start new:
tmux
start new with session name:
tmux new -s myname
import paramiko | |
k = paramiko.RSAKey.from_private_key_file("/Users/whatever/Downloads/mykey.pem") | |
c = paramiko.SSHClient() | |
c.set_missing_host_key_policy(paramiko.AutoAddPolicy()) | |
print "connecting" | |
c.connect( hostname = "www.acme.com", username = "ubuntu", pkey = k ) | |
print "connected" | |
commands = [ "/home/ubuntu/firstscript.sh", "/home/ubuntu/secondscript.sh" ] | |
for command in commands: | |
print "Executing {}".format( command ) |
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This is free and unencumbered software released into the public domain. | |
Anyone is free to copy, modify, publish, use, compile, sell, or | |
distribute this software, either in source code form or as a compiled | |
binary, for any purpose, commercial or non-commercial, and by any | |
means. | |
In jurisdictions that recognize copyright laws, the author or authors | |
of this software dedicate any and all copyright interest in the | |
software to the public domain. We make this dedication for the benefit |
Many developers are confused about when and how to use RAG after reading articles claiming "RAG is dead." Understanding what RAG actually means versus the narrow marketing definitions will help you make better architectural decisions for your AI applications.
Answer: The viral article claiming RAG is dead specifically argues against using naive vector database retrieval for autonomous coding agents, not RAG as a whole. This is a crucial distinction that many developers miss due to misleading marketing.
RAG simply means Retrieval-Augmented Generation - using retrieval to provide relevant context that improves your model's output. The core principle remains essential: your LLM needs the right context to generate accurate answers. The question isn't whether to use retrieval, but how to retrieve effectively.
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