September 26: Support for Google AI and Cerebras models, and latest Groq models

New Features

• 💡 Graphlit now supports the Cerebras model service which offers the LLAMA_3_1_70B and LLAMA_3_1_8B models.
• 💡 Graphlit now supports the Google AI model service which offers the GEMINI_1_5_PRO and GEMINI_1_5_FLASH models.
• We have added support for the latest Groq Llama 3.2 preview models, including LLAMA_3_2_1B_PREVIEW, LLAMA_3_2_3B_PREVIEW, LLAMA_3_2_11B_TEXT_PREVIEW, and LLAMA_3_2_90B_TEXT_PREVIEW. We have also added support for the Llama 3.2 multimodal model LLAMA_3_2_11B_VISION_PREVIEW.

• We have added a new specification parameter to the promptConversation mutation. Now you can specify your initial specification for a new conversation, or update an existing conversation, without requiring additional API calls.

• ⚡ We have changed the retrieval behavior of the promptConversation mutation. Now, if no relevant content was found via vector-based semantic search (given the user prompt), we will fallback to any relevant content from the message in the conversation. If there was no content from the conversation to fallback to, we will fallback to the last ingested content in the project. This solves an issue where a first prompt like 'Summarize this' would find no relevant content. Now it will fallback to retrieve the last ingested content.
• ⚡ We have renamed the Groq model enum from LLAVA_1_5_7B to LLAVA_1_5_7B_PREVIEW.

Bugs Fixed

• GPLA-3083: Not sending custom instructions/guidance with extraction prompt

• GPLA-3146: Filtering Persons by email not working

• GPLA-3171: Not failing on deprecated OpenAI model

• GPLA-3158: Summarization not using revision strategy