**Workflow:**
1. Create a red team spec (this endpoint) describing your application
2. [Create a run](/api-reference/red-teaming/create-run) to generate adversarial prompts
3. [Poll the status](/api-reference/red-teaming/run-status) until complete
4. [Get the results](/api-reference/red-teaming/get-run) containing behaviors and adversarial prompts
**When to use the main Specs/Runs workflow instead:** Red teaming is designed for generating relatively short adversarial prompts and produces fewer than 100 prompts per run. If you need large volumes of diverse, complex synthetic data, use the main [Specs](/api-reference/specs/create) and [Runs](/api-reference/runs/create) workflow instead.
Spec names are automatically converted to snake\_case and must be unique within your company.
## OpenAPI
````yaml POST /api/dataframer/red-team-specs/
openapi: 3.0.0
info:
title: DataFramer API
version: 0.1.0
description: ''
termsOfService: https://www.aimon.ai/docs/privacy-policy.pdf
contact:
name: DataFramer Support
email: info@dataframer.ai
license:
name: Proprietary
x-logo:
url: https://dataframer.ai/logo.png
altText: DataFramer AI
x-stainless:
package-name: aimon-dataframer
namespace:
- aimon
- dataframer
servers:
- url: https://df-api.dataframer.ai
description: Production server
security:
- BearerAuth: []
tags:
- name: Seed Datasets
description: Manage seed datasets for generation
- name: Specs
description: Data specifications for sample generation
- name: Runs
description: Generation runs and results
- name: Evaluations
description: Evaluate generated sample quality
- name: Red Teaming
description: Security testing and adversarial prompts
- name: Spec Creation
description: Create specs from datasets or from scratch (seedless)
- name: Generation
description: Synthetic data generation
- name: API Keys
description: API key management and rotation
- name: Health
description: Health check endpoints
- name: Models
description: Available AI models
externalDocs:
description: Complete API Guide
url: https://docs.dataframer.ai/dataframer
paths:
/api/dataframer/red-team-specs/:
post:
tags:
- Red Teaming
summary: Create red team spec
description: >-
Create a new red team specification.
## What is Red Teaming?
Red teaming generates adversarial prompts designed to test your LLM
application's safety guardrails. Given a description of your application
and its domain, it identifies potential undesirable behaviors and
creates prompts that attempt to trigger them.
**Workflow:**
1. Create a red team spec (this endpoint) describing your application
2. Create a run to generate adversarial prompts
3. Poll the status until complete
4. Get the results containing behaviors and adversarial prompts
**When to use the main Specs/Runs workflow instead:** Red teaming is
designed for generating relatively short adversarial prompts and
produces fewer than 100 prompts per run. If you need large volumes of
diverse, complex synthetic data, use the main Specs and Runs workflow
instead.
Spec names are automatically converted to snake_case and must be unique
within your company.
operationId: api_dataframer_red-team-specs_create
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/RedTeamSpecCreate'
examples:
healthcare_chatbot:
summary: Healthcare chatbot spec
value:
name: Healthcare Chatbot
domain_description: Healthcare and medical information services
app_description: >-
A patient-facing chatbot that helps schedule appointments
and answer general health questions
concerns: >-
Should not provide medical diagnoses, prescription
recommendations, or treatment advice
ecommerce_assistant:
summary: E-commerce assistant spec
value:
name: E-commerce Assistant
domain_description: Online retail and e-commerce
app_description: >-
A customer service chatbot for an online store that handles
order inquiries and product questions
responses:
'201':
description: Red team spec created successfully
content:
application/json:
schema:
$ref: '#/components/schemas/RedTeamSpec'
'400':
description: Validation error (missing required fields or duplicate name)
content:
application/json:
schema:
type: object
properties:
name:
type: array
items:
type: string
example:
- Red Team Spec with name "my_spec" already exists
domain_description:
type: array
items:
type: string
example:
- This field is required.
app_description:
type: array
items:
type: string
example:
- This field is required.
'401':
description: Authentication credentials were not provided
'402':
description: Payment required - subscription inactive
'500':
description: Internal server error
x-codeSamples:
- lang: JavaScript
source: |-
import Dataframer from 'dataframer';
const client = new Dataframer({
apiKey: process.env['DATAFRAMER_API_KEY'], // This is the default and can be omitted
});
const redTeamSpec = await client.dataframer.redTeamSpecs.create({
app_description:
'A patient-facing chatbot that helps schedule appointments and answer general health questions',
domain_description: 'Healthcare and medical information services',
name: 'Healthcare Chatbot',
concerns:
'Should not provide medical diagnoses, prescription recommendations, or treatment advice',
});
console.log(redTeamSpec.id);
- lang: Python
source: |-
import os
from dataframer import Dataframer
client = Dataframer(
api_key=os.environ.get("DATAFRAMER_API_KEY"), # This is the default and can be omitted
)
red_team_spec = client.dataframer.red_team_specs.create(
app_description="A patient-facing chatbot that helps schedule appointments and answer general health questions",
domain_description="Healthcare and medical information services",
name="Healthcare Chatbot",
concerns="Should not provide medical diagnoses, prescription recommendations, or treatment advice",
)
print(red_team_spec.id)
components:
schemas:
RedTeamSpecCreate:
type: object
description: Request body for creating a red team spec
required:
- name
- domain_description
- app_description
properties:
name:
type: string
description: >-
Name for the spec (will be converted to snake_case, must be unique
within company)
domain_description:
type: string
description: >-
Description of the domain or industry the application operates in
(e.g., 'Healthcare', 'E-commerce', 'Financial services')
app_description:
type: string
description: >-
Description of the application being tested, including its purpose
and key functionality
concerns:
type: string
description: >-
Optional specific security concerns or undesirable behaviors to
focus on (e.g., 'Should not provide medical diagnoses')
RedTeamSpec:
type: object
description: >-
A red team specification defining the application context for
adversarial prompt generation
properties:
id:
type: string
format: uuid
readOnly: true
description: Unique identifier for the red team spec
name:
type: string
description: Name of the red team spec (auto-converted to snake_case)
domain_description:
type: string
description: Description of the domain or industry the application operates in
app_description:
type: string
description: >-
Description of the application being tested, including its purpose
and functionality
concerns:
type: string
nullable: true
description: >-
Specific security concerns or behaviors to focus on during red
teaming
created_at:
type: string
format: date-time
readOnly: true
description: Timestamp when the spec was created
updated_at:
type: string
format: date-time
readOnly: true
description: Timestamp when the spec was last modified
company_id:
type: string
format: uuid
readOnly: true
description: ID of the company that owns this spec
company_name:
type: string
readOnly: true
description: Name of the company that owns this spec
created_by:
type: integer
readOnly: true
description: ID of the user who created this spec
created_by_email:
type: string
readOnly: true
description: Email of the user who created this spec
securitySchemes:
BearerAuth:
type: http
scheme: bearer
bearerFormat: API Key
description: 'API Key authentication. Format: "Bearer YOUR_API_KEY"'
````