# October 30: Optimized conversation responses; added observable aliases; bug fixes ### New Features * :bulb: Graphlit now supports 'aliases' of observable names, as the `alternateNames` property. When an observed entity, such as Organization, is enriched, we store the original name and the enriched name as an alias. For example, "OpenAI" may be enriched to "OpenAI, Inc.", and we store "OpenAI" as an alias, and update the name to "OpenAI, Inc.". * :bulb: Added `workflows` filter to ContentCriteriaInput type, for filtering content by workflow(s) when creating conversation. * Optimized formatting of content sources into prompt context, for more accurate conversation responses. * Optimized formatting of extracted text from Slack messages, for better knowledge retrieval. * Updated text tokenizer for more accurate token counting. * Upgraded Azure Text Analytics to latest preview API version. * Authors found in RSS feeds are now stored as observations of Person entities. * Added rate limiting for Reddit feeds. * Added rate limiting for Wikipedia enrichment. * Added support for reading Reddit post comments when reading Reddit feed. * :zap: `EmbedFacets` has been renamed to `EnableFacets` in the conversation strategy. * :zap: Removed extra `content` level in IngestionWorkflowStage type. Now, the `if` property is of type IngestionContentFilter. ### Bugs Fixed * GPLA-1556: Better handling of very long user prompts. * GPLA-1627: Optimized token budget for more accurate prompt completion. * GPLA-1585: More accurate entity matching in Wikipedia entity enrichment. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://changelog.graphlit.dev/october-2023/october-30-optimized-conversation-responses-added-observable-aliases-bug-fixes.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.