feat(librechat): install librechat
This commit is contained in:
Masaki Yatsu
246
README.md
246
README.md
@@ -62,6 +62,8 @@ A remotely accessible Kubernetes home lab with OIDC authentication. Build a mode
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### LLM & AI Applications (Optional)
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- **[Ollama](https://ollama.com/)**: Local LLM inference server with GPU acceleration
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- **[LibreChat](https://www.librechat.ai/)**: Web-based chat interface with multi-model support and MCP integration
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- **[Langfuse](https://langfuse.com/)**: LLM observability and analytics platform for tracking and debugging AI applications
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### Orchestration (Optional)
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@@ -116,21 +118,13 @@ Lightweight Kubernetes distribution optimized for edge computing:
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- **Production Ready**: Full Kubernetes functionality with minimal overhead
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- **Easy Deployment**: Single binary installation with built-in ingress
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### Longhorn
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### PostgreSQL
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Enterprise-grade distributed storage system:
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Production-ready relational database:
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- **Highly Available**: Block storage with no single point of failure
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- **Backup & Recovery**: Built-in disaster recovery capabilities
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- **NFS Support**: Persistent volumes with NFS compatibility
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### HashiCorp Vault
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Centralized secrets management:
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- **Secure Storage**: Encrypted secret storage with access control
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- **Dynamic Secrets**: Automatic credential generation and rotation
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- **External Secrets Integration**: Syncs with Kubernetes via External Secrets Operator
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- **High Availability**: Clustered deployment with CloudNativePG
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- **pgvector Extension**: Vector similarity search for AI/ML workloads
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- **Multi-Tenant**: Shared database for Keycloak and applications
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### Keycloak
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@@ -140,13 +134,21 @@ Open-source identity and access management:
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- **User Federation**: Identity brokering and external provider integration
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- **Group-Based Access**: Role and permission management
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### PostgreSQL
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### HashiCorp Vault
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Production-ready relational database:
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Centralized secrets management:
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- **High Availability**: Clustered deployment with CloudNativePG
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- **pgvector Extension**: Vector similarity search for AI/ML workloads
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- **Multi-Tenant**: Shared database for Keycloak and applications
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- **Secure Storage**: Encrypted secret storage with access control
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- **Dynamic Secrets**: Automatic credential generation and rotation
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- **External Secrets Integration**: Syncs with Kubernetes via External Secrets Operator
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### External Secrets Operator
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Kubernetes operator for secret synchronization:
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- **Vault Integration**: Automatically syncs secrets from Vault to Kubernetes
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- **Multiple Backends**: Supports various secret management systems
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- **Secure Rotation**: Automatic secret lifecycle management
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### Prometheus and Grafana
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@@ -160,13 +162,27 @@ Comprehensive monitoring and observability stack:
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[📖 See Prometheus Documentation](./prometheus/README.md)
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### External Secrets Operator
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### Goldilocks
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Kubernetes operator for secret synchronization:
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Resource recommendation dashboard for right-sizing workloads:
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- **Vault Integration**: Automatically syncs secrets from Vault to Kubernetes
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- **Multiple Backends**: Supports various secret management systems
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- **Secure Rotation**: Automatic secret lifecycle management
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- **VPA Integration**: Powered by Vertical Pod Autoscaler for metrics-based recommendations
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- **Visual Dashboard**: User-friendly interface for viewing resource recommendations
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- **QoS Guidance**: Recommendations for Guaranteed, Burstable, and BestEffort classes
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- **Monitoring-Only Mode**: Observes workloads without automatic scaling
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- **Namespace-Based**: Enable monitoring per namespace with labels
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[📖 See Goldilocks Documentation](./goldilocks/README.md)
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[📖 See VPA Documentation](./vpa/README.md)
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### Longhorn
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Enterprise-grade distributed storage system:
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- **Highly Available**: Block storage with no single point of failure
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- **Backup & Recovery**: Built-in disaster recovery capabilities
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- **NFS Support**: Persistent volumes with NFS compatibility
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### MinIO
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@@ -187,68 +203,6 @@ Multi-user platform for interactive computing:
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[📖 See JupyterHub Documentation](./jupyterhub/README.md)
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### MLflow
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Machine learning lifecycle management platform:
