OpeanAI MemGPT: Dealing with NonAnswers and estimating cost
Accessing OpenAI as an academic guidance counselor through MemGPT/Streamit
Here are the statistics:
Total words exchanged: 1,283 (8,211 characters)
Total words sent to chatbot: 183 (1,070 characters)
Total words generated by chatbot: 1,086 (7,031 characters)
78 sentences, 11 pairs of Question and Answer
Cost:
1.84 $
Note that I was using GPT4.
Furthermore, the outcome at the conclusion of the experiment didn’t quite live up to expectations. When I inquired with the chatbot about recommendations for reputable universities based on our earlier discussion regarding suitable choices, the response I received was somewhat diplomatically vague.
Maybe Academic counselor was not a good role for ChatGPT or maybe my questions weren’t crafty enough to extract answers from it.
Overall review: Not satisfactory.
That is all for now. Cheers.
Open Source LLM:
**Textfiles on MemGPT** (Keep your eyes on this)
Paradigm Shift in Retrieval Augmented Generation: MemGPT [Not really open source as the article mentions use of OpenAI] — This is the old MemGPT, restricted to text only
MemGPT: Assimilating information from multiple PDFs
MemGPT As A Service (MAAS): Building a chat interface around MemGPT
Multimodal Image Chat
Super Quick Visual Conversations: Unleashing LLaVA 1.5
PDF Related
Advanced Retrieval with LlamaPacks: Elevating RAG in Fewer Lines of Code!
Super Quick: Retrieval Augmented Generation Using Ollama
Super Quick: Retrieval Augmented Generation (RAG) with Llama 2.0 on Company Information using CPU
Evaluating the Suitability of CPU-based LLMs for Online Usage [Compare the time to response of three different LLMs for RAG activities]
Database Related
Super Quick: LLAMA2 on CPU Machine to Generate SQL Queries from Schema
Close Source LLM (OpenAI):
PDF Related
Chatbot Document Retrieval: Asking Non-Trivial Questions
Database Related
Super Quick: Connecting ChatGPT to a PostgreSQL database
General Info:
OpenAI Dev Day: 6 Announcements and why us RAGgers need to be worried
Super Quick: RAG Comparison between GPT4 and Open-Source
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