feat: add implementation plan and monorepo guide for DreamChat project
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GW_MC
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doc/database-schema.md
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doc/database-schema.md
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# DreamChat Database Schema
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## Overview
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PostgreSQL with pgvector extension for vector storage. All data is stored locally (offline-first).
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## Extensions Required
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```sql
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-- Enable required extensions
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CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
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CREATE EXTENSION IF NOT EXISTS "pgvector";
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```
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## Entity Relationship Diagram
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```
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ users │ │ characters │ │ conversations │
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├─────────────────┤ ├─────────────────┤ ├─────────────────┤
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│ id (PK) │◄──────│ user_id (FK) │ │ id (PK) │
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│ email │ │ id (PK) │◄──────│ character_id(FK)│
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│ username │ │ name │ │ user_id (FK) │
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│ password_hash │ │ avatar_url │ │ title │
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│ keycloak_sub │ │ personality │ │ created_at │
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│ role │ │ backstory │ │ updated_at │
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│ created_at │ │ attributes │ └────────┬────────┘
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│ updated_at │ │ created_at │ │
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└─────────────────┘ │ updated_at │ │
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└─────────────────┘ │
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┌─────────────────┐ │
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│import_documents │ │
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├─────────────────┤ │
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│ id (PK) │ │
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│ user_id (FK) │ │
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│ source_type │ ┌─────────────────┐ │
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│ source_name │ │ messages │◄───────────────┘
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│ content │ ├─────────────────┤
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│ metadata │ │ id (PK) │
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│ vector_id │ │ conversation_id │
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│ created_at │ │ role │
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└─────────────────┘ │ content │
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│ tokens_used │
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│ model │
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┌─────────────────┐ │ metadata │
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│vector_memories │ │ created_at │
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├─────────────────┤ └─────────────────┘
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│ id (PK) │
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│ conversation_id │ ┌─────────────────┐
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│ content │ │ story_branches │ (Phase 2)
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│ embedding │ ├─────────────────┤
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│ metadata │ │ id (PK) │
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│ created_at │ │ conversation_id │
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└─────────────────┘ │ parent_id (FK) │
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│ content │
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│ direction │
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│ metadata │
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│ created_at │
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└─────────────────┘
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```
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## Table Definitions
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### 1. users
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Stores user account information. Supports both Keycloak (OIDC) and local password authentication.
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```sql
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CREATE TABLE users (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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email VARCHAR(255) UNIQUE NOT NULL,
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username VARCHAR(100) UNIQUE NOT NULL,
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password_hash VARCHAR(255), -- NULL if using Keycloak
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keycloak_sub VARCHAR(255) UNIQUE, -- NULL if using password auth
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role VARCHAR(20) DEFAULT 'USER' CHECK (role IN ('USER', 'ADMIN')),
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is_active BOOLEAN DEFAULT true,
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
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updated_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
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-- At least one auth method must be set
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CONSTRAINT auth_method_check CHECK (
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(password_hash IS NOT NULL) OR (keycloak_sub IS NOT NULL)
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)
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);
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CREATE INDEX idx_users_email ON users(email);
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CREATE INDEX idx_users_keycloak_sub ON users(keycloak_sub);
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```
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### 2. characters
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Character definitions with complex attribute system (JSONB for flexibility).
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```sql
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CREATE TABLE characters (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
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name VARCHAR(255) NOT NULL,
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avatar_url TEXT,
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-- Core personality prompt sent to LLM
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personality_prompt TEXT NOT NULL,
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-- Backstory context for the character
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backstory TEXT,
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-- Complex attribute system (structured JSON)
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-- Example: {"traits": ["brave", "witty"], "age": 25, "species": "human"}
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attributes JSONB DEFAULT '{}',
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-- Character configuration
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config JSONB DEFAULT '{
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"model": "openai/gpt-4o",
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"temperature": 0.7,
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"max_tokens": 2048,
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"memory_enabled": true
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}',
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is_public BOOLEAN DEFAULT false,
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
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updated_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
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);
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CREATE INDEX idx_characters_user_id ON characters(user_id);
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CREATE INDEX idx_characters_name ON characters(name);
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CREATE INDEX idx_characters_attributes ON characters USING GIN(attributes);
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```
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### 3. conversations
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Chat sessions between user and character.
