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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"
        }
    ]
}'