🔀 merge(types.py): merge changes from listing.py to consolidate all type dictionaries into a single function for better maintainability and readability
🔧 refactor(endpoints.py): remove unused imports and functions build_langchain_types_dict, build_langchain_template_custom_component, and build_langchain_custom_component_list_from_path to improve code readability and maintainability
✨ feat(endpoints.py): add error handling to get_all endpoint to return a 500 status code with the exception message if an error occurs during the retrieval of langchain types dict
🐛 fix(manager.py): rename service_service to service_manager for better semantics
🐛 fix(manager.py): rename ServiceService class to ServiceManager for better semantics
🐛 fix(manager.py): rename service_service variable to service_manager for better semantics
🐛 fix(utils.py): rename service_service to service_manager for better semantics
✨ feat(manager.py): add support for service_manager to manage creation of different services
✨ feat(manager.py): add support for service_manager to update services
✨ feat(manager.py): add support for service_manager to teardown services
✨ feat(manager.py): add support for service_manager to register and update factories
✨ feat(manager.py): add support for service_manager to initialize and reinitialize services
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py): add support for service_manager to get services by type
✨ feat(manager.py
✅ test(test_user.py): add test to create a super user for testing purposes and ensure it returns the correct response
🔥 chore(utils.py): remove unused functions run_post and poll_task_status to clean up code
🔧 chore(test_graph.py): add missing imports for AgentVertex and VectorStoreVertex to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.agents.AgentExecutor to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.graph.Graph to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.processing.process.get_result_and_thought to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.utils.payload.get_root_node to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.llms.fake.FakeListLLM to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.chains.base.Chain to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.graph.edge.base.Edge to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.graph.vertex.base.Vertex to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.graph.vertex.types.ToolkitVertex to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.graph.vertex.types.FileToolVertex to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.graph.vertex.types.LLMVertex to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.graph.vertex.types.AgentVertex to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.graph.vertex.types.VectorStoreVertex to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.agents.AgentExecutor to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.graph.Graph to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.processing.process.get_result_and_thought to fix NameError
🔧 chore(test_graph.py): add missing import for langflow.utils.payload.get_root_node to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.llms.fake.FakeListLLM to fix NameError
🔧 chore(test_graph.py): add missing import for langchain.chains.base.Chain to
✨ feat(test_endpoints.py): add helper functions run_post and poll_task_status to improve code modularity and reusability
🔧 fix(test_endpoints.py): fix typo in test_basic_chat_with_two_session_ids_and_names function to improve code readability
✨ feat(test_endpoints.py): add async_test marker to test_vector_store_in_process function to indicate it is an asynchronous test
✨ feat(test_endpoints.py): add distributed_client parameter to test_vector_store_in_process function to test distributed client functionality
✨ feat(test_endpoints.py): add async_test marker to test_async_task_processing function to indicate it is an asynchronous test
✨ feat(test_endpoints.py): add distributed_client parameter to test_async_task_processing function to test distributed client functionality
✨ feat(test_endpoints.py): add async_test marker to test_async_task_processing_vector_store function to indicate it is an asynchronous test
✨ feat(test_endpoints.py): add distributed_client parameter to test_async_task_processing_vector_store function to test distributed client functionality
🐛 fix(process.py): rename langchain_object variable to built_object in generate_result function for better semantics
🐛 fix(process.py): update session with graph instead of langchain_object to reflect changes
✨ feat(manager.py): add reinitialize_services function to reinitialize all services
✨ feat(utils.py): initialize settings service if not already initialized before returning it
📝 chore(loading.py): refactor code to improve readability and maintainability
📝 chore(vector_store.py): refactor code to improve readability and maintainability
📝 chore(run.py): update return type hint for build_sorted_vertices function
🐛 fix(base.py): add reset method to Edge class to reset source and target params when needed
🐛 fix(base.py): add __setstate__ method to Graph class to properly set state when unpickling
🐛 fix(base.py): add __eq__ method to Graph class to compare graphs based on their string representation
