
chat-ollama
ChatOllama is an open-source AI chatbot that brings cutting-edge language models to your fingertips while keeping your data private and secure.
Stars: 3357

ChatOllama is an open-source chatbot based on LLMs (Large Language Models). It supports a wide range of language models, including Ollama served models, OpenAI, Azure OpenAI, and Anthropic. ChatOllama supports multiple types of chat, including free chat with LLMs and chat with LLMs based on a knowledge base. Key features of ChatOllama include Ollama models management, knowledge bases management, chat, and commercial LLMs API keys management.
README:
English | 简体中文
🔐 New ACL Feature (2025-08-25): Access Control Lists (ACL) for MCP server management! Control who can configure MCP servers with
ACL_ENABLED
environment variable. Learn more about ACL configuration →
🤖 Deep Agents Support (2025-08-19): ChatOllama now supports AI Agents with tool access! Currently requires Anthropic API key. Please refer to
.env.example
and setANTHROPIC_API_KEY
in.env
. Tools are configured through MCP settings. Visit/agents
to get started.
📢 Database Migration Notice (2025-08-14): ChatOllama has moved from SQLite to PostgreSQL as the primary database provider for better performance and scalability.
ChatOllama
is an open source chatbot platform built with Nuxt 3, supporting a wide range of language models and advanced features including knowledge bases, realtime voice chat, and Model Context Protocol (MCP) integration.
- OpenAI / Azure OpenAI
- Anthropic
- Google Gemini
- Groq
- Moonshot
- Ollama
- OpenAI API compatible service providers
- AI Agents - Intelligent agents with tool access for research and task execution
- Multi-modal Chat - Text and image input support
- Knowledge Bases - RAG (Retrieval Augmented Generation) with document upload
- Realtime Voice Chat - Voice conversations with Gemini 2.0 Flash
- Model Context Protocol (MCP) - Extensible tool integration
- Vector Databases - Chroma and Milvus support
- Docker Support - Easy deployment with Docker Compose
- Internationalization - Multi-language support
Choose your preferred deployment method:
The easiest way to get started. Download docker-compose.yaml and run:
docker compose up
Access ChatOllama at http://localhost:3000
For development or customization:
-
Prerequisites
- Node.js 18+ and pnpm
- Local PostgreSQL database server
- Ollama server running on http://localhost:11434
- ChromaDB or Milvus vector database
-
Installation
git clone [email protected]:sugarforever/chat-ollama.git cd chat-ollama cp .env.example .env pnpm install
-
Database Setup
- Create a PostgreSQL database
- Configure the database URL in
.env
- Run migrations:
pnpm prisma migrate deploy
-
Start Development
pnpm dev
If you're upgrading from a previous version that used SQLite, follow these steps to migrate your data:
No action required! Docker deployments handle the migration automatically:
- The PostgreSQL service starts automatically
- Database migrations run on container startup
- Your existing data will be preserved
-
Backup your existing SQLite data (if you have important chat history):
cp chatollama.sqlite chatollama.sqlite.backup
-
Install and setup PostgreSQL:
# macOS with Homebrew brew install postgresql brew services start postgresql # Create database and user psql postgres CREATE DATABASE chatollama; CREATE USER chatollama WITH PASSWORD 'your_password'; GRANT ALL PRIVILEGES ON DATABASE chatollama TO chatollama; \q
-
Update your
.env
file:# Replace SQLite URL with PostgreSQL DATABASE_URL="postgresql://chatollama:your_password@localhost:5432/chatollama"
-
Run database migrations:
pnpm prisma migrate deploy
-
Migrate existing SQLite data (if you have chat history to preserve):
pnpm migrate:sqlite-to-postgres
ChatOllama supports two vector databases. Configure in your .env
file:
# Choose: chroma or milvus
VECTOR_STORE=chroma
CHROMADB_URL=http://localhost:8000
MILVUS_URL=http://localhost:19530
ChromaDB Setup (Default)
docker run -d -p 8000:8000 chromadb/chroma
Key configuration options in .env
:
# Access Control
ACL_ENABLED=false # Set to 'true' for production (admin-only MCP management)
# Database
DATABASE_URL=file:../../chatollama.sqlite
# Server
PORT=3000
HOST=
# Vector Database
VECTOR_STORE=chroma
CHROMADB_URL=http://localhost:8000
# Optional: API Keys for commercial models
OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key
GOOGLE_API_KEY=your_gemini_key
GROQ_API_KEY=your_groq_key
MOONSHOT_API_KEY=your_moonshot_key
# Optional: Proxy settings
NUXT_PUBLIC_MODEL_PROXY_ENABLED=false
NUXT_MODEL_PROXY_URL=http://127.0.0.1:1080
# Optional: Cohere for reranking
COHERE_API_KEY=your_cohere_key
You can enable or disable major product areas via feature flags. These can be set at build time using .env
, or at runtime in Docker using NUXT_
-prefixed variables.
