./ai.py chat <msg>
Send <msg> directly to GPT and print its response.
./ai.py embed <filenames...>
Chunk and index sections in filenames delimited by '\\n\\n'. save to embeddings.jsonl
./ai.py query <question>
Find top documents that match <question> and send them to GPT along with <question>, and print its response.
- mention
VisiData
in its presence, or start a message with `!', and it will find 5 relevant embedded documents and send them via the OpenAI API to GPT, and reply with its response.