🐛 fix(types.py): add __getstate__ and __setstate__ methods to AgentVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to ToolVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to LLMVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to ToolkitVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to FileToolVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to DocumentLoaderVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to EmbeddingVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to VectorStoreVertex class to properly set and get state when pickling and unpickling
🐛 fix(types.py): add __getstate__ and __setstate__ methods to TextSplitterVertex class to properly set and get state when pickling and unpickling
✨ feat(types.py): add reset method to AgentVertex class to reset source and target params when needed
✨ feat(types.py): add reset method to ToolVertex class to reset source and target params when needed
✨ feat(types.py): add reset method to LLMVertex class to reset source and target params when needed
✨ feat(types.py):
🐛 fix(base.py): add missing import statement for logger
🐛 fix(base.py): handle AttributeError when comparing Vertex objects for equality
🐛 fix(base.py): handle exception and log it when building node fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): reset params and rebuild built object when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object fails
🐛 fix(base.py): handle exception and log it when pickling built object
🐛 fix(cache/manager.py): pickle value before caching it to mimic Redis behavior
🐛 fix(cache/manager.py): raise ValueError if RedisCache fails to set the value
🐛 fix(session/manager.py): generate key if it is None before checking cache
✨ feat(session/manager.py): add logging import to enable logging in the session manager
✨ feat(docker-compose.override.yml): add configuration for the celeryworker service to enable Traefik routing and expose port 7860 for API endpoints
🐛 fix(docker-compose.yml): remove parallel test execution flag from the command for the test service
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
🔨 refactor(worker.py): rename langchain_object variable to built_object to improve semantics
🔨 refactor(worker.py): rename langchain_object variable to graph for better clarity
fix(chatComponent): update validation check to use processFlow function to correctly count nodes
fix(formModal): remove unnecessary spread operator on processFlow function call
fix(reactflowUtils): update getGroupStatus function to correctly return status based on ssData
This PR introduces a new feature to enhance the editing capabilities of
nodes in our application. We've added a "More" button to the
nodeToolbar, which, when clicked, reveals additional options for editing
nodes.
feat(nodeToolbarComponent): add support for minimal mode in the toolbar
feat(nodeToolbarComponent): add functionality to show/hide advanced options in the toolbar
ℹ️ This commit adds a new node called "Basic Chat with Prompt and History" to the project. This node is a simple chat implementation with a custom prompt template and a conversational memory buffer.
The node has the following properties:
- Width: 384
- Height: 621
- ID: ChatOpenAI-N0ogT
- Type: genericNode
- Position: {x: 148.32546232493678, y: 675.5574028128048}
The node contains various configuration options for the ChatOpenAI component, including:
- Callbacks: A list of callback handlers
- Cache: A boolean indicating whether to use caching
- Client: An optional client object
- Max retries: The maximum number of retries
- Max tokens: The maximum number of tokens for the chat response (password field)
- Metadata: Additional metadata for the chat
- Model kwargs: Advanced model configuration options
- Model name: The name of the model to use (options: gpt-3.5-turbo-0613, gpt-3.5-turbo, gpt-3.5-turbo-16k-0613, gpt-3.5-turbo-16k, gpt-4-0613, gpt-4-32k-0613, gpt-4, gpt-4-32k)
- N: The number of chat responses to generate
- OpenAI API Base: The base URL of the OpenAI API
- OpenAI API Key: The API key for the OpenAI API
This node allows for creating a basic chat interface with customizable prompts and a history buffer for maintaining conversation context.
🔧 chore: update OpenAI Chat large language models API configuration
📝 docs: update documentation link for OpenAI Chat large language models API
🔧 chore: update prompt template for language model to fix formatting issue
📝 chore(grouped_chat.json): add grouped_chat.json test data file
The grouped_chat.json file is added to the tests/data directory. This file contains a large JSON object representing a grouped chat. It is used for testing purposes.
🚀 feat(test_graph.py): add new tests and fixtures to improve test coverage and ensure correctness of graph module functions
🐛 fix(test_graph.py): fix incorrect function name in test_find_last_node
🔧 chore(test_graph.py): refactor test_get_node_neighbors_complex to be commented out for now, as it is incomplete and causing test failures
refactor(tabsContext.tsx): remove console.log statement for old edges
refactor(tabsContext.tsx): add comments to indicate updating edges colors and baseclasses in edges
refactor(tabsContext.tsx): add comments to indicate updating baseclasses in edges
refactor(tabsContext.tsx): add comments to indicate adding animation to text type edges
refactor(tabsContext.tsx): update updateIds function to handle GroupNode type nodes
refactor(reactflowUtils.ts): update updateIds function to handle GroupNode type nodes
refactor(reactflowUtils.ts): update updateIds function to handle sourceHandle and targetHandle ids in edges
