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koboldcpp.py
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koboldcpp.py
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#!/usr/bin/env python3
#-*- coding: utf-8 -*-
# A hacky little script from Concedo that exposes llama.cpp function bindings
# allowing it to be used via a simulated kobold api endpoint
# generation delay scales linearly with original prompt length.
import ctypes
import os
import argparse
import json, sys, http.server, time, asyncio, socket, threading
from concurrent.futures import ThreadPoolExecutor
stop_token_max = 10
sampler_order_max = 7
ban_token_max = 10
tensor_split_max = 16
class load_model_inputs(ctypes.Structure):
_fields_ = [("threads", ctypes.c_int),
("blasthreads", ctypes.c_int),
("max_context_length", ctypes.c_int),
("batch_size", ctypes.c_int),
("f16_kv", ctypes.c_bool),
("low_vram", ctypes.c_bool),
("use_mmq", ctypes.c_bool),
("executable_path", ctypes.c_char_p),
("model_filename", ctypes.c_char_p),
("lora_filename", ctypes.c_char_p),
("lora_base", ctypes.c_char_p),
("use_mmap", ctypes.c_bool),
("use_mlock", ctypes.c_bool),
("use_smartcontext", ctypes.c_bool),
("unban_tokens", ctypes.c_bool),
("clblast_info", ctypes.c_int),
("cublas_info", ctypes.c_int),
("blasbatchsize", ctypes.c_int),
("debugmode", ctypes.c_int),
("forceversion", ctypes.c_int),
("gpulayers", ctypes.c_int),
("rope_freq_scale", ctypes.c_float),
("rope_freq_base", ctypes.c_float),
("banned_tokens", ctypes.c_char_p * ban_token_max),
("tensor_split", ctypes.c_float * tensor_split_max)]
class generation_inputs(ctypes.Structure):
_fields_ = [("seed", ctypes.c_int),
("prompt", ctypes.c_char_p),
("max_context_length", ctypes.c_int),
("max_length", ctypes.c_int),
("temperature", ctypes.c_float),
("top_k", ctypes.c_int),
("top_a", ctypes.c_float),
("top_p", ctypes.c_float),
("typical_p", ctypes.c_float),
("tfs", ctypes.c_float),
("rep_pen", ctypes.c_float),
("rep_pen_range", ctypes.c_int),
("mirostat", ctypes.c_int),
("mirostat_tau", ctypes.c_float),
("mirostat_eta", ctypes.c_float),
("sampler_order", ctypes.c_int * sampler_order_max),
("sampler_len", ctypes.c_int),
("unban_tokens_rt", ctypes.c_bool),
("stop_sequence", ctypes.c_char_p * stop_token_max),
("stream_sse", ctypes.c_bool)]
class generation_outputs(ctypes.Structure):
_fields_ = [("status", ctypes.c_int),
("text", ctypes.c_char * 24576)]
handle = None
def getdirpath():
return os.path.dirname(os.path.realpath(__file__))
def file_exists(filename):
return os.path.exists(os.path.join(getdirpath(), filename))
def pick_existant_file(ntoption,nonntoption):
precompiled_prefix = "precompiled_"
ntexist = file_exists(ntoption)
nonntexist = file_exists(nonntoption)
precompiled_ntexist = file_exists(precompiled_prefix+ntoption)
precompiled_nonntexist = file_exists(precompiled_prefix+nonntoption)
if os.name == 'nt':
if not ntexist and precompiled_ntexist:
return (precompiled_prefix+ntoption)
if nonntexist and not ntexist:
return nonntoption
return ntoption
else:
if not nonntexist and precompiled_nonntexist:
return (precompiled_prefix+nonntoption)
if ntexist and not nonntexist:
return ntoption
return nonntoption
lib_default = pick_existant_file("koboldcpp_default.dll","koboldcpp_default.so")
lib_failsafe = pick_existant_file("koboldcpp_failsafe.dll","koboldcpp_failsafe.so")
lib_openblas = pick_existant_file("koboldcpp_openblas.dll","koboldcpp_openblas.so")
lib_noavx2 = pick_existant_file("koboldcpp_noavx2.dll","koboldcpp_noavx2.so")
lib_clblast = pick_existant_file("koboldcpp_clblast.dll","koboldcpp_clblast.so")
lib_cublas = pick_existant_file("koboldcpp_cublas.dll","koboldcpp_cublas.so")
def init_library():
global handle, args
global lib_default,lib_failsafe,lib_openblas,lib_noavx2,lib_clblast,lib_cublas
libname = ""
use_openblas = False # if true, uses OpenBLAS for acceleration. libopenblas.dll must exist in the same dir.
use_clblast = False #uses CLBlast instead
use_cublas = False #uses cublas instead
use_noavx2 = False #uses no avx2 instructions
use_failsafe = False #uses no intrinsics, failsafe mode
if args.noavx2:
use_noavx2 = True
if not file_exists(lib_noavx2):
print("Warning: NoAVX2 library file not found. Failsafe library will be used.")
