" LLM-based text completion using llama.cpp
"
" requires:
"
" - neovim or vim
" - curl
" - llama.cpp server instance
" - FIM-compatible model
"
" sample config:
"
" - Tab - accept the current suggestion
" - Shift+Tab - accept just the first line of the suggestion
" - Ctrl+F - toggle FIM completion manually
"
" make symlink or copy this file to ~/.config/nvim/autoload/llama.vim
"
" start the llama.cpp server with a FIM-compatible model. for example:
"
" $ llama-server -m {model.gguf} --port 8012 -ngl 99 -fa --ubatch-size 512 --batch-size 1024 --cache-reuse 256
"
" --batch-size [512, model max context]
"
" adjust the batch size to control how much of the provided local context will be used during the inference
" lower values will use smaller part of the context around the cursor, which will result in faster processing
"
" --ubatch-size [64, 2048]
"
" chunks the batch into smaller chunks for faster processing
" depends on the specific hardware. use llama-bench to profile and determine the best size
"
" --cache-reuse (ge:llama_config.n_predict, 1024]
"
" this should be either 0 (disabled) or strictly larger than g:llama_config.n_predict
" using non-zero value enables context reuse on the server side which dramatically improves the performance at
" large contexts. a value of 256 should be good for all cases
"
" run this once to initialise llama.vim:
"
" :call llama#init()
"
" more info: https://github.com/ggml-org/llama.cpp/pull/9787
"
" colors (adjust to your liking)
highlight llama_hl_hint guifg=#ff772f ctermfg=202
highlight llama_hl_info guifg=#77ff2f ctermfg=119
" general parameters:
"
" endpoint: llama.cpp server endpoint
" n_prefix: number of lines before the cursor location to include in the local prefix
" n_suffix: number of lines after the cursor location to include in the local suffix
" n_predict: max number of tokens to predict
" t_max_prompt_ms: max allotted time for the prompt processing (TODO: not yet supported)
" t_max_predict_ms: max allotted time for the prediction
" show_info: show extra info about the inference (0 - disabled, 1 - statusline, 2 - inline)
" auto_fim: trigger FIM completion automatically on cursor movement
" max_line_suffix: do not auto-trigger FIM completion if there are more than this number of characters to the right of the cursor
"
" ring buffer of chunks, accumulated with time upon:
"
" - completion request
" - yank
" - entering a buffer
" - leaving a buffer
" - writing a file
"
" parameters for the ring-buffer with extra context:
"
" ring_n_chunks: max number of chunks to pass as extra context to the server (0 to disable)
" ring_chunk_size: max size of the chunks (in number of lines)
" note: adjust these numbers so that you don't overrun your context
" at ring_n_chunks = 64 and ring_chunk_size = 64 you need ~32k context
" ring_scope: the range around the cursor position (in number of lines) for gathering chunks after FIM
" ring_update_ms: how often to process queued chunks in normal mode
"
let s:default_config = {
\ 'endpoint': 'http://127.0.0.1:8012/infill',
\ 'n_prefix': 256,
\ 'n_suffix': 64,
\ 'n_predict': 128,
\ 't_max_prompt_ms': 500,
\ 't_max_predict_ms': 3000,
\ 'show_info': 2,
\ 'auto_fim': v:true,
\ 'max_line_suffix': 8,
\ 'ring_n_chunks': 64,
\ 'ring_chunk_size': 64,
\ 'ring_scope': 1024,
\ 'ring_update_ms': 1000,
\ }
let g:llama_config = get(g:, 'llama_config', s:default_config)
function! s:get_indent(str)
let l:count = 0
for i in range(len(a:str))
if a:str[i] == "\t"
let l:count += &tabstop - 1
else
break
endif
endfor
return l:count
endfunction
function! s:rand(i0, i1) abort
return a:i0 + rand() % (a:i1 - a:i0 + 1)
endfunction
function! llama#init()
if !executable('curl')
echohl WarningMsg
echo 'llama.vim requires the "curl" command to be available'
echohl None
return
endif
let s:pos_x = 0 " cursor position upon start of completion
let s:pos_y = 0
let s:line_cur = ''
let s:line_cur_prefix = ''
let s:line_cur_suffix = ''
let s:ring_chunks = [] " current set of chunks used as extra context
let s:ring_queued = [] " chunks that are queued to be sent for processing
let s:ring_n_evict = 0
let s:hint_shown = v:false
let s:pos_y_pick = -9999 " last y where we picked a chunk
let s:pos_dx = 0
let s:content = []
let s:can_accept = v:false
let s:timer_fim = -1
let s:t_fim_start = reltime() " used to measure total FIM time
let s:t_last_move = reltime() " last time the cursor moved
let s:current_job = v:null
let s:ghost_text_nvim = exists('*nvim_buf_get_mark')
let s:ghost_text_vim = has('textprop')
if s:ghost_text_vim
let s:hlgroup_hint = 'llama_hl_hint'
let s:hlgroup_info = 'llama_hl_info'
if empty(prop_type_get(s:hlgroup_hint))
call prop_type_add(s:hlgroup_hint, {'highlight': s:hlgroup_hint})
endif
if empty(prop_type_get(s:hlgroup_info))
call prop_type_add(s:hlgroup_info, {'highlight': s:hlgroup_info})
endif
endif
augroup llama
autocmd!