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- **Experiment Tracking**: Log parameters, metrics, and artifacts for ML experiments
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- **Model Registry**: Version and manage ML models with deployment lifecycle
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- **Keycloak Authentication**: OAuth2 integration with group-based access control
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[📖 See MLflow Documentation](./mlflow/README.md)
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### KServe
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Model serving platform for deploying ML models on Kubernetes:
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- **Multi-Framework Support**: TensorFlow, PyTorch, scikit-learn, XGBoost, MLflow, and more
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- **MLflow Integration**: Deploy models directly from MLflow Model Registry
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- **Inference Protocols**: REST and gRPC with v2 Open Inference Protocol
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- **RawDeployment Mode**: Uses native Kubernetes Deployments without Knative dependency
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[📖 See KServe Documentation](./kserve/README.md)
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### Langfuse
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LLM observability and analytics platform:
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- **Trace Tracking**: Monitor LLM calls, chains, and agent executions with detailed traces
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- **Prompt Management**: Version and test prompts with playground interface
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- **Analytics**: Track costs, latency, and token usage across all LLM applications
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- **Keycloak Authentication**: OAuth2 integration with automatic user provisioning
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[📖 See Langfuse Documentation](./langfuse/README.md)
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### Apache Superset
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Modern business intelligence platform:
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- **Rich Visualizations**: 40+ chart types including mixed charts, treemaps, and heatmaps
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- **SQL Lab**: Powerful editor for complex queries and dataset creation
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- **Keycloak & Trino**: OAuth2 authentication and Iceberg data lake integration
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[📖 See Superset Documentation](./superset/README.md)
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### Metabase
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Lightweight business intelligence:
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- **Simple Setup**: Quick configuration with clean, modern UI
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- **Multiple Databases**: Connect to PostgreSQL, Trino, and more
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- **Keycloak Authentication**: OAuth2 integration for user management
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[📖 See Metabase Documentation](./metabase/README.md)
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### Querybook
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Big data querying UI with notebook interface:
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- **Trino Integration**: SQL queries against multiple data sources with user impersonation
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- **Notebook Interface**: Shareable datadocs with queries and visualizations
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- **Real-time Execution**: WebSocket-based query progress updates
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[📖 See Querybook Documentation](./querybook/README.md)
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### Trino
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Fast distributed SQL query engine:
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@@ -259,15 +213,15 @@ Fast distributed SQL query engine:
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[📖 See Trino Documentation](./trino/README.md)
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### DataHub
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### Querybook
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Modern data catalog and metadata management:
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Big data querying UI with notebook interface:
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- **OIDC Integration**: Keycloak authentication for unified access
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- **Metadata Discovery**: Search and browse data assets across platforms
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- **Lineage Tracking**: Visualize data flow and dependencies
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- **Trino Integration**: SQL queries against multiple data sources with user impersonation
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- **Notebook Interface**: Shareable datadocs with queries and visualizations
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- **Real-time Execution**: WebSocket-based query progress updates
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[📖 See DataHub Documentation](./datahub/README.md)
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[📖 See Querybook Documentation](./querybook/README.md)
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### ClickHouse
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@@ -309,15 +263,88 @@ Apache Iceberg REST Catalog:
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[📖 See Lakekeeper Documentation](./lakekeeper/README.md)
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### Apache Airflow
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### Apache Superset
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Workflow orchestration platform:
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Modern business intelligence platform:
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- **DAG-Based**: Define data pipelines as code with Python
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- **JupyterHub Integration**: Develop and test workflows in notebooks
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- **Keycloak Authentication**: OAuth2 for user management
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- **Rich Visualizations**: 40+ chart types including mixed charts, treemaps, and heatmaps
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- **SQL Lab**: Powerful editor for complex queries and dataset creation
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- **Keycloak & Trino**: OAuth2 authentication and Iceberg data lake integration
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[📖 See Airflow Documentation](./airflow/README.md)
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[📖 See Superset Documentation](./superset/README.md)
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### Metabase
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Lightweight business intelligence:
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- **Simple Setup**: Quick configuration with clean, modern UI
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- **Multiple Databases**: Connect to PostgreSQL, Trino, and more
