Data Privacy & Retention

const completion = await openai.chat.completions.create({
  model: "",  // Enable intelligent routing
  messages: [{ role: "user", content: "Sensitive data analysis" }],
  model_router: {
    // Prefer providers with better privacy policies
    models: [
      { provider: "groq" },      // Zero retention
      { provider: "fireworks" }, // Zero retention
      { provider: "together" }   // Zero retention
    ]
  }
});

-- Conversations support soft deletion
model Conversation {
  id        Int       @id @default(autoincrement())
  title     String
  createdAt DateTime  @default(now())
  updatedAt DateTime  @updatedAt
  deletedAt DateTime? -- Soft deletion support
  userId    String    -- User isolation

  messages Message[]
  @@index([deletedAt]) -- Efficient deletion queries
}

-- Messages also support soft deletion  
model Message {
  id        String    @id @default(cuid())
  role      String
  parts     Json      -- Message content
  createdAt DateTime  @default(now())
  deletedAt DateTime? -- Soft deletion support
  
  @@index([deletedAt])
}

# From classification_result_embedding_cache.py
class EmbeddingCache:
    def __init__(self, max_size: int = 1000):
        self.vectorstore = InMemoryVectorStore()  # In-memory only
        self.max_size = max_size
        self._cached_size = 0
    
    def add_to_cache(self, classification_result, orchestrator_response):
        # Only stores classification results, not raw prompts
        json_string = self._classification_result_to_json_string(classification_result)
        # Automatic LRU eviction when max_size reached