mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-11-01 15:40:21 +01:00
125d03a503
Co-authored-by: Michael Coppola <info@michaeljcoppola.com>
136 lines
5.1 KiB
VimL
136 lines
5.1 KiB
VimL
" Requires an already running llama.cpp server
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" To install either copy or symlink to ~/.vim/autoload/llama.vim
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" Then start with either :call llama#doLlamaGen(),
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" or add a keybind to your vimrc such as
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" nnoremap Z :call llama#doLlamaGen()<CR>
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" Similarly, you could add an insert mode keybind with
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" inoremap <C-B> <Cmd>call llama#doLlamaGen()<CR>
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"
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" g:llama_api_url, g:llama_api_key and g:llama_overrides can be configured in your .vimrc
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" let g:llama_api_url = "192.168.1.10:8080"
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" llama_overrides can also be set through buffer/window scopes. For instance
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" autocmd filetype python let b:llama_overrides = {"temp": 0.2}
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" Could be added to your .vimrc to automatically set a lower temperature when
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" editing a python script
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" Additionally, an override dict can be stored at the top of a file
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" !*{"stop": ["User:"]}
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" Could be added to the start of your chatlog.txt to set the stopping token
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" These parameter dicts are merged together from lowest to highest priority:
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" server default -> g:llama_overrides -> w:llama_overrides ->
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" b:llama_overrides -> in file (!*) overrides
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"
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" Sublists (like logit_bias and stop) are overridden, not merged
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" Example override:
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" !*{"logit_bias": [[13, -5], [2, false]], "temperature": 1, "top_k": 5, "top_p": 0.5, "n_predict": 256, "repeat_last_n": 256, "repeat_penalty": 1.17647}
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if !exists("g:llama_api_url")
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let g:llama_api_url= "127.0.0.1:8080"
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endif
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if !exists("g:llama_overrides")
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let g:llama_overrides = {}
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endif
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const s:querydata = {"n_predict": 256, "stop": [ "\n" ], "stream": v:true }
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const s:curlcommand = ['curl','--data-raw', "{\"prompt\":\"### System:\"}", '--silent', '--no-buffer', '--request', 'POST', '--url', g:llama_api_url .. '/completion', '--header', "Content-Type: application/json"]
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let s:linedict = {}
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func s:callbackHandler(bufn, channel, msg)
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if len(a:msg) < 3
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return
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elseif a:msg[0] == "d"
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let l:msg = a:msg[6:-1]
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else
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let l:msg = a:msg
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endif
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let l:decoded_msg = json_decode(l:msg)
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let l:newtext = split(l:decoded_msg['content'], "\n", 1)
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if len(l:newtext) > 0
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call setbufline(a:bufn, s:linedict[a:bufn], getbufline(a:bufn, s:linedict[a:bufn])[0] .. newtext[0])
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else
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echo "nothing genned"
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endif
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if len(newtext) > 1
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let l:failed = appendbufline(a:bufn, s:linedict[a:bufn], newtext[1:-1])
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let s:linedict[a:bufn] = s:linedict[a:bufn] + len(newtext)-1
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endif
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if has_key(l:decoded_msg, "stop") && l:decoded_msg.stop
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echo "Finished generation"
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endif
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endfunction
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func llama#doLlamaGen()
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if exists("b:job")
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if job_status(b:job) == "run"
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call job_stop(b:job)
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return
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endif
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endif
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let l:cbuffer = bufnr("%")
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let s:linedict[l:cbuffer] = line('$')
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let l:buflines = getbufline(l:cbuffer, 1, 1000)
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let l:querydata = copy(s:querydata)
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call extend(l:querydata, g:llama_overrides)
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if exists("w:llama_overrides")
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call extend(l:querydata, w:llama_overrides)
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endif
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if exists("b:llama_overrides")
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call extend(l:querydata, b:llama_overrides)
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endif
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if l:buflines[0][0:1] == '!*'
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let l:userdata = json_decode(l:buflines[0][2:-1])
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call extend(l:querydata, l:userdata)
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let l:buflines = l:buflines[1:-1]
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endif
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let l:querydata.prompt = join(l:buflines, "\n")
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let l:curlcommand = copy(s:curlcommand)
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if exists("g:llama_api_key")
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call extend(l:curlcommand, ['--header', 'Authorization: Bearer ' .. g:llama_api_key])
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endif
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let l:curlcommand[2] = json_encode(l:querydata)
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let b:job = job_start(l:curlcommand, {"callback": function("s:callbackHandler", [l:cbuffer])})
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endfunction
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" Echos the tokkenization of the provided string , or cursor to end of word
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" Onus is placed on the user to include the preceding space
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func llama#tokenizeWord(...)
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if (a:0 > 0)
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let l:input = a:1
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else
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exe "normal \"*ye"
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let l:input = @*
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endif
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let l:querydata = {"content": l:input}
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let l:curlcommand = copy(s:curlcommand)
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let l:curlcommand[2] = json_encode(l:querydata)
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let l:curlcommand[8] = g:llama_api_url .. "/tokenize"
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let s:token_job = job_start(l:curlcommand, {"callback": function("s:tokenizeWordCallback", [l:input])})
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endfunction
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func s:tokenizeWordCallback(plaintext, channel, msg)
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echo '"' .. a:plaintext ..'" - ' .. string(json_decode(a:msg).tokens)
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endfunction
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" Echos the token count of the entire buffer (or provided string)
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" Example usage :echo llama#tokenCount()
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func llama#tokenCount(...)
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if (a:0 > 0)
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let l:buflines = a:1
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else
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let l:buflines = getline(1,1000)
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if l:buflines[0][0:1] == '!*'
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let l:buflines = l:buflines[1:-1]
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endif
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let l:buflines = join(l:buflines, "\n")
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endif
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let l:querydata = {"content": l:buflines}
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let l:curlcommand = copy(s:curlcommand)
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let l:curlcommand[2] = json_encode(l:querydata)
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let l:curlcommand[8] = g:llama_api_url .. "/tokenize"
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let s:token_job = job_start(l:curlcommand, {"callback": "s:tokenCountCallback"})
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endfunction
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func s:tokenCountCallback(channel, msg)
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let resp = json_decode(a:msg)
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echo len(resp.tokens)
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endfunction
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