autocmd InsertEnter * inoremap <expr> <silent> <C-F> llama#fim_inline(v:false)
autocmd InsertLeavePre * call llama#fim_cancel()
autocmd CursorMoved * call s:on_move()
autocmd CursorMovedI * call s:on_move()
autocmd CompleteChanged * call llama#fim_cancel()
if g:llama_config.auto_fim
autocmd CursorMovedI * call llama#fim(v:true)
endif
" gather chunks upon yanking
autocmd TextYankPost * if v:event.operator ==# 'y' | call s:pick_chunk(v:event.regcontents, v:false, v:true) | endif
" gather chunks upon entering/leaving a buffer
autocmd BufEnter * call timer_start(100, {-> s:pick_chunk(getline(max([1, line('.') - g:llama_config.ring_chunk_size/2]), min([line('.') + g:llama_config.ring_chunk_size/2, line('$')])), v:true, v:true)})
autocmd BufLeave * call s:pick_chunk(getline(max([1, line('.') - g:llama_config.ring_chunk_size/2]), min([line('.') + g:llama_config.ring_chunk_size/2, line('$')])), v:true, v:true)
" gather chunk upon saving the file
autocmd BufWritePost * call s:pick_chunk(getline(max([1, line('.') - g:llama_config.ring_chunk_size/2]), min([line('.') + g:llama_config.ring_chunk_size/2, line('$')])), v:true, v:true)
augroup END
silent! call llama#fim_cancel()
" init background update of the ring buffer
if g:llama_config.ring_n_chunks > 0
call s:ring_update()
endif
endfunction
" compute how similar two chunks of text are
" 0 - no similarity, 1 - high similarity
" TODO: figure out something better
function! s:chunk_sim(c0, c1)
let l:lines0 = len(a:c0)
let l:lines1 = len(a:c1)
let l:common = 0
for l:line0 in a:c0
for l:line1 in a:c1
if l:line0 == l:line1
let l:common += 1
break
endif
endfor
endfor
return 2.0 * l:common / (l:lines0 + l:lines1)
endfunction
" pick a random chunk of size g:llama_config.ring_chunk_size from the provided text and queue it for processing
"
" no_mod - do not pick chunks from buffers with pending changes
" do_evict - evict chunks that are very similar to the new one
"
function! s:pick_chunk(text, no_mod, do_evict)
" do not pick chunks from buffers with pending changes or buffers that are not files
if a:no_mod && (getbufvar(bufnr('%'), '&modified') || !buflisted(bufnr('%')) || !filereadable(expand('%')))
return
endif
" if the extra context option is disabled - do nothing
if g:llama_config.ring_n_chunks <= 0
return
endif
" don't pick very small chunks
if len(a:text) < 3
return
endif
if len(a:text) + 1 < g:llama_config.ring_chunk_size
let l:chunk = a:text
else
let l:l0 = s:rand(0, max([0, len(a:text) - g:llama_config.ring_chunk_size/2]))
let l:l1 = min([l:l0 + g:llama_config.ring_chunk_size/2, len(a:text)])
let l:chunk = a:text[l:l0:l:l1]
endif
let l:chunk_str = join(l:chunk, "\n") . "\n"
" check if this chunk is already added
let l:exist = v:false
for i in range(len(s:ring_chunks))
if s:ring_chunks[i].data == l:chunk
let l:exist = v:true
break
endif
endfor
for i in range(len(s:ring_queued))
if s:ring_queued[i].data == l:chunk
let l:exist = v:true
break
endif
endfor
if l:exist
return
endif
" evict queued chunks that are very similar to the new one
for i in range(len(s:ring_queued) - 1, 0, -1)
if s:chunk_sim(s:ring_queued[i].data, l:chunk) > 0.9
if a:do_evict
call remove(s:ring_queued, i)
let s:ring_n_evict += 1
else
return
endif
endif
endfor
" also from s:ring_chunks
for i in range(len(s:ring_chunks) - 1, 0, -1)
if s:chunk_sim(s:ring_chunks[i].data, l:chunk) > 0.9
if a:do_evict
call remove(s:ring_chunks, i)
let s:ring_n_evict += 1
else
return
endif
endif
endfor
" TODO: become parameter ?