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```sql
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CREATE TABLE conversations (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
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character_id UUID NOT NULL REFERENCES characters(id) ON DELETE CASCADE,
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title VARCHAR(255), -- Auto-generated or user-defined
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-- Context window management
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message_count INTEGER DEFAULT 0,
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total_tokens INTEGER DEFAULT 0,
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-- Conversation settings
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settings JSONB DEFAULT '{}',
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
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updated_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
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);
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CREATE INDEX idx_conversations_user_id ON conversations(user_id);
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CREATE INDEX idx_conversations_character_id ON conversations(character_id);
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CREATE INDEX idx_conversations_created_at ON conversations(created_at);
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```
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### 4. messages
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Individual chat messages.
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```sql
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CREATE TYPE message_role AS ENUM ('user', 'assistant', 'system');
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CREATE TABLE messages (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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conversation_id UUID NOT NULL REFERENCES conversations(id) ON DELETE CASCADE,
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role message_role NOT NULL,
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content TEXT NOT NULL,
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-- LLM metadata
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tokens_used INTEGER,
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model VARCHAR(100),
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-- Additional metadata (temperature, latency, etc.)
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metadata JSONB DEFAULT '{}',
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
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);
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CREATE INDEX idx_messages_conversation_id ON messages(conversation_id);
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CREATE INDEX idx_messages_created_at ON messages(created_at);
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CREATE INDEX idx_messages_conversation_created ON messages(conversation_id, created_at);
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```
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### 5. vector_memories
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Vector embeddings for conversation memory using pgvector. Stores chunked content for semantic search.
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```sql
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-- Create vector extension first
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CREATE EXTENSION IF NOT EXISTS vector;
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CREATE TABLE vector_memories (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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conversation_id UUID NOT NULL REFERENCES conversations(id) ON DELETE CASCADE,
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-- The text content
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content TEXT NOT NULL,
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-- Vector embedding (configurable dimension based on model)
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-- Common sizes: 384 (all-MiniLM-L6-v2), 768 (all-mpnet-base-v2), 1024 (BGE)
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-- Must match the EMBEDDING_DIMENSION env var
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embedding VECTOR({{EMBEDDING_DIMENSION}}),
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-- Metadata for filtering
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metadata JSONB DEFAULT '{
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"chunk_index": 0,
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"source": "conversation",
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"timestamp": null
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}',
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
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);
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-- HNSW index for efficient similarity search
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-- Note: Index is created after table creation based on actual dimension
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-- CREATE INDEX idx_vector_memories_embedding ON vector_memories
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-- USING hnsw (embedding vector_cosine_ops);
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CREATE INDEX idx_vector_memories_conversation ON vector_memories(conversation_id);
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```
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### 6. import_documents
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Raw imported documents from files or web scraping.
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```sql
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CREATE TYPE import_source_type AS ENUM ('file', 'url');
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CREATE TYPE import_status AS ENUM ('pending', 'processing', 'completed', 'failed');
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CREATE TABLE import_documents (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
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source_type import_source_type NOT NULL,
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source_name VARCHAR(255) NOT NULL, -- filename or URL
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-- Mime type for files
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mime_type VARCHAR(100),
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-- File size in bytes
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file_size BIGINT,
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-- Raw content (preprocessed)
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content TEXT,
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-- Processing status
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status import_status DEFAULT 'pending',
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error_message TEXT,
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-- Metadata (source info, extraction method, etc.)
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metadata JSONB DEFAULT '{}',
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
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updated_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
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);
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CREATE INDEX idx_import_documents_user_id ON import_documents(user_id);
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CREATE INDEX idx_import_documents_status ON import_documents(status);
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```
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### 7. story_branches (Phase 2)
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Tree structure for branching narratives.