elif (args.noblas and args.nommap):
use_failsafe = True
print("!!! Attempting to use FAILSAFE MODE !!!")
else:
print("Attempting to use non-avx2 compatibility library.")
elif args.useclblast:
if not file_exists(lib_clblast) or (os.name=='nt' and not file_exists("clblast.dll")):
print("Warning: CLBlast library file not found. Non-BLAS library will be used.")
else:
print("Attempting to use CLBlast library for faster prompt ingestion. A compatible clblast will be required.")
use_clblast = True
elif (args.usecublas is not None):
if not file_exists(lib_cublas):
print("Warning: CuBLAS library file not found. Non-BLAS library will be used.")
else:
print("Attempting to use CuBLAS library for faster prompt ingestion. A compatible CuBLAS will be required.")
use_cublas = True
else:
if not file_exists(lib_openblas) or (os.name=='nt' and not file_exists("libopenblas.dll")):
print("Warning: OpenBLAS library file not found. Non-BLAS library will be used.")
elif args.noblas:
print("Attempting to library without OpenBLAS.")
else:
use_openblas = True
print("Attempting to use OpenBLAS library for faster prompt ingestion. A compatible libopenblas will be required.")
if sys.platform=="darwin":
print("Mac OSX note: Some people have found Accelerate actually faster than OpenBLAS. To compare, run Koboldcpp with --noblas instead.")
if use_noavx2:
if use_failsafe:
libname = lib_failsafe
else:
libname = lib_noavx2
else:
if use_clblast:
libname = lib_clblast
elif use_cublas:
libname = lib_cublas
elif use_openblas:
libname = lib_openblas
else:
libname = lib_default
print("Initializing dynamic library: " + libname)
dir_path = getdirpath()
#OpenBLAS should provide about a 2x speedup on prompt ingestion if compatible.
handle = ctypes.CDLL(os.path.join(dir_path, libname))
handle.load_model.argtypes = [load_model_inputs]
handle.load_model.restype = ctypes.c_bool
handle.generate.argtypes = [generation_inputs, ctypes.c_wchar_p] #apparently needed for osx to work. i duno why they need to interpret it that way but whatever
handle.generate.restype = generation_outputs
handle.new_token.restype = ctypes.c_char_p
handle.new_token.argtypes = [ctypes.c_int]
handle.get_stream_count.restype = ctypes.c_int
handle.has_finished.restype = ctypes.c_bool
handle.get_last_eval_time.restype = ctypes.c_float
handle.get_last_process_time.restype = ctypes.c_float
handle.get_last_token_count.restype = ctypes.c_int
handle.get_last_stop_reason.restype = ctypes.c_int
handle.abort_generate.restype = ctypes.c_bool
handle.token_count.restype = ctypes.c_int
handle.get_pending_output.restype = ctypes.c_char_p
def load_model(model_filename):
global args
inputs = load_model_inputs()
inputs.model_filename = model_filename.encode("UTF-8")
inputs.batch_size = 8
inputs.max_context_length = maxctx #initial value to use for ctx, can be overwritten
inputs.threads = args.threads
inputs.low_vram = (True if (args.usecublas and "lowvram" in args.usecublas) else False)
inputs.use_mmq = (True if (args.usecublas and "mmq" in args.usecublas) else False)
inputs.blasthreads = args.blasthreads
inputs.f16_kv = True
inputs.use_mmap = (not args.nommap)
inputs.use_mlock = args.usemlock
inputs.lora_filename = "".encode("UTF-8")
inputs.lora_base = "".encode("UTF-8")
if args.lora:
inputs.lora_filename = args.lora[0].encode("UTF-8")
inputs.use_mmap = False
if len(args.lora) > 1:
inputs.lora_base = args.lora[1].encode("UTF-8")
inputs.use_smartcontext = args.smartcontext
inputs.unban_tokens = args.unbantokens
inputs.blasbatchsize = args.blasbatchsize
inputs.forceversion = args.forceversion
inputs.gpulayers = args.gpulayers
inputs.rope_freq_scale = args.ropeconfig[0]
if len(args.ropeconfig)>1:
inputs.rope_freq_base = args.ropeconfig[1]
else:
inputs.rope_freq_base = 10000
clblastids = 0
if args.useclblast:
clblastids = 100 + int(args.useclblast[0])*10 + int(args.useclblast[1])
inputs.clblast_info = clblastids
for n in range(tensor_split_max):
if args.tensor_split and n < len(args.tensor_split):
inputs.tensor_split[n] = float(args.tensor_split[n])
else:
inputs.tensor_split[n] = 0
# we must force an explicit tensor split
# otherwise the default will divide equally and multigpu crap will slow it down badly
inputs.cublas_info = 0
if not args.tensor_split:
if (args.usecublas and "0" in args.usecublas):
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
os.environ["HIP_VISIBLE_DEVICES"] = "0"
