Introduces opensearch_multimodel.py, a new component supporting multi-model hybrid search and ingestion in OpenSearch with dynamic vector fields, parallel embedding, and advanced filtering. Refactors embedding generation in opensearch.py to use tenacity-based retry logic and IBM/Watsonx rate limiting. Updates related flow JSONs to integrate the new component.
* Changed backend to mount config at volume
* update lock
* Changed backend to reapply settings after detecting that flow is reset
* Added periodic backup for flows, make better reset
* tui warning
* Changed settings page to alert user that he has to disable lock flow
* Changed flows to be locked
* Do periodic backup only if onboarding is done
* Change backup function to only back up flows if flow lock is disabled
* Added session manager to reapply all settings
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Co-authored-by: Sebastián Estévez <estevezsebastian@gmail.com>
Introduces a 'fail_safe_mode' option to the Embedding Model and OpenSearch (Multi-Model Multi-Embedding) components, allowing errors to be logged and None returned instead of raising exceptions. Refactors embedding model fetching logic for better error handling and updates component metadata, field order, and dependencies. Also adds 'className' fields and updates frontend node folder IDs for improved UI consistency.
Replaces OpenSearchHybrid with OpenSearchVectorStoreComponentMultimodalMultiEmbedding in ingestion_flow.json, updating all relevant edges and embedding connections. Updates docker-compose.yml to use local builds for backend, frontend, and langflow, and improves environment variable handling for API keys. This refactor enables multi-model and multimodal embedding support for document ingestion and search.
Switches Docker Compose services to local builds for backend, frontend, and langflow. Updates embedding model component to support IBM watsonx.ai features, including input token truncation and original text output, adds new dependencies, and improves configuration options in ingestion and agent flows.
* Added flows with new components
* commented model provider assignment
* Added agent component display name
* commented provider assignment, assign provider on the generic component, assign custom values
* fixed ollama not showing loading steps, fixed loading steps never being removed
* made embedding and llm model optional on onboarding call
* added isEmbedding handling on useModelSelection
* added isEmbedding on onboarding card, separating embedding from non embedding card
* Added one additional step to configure embeddings
* Added embedding provider config
* Changed settings.py to return if not embedding
* Added editing fields to onboarding
* updated onboarding and flows_service to change embedding and llm separately
* updated templates that needs to be changed with provider values
* updated flows with new components
* Changed config manager to not have default models
* Changed flows_service settings
* Complete steps if not embedding
* Add more onboarding steps
* Removed one step from llm steps
* Added Anthropic as a model for the language model on the frontend
* Added anthropic models
* Added anthropic support on Backend
* Fixed provider health and validation
* Format settings
* Change anthropic logo
* Changed button to not jump
* Changed flows service to make anthropic work
* Fixed some things
* add embedding specific global variables
* updated flows
* fixed ingestion flow
* Implemented anthropic on settings page
* add embedding provider logo
* updated backend to work with multiple provider config
* update useUpdateSettings with new settings type
* updated provider health banner to check for health with new api
* changed queries and mutations to use new api
* changed embedding model input to work with new api
* Implemented provider based config on the frontend
* update existing design
* fixed settings configured
* fixed provider health query to include health check for both the providers
* Changed model-providers to show correctly the configured providers
* Updated prompt
* updated openrag agent
* Fixed settings to allow editing providers and changing llm and embedding models
* updated settings
* changed lf ver
* bump openrag version
* added more steps
* update settings to create the global variables
* updated steps
* updated default prompt
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Co-authored-by: Sebastián Estévez <estevezsebastian@gmail.com>
Introduces the CONNECTOR_TYPE_URL environment variable to docker-compose files and assets, updates the OpenRAG URL ingestion flow to use it, and ensures it is set in the auth service global variables. This enables explicit configuration and handling of URL-based connectors in the OpenRAG system.
Added a new flow definition for OpenRAG with OpenSearch hybrid search in flows/openrag_url_mcp.json. Updated .gitignore to allow tracked JSON files in the flows directory while ignoring others.