if len(s:ring_queued) == 16
call remove(s:ring_queued, 0)
endif
call add(s:ring_queued, {'data': l:chunk, 'str': l:chunk_str, 'time': reltime(), 'filename': expand('%')})
"let &statusline = 'extra context: ' . len(s:ring_chunks) . ' / ' . len(s:ring_queued)
endfunction
" picks a queued chunk, sends it for processing and adds it to s:ring_chunks
" called every g:llama_config.ring_update_ms
function! s:ring_update()
call timer_start(g:llama_config.ring_update_ms, {-> s:ring_update()})
" update only if in normal mode or if the cursor hasn't moved for a while
if mode() !=# 'n' && reltimefloat(reltime(s:t_last_move)) < 3.0
return
endif
if len(s:ring_queued) == 0
return
endif
" move the first queued chunk to the ring buffer
if len(s:ring_chunks) == g:llama_config.ring_n_chunks
call remove(s:ring_chunks, 0)
endif
call add(s:ring_chunks, remove(s:ring_queued, 0))
"let &statusline = 'updated context: ' . len(s:ring_chunks) . ' / ' . len(s:ring_queued)
" send asynchronous job with the new extra context so that it is ready for the next FIM
let l:extra_context = []
for l:chunk in s:ring_chunks
call add(l:extra_context, {
\ 'text': l:chunk.str,
\ 'time': l:chunk.time,
\ 'filename': l:chunk.filename
\ })
endfor
" no samplers needed here
let l:request = json_encode({
\ 'input_prefix': "",
\ 'input_suffix': "",
\ 'input_extra': l:extra_context,
\ 'prompt': "",
\ 'n_predict': 1,
\ 'temperature': 0.0,
\ 'stream': v:false,
\ 'samplers': ["temperature"],
\ 'cache_prompt': v:true,
\ 't_max_prompt_ms': 1,
\ 't_max_predict_ms': 1
\ })
let l:curl_command = [
\ "curl",
\ "--silent",
\ "--no-buffer",
\ "--request", "POST",
\ "--url", g:llama_config.endpoint,
\ "--header", "Content-Type: application/json",
\ "--data", l:request
\ ]
" no callbacks because we don't need to process the response
if s:ghost_text_nvim
call jobstart(l:curl_command, {})
elseif s:ghost_text_vim
call job_start(l:curl_command, {})
endif
endfunction
" necessary for 'inoremap <expr>'
function! llama#fim_inline(is_auto) abort
call llama#fim(a:is_auto)
return ''
endfunction
" the main FIM call
" takes local context around the cursor and sends it together with the extra context to the server for completion
function! llama#fim(is_auto) abort
" we already have a suggestion for the current cursor position
if s:hint_shown && !a:is_auto
call llama#fim_cancel()
return
endif
call llama#fim_cancel()
" avoid sending repeated requests too fast
if reltimefloat(reltime(s:t_fim_start)) < 0.6
if s:timer_fim != -1
call timer_stop(s:timer_fim)
let s:timer_fim = -1
endif
let s:t_fim_start = reltime()
let s:timer_fim = timer_start(600, {-> llama#fim(v:true)})
return
endif
let s:t_fim_start = reltime()
let s:content = []
let s:can_accept = v:false
let s:pos_x = col('.') - 1
let s:pos_y = line('.')
let l:max_y = line('$')
let l:lines_prefix = getline(max([1, s:pos_y - g:llama_config.n_prefix]), s:pos_y - 1)
let l:lines_suffix = getline(s:pos_y + 1, min([l:max_y, s:pos_y + g:llama_config.n_suffix]))
let s:line_cur = getline('.')