-
Available features
-
MCP (Model Context Protocol) → toggles
Settings → MCP
module. Flag:mcpEnabled
-
Knowledge Bases → toggles Knowledge Bases menu and pages. Flag:
knowledgeBaseEnabled
-
Realtime Chat → toggles
/realtime
voice chat page. Flag:realtimeChatEnabled
-
Models Management → toggles
Models
menu and/models
page. Flag:modelsManagementEnabled
-
MCP (Model Context Protocol) → toggles
-
Docker (recommended for deployments) Set runtime overrides with
NUXT_
variables indocker-compose.yaml
:services: chatollama: environment: - NUXT_MCP_ENABLED=true - NUXT_KNOWLEDGE_BASE_ENABLED=true - NUXT_REALTIME_CHAT_ENABLED=true - NUXT_MODELS_MANAGEMENT_ENABLED=true
-
.env (build time during
pnpm build
) If you are building locally (non-Docker) or creating a custom image, you can set:MCP_ENABLED=true KNOWLEDGE_BASE_ENABLED=true REALTIME_CHAT_ENABLED=true MODELS_MANAGEMENT_ENABLED=true
Note: These are evaluated when
nuxt.config.ts
is built. For prebuilt Docker images, prefer theNUXT_
variables above to override at runtime. -
Notes
-
NUXT_
variables map directly toruntimeConfig
keys at runtime and take precedence in containers. - Using
MCP_ENABLED=true
in Compose will not override a prebuilt image’sruntimeConfig
; useNUXT_MCP_ENABLED=true
instead.
-
ChatOllama integrates with MCP to extend AI capabilities through external tools and data sources. MCP servers are managed through a user-friendly interface in Settings.
ChatOllama provides flexible access control for MCP server management to support both development and production environments.
Permission Modes:
-
ACL_ENABLED=false
(default): Open access - all users can manage MCP servers -
ACL_ENABLED=true
: Restricted access - only admin/superadmin users can manage MCP servers
🔧 Development & Personal Use (Recommended: ACL_ENABLED=false)
# .env file
ACL_ENABLED=false
User Experience by Role:
User Type | ACL_ENABLED=false | ACL_ENABLED=true |
---|---|---|
Unauthenticated | ✅ Full MCP access | ❌ Admin required |
Regular User | ✅ Full MCP access | ❌ Admin required |
Admin | ✅ Full MCP access | ✅ Full MCP access |
Super Admin | ✅ Full MCP access | ✅ Full MCP access |
Important Notes:
- MCP Tool Usage: All users can use configured MCP tools in chat regardless of ACL setting
- Backward Compatibility: Existing installations continue working without changes
-
Migration Safe: Enable ACL anytime by setting
ACL_ENABLED=true
Supported Transport Types:
- STDIO - Command-line tools (most common)
- Server-Sent Events (SSE) - HTTP-based streaming
- Streamable HTTP - HTTP-based communication
Configuration via Settings UI:
- Navigate to Settings → MCP
- Click "Add Server" to create a new MCP server
- Configure server details:
- Name: Descriptive server name
- Transport: Choose STDIO, SSE, or Streamable HTTP
- Command/Args (STDIO): Executable path and arguments
- URL (SSE/HTTP): Server endpoint URL
- Environment Variables: API keys and configuration
- Enable/Disable: Toggle server status
STDIO Server Example:
Name: Filesystem Tools
Transport: stdio
Command: uvx
Args: mcp-server-filesystem
Environment Variables:
PATH: ${PATH}
Migration from Legacy Config:
If you have an existing .mcp-servers.json
file:
pnpm exec ts-node scripts/migrate-mcp-servers.ts
Popular MCP Servers:
-
mcp-server-filesystem
- File system operations -
mcp-server-git
- Git repository management -
mcp-server-sqlite
- SQLite database queries -
mcp-server-brave-search
- Web search capabilities
How MCP Works in Chat: When MCP servers are enabled, their tools become available to AI models during conversations. The AI can automatically call these tools to:
- Read/write files when discussing code
- Search the web for current information
- Query databases for specific data
- Perform system operations as needed
Tools are loaded dynamically and integrated seamlessly into the chat experience.
