added llm completion
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83202acadb
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@ -0,0 +1,48 @@
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return {
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{
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'milanglacier/minuet-ai.nvim',
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config = function()
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require('minuet').setup {
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virtualtext = {
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auto_trigger_ft = {},
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keymap = {
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-- accept whole completion
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accept = '<A-A>',
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-- accept one line
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accept_line = '<A-a>',
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-- accept n lines (prompts for number)
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-- e.g. "A-z 2 CR" will accept 2 lines
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accept_n_lines = '<A-z>',
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-- Cycle to prev completion item, or manually invoke completion
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prev = '<A-[>',
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-- Cycle to next completion item, or manually invoke completion
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next = '<A-]>',
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dismiss = '<A-e>',
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},
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},
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provider = 'openai_fim_compatible',
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n_completions = 1, -- recommend for local model for resource saving
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-- I recommend beginning with a small context window size and incrementally
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-- expanding it, depending on your local computing power. A context window
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-- of 512, serves as an good starting point to estimate your computing
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-- power. Once you have a reliable estimate of your local computing power,
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-- you should adjust the context window to a larger value.
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context_window = 512,
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provider_options = {
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openai_fim_compatible = {
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-- For Windows users, TERM may not be present in environment variables.
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-- Consider using APPDATA instead.
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api_key = 'TERM',
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name = 'Ollama',
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end_point = 'http://localhost:11434/v1/completions',
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model = 'qwen2.5-coder:7b',
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optional = {
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max_tokens = 56,
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top_p = 0.9,
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},
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},
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},
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}
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end,
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},
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}
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