Changelog

Note: version releases in the 0.x.y range may introduce breaking changes.

0.2.1

patch: Added default columns for vector store at create_pipeline_config. No change for other cases.
patch: Change json parsing error in the map step of global search to warning
patch: Fix Local Search breaking when loading Embeddings input. Defaulting overwrite to True as in the rest of the vector store config
patch: Fix json parsing when LLM returns faulty responses
patch: Fix missing community reports and refactor community context builder
patch: Fixed a bug that erased the vector database, added a new parameter to specify the config file path, and updated the documentation accordingly.
patch: Try parsing json before even repairing
patch: Update Prompt Tuning meta prompts with finer examples
patch: Update default entity extraction and gleaning prompts to reduce hallucinations
patch: add encoding-model to entity/claim extraction config
patch: add encoding-model to text chunking config
patch: add user prompt to history-tracking llm
patch: update config reader to allow for zero gleans
patch: update config-reader to allow for empty chunk-by arrays
patch: update history-tracking LLm to use 'assistant' instead of 'system' in output history.
patch: use history argument in hash key computation; add history input to cache data

minor: Add content-based KNN for selecting prompt tune few shot examples
minor: Add dynamic community report rating to the prompt tuning engine
patch: Add Minute-based Rate Limiting and fix rpm, tpm settings
patch: Add N parameter support
patch: Add cli flag to overlay default values onto a provided config.
patch: Add exception handling on file load
patch: Add language support to prompt tuning
patch: Add llm params to local and global search
patch: Fix broken prompt tuning link on docs
patch: Fix delta none on query calls
patch: Fix docsite base url
patch: Fix encoding model parameter on prompt tune
patch: Fix for --limit exceeding the dataframe length
patch: Fix for Ruff 0.5.2
patch: Fixed an issue where base OpenAI embeddings can't work with Azure OpenAI LLM
patch: Modify defaults for CHUNK_SIZE, CHUNK_OVERLAP and GLEANINGS to reduce time and LLM calls
patch: fix community_report doesn't work in settings.yaml
patch: fix llm response content is None in query
patch: fix the organization parameter is ineffective during queries
patch: remove duplicate file read
patch: support non-open ai model config to prompt tune
patch: use binary io processing for all file io operations