Common Issues and Solutions:
-
"Admin access required" message appears:
-
Cause:
ACL_ENABLED=true
and user lacks admin privileges - Solution: Either disable ACL or promote user to admin
# Option 1: Disable ACL (development) ACL_ENABLED=false # Option 2: Promote user to admin (contact super admin)
-
Cause:
-
Cannot access MCP settings after enabling ACL:
- Cause: No admin account exists
- Solution: Create super admin account
# Set before first user signup SUPER_ADMIN_NAME=admin-username
-
MCP tools not working in chat:
- Cause: MCP feature disabled or servers misconfigured
- Solution: Check MCP feature flag and server status
# Enable MCP feature NUXT_MCP_ENABLED=true # Docker MCP_ENABLED=true # .env
-
Permission changes not taking effect:
- Cause: Browser cache or session issue
- Solution: Logout and login again, or restart application
Before setting SUPER_ADMIN_NAME:
- The first user to sign up automatically becomes super admin
After setting SUPER_ADMIN_NAME:
- Only the user with the specified username becomes super admin when they sign up
- Set in
.env
file:SUPER_ADMIN_NAME=your-admin-username
- Or in Docker: add to environment variables
Managing existing users:
- Use the promotion script tool to manage super admin roles:
# Promote existing user to super admin pnpm promote-super-admin username_or_email # List current super admins pnpm promote-super-admin --list
Super Admin Capabilities:
- Promote regular users to admin
- Manage all MCP servers (when ACL enabled)
- Access user management interface
- Configure system-wide settings
Admin Capabilities:
- Manage MCP servers (when ACL enabled)
- Cannot promote other users
Regular User Capabilities:
- Use all chat features and MCP tools
- Manage MCP servers (only when ACL disabled)
# Recommended production settings
ACL_ENABLED=false # Default: open access to MCP management
SUPER_ADMIN_NAME=admin # Set super admin username
AUTH_SECRET=your-long-random-secret-key-here
Enable voice conversations with Gemini 2.0 Flash:
- Set your Google API key in Settings
- Enable "Realtime Chat" in Settings
- Click the microphone icon to start voice conversations
- Access via
/realtime
page
Create knowledge bases for RAG conversations:
- Create Knowledge Base - Name and configure chunking parameters
- Upload Documents - PDF, DOCX, TXT files supported
- Chat with Knowledge - Reference your documents in conversations
Supported Vector Databases:
- ChromaDB (default) - Lightweight, easy setup
- Milvus - Production-scale vector database
Docker Deployment:
- Vector Data - Stored in Docker volumes (chromadb_volume)
-
Relational Data - SQLite database at
~/.chatollama/chatollama.sqlite
- Redis - Session and caching data
Development:
- Database - Local SQLite file
- Vector Store - External ChromaDB/Milvus instance
chatollama/
├── components/ # Vue components
├── pages/ # Nuxt pages (routing)
├── server/ # API routes and server logic
├── prisma/ # Database schema and migrations
├── locales/ # Internationalization files
├── config/ # Configuration files
└── docker-compose.yaml # Docker deployment
# Development
pnpm dev # Start development server
pnpm build # Build for production
pnpm preview # Preview production build
# Database
pnpm prisma-migrate # Run database migrations
pnpm prisma-generate # Generate Prisma client
pnpm prisma-push # Push schema changes
# User Management
pnpm promote-super-admin <username|email> # Promote user to super admin
pnpm promote-super-admin --list # List all super admins
-
Keep dependencies updated:
pnpm install
after eachgit pull
-
Run migrations:
pnpm prisma-migrate
when schema changes - Follow conventions: Use TypeScript, Vue 3 Composition API, and Tailwind CSS
- Test thoroughly: Verify both Docker and development setups
- Frontend: Nuxt 3, Vue 3, Nuxt UI, Tailwind CSS
- Backend: Nitro (Nuxt server), Prisma ORM
- Database: SQLite (development), PostgreSQL (production ready)
- Vector DB: ChromaDB, Milvus
- AI/ML: LangChain, Ollama, OpenAI, Anthropic, Google AI
- Deployment: Docker, Docker Compose
Join our Discord community for support, discussions, and updates:
- #technical-discussion - For contributors and technical discussions
- #customer-support - Get help with usage issues and troubleshooting
- #general - Community chat and announcements
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