litellm/docs/my-website/docs/proxy/guardrails/aporia_api.md

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Aporia

Use Aporia to detect PII in requests and profanity in responses

1. Setup guardrails on Aporia

Create Aporia Projects

Create two projects on Aporia

1. Pre LLM API Call - Set all the policies you want to run on pre LLM API call
2. Post LLM API Call - Set all the policies you want to run post LLM API call

<Image img={require('../../../img/aporia_projs.png')} />

Pre-Call: Detect PII

Add the PII - Prompt to your Pre LLM API Call project

<Image img={require('../../../img/aporia_pre.png')} />

Post-Call: Detect Profanity in Responses

Add the Toxicity - Response to your Post LLM API Call project

<Image img={require('../../../img/aporia_post.png')} />

2. Define Guardrails on your LiteLLM config.yaml

• Define your guardrails under the guardrails section

model_list:
  - model_name: gpt-3.5-turbo
    litellm_params:
      model: openai/gpt-3.5-turbo
      api_key: os.environ/OPENAI_API_KEY

guardrails:
  - guardrail_name: "aporia-pre-guard"
    litellm_params:
      guardrail: aporia  # supported values: "aporia", "lakera"
      mode: "during_call"
      api_key: os.environ/APORIA_API_KEY_1
      api_base: os.environ/APORIA_API_BASE_1
  - guardrail_name: "aporia-post-guard"
    litellm_params:
      guardrail: aporia  # supported values: "aporia", "lakera"
      mode: "post_call"
      api_key: os.environ/APORIA_API_KEY_2
      api_base: os.environ/APORIA_API_BASE_2

Supported values for mode

• pre_call Run before LLM call, on input
• post_call Run after LLM call, on input & output
• during_call Run during LLM call, on input Same as pre_call but runs in parallel as LLM call. Response not returned until guardrail check completes

3. Start LiteLLM Gateway

litellm --config config.yaml --detailed_debug

4. Test request

Langchain, OpenAI SDK Usage Examples

Expect this to fail since since ishaan@berri.ai in the request is PII

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": ["aporia-pre-guard", "aporia-post-guard"]
  }'

Expected response on failure

{
  "error": {
    "message": {
      "error": "Violated guardrail policy",
      "aporia_ai_response": {
        "action": "block",
        "revised_prompt": null,
        "revised_response": "Aporia detected and blocked PII",
        "explain_log": null
      }
    },
    "type": "None",
    "param": "None",
    "code": "400"
  }
}

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 what is the weather"}
    ],
    "guardrails": ["aporia-pre-guard", "aporia-post-guard"]
  }'

5. ✨ 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": ["aporia-pre-guard", "aporia-post-guard"]
        }
    }'

curl --location 'http://0.0.0.0:4000/key/update' \
    --header 'Authorization: Bearer sk-1234' \
    --header 'Content-Type: application/json' \
    --data '{
        "key": "sk-jNm1Zar7XfNdZXp49Z1kSQ",
        "guardrails": ["aporia-pre-guard", "aporia-post-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"
        }
    ]
}'