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```sql
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CREATE TABLE story_branches (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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conversation_id UUID NOT NULL REFERENCES conversations(id) ON DELETE CASCADE,
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-- Self-referential for tree structure
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parent_id UUID REFERENCES story_branches(id) ON DELETE CASCADE,
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-- Branch content
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title VARCHAR(255),
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content TEXT NOT NULL, -- The generated story content
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-- User direction that led to this branch
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user_direction TEXT,
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-- Branch metadata
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generation_params JSONB DEFAULT '{}',
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-- Tree position
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depth INTEGER DEFAULT 0,
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branch_order INTEGER DEFAULT 0,
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
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);
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CREATE INDEX idx_story_branches_conversation ON story_branches(conversation_id);
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CREATE INDEX idx_story_branches_parent ON story_branches(parent_id);
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```
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### 8. conversation_participants (Phase 3 - Multi-Character)
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Supports multiple characters in a single conversation.
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```sql
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CREATE TABLE conversation_participants (
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id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
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conversation_id UUID NOT NULL REFERENCES conversations(id) ON DELETE CASCADE,
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character_id UUID NOT NULL REFERENCES characters(id) ON DELETE CASCADE,
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-- Participant settings
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is_active BOOLEAN DEFAULT true,
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auto_respond BOOLEAN DEFAULT true, -- Auto-generate responses
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created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
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UNIQUE(conversation_id, character_id)
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);
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CREATE INDEX idx_participants_conversation ON conversation_participants(conversation_id);
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```
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## Prisma Schema (Reference)
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### Full Schema Definition
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```prisma
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// schema.prisma
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generator client {
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provider = "prisma-client-js"
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}
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datasource db {
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provider = "postgresql"
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url = env("DATABASE_URL")
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}
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// Enums
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enum UserRole {
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USER
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ADMIN
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}
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enum MessageRole {
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user
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assistant
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system
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}
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enum ImportSourceType {
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file
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url
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}
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enum ImportStatus {
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pending
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processing
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completed
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failed
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}
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// Models
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model User {
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id String @id @default(uuid())
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email String @unique
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username String @unique
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passwordHash String?
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keycloakSub String? @unique
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role UserRole @default(USER)
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isActive Boolean @default(true)
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createdAt DateTime @default(now())
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updatedAt DateTime @updatedAt
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characters Character[]
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conversations Conversation[]
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importDocs ImportDocument[]
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@@index([email])
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@@index([keycloakSub])
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}
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model Character {
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id String @id @default(uuid())
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name String
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avatarUrl String?
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personalityPrompt String
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backstory String?
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attributes Json @default("{}")
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config Json @default("{}")
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isPublic Boolean @default(false)
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createdAt DateTime @default(now())
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updatedAt DateTime @updatedAt
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userId String
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user User @relation(fields: [userId], references: [id], onDelete: Cascade)
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conversations Conversation[]
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@@index([userId])
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@@index([name])
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}
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model Conversation {
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id String @id @default(uuid())
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title String?
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messageCount Int @default(0)
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totalTokens Int @default(0)
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settings Json @default("{}")
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createdAt DateTime @default(now())
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updatedAt DateTime @updatedAt
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userId String
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user User @relation(fields: [userId], references: [id], onDelete: Cascade)
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characterId String
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character Character @relation(fields: [characterId], references: [id], onDelete: Cascade)
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messages Message[]
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vectorMemories VectorMemory[]
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storyBranches StoryBranch[]
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participants ConversationParticipant[]
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@@index([userId])
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@@index([characterId])
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@@index([createdAt])
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}
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model Message {
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id String @id @default(uuid())
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role MessageRole
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content String
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tokensUsed Int?
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model String?
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metadata Json?
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createdAt DateTime @default(now())
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conversationId String
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conversation Conversation @relation(fields: [conversationId], references: [id], onDelete: Cascade)
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@@index([conversationId])
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@@index([createdAt])
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@@index([conversationId, createdAt])
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}
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model VectorMemory {
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id String @id @default(uuid())
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content String
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embedding Unsupported("vector")? // pgvector extension
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metadata Json?
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createdAt DateTime @default(now())
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conversationId String
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conversation Conversation @relation(fields: [conversationId], references: [id], onDelete: Cascade)
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@@index([conversationId])
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}
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model ImportDocument {
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id String @id @default(uuid())
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sourceType ImportSourceType
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sourceName String
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mimeType String?
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fileSize BigInt?
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content String?