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- **Keycloak Authentication**: OAuth2 integration for user management
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[📖 See Metabase Documentation](./metabase/README.md)
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### DataHub
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Modern data catalog and metadata management:
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- **OIDC Integration**: Keycloak authentication for unified access
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- **Metadata Discovery**: Search and browse data assets across platforms
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- **Lineage Tracking**: Visualize data flow and dependencies
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[📖 See DataHub Documentation](./datahub/README.md)
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### MLflow
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Machine learning lifecycle management platform:
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- **Experiment Tracking**: Log parameters, metrics, and artifacts for ML experiments
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- **Model Registry**: Version and manage ML models with deployment lifecycle
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- **Keycloak Authentication**: OAuth2 integration with group-based access control
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[📖 See MLflow Documentation](./mlflow/README.md)
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### KServe
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Model serving platform for deploying ML models on Kubernetes:
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- **Multi-Framework Support**: TensorFlow, PyTorch, scikit-learn, XGBoost, MLflow, and more
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- **MLflow Integration**: Deploy models directly from MLflow Model Registry
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- **Inference Protocols**: REST and gRPC with v2 Open Inference Protocol
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- **RawDeployment Mode**: Uses native Kubernetes Deployments without Knative dependency
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[📖 See KServe Documentation](./kserve/README.md)
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### Ollama
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Local LLM inference server:
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- **Local Inference**: Run LLMs locally without external API dependencies
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- **GPU Acceleration**: NVIDIA GPU support with automatic runtime configuration
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- **Model Library**: Access to thousands of open-source models (Llama, Qwen, DeepSeek, etc.)
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- **OpenAI-Compatible API**: Drop-in replacement for OpenAI API endpoints
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[📖 See Ollama Documentation](./ollama/README.md)
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### LibreChat
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Web-based chat interface for LLMs:
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- **Multi-Model Support**: Connect to Ollama, OpenAI, Anthropic, and custom endpoints
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- **MCP Integration**: Model Context Protocol support for web search and tools
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- **Keycloak Authentication**: OAuth2 integration for user management
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[📖 See LibreChat Documentation](./librechat/README.md)
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### Langfuse
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LLM observability and analytics platform:
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- **Trace Tracking**: Monitor LLM calls, chains, and agent executions with detailed traces
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- **Prompt Management**: Version and test prompts with playground interface
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- **Analytics**: Track costs, latency, and token usage across all LLM applications
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- **Keycloak Authentication**: OAuth2 integration with automatic user provisioning
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[📖 See Langfuse Documentation](./langfuse/README.md)
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### Dagster
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@@ -329,6 +356,16 @@ Modern data orchestration platform:
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[📖 See Dagster Documentation](./dagster/README.md)
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### Apache Airflow
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Workflow orchestration platform:
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- **DAG-Based**: Define data pipelines as code with Python
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- **JupyterHub Integration**: Develop and test workflows in notebooks
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- **Keycloak Authentication**: OAuth2 for user management
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[📖 See Airflow Documentation](./airflow/README.md)
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### Fairwinds Polaris
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Kubernetes configuration validation and best practices auditing:
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@@ -340,20 +377,6 @@ Kubernetes configuration validation and best practices auditing:
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[📖 See Fairwinds Polaris Documentation](./fairwinds-polaris/README.md)
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### Goldilocks
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Resource recommendation dashboard for right-sizing workloads:
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- **VPA Integration**: Powered by Vertical Pod Autoscaler for metrics-based recommendations
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- **Visual Dashboard**: User-friendly interface for viewing resource recommendations
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- **QoS Guidance**: Recommendations for Guaranteed, Burstable, and BestEffort classes
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- **Monitoring-Only Mode**: Observes workloads without automatic scaling
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- **Namespace-Based**: Enable monitoring per namespace with labels
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[📖 See Goldilocks Documentation](./goldilocks/README.md)
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[📖 See VPA Documentation](./vpa/README.md)
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## Common Operations
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### User Management
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@@ -462,6 +485,7 @@ kubectl --context yourpc-oidc get nodes
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# JupyterHub: https://jupyter.yourdomain.com
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# MLflow: https://mlflow.yourdomain.com
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# Langfuse: https://langfuse.yourdomain.com
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# LibreChat: https://chat.yourdomain.com
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```
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## Customization
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