* wip: initial cache control implementation, add typing for transactions handling
* feat: first pass of Anthropic Prompt Caching
* feat: standardize stream usage as pass in when calculating token counts
* feat: Add getCacheMultiplier function to calculate cache multiplier for different valueKeys and cacheTypes
* chore: imports order
* refactor: token usage recording in AnthropicClient, no need to "correct" as we have the correct amount
* feat: more accurate token counting using stream usage data
* feat: Improve token counting accuracy with stream usage data
* refactor: ensure more accurate than not token estimations if custom instructions or files are not being resent with every request
* refactor: cleanup updateUserMessageTokenCount to allow transactions to be as accurate as possible even if we shouldn't update user message token counts
* ci: fix tests
* WIP: gemini-1.5 support
* feat: extended vertex ai support
* fix: handle possibly undefined modelName
* fix: gpt-4-turbo-preview invalid vision model
* feat: specify `fileConfig.imageOutputType` and make PNG default image conversion type
* feat: better truncation for errors including base64 strings
* fix: gemini inlineData formatting
* feat: RAG augmented prompt for gemini-1.5
* feat: gemini-1.5 rates and token window
* chore: adjust tokens, update docs, update vision Models
* chore: add back `ChatGoogleVertexAI` for chat models via vertex ai
* refactor: ask/edit controllers to not use `unfinished` field for google endpoint
* chore: remove comment
* chore(ci): fix AppService test
* chore: remove comment
* refactor(GoogleSearch): use `GOOGLE_SEARCH_API_KEY` instead, issue warning for old variable
* chore: bump data-provider to 0.5.4
* chore: update docs
* fix: condition for gemini-1.5 using generative ai lib
* chore: update docs
* ci: add additional AppService test for `imageOutputType`
* refactor: optimize new config value `imageOutputType`
* chore: bump CONFIG_VERSION
* fix(assistants): avatar upload
* refactor(assistants/chat): use promises to speed up initialization, initialize shared variables, include `attachedFileIds` to streamRunManager
* chore: additional typedefs
* fix(OpenAIClient): handle edge case where attachments promise is resolved
* feat: createVisionPrompt
* feat: Vision Support for Assistants
* refactor: re-purpose `resendImages` as `resendFiles`
* refactor: re-purpose `resendImages` as `resendFiles`
* feat: upload general files
* feat: embed file during upload
* feat: delete file embeddings on file deletion
* chore(fileConfig): add epub+zip type
* feat(encodeAndFormat): handle non-image files
* feat(createContextHandlers): build context prompt from file attachments and successful RAG
* fix: prevent non-temp files as well as embedded files to be deleted on new conversation
* fix: remove temp_file_id on usage, prevent non-temp files as well as embedded files to be deleted on new conversation
* fix: prevent non-temp files as well as embedded files to be deleted on new conversation
* feat(OpenAI/Anthropic/Google): basic RAG support
* fix: delete `resendFiles` only when true (Default)
* refactor(RAG): update endpoints and pass JWT
* fix(resendFiles): default values
* fix(context/processFile): query unique ids only
* feat: rag-api.yaml
* feat: file upload improved ux for longer uploads
* chore: await embed call and catch embedding errors
* refactor: store augmentedPrompt in Client
* refactor(processFileUpload): throw error if not assistant file upload
* fix(useFileHandling): handle markdown empty mimetype issue
* chore: necessary compose file changes
* refactor: pass model in message edit payload, use encoder in standalone util function
* feat: add summaryBuffer helper
* refactor(api/messages): use new countTokens helper and add auth middleware at top
* wip: ConversationSummaryBufferMemory
* refactor: move pre-generation helpers to prompts dir
* chore: remove console log
* chore: remove test as payload will no longer carry tokenCount
* chore: update getMessagesWithinTokenLimit JSDoc
* refactor: optimize getMessagesForConversation and also break on summary, feat(ci): getMessagesForConversation tests
* refactor(getMessagesForConvo): count '00000000-0000-0000-0000-000000000000' as root message
* chore: add newer model to token map
* fix: condition was point to prop of array instead of message prop
* refactor(BaseClient): use object for refineMessages param, rename 'summary' to 'summaryMessage', add previous_summary
refactor(getMessagesWithinTokenLimit): replace text and tokenCount if should summarize, summary, and summaryTokenCount are present
fix/refactor(handleContextStrategy): use the right comparison length for context diff, and replace payload first message when a summary is present
* chore: log previous_summary if debugging
* refactor(formatMessage): assume if role is defined that it's a valid value
* refactor(getMessagesWithinTokenLimit): remove summary logic
refactor(handleContextStrategy): add usePrevSummary logic in case only summary was pruned
refactor(loadHistory): initial message query will return all ordered messages but keep track of the latest summary
refactor(getMessagesForConversation): use object for single param, edit jsdoc, edit all files using the method
refactor(ChatGPTClient): order messages before buildPrompt is called, TODO: add convoSumBuffMemory logic
* fix: undefined handling and summarizing only when shouldRefineContext is true
* chore(BaseClient): fix test results omitting system role for summaries and test edge case
* chore: export summaryBuffer from index file
* refactor(OpenAIClient/BaseClient): move refineMessages to subclass, implement LLM initialization for summaryBuffer
* feat: add OPENAI_SUMMARIZE to enable summarizing, refactor: rename client prop 'shouldRefineContext' to 'shouldSummarize', change contextStrategy value to 'summarize' from 'refine'
* refactor: rename refineMessages method to summarizeMessages for clarity
* chore: clarify summary future intent in .env.example
* refactor(initializeLLM): handle case for either 'model' or 'modelName' being passed
* feat(gptPlugins): enable summarization for plugins
