* refactor stream/chat/embed-stram to be a single execution logic path so that it is easier to maintain and build upon
* no thread in sync chat since only api uses it
adjust import locations
* add support for mistral api
* update docs to show support for Mistral
* add default temp to all providers, suggest different results per provider
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Co-authored-by: timothycarambat <rambat1010@gmail.com>
* WIP model selection per workspace (migrations and openai saves properly
* revert OpenAiOption
* add support for models per workspace for anthropic, localAi, ollama, openAi, and togetherAi
* remove unneeded comments
* update logic for when LLMProvider is reset, reset Ai provider files with master
* remove frontend/api reset of workspace chat and move logic to updateENV
add postUpdate callbacks to envs
* set preferred model for chat on class instantiation
* remove extra param
* linting
* remove unused var
* refactor chat model selection on workspace
* linting
* add fallback for base path to localai models
---------
Co-authored-by: timothycarambat <rambat1010@gmail.com>
* allow use of any embedder for any llm/update data handling modal
* Apply embedder override and fallback to OpenAI and Azure models
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Co-authored-by: timothycarambat <rambat1010@gmail.com>
* WIP on continuous prompt window summary
* wip
* Move chat out of VDB
simplify chat interface
normalize LLM model interface
have compression abstraction
Cleanup compressor
TODO: Anthropic stuff
* Implement compression for Anythropic
Fix lancedb sources
* cleanup vectorDBs and check that lance, chroma, and pinecone are returning valid metadata sources
* Resolve Weaviate citation sources not working with schema
* comment cleanup
* WIP Anythropic support for chat, chat and query w/context
* Add onboarding support for Anthropic
* cleanup
* fix Anthropic answer parsing
move embedding selector to general util
Limit is due to POST body max size. Sufficiently large requests will abort automatically
We should report that error back on the frontend during embedding
Update vectordb providers to return on failed
* Remove LangchainJS for chat support chaining
Implement runtime LLM selection
Implement AzureOpenAI Support for LLM + Emebedding
WIP on frontend
Update env to reflect the new fields
* Remove LangchainJS for chat support chaining
Implement runtime LLM selection
Implement AzureOpenAI Support for LLM + Emebedding
WIP on frontend
Update env to reflect the new fields
* Replace keys with LLM Selection in settings modal
Enforce checks for new ENVs depending on LLM selection
