Event JSON
{
"id": "3b3631b523734f763bb16477ae34eb2cf1baa9a1d434e6ef1846da4ff0c0c88f",
"pubkey": "efd4d4a38bcd0004d31031a17972a6a6a3b32fe6f3953958c47d6325f2b8d106",
"created_at": 1721223645,
"kind": 1,
"tags": [
[
"t",
"PromptQL"
],
[
"t",
"promptengineering"
],
[
"t",
"prompts"
],
[
"t",
"ai"
],
[
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"golang"
],
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],
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],
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],
[
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],
[
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],
[
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],
[
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],
[
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],
[
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],
[
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],
[
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],
[
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],
"content": "4 months ago I wrote another article on making bots by prompt engineering with PromptQL. I explained how expansion and execution of code embeddings brings full power to prompt templates. Here it is:\nhttps://medium.com/@jzx777/making-bots-with-promptql-code-embeddings-5b21efd52c51\nFor purpose of examples, I ran bot with the Openhermes Mistral 2.5B model and the llama.cpp server.\nOpenhermes model: https://huggingface.co/TheBloke/OpenHermes-2.5-Mistral-7B-GGUF\nllama.cpp server: https://github.com/ggerganov/llama.cpp/tree/master/examples/server\n#PromptQL #promptengineering #prompts #ai #golang #go #programming #opensource #library #programminglanguage #llm #LocalLLM #openhermes #llamacpp #cottagesoftware #craftprogramming #indietech",
"sig": "a2552461d0085c04b044d27dbe5a690bd10a22cfda04a28992306372e77bb6f9b258cb0e6cda264b1e29a7dbf2d719f5b8d96639c8f97af5ca0477cd9c721e18"
}