elif (args.usecublas and "1" in args.usecublas):
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
os.environ["HIP_VISIBLE_DEVICES"] = "1"
elif (args.usecublas and "2" in args.usecublas):
os.environ["CUDA_VISIBLE_DEVICES"] = "2"
os.environ["HIP_VISIBLE_DEVICES"] = "2"
else:
if (args.usecublas and "0" in args.usecublas):
inputs.cublas_info = 0
elif (args.usecublas and "1" in args.usecublas):
inputs.cublas_info = 1
elif (args.usecublas and "2" in args.usecublas):
inputs.cublas_info = 2
inputs.executable_path = (getdirpath()+"/").encode("UTF-8")
inputs.debugmode = args.debugmode
banned_tokens = args.bantokens
for n in range(ban_token_max):
if not banned_tokens or n >= len(banned_tokens):
inputs.banned_tokens[n] = "".encode("UTF-8")
else:
inputs.banned_tokens[n] = banned_tokens[n].encode("UTF-8")
ret = handle.load_model(inputs)
return ret
def generate(prompt,max_length=20, max_context_length=512, temperature=0.8, top_k=120, top_a=0.0, top_p=0.85, typical_p=1.0, tfs=1.0, rep_pen=1.1, rep_pen_range=128, mirostat=0, mirostat_tau=5.0, mirostat_eta=0.1, sampler_order=[6,0,1,3,4,2,5], seed=-1, stop_sequence=[], use_default_badwordsids=True, stream_sse=False):
global maxctx, args
inputs = generation_inputs()
outputs = ctypes.create_unicode_buffer(ctypes.sizeof(generation_outputs))
inputs.prompt = prompt.encode("UTF-8")
if max_length >= max_context_length:
max_length = max_context_length-1
inputs.max_context_length = max_context_length # this will resize the context buffer if changed
global showmaxctxwarning
if showmaxctxwarning and max_context_length > maxctx:
print(f"\n(Warning! Request max_context_length={max_context_length} exceeds allocated context size of {maxctx}. Consider launching with increased --contextsize to avoid errors. This message will only show once per session.)")
showmaxctxwarning = False
inputs.max_length = max_length
inputs.temperature = temperature
inputs.top_k = top_k
inputs.top_a = top_a
inputs.top_p = top_p
inputs.typical_p = typical_p
inputs.tfs = tfs
inputs.rep_pen = rep_pen
inputs.rep_pen_range = rep_pen_range
inputs.stream_sse = stream_sse
inputs.unban_tokens_rt = not use_default_badwordsids
if args.usemirostat and args.usemirostat[0]>0:
inputs.mirostat = int(args.usemirostat[0])
inputs.mirostat_tau = float(args.usemirostat[1])
inputs.mirostat_eta = float(args.usemirostat[2])
elif mirostat in (1, 2):
inputs.mirostat = mirostat
inputs.mirostat_tau = mirostat_tau
inputs.mirostat_eta = mirostat_eta
else:
inputs.mirostat = inputs.mirostat_tau = inputs.mirostat_eta = 0
if sampler_order and 0 < len(sampler_order) <= sampler_order_max:
try:
for i, sampler in enumerate(sampler_order):
inputs.sampler_order[i] = sampler
inputs.sampler_len = len(sampler_order)
global showsamplerwarning
if showsamplerwarning and inputs.mirostat==0 and inputs.sampler_len>0 and (inputs.sampler_order[0]!=6 or inputs.sampler_order[inputs.sampler_len-1]!=5):
print("\n(Note: Sub-optimal sampler_order detected. You may have reduced quality. Recommended sampler values are [6,0,1,3,4,2,5]. This message will only show once per session.)")
showsamplerwarning = False
except TypeError as e:
print("ERROR: sampler_order must be a list of integers: " + str(e))
inputs.seed = seed
for n in range(stop_token_max):
if not stop_sequence or n >= len(stop_sequence):
inputs.stop_sequence[n] = "".encode("UTF-8")
else:
inputs.stop_sequence[n] = stop_sequence[n].encode("UTF-8")
ret = handle.generate(inputs,outputs)
if(ret.status==1):
return ret.text.decode("UTF-8","ignore")
return ""
def utfprint(str):
try:
print(str)
except UnicodeEncodeError:
# Replace or omit the problematic character
utf_string = str.encode('ascii', 'ignore').decode('ascii')
utf_string = utf_string.replace('\a', '') #remove bell characters
print(utf_string)
#################################################################
### A hacky simple HTTP server simulating a kobold api by Concedo
### we are intentionally NOT using flask, because we want MINIMAL dependencies
#################################################################
friendlymodelname = "concedo/koboldcpp" # local kobold api apparently needs a hardcoded known HF model name
maxctx = 2048
maxhordectx = 1024
maxhordelen = 256
modelbusy = threading.Lock()
defaultport = 5001
KcppVersion = "1.43"
showdebug = True
showsamplerwarning = True
showmaxctxwarning = True
exitcounter = 0
args = None #global args
class ServerRequestHandler(http.server.