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Overview

The consent API manages user privacy preferences for AI/LLM usage during analysis. Artifact Miner respects your data privacy by letting you choose how your code is processed.
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consent_level
string
required
User’s consent level for data processing
  • none - No processing (static analysis only)
  • local - Static analysis only, no LLM
  • local-llm - Use local LLM models
  • cloud - Allow cloud LLM API calls
Retrieve the current consent level.
GET /consent
curl http://127.0.0.1:8000/consent
Response: 
{
  "consent_level": "local",
  "accepted_at": "2024-03-05T10:30:00"
}
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consent_level
string
Current consent level: none, local, local-llm, or cloud
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accepted_at
datetime
Timestamp when consent was accepted. null if consent_level is none
Change the consent level for data processing.
PUT /consent
curl -X PUT http://127.0.0.1:8000/consent \
  -H "Content-Type: application/json" \
  -d '{
    "consent_level": "local-llm"
  }'
Request Body:
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consent_level
string
required
New consent level. Must be one of: none, local, local-llm, cloud
Response: 
{
  "consent_level": "local-llm",
  "accepted_at": "2024-03-05T12:45:00"
}
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consent_level
string
Updated consent level
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accepted_at
datetime
Timestamp when consent was accepted. Set to current time for non-none levels

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none or local

  • Uses deterministic static analysis only
  • No LLM calls are made
  • Skills extracted from file analysis and git metadata
  • Template-based summaries for projects

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local-llm

  • Uses local LLM models for enhanced analysis
  • No data sent to external services
  • Better quality summaries and insights
  • Requires local LLM setup

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cloud

  • Enables cloud-based LLM API calls
  • Best quality analysis and summaries
  • Code snippets may be sent to LLM providers
  • Follow your organization’s data policies

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Privacy Considerations

If you work with proprietary or sensitive code, use local or local-llm consent levels to avoid sending data to external services.
  • The consent level is stored locally in your database
  • You can change it at any time
  • Existing analysis results are not affected by consent changes
  • Re-run analysis to apply new consent settings

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Example Workflow

import requests

BASE_URL = 'http://127.0.0.1:8000'

# Check current consent level
consent = requests.get(f'{BASE_URL}/consent').json()
print(f"Current consent: {consent['consent_level']}")

# Update to allow local LLM usage
if consent['consent_level'] == 'none':
    response = requests.put(
        f'{BASE_URL}/consent',
        json={'consent_level': 'local-llm'}
    )
    print(f"Updated to: {response.json()['consent_level']}")

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Database Schema

Consent is stored in a singleton row (id=1) in the consent table: 
CREATE TABLE consent (
    id INTEGER PRIMARY KEY,
    consent_level VARCHAR NOT NULL,
    accepted_at TIMESTAMP
);
If no consent record exists, it defaults to none when first accessed.

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