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status ImportStatus @default(pending)
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errorMessage String?
|
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metadata Json?
|
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createdAt DateTime @default(now())
|
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updatedAt DateTime @updatedAt
|
||||
|
||||
userId String
|
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user User @relation(fields: [userId], references: [id], onDelete: Cascade)
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||||
|
||||
@@index([userId])
|
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@@index([status])
|
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}
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||||
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model StoryBranch {
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id String @id @default(uuid())
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title String?
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content String
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userDirection String
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generationParams Json?
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depth Int @default(0)
|
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branchOrder Int @default(0)
|
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createdAt DateTime @default(now())
|
||||
|
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conversationId String
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conversation Conversation @relation(fields: [conversationId], references: [id], onDelete: Cascade)
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parentId String?
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parent StoryBranch? @relation("BranchTree", fields: [parentId], references: [id], onDelete: Cascade)
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children StoryBranch[] @relation("BranchTree")
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||||
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@@index([conversationId])
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@@index([parentId])
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}
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||||
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||||
model ConversationParticipant {
|
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id String @id @default(uuid())
|
||||
isActive Boolean @default(true)
|
||||
autoRespond Boolean @default(true)
|
||||
createdAt DateTime @default(now())
|
||||
|
||||
conversationId String
|
||||
conversation Conversation @relation(fields: [conversationId], references: [id], onDelete: Cascade)
|
||||
characterId String
|
||||
|
||||
@@unique([conversationId, characterId])
|
||||
@@index([conversationId])
|
||||
}
|
||||
```
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||||
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||||
### Prisma Client Usage Examples
|
||||
|
||||
```typescript
|
||||
// src/shared/prisma/prisma.service.ts
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||||
import { Injectable, OnModuleInit, OnModuleDestroy } from '@nestjs/common';
|
||||
import { PrismaClient } from '@prisma/client';
|
||||
|
||||
@Injectable()
|
||||
export class PrismaService extends PrismaClient implements OnModuleInit, OnModuleDestroy {
|
||||
async onModuleInit() {
|
||||
await this.$connect();
|
||||
}
|
||||
|
||||
async onModuleDestroy() {
|
||||
await this.$disconnect();
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
```typescript
|
||||
// Repository pattern with Prisma
|
||||
@Injectable()
|
||||
export class CharacterRepository {
|
||||
constructor(private prisma: PrismaService) {}
|
||||
|
||||
async findByUser(userId: string) {
|
||||
return this.prisma.character.findMany({
|
||||
where: { userId },
|
||||
orderBy: { updatedAt: 'desc' },
|
||||
});
|
||||
}
|
||||
|
||||
async create(data: CreateCharacterDto, userId: string) {
|
||||
return this.prisma.character.create({
|
||||
data: { ...data, userId },
|
||||
});
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Vector Memory Query with Prisma
|
||||
|
||||
```typescript
|
||||
