@ -128,3 +128,14 @@ Must be a list of dictionaries with key value from "system", "question", "answer
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# More Resources
- [ChatGPT+ Vector database + prompt-as-code - The CVP Stack - Zilliz blog](https://zilliz.com/blog/ChatGPT-VectorDB-Prompt-as-code): Extend the capability of ChatGPT with a Vector database and prompts-as-code
- [OpenAI's ChatGPT - Zilliz blog](https://zilliz.com/learn/ChatGPT-Vector-Database-Prompt-as-code): A guide to the new AI Stack - ChatGPT, your Vector Database, and Prompt as code
- [OpenAI Whisper: Transforming Speech-to-Text with Advanced AI - Zilliz blog](https://zilliz.com/learn/open-ai-whisper-transforming-speech-to-text-with-advanced-ai): Understand Open AI Whisper and follow this step-by-step article to implement it in projects that can significantly enhance the efficiency of speech-to-text tasks.
- [OpenAI RAG vs. Your Customized RAG: Which One Is Better? - Zilliz blog](https://zilliz.com/blog/openai-rag-vs-customized-rag-which-one-is-better): Comparing the performance of the OpenAI Assistants-enabled RAG system and the Milvus vector database-powered customized RAG system.
- [Prompting in LangChain - Zilliz blog](https://zilliz.com/blog/prompting-langchain): Prompting is one of today's most popular and important tasks in AI app building. Learn how to use LangChain for more complex prompts.
- [Improving ChatGPTâs Ability to Understand Ambiguous Prompts - Zilliz blog](https://zilliz.com/blog/improving-chatgpts-ability-to-understand-ambiguous-prompts): Prompt engineering technique helps large language models (LLMs) handle pronouns and other complex coreferences in retrieval augmented generation (RAG) systems.
- [How to Integrate OpenAI Embedding API with Zilliz Cloud - Zilliz blog](https://zilliz.com/blog/how-to-integrate-openai-embedding-api-with-zilliz-cloud): We are proud to announce that we'll be providing embedding model integrations - a way to connect your Milvus and/or Zilliz Cloud database to open source or paid embedding models.
