Add verbose and fix_memory_inputs to langchain_object in load_flow_from_json function. The verbose attribute is set to True if it exists in the langchain_object. The fix_memory_inputs function is called on the langchain_object.
fix(api/chat_manager.py): remove async from ChatHistory.add_message and on_chat_history_update
fix(interface/run.py): remove async from async_get_result_and_steps
refactor(utils/util.py): remove unused code and simplify sync_to_async decorator
fix(api): fix ChatManager.get_history method to exclude start and stream messages
feat(api): add is_bot field to ChatMessage, ChatResponse, and FileResponse schemas
fix(validate): set validation status to "success" or "error" based on response status
feat(validate): add state for validation status and outline color in GenericNode component
refactor(validate): use useDebouncedCallback hook for debouncing validation function
refactor(validate): simplify useEffect dependencies in GenericNode component
This change adds error handling to catch a specific exception that may occur when processing documents with the ChromaDB library. If there are not enough documents for indexing, the error message will suggest reducing the chunk size in TextSplitter.
Add a new file `callback.py` that contains a new class `StreamingLLMCallbackHandler` that inherits from `AsyncCallbackHandler`. This class handles streaming LLM responses. It has a constructor that takes a `websocket` parameter and sets it as an instance variable. It also has an `on_llm_new_token` method that takes a `token` parameter and sends a `ChatResponse` object to the `websocket` instance variable.
Update `chat_manager.py` to import the new `StreamingLLMCallbackHandler` class. Add a new function `try_setting_streaming_options` that takes a `langchain_object` and a `websocket` parameter. This function checks if the `llm` attribute of the `langchain_object` is an instance of `OpenAI`, `ChatOpenAI`, `AzureOpenAI`, or `AzureChatOpenAI`. If it is, it sets the
"UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 9465: character maps to
<undefined>".
Specifying the encodint type in the function helps to fix that error.
fix(schemas.py): add validation for file response type and data type
test(test_websocket.py): remove data and data_type fields from ChatResponse messages in tests
feat(cache): add support for multiple clients and context manager to set client_id
feat(cache): add observer pattern to notify on cache changes
feat(cache): add async observer pattern to notify on cache changes in async functions
feat(cache): add methods to add pandas DataFrame or Series and PIL Image to cache
feat(cache): add method to get an object from cache by key
feat(cache): add method to get the last added item in cache
feat(chat.py, chat_manager.py): add error handling for async_get_result_and_steps
feat(chat.py): add client_id to websocket endpoint
feat(schemas.py): add data_type field to ChatResponse schema
refactor(run.py): memoize build_langchain_object_with_caching function with maxsize of 10
feat(cache): add support for pandas and PIL Image objects caching
fix(interface): import cache-related functions from base.py module
test(cache): update import statements in cache-related test file
refactor(tools/base.py): comment out unused code for ToolCreator
feat(nodes.py): add 'return_direct' field to ToolNode template and set base class to 'Tool'
