Quickstart

pip install ambientmeta

from ambientmeta import AmbientMeta

client = AmbientMeta(api_key="am_live_your_key_here")

# Sanitize text before sending to an LLM
result = client.sanitize("Email John Smith at john@acme.com about the project")

print(result.sanitized)
# "Email [PERSON_1] at [EMAIL_ADDRESS_1] about the project"

print(result.session_id)
# "ses_abc123..."

import openai

response = openai.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": result.sanitized}]
)

llm_response = response.choices[0].message.content

final = client.rehydrate(llm_response, result.session_id)

print(final.text)
# Original names and emails restored

curl -X POST https://api.ambientmeta.com/v1/sanitize \
  -H "X-API-Key: am_live_xxx" \
  -H "Content-Type: application/json" \
  -d '{"text": "Email John Smith at john@acme.com about the merger"}'

{
  "sanitized": "Email [PERSON_1] at [EMAIL_ADDRESS_1] about the merger",
  "session_id": "ses_a1b2c3d4e5f6",
  "redacted": false,
  "entities_found": 2,
  "entities": [
    {"placeholder": "[PERSON_1]", "type": "PERSON", "confidence": 0.97, "start": 6, "end": 16},
    {"placeholder": "[EMAIL_ADDRESS_1]", "type": "EMAIL_ADDRESS", "confidence": 0.99, "start": 20, "end": 33}
  ],
  "processing_ms": 12.3
}

curl -X POST https://api.ambientmeta.com/v1/rehydrate \
  -H "X-API-Key: am_live_xxx" \
  -H "Content-Type: application/json" \
  -d '{"text": "I will contact [PERSON_1] at [EMAIL_ADDRESS_1] tomorrow.", "session_id": "ses_a1b2c3d4e5f6"}'

{
  "text": "I will contact John Smith at john@acme.com tomorrow.",
  "entities_restored": 2,
  "processing_ms": 3.1
}