* Implement use of native embedder (all-Mini-L6-v2)
stop showing prisma queries during dev
* Add native embedder as an available embedder selection
* wrap model loader in try/catch
* print progress on download
* add built-in LLM support (expiermental)
* Update to progress output for embedder
* move embedder selection options to component
* saftey checks for modelfile
* update ref
* Hide selection when on hosted subdomain
* update documentation
hide localLlama when on hosted
* saftey checks for storage of models
* update dockerfile to pre-build Llama.cpp bindings
* update lockfile
* add langchain doc comment
* remove extraneous --no-metal option
* Show data handling for private LLM
* persist model in memory for N+1 chats
* update import
update dev comment on token model size
* update primary README
* chore: more readme updates and remove screenshots - too much to maintain, just use the app!
* remove screeshot link
* allow use of any embedder for any llm/update data handling modal
* Apply embedder override and fallback to OpenAI and Azure models
---------
Co-authored-by: timothycarambat <rambat1010@gmail.com>
* feature: add LocalAI as llm provider
* update Onboarding/mgmt settings
Grab models from models endpoint for localai
merge with master
* update streaming for complete chunk streaming
update localAI LLM to be able to stream
* force schema on URL
---------
Co-authored-by: timothycarambat <rambat1010@gmail.com>
Co-authored-by: tlandenberger <tobiaslandenberger@gmail.com>
* Using OpenAI API locally
* Infinite prompt input and compression implementation (#332)
* 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
* disable import on hosted instances (#339)
* disable import on hosted instances
* Update UI on disabled import/export
---------
Co-authored-by: timothycarambat <rambat1010@gmail.com>
* Add support for gpt-4-turbo 128K model (#340)
resolves#336
Add support for gpt-4-turbo 128K model
* 315 show citations based on relevancy score (#316)
* settings for similarity score threshold and prisma schema updated
* prisma schema migration for adding similarityScore setting
* WIP
* Min score default change
* added similarityThreshold checking for all vectordb providers
* linting
---------
Co-authored-by: shatfield4 <seanhatfield5@gmail.com>
* rename localai to lmstudio
* forgot files that were renamed
* normalize model interface
* add model and context window limits
* update LMStudio tagline
* Fully working LMStudio integration
---------
Co-authored-by: Francisco Bischoff <984592+franzbischoff@users.noreply.github.com>
Co-authored-by: Timothy Carambat <rambat1010@gmail.com>
Co-authored-by: Sean Hatfield <seanhatfield5@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