* refactor(gptPlugins): utilize new initializeLLM method and formatting methods for messages, use payload array for currentMessages and assign pastMessages sooner
* refactor(agents): use ConversationSummaryBufferMemory for both agent types
* refactor(formatMessage): optimize original method for langchain, add helper function for langchain messages, add JSDocs and tests
* refactor(summaryBuffer): add helper to createSummaryBufferMemory, and use new formatting helpers
* fix: forgot to spread formatMessages also took opportunity to pluralize filename
* refactor: pass memory to tools, namely openapi specs. not used and may never be used by new method but added for testing
* ci(formatMessages): add more exhaustive checks for langchain messages
* feat: add debug env var for OpenAI
* chore: delete unnecessary comments
* chore: add extra note about summary feature
* fix: remove tokenCount from payload instructions
* fix: test fail
* fix: only pass instructions to payload when defined or not empty object
* refactor: fromPromptMessages is deprecated, use renamed method fromMessages
* refactor: use 'includes' instead of 'startsWith' for extended OpenRouter compatibility
* fix(PluginsClient.buildPromptBody): handle undefined message strings
* chore: log langchain titling error
* feat: getModelMaxTokens helper
* feat: tokenSplit helper
* feat: summary prompts updated
* fix: optimize _CUT_OFF_SUMMARIZER prompt
* refactor(summaryBuffer): use custom summary prompt, allow prompt to be passed, pass humanPrefix and aiPrefix to memory, along with any future variables, rename messagesToRefine to context
* fix(summaryBuffer): handle edge case where messagesToRefine exceeds summary context,
refactor(BaseClient): allow custom maxContextTokens to be passed to getMessagesWithinTokenLimit, add defined check before unshifting summaryMessage, update shouldSummarize based on this
refactor(OpenAIClient): use getModelMaxTokens, use cut-off message method for summary if no messages were left after pruning
* fix(handleContextStrategy): handle case where incoming prompt is bigger than model context
* chore: rename refinedContent to splitText
* chore: remove unnecessary debug log
* feat: add option to disable titling as well as decide what model to use for OpenAI titling
refactor: truncate conversation text so it caps around 200 tokens for titling requests, optimize some of the title prompts
* feat: disable bing titling with TITLE_CONVO as well
* docs: make_your_own.md formatting fix for mkdocs
* feat: add express-mongo-sanitize
feat: add login/registration rate limiting
* chore: remove unnecessary console log
* wip: remove token handling from localStorage to encrypted DB solution
* refactor: minor change to UserService
* fix mongo query and add keys route to server
* fix backend controllers and simplify schema/crud
* refactor: rename token to key to separate from access/refresh tokens, setTokenDialog -> setKeyDialog
* refactor(schemas): TEndpointOption token -> key
* refactor(api): use new encrypted key retrieval system
* fix(SetKeyDialog): fix key prop error
* fix(abortMiddleware): pass random UUID if messageId is not generated yet for proper error display on frontend
* fix(getUserKey): wrong prop passed in arg, adds error handling
* fix: prevent message without conversationId from saving to DB, prevents branching on the frontend to a new top-level branch
* refactor: change wording of multiple display messages
* refactor(checkExpiry -> checkUserKeyExpiry): move to UserService file
* fix: type imports from common
* refactor(SubmitButton): convert to TS
* refactor(key.ts): change localStorage map key name
* refactor: add new custom tailwind classes to better match openAI colors
* chore: remove unnecessary warning and catch ScreenShot error
* refactor: move userKey frontend logic to hooks and remove use of localStorage and instead query the DB
* refactor: invalidate correct query key, memoize userKey hook, conditionally render SetKeyDialog to avoid unnecessary calls, refactor SubmitButton props and useEffect for showing 'provide key first'
* fix(SetKeyDialog): use enum-like object for expiry values
feat(Dropdown): add optionsClassName to dynamically change dropdown options container classes
* fix: handle edge case where user had provided a key but the server changes to env variable for keys
* refactor(OpenAI/titleConvo): move titling to client to retain authorized credentials in message lifecycle for titling
* fix(azure): handle user_provided keys correctly for azure
* feat: send user Id to OpenAI to differentiate users in completion requests
* refactor(OpenAI/titleConvo): adding tokens helps minimize LLM from using the language in title response
* feat: add delete endpoint for keys
* chore: remove throttling of title
* feat: add 'Data controls' to Settings, add 'Revoke' keys feature in Key Dialog and Data controls
* refactor: reorganize PluginsClient files in langchain format
* feat: use langchain for titling convos
* chore: cleanup titling convo, with fallback to original method, escape braces, use only snippet for language detection
* refactor: move helper functions to appropriate langchain folders for reusability
* fix: userProvidesKey handling for gptPlugins
* fix: frontend handling of plugins key
* chore: cleanup logging and ts-ignore SSE
* fix: forwardRef misuse in DangerButton
* fix(GoogleConfig/FileUpload): localize errors and simplify validation with zod
* fix: cleanup google logging and fix user provided key handling
* chore: remove titling from google
* chore: removing logging from browser endpoint
* wip: fix menu flicker
* feat: useLocalStorage hook
* feat: add Tooltip for UI
* refactor(EndpointMenu): utilize Tooltip and useLocalStorage, remove old 'New Chat' slide-over
* fix(e2e): use testId for endpoint menu trigger
* chore: final touches to EndpointMenu before future refactor to declutter component
* refactor(localization): change select endpoint to open menu and add translations
* chore: add final prop to error message response
* ci: minor edits to facilitate testing
* ci: new e2e test which tests for new key setting/revoking features