let s:line_cur_prefix = strpart(s:line_cur, 0, s:pos_x)
let s:line_cur_suffix = strpart(s:line_cur, s:pos_x)
if a:is_auto && len(s:line_cur_suffix) > g:llama_config.max_line_suffix
return
endif
let l:prefix = ""
\ . join(l:lines_prefix, "\n")
\ . "\n"
let l:prompt = ""
\ . s:line_cur_prefix
let l:suffix = ""
\ . s:line_cur_suffix
\ . "\n"
\ . join(l:lines_suffix, "\n")
\ . "\n"
" prepare the extra context data
let l:extra_context = []
for l:chunk in s:ring_chunks
call add(l:extra_context, {
\ 'text': l:chunk.str,
\ 'time': l:chunk.time,
\ 'filename': l:chunk.filename
\ })
endfor
" the indentation of the current line
let l:indent = strlen(matchstr(s:line_cur_prefix, '^\s*'))
let l:request = json_encode({
\ 'input_prefix': l:prefix,
\ 'input_suffix': l:suffix,
\ 'input_extra': l:extra_context,
\ 'prompt': l:prompt,
\ 'n_predict': g:llama_config.n_predict,
\ 'n_indent': l:indent,
\ 'top_k': 40,
\ 'top_p': 0.99,
\ 'stream': v:false,
\ 'samplers': ["top_k", "top_p", "infill"],
\ 'cache_prompt': v:true,
\ 't_max_prompt_ms': g:llama_config.t_max_prompt_ms,
\ 't_max_predict_ms': g:llama_config.t_max_predict_ms
\ })
let l:curl_command = [
\ "curl",
\ "--silent",
\ "--no-buffer",
\ "--request", "POST",
\ "--url", g:llama_config.endpoint,
\ "--header", "Content-Type: application/json",
\ "--data", l:request
\ ]
if s:current_job != v:null
if s:ghost_text_nvim
call jobstop(s:current_job)
elseif s:ghost_text_vim
call job_stop(s:current_job)
endif
endif
" send the request asynchronously
if s:ghost_text_nvim
let s:current_job = jobstart(l:curl_command, {
\ 'on_stdout': function('s:fim_on_stdout', [s:pos_x, s:pos_y, a:is_auto]),
\ 'on_exit': function('s:fim_on_exit'),
\ 'stdout_buffered': v:true
\ })
elseif s:ghost_text_vim
let s:current_job = job_start(l:curl_command, {
\ 'out_cb': function('s:fim_on_stdout', [s:pos_x, s:pos_y, a:is_auto]),
\ 'exit_cb': function('s:fim_on_exit')
\ })
endif
" TODO: per-file location
let l:delta_y = abs(s:pos_y - s:pos_y_pick)
" gather some extra context nearby and process it in the background
" only gather chunks if the cursor has moved a lot
" TODO: something more clever? reranking?
if a:is_auto && l:delta_y > 32
" expand the prefix even further
call s:pick_chunk(getline(max([1, s:pos_y - g:llama_config.ring_scope]), max([1, s:pos_y - g:llama_config.n_prefix])), v:false, v:false)
" pick a suffix chunk
call s:pick_chunk(getline(min([l:max_y, s:pos_y + g:llama_config.n_suffix]), min([l:max_y, s:pos_y + g:llama_config.n_suffix + g:llama_config.ring_chunk_size])), v:false, v:false)
let s:pos_y_pick = s:pos_y
endif
endfunction
" if first_line == v:true accept only the first line of the response
function! llama#fim_accept(first_line)
" insert the suggestion at the cursor location
if s:can_accept && len(s:content) > 0
call setline(s:pos_y, s:line_cur[:(s:pos_x - 1)] . s:content[0])
if len(s:content) > 1
if !a:first_line
call append(s:pos_y, s:content[1:-1])
endif
endif
" move the cursor to the end of the accepted text
if !a:first_line && len(s:content) > 1
call cursor(s:pos_y + len(s:content) - 1, s:pos_x + s:pos_dx + 1)
else
call cursor(s:pos_y, s:pos_x + len(s:content[0]))
endif
endif
call llama#fim_cancel()
endfunction
function! llama#fim_cancel()
let s:hint_shown = v:false
" clear the virtual text
let l:bufnr = bufnr('%')
if s:ghost_text_nvim
let l:id_vt_fim = nvim_create_namespace('vt_fim')
call nvim_buf_clear_namespace(l:bufnr, l:id_vt_fim, 0, -1)
elseif s:ghost_text_vim
call prop_remove({'type': s:hlgroup_hint, 'all': v:true})
call prop_remove({'type': s:hlgroup_info, 'all': v:true})
endif
" remove the mappings
silent! iunmap <buffer> <Tab>
silent! iunmap <buffer> <S-Tab>
silent! iunmap <buffer> <Esc>
endfunction
function! s:on_move()
let s:t_last_move = reltime()
call llama#fim_cancel()
endfunction
" callback that processes the FIM result from the server and displays the suggestion
function! s:fim_on_stdout(pos_x, pos_y, is_auto, job_id, data, event = v:null)
if s:ghost_text_nvim
let l:raw = join(a:data, "\n")
elseif s:ghost_text_vim
let l:raw = a:data
endif
if len(l:raw) == 0
return
endif
if a:pos_x != col('.') - 1 || a:pos_y != line('.')
