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Guardrails.ai

Use Guardrails.ai to add checks to LLM output.

Pre-requisites​

Usage​

  1. Setup config.yaml
model_list:
- model_name: gpt-3.5-turbo
litellm_params:
model: gpt-3.5-turbo
api_key: os.environ/OPENAI_API_KEY

guardrails:
- guardrail_name: "guardrails_ai-guard"
litellm_params:
guardrail: guardrails_ai
guard_name: "gibberish_guard" # 👈 Guardrail AI guard name
mode: "post_call"
api_base: os.environ/GUARDRAILS_AI_API_BASE # 👈 Guardrails AI API Base. Defaults to "http://0.0.0.0:8000"
  1. Start LiteLLM Gateway
litellm --config config.yaml --detailed_debug
  1. Test request

Langchain, OpenAI SDK Usage Examples

curl -i http://localhost:4000/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-npnwjPQciVRok5yNZgKmFQ" \
-d '{
"model": "gpt-3.5-turbo",
"messages": [
{"role": "user", "content": "hi my email is ishaan@berri.ai"}
],
"guardrails": ["guardrails_ai-guard"]
}'

✨ Control Guardrails per Project (API Key)​

info

✨ This is an Enterprise only feature Contact us to get a free trial

Use this to control what guardrails run per project. In this tutorial we only want the following guardrails to run for 1 project (API Key)

  • guardrails: ["aporia-pre-guard", "aporia-post-guard"]

Step 1 Create Key with guardrail settings

curl -X POST 'http://0.0.0.0:4000/key/generate' \
-H 'Authorization: Bearer sk-1234' \
-H 'Content-Type: application/json' \
-D '{
"guardrails": ["guardrails_ai-guard"]
}
}'

Step 2 Test it with new key

curl --location 'http://0.0.0.0:4000/chat/completions' \
--header 'Authorization: Bearer sk-jNm1Zar7XfNdZXp49Z1kSQ' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-3.5-turbo",
"messages": [
{
"role": "user",
"content": "my email is ishaan@berri.ai"
}
]
}'