// Similarity search using pgvector with Prisma
|
||||
async similaritySearch(
|
||||
conversationId: string,
|
||||
queryEmbedding: number[],
|
||||
k: number = 5
|
||||
) {
|
||||
// Using raw query for pgvector-specific operations
|
||||
const results = await this.prisma.$queryRaw`
|
||||
SELECT
|
||||
id,
|
||||
content,
|
||||
metadata,
|
||||
embedding <=> ${queryEmbedding}::vector as distance
|
||||
FROM "VectorMemory"
|
||||
WHERE "conversationId" = ${conversationId}
|
||||
ORDER BY embedding <=> ${queryEmbedding}::vector
|
||||
LIMIT ${k}
|
||||
`;
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
// Alternative: using cosine similarity
|
||||
async similaritySearchCosine(
|
||||
conversationId: string,
|
||||
queryEmbedding: number[],
|
||||
k: number = 5
|
||||
) {
|
||||
const results = await this.prisma.$queryRaw`
|
||||
SELECT
|
||||
id,
|
||||
content,
|
||||
metadata,
|
||||
1 - (embedding <=> ${queryEmbedding}::vector) as similarity
|
||||
FROM "VectorMemory"
|
||||
WHERE "conversationId" = ${conversationId}
|
||||
ORDER BY similarity DESC
|
||||
LIMIT ${k}
|
||||
`;
|
||||
|
||||
return results;
|
||||
}
|
||||
```
|
||||
|
||||
### Embedding Configuration
|
||||
|
||||
```typescript
|
||||
// Configuration for embedding providers
|
||||
interface EmbeddingConfig {
|
||||
provider: 'local' | 'huggingface-api';
|
||||
model: string;
|
||||
dimension: number;
|
||||
// For local provider
|
||||
localModelPath?: string;
|
||||
// For HuggingFace API
|
||||
apiKey?: string;
|
||||
apiEndpoint?: string;
|
||||
}
|
||||
|
||||
// Example configurations:
|
||||
// Local: { provider: 'local', model: 'Xenova/all-MiniLM-L6-v2', dimension: 384 }
|
||||
// HF API: { provider: 'huggingface-api', model: 'sentence-transformers/all-mpnet-base-v2', dimension: 768 }
|
||||
```
|
||||
|
||||
## Prisma Migration Strategy
|
||||
|
||||
### Initial Migration
|
||||
|
||||
```bash
|
||||
# 1. Initialize Prisma
|
||||
npx prisma init
|
||||
|
||||
# 2. Define schema in prisma/schema.prisma
|
||||
|
||||
# 3. Create first migration
|
||||
npx prisma migrate dev --name init
|
||||
|
||||
# 4. Generate Prisma Client
|
||||
npx prisma generate
|
||||
```
|
||||
|
||||
### Migration Workflow
|
||||
|
||||
```bash
|
||||
# After schema changes
|
||||
npx prisma migrate dev --name descriptive_name
|
||||
|
||||
# Production deployment
|
||||
npx prisma migrate deploy
|
||||
|
||||
# Generate client (in CI/CD)
|
||||
npx prisma generate
|
||||
```
|
||||
|
||||
### Migration File Example
|
||||
|
||||
```sql
|
||||
-- migrations/20240223120000_init/migration.sql
|
||||
|
||||
-- Enable extensions
|
||||
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
|
||||
CREATE EXTENSION IF NOT EXISTS "vector";
|
||||
|
||||
-- CreateEnum
|
||||
CREATE TYPE "UserRole" AS ENUM ('USER', 'ADMIN');
|
||||
|
||||
-- CreateEnum
|
||||
CREATE TYPE "MessageRole" AS ENUM ('user', 'assistant', 'system');
|
||||
|
||||
-- CreateTable
|
||||
CREATE TABLE "User" (
|
||||
"id" UUID NOT NULL DEFAULT uuid_generate_v4(),
|
||||
"email" TEXT NOT NULL,
|
||||
"username" TEXT NOT NULL,
|
||||
-- ... etc
|
||||
);
|
||||
|
||||
-- CreateIndex
|
||||
CREATE UNIQUE INDEX "User_email_key" ON "User"("email");
|
||||
|
||||
-- Vector index (HNSW) - created manually after migration
|
||||
CREATE INDEX idx_vector_memories_embedding ON "VectorMemory"
|
||||
USING hnsw (embedding vector_cosine_ops);
|
||||
```
|
||||
|
||||
### Seeding
|
||||
|
||||
```typescript
|
||||
// prisma/seed.ts
|
||||
import { PrismaClient } from '@prisma/client';
|
||||
|
||||
const prisma = new PrismaClient();
|
||||
|
||||
async function main() {
|
||||
// Seed default admin or test data
|
||||
await prisma.user.create({
|
||||
data: {
|
||||
email: 'admin@dreamchat.local',
|
||||
username: 'admin',
|
||||
role: 'ADMIN',
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
main()
|
||||
.catch(console.error)
|
||||
.finally(() => prisma.$disconnect());
|
||||
```
|
||||
|
||||
```bash
|
||||
# Run seed
|
||||
npx prisma db seed
|
||||
```
|
||||
|
||||
## Backup Strategy
|
||||
|
||||
```bash
|
||||
# pg_dump with custom format
|
||||
docker exec dreamchat-postgres pg_dump -U postgres -Fc dreamchat > backup.dump
|
||||
|
||||
# Restore
|
||||
pg_restore -U postgres -d dreamchat backup.dump
|
||||
```
|
||||
Reference in New Issue
Block a user