return
endif
" show the suggestion only in insert mode
if mode() !=# 'i'
return
endif
let s:pos_x = a:pos_x
let s:pos_y = a:pos_y
let s:can_accept = v:true
let l:has_info = v:false
if s:can_accept && v:shell_error
if !a:is_auto
call add(s:content, "<| curl error: is the server on? |>")
endif
let s:can_accept = v:false
endif
let l:n_prompt = 0
let l:t_prompt_ms = 1.0
let l:s_prompt = 0
let l:n_predict = 0
let l:t_predict_ms = 1.0
let l:s_predict = 0
" get the generated suggestion
if s:can_accept
let l:response = json_decode(l:raw)
for l:part in split(get(l:response, 'content', ''), "\n", 1)
call add(s:content, l:part)
endfor
" remove trailing new lines
while len(s:content) > 0 && s:content[-1] == ""
call remove(s:content, -1)
endwhile
let l:generation_settings = get(l:response, 'generation_settings', {})
let l:n_ctx = get(l:generation_settings, 'n_ctx', 0)
let l:n_cached = get(l:response, 'tokens_cached', 0)
let l:truncated = get(l:response, 'truncated', v:false)
" if response.timings is available
if len(get(l:response, 'timings', {})) > 0
let l:has_info = v:true
let l:timings = get(l:response, 'timings', {})
let l:n_prompt = get(l:timings, 'prompt_n', 0)
let l:t_prompt_ms = get(l:timings, 'prompt_ms', 1)
let l:s_prompt = get(l:timings, 'prompt_per_second', 0)
let l:n_predict = get(l:timings, 'predicted_n', 0)
let l:t_predict_ms = get(l:timings, 'predicted_ms', 1)
let l:s_predict = get(l:timings, 'predicted_per_second', 0)
endif
endif
if len(s:content) == 0
call add(s:content, "")
let s:can_accept = v:false
endif
if len(s:content) == 0
return
endif
" NOTE: the following is logic for discarding predictions that repeat existing text
" the code is quite ugly and there is very likely a simpler and more canonical way to implement this
"
" still, I wonder if there is some better way that avoids having to do these special hacks?
