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.
Introduces a 'fail_safe_mode' option to the Embedding Model component, allowing errors to be logged and None returned instead of raising exceptions. Refactors embedding initialization logic for OpenAI, Ollama, and IBM watsonx.ai providers to support this mode, and updates UI configuration and metadata accordingly.
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.
* remove connection dot indicators on settings page, better toast message for provider setup dialogs, fix typo in default agent prompt
* format
* open llm model select when toast button to settings is clicked
* 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>
* Removed upload start message
* Made onboarding upload refetch nudges and only finish when document is ingested
* Implemented query filters on nudges
* changed get to post
* Implemented filtering for documents that are not sample data on nudges
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Co-authored-by: Sebastián Estévez <estevezsebastian@gmail.com>
* Updated ollama components
* Changed ollama display name to be correct
* Changed prompt of provider validation
* removed event dispatched from file upload
* Changed onboarding to upload the entire knowledge
* Changed default models for ollama
* Changed prompts to include info about OpenRAG, change status of As Dataframe and As Vector Store to false on OpenSearch component
* added markdown to onboarding step
* added className to markdown renderer
* changed onboarding step to not render span
* Added nudges to onboarding content
* Added onboarding style for nudges
* updated user message and assistant message designs
* updated route.ts to handle streaming messages
* created new useChatStreaming to handle streaming
* changed useChatStreaming to work with the chat page
* changed onboarding content to use default messages instead of onboarding steps, and to use the new hook to send messages
* added span to the markdown renderer on stream
* updated page to use new chat streaming hook
* disable animation on completed steps
* changed markdown renderer margins
* changed css to not display markdown links and texts on white always
* added isCompleted to assistant and user messages
* removed space between elements on onboarding step to ensure smoother animation
* removed opacity 50 on onboarding messages
* changed default api to be langflow on chat streaming
* added fade in and color transition
* added color transition
* Rendered onboarding with use-stick-to-bottom
* Added use stick to bottom on page
* fixed nudges design
* changed chat input design
* fixed nudges design
* made overflow be hidden on main
* Added overflow y auto on other pages
* Put animate on messages
* Add source to types
* Adds animate and delay props to messages
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.
Replaces the File component with a new OpenSearch hybrid search component in the ingestion flow, adds support for document metadata, and updates flow edges for DataFrame operations. Updates OpenSearch component implementation with advanced authentication, metadata handling, and vector store features. Docker Compose files and related service references are also updated to support the new OpenSearch integration.
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.
Changed Dockerfile.langflow to use the 'test-openai-responses' branch. Improved file handling in ChatInput, updated ChatOutput to fix source property unpacking, and made AgentComponent use LCToolsAgentComponent._base_inputs. Also updated code hashes, dependency versions, and metadata timestamps in openrag_agent.json.
* changed tooltip stype
* added start on label wrapper
* changed switch to checkbox on openai onboarding and changed copies
* made border be red when api key is invalid
* Added embedding configuration after onboarding
* changed openrag ingest docling to have same embedding model component as other flows
* changed flows service to get flow by id, not by path
* modify reset_langflow to also put right embedding model
* added endpoint and project id to provider config
* added replacing the model with the provider model when resetting
* Moved consts to settings.py
* raise when flow_id is not found
Switched OpenRAG backend and frontend in docker-compose.yml to use local Dockerfile builds instead of remote images. Updated environment variables for better clarity and system integration. In flows/openrag_agent.json and langflow_file_service, improved handling of docs_metadata to support Data objects and added logging for metadata ingestion. Added agent_llm edge to agent node in flow definition.
Added OWNER, OWNER_NAME, OWNER_EMAIL, and CONNECTOR_TYPE environment variables to docker-compose.yml and updated LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT accordingly. Modified ingestion_flow.json to adjust node selection and className, and cleared a sensitive value. Added logging for metadata tweaks in langflow_file_service.py for better traceability.
Updated the OpenSearchVectorStoreComponent to improve document metadata ingestion, including support for Data objects in docs_metadata. Added new edges and nodes to ingestion_flow.json for dynamic metadata input. Changed Dockerfile.langflow to use the fix-file-component branch.
