AnythingLLM

Seamlessly switch between different LLM providers (OpenAI, Claude, Llama, Ollama, HuggingFace, local models) without rebuilding workflows or losing context. Enables vendor-agnostic AI infrastructure with zero lock-in.

Ingest multiple document types (PDFs, Word docs, websites, markdown, text files) into searchable knowledge bases that augment LLM responses with retrieved context. Supports nested folder organization and batch document uploads.

Ingest and process documents in diverse formats including PDFs, images with text (via OCR), Word documents, spreadsheets, and web content. Automatically extracts and indexes text for retrieval.

Maintain conversation history and context across multiple chat turns, allowing the AI to reference previous messages and build on prior discussions. Supports long-form conversations with persistent context.

Deploy AnythingLLM on your own infrastructure (Docker, Kubernetes, VPS) with complete control over hardware, network, and data location. Enables air-gapped or on-premise deployments.

Create isolated workspaces with separate document collections, LLM settings, and user permissions. Enables multi-project or multi-team setups with granular access control and independent configurations.

Chat with an LLM that automatically retrieves and references relevant documents from your knowledge base to ground responses in your specific data. Maintains conversation history and context across multiple turns.

Process and index documents locally without sending them to third-party servers, keeping sensitive data within your infrastructure. Supports self-hosted deployment for complete data privacy.

Configure workspace-specific settings including LLM selection, temperature/parameters, system prompts, document retrieval settings, and response behavior. Tailor each workspace to specific use cases.

Control user access at workspace and document level, assigning roles and permissions to manage who can view, edit, or delete documents and conversations. Supports team collaboration with access controls.

Export conversations and chat histories in multiple formats (PDF, markdown, text) and share them with team members or external stakeholders. Preserve context and document references in exports.

Organize documents into hierarchical folder structures within workspaces for better categorization and navigation. Supports bulk operations on folder contents.

Access AnythingLLM functionality via REST API for building custom applications, automating workflows, or integrating with existing tools. Enables headless usage and third-party integrations.