" on one hand, the LLM 'sees' the contents of the file before we start editing, so it is normal that it would
" start generating whatever we have given it via the extra context. but on the other hand, it's not very
" helpful to re-generate the same code that is already there
" truncate the suggestion if the first line is empty
if len(s:content) == 1 && s:content[0] == ""
let s:content = [""]
endif
" ... and the next lines are repeated
if len(s:content) > 1 && s:content[0] == "" && s:content[1:] == getline(s:pos_y + 1, s:pos_y + len(s:content) - 1)
let s:content = [""]
endif
" truncate the suggestion if it repeats the suffix
if len(s:content) == 1 && s:content[0] == s:line_cur_suffix
let s:content = [""]
endif
" find the first non-empty line (strip whitespace)
let l:cmp_y = s:pos_y + 1
while l:cmp_y < line('$') && getline(l:cmp_y) =~? '^\s*$'
let l:cmp_y += 1
endwhile
if (s:line_cur_prefix . s:content[0]) == getline(l:cmp_y)
" truncate the suggestion if it repeats the next line
if len(s:content) == 1
let s:content = [""]
endif
" ... or if the second line of the suggestion is the prefix of line l:cmp_y + 1
if len(s:content) == 2 && s:content[-1] == getline(l:cmp_y + 1)[:len(s:content[-1]) - 1]
let s:content = [""]
endif
" ... or if the middle chunk of lines of the suggestion is the same as [l:cmp_y + 1, l:cmp_y + len(s:content) - 1)
if len(s:content) > 2 && join(s:content[1:-1], "\n") == join(getline(l:cmp_y + 1, l:cmp_y + len(s:content) - 1), "\n")
let s:content = [""]
endif
endif
" keep only lines that have the same or larger whitespace prefix as s:line_cur_prefix
"let l:indent = strlen(matchstr(s:line_cur_prefix, '^\s*'))
"for i in range(1, len(s:content) - 1)
" if strlen(matchstr(s:content[i], '^\s*')) < l:indent
" let s:content = s:content[:i - 1]
" break
" endif
"endfor
let s:pos_dx = len(s:content[-1])
let s:content[-1] .= s:line_cur_suffix
call llama#fim_cancel()
" display virtual text with the suggestion
let l:bufnr = bufnr('%')
if s:ghost_text_nvim
let l:id_vt_fim = nvim_create_namespace('vt_fim')
endif
" construct the info message
if g:llama_config.show_info > 0 && l:has_info
let l:prefix = ' '
if l:truncated
let l:info = printf("%s | WARNING: the context is full: %d / %d, increase the server context size or reduce g:llama_config.ring_n_chunks",
\ g:llama_config.show_info == 2 ? l:prefix : 'llama.vim',
\ l:n_cached, l:n_ctx
\ )
else
let l:info = printf("%s | c: %d / %d, r: %d / %d, e: %d, q: %d / 16 | p: %d (%.2f ms, %.2f t/s) | g: %d (%.2f ms, %.2f t/s) | t: %.2f ms",
\ g:llama_config.show_info == 2 ? l:prefix : 'llama.vim',
\ l:n_cached, l:n_ctx, len(s:ring_chunks), g:llama_config.ring_n_chunks, s:ring_n_evict, len(s:ring_queued),
\ l:n_prompt, l:t_prompt_ms, l:s_prompt,
\ l:n_predict, l:t_predict_ms, l:s_predict,
\ 1000.0 * reltimefloat(reltime(s:t_fim_start))
\ )
endif
if g:llama_config.show_info == 1
" display the info in the statusline
let &statusline = l:info
let l:info = ''
endif
endif
" display the suggestion and append the info to the end of the first line
if s:ghost_text_nvim
call nvim_buf_set_extmark(l:bufnr, l:id_vt_fim, s:pos_y - 1, s:pos_x - 1, {
\ 'virt_text': [[s:content[0], 'llama_hl_hint'], [l:info, 'llama_hl_info']],
\ 'virt_text_win_col': virtcol('.') - 1
\ })
call nvim_buf_set_extmark(l:bufnr, l:id_vt_fim, s:pos_y - 1, 0, {
\ 'virt_lines': map(s:content[1:], {idx, val -> [[val, 'llama_hl_hint']]}),
\ 'virt_text_win_col': virtcol('.')
\ })
elseif s:ghost_text_vim
let l:new_suffix = s:content[0]
if !empty(l:new_suffix)
call prop_add(s:pos_y, s:pos_x + 1, {
\ 'type': s:hlgroup_hint,
\ 'text': l:new_suffix
\ })
endif
for line in s:content[1:]
call prop_add(s:pos_y, 0, {
\ 'type': s:hlgroup_hint,
\ 'text': line,
\ 'text_padding_left': s:get_indent(line),
\ 'text_align': 'below'
\ })
endfor
if !empty(l:info)
call prop_add(s:pos_y, 0, {
\ 'type': s:hlgroup_info,
\ 'text': l:info,
\ 'text_padding_left': col('$'),
\ 'text_wrap': 'truncate'
\ })
endif
endif
" setup accept shortcuts
inoremap <buffer> <Tab> <C-O>:call llama#fim_accept(v:false)<CR>
inoremap <buffer> <S-Tab> <C-O>:call llama#fim_accept(v:true)<CR>
let s:hint_shown = v:true
endfunction
function! s:fim_on_exit(job_id, exit_code, event = v:null)
if a:exit_code != 0
echom "Job failed with exit code: " . a:exit_code
endif
let s:current_job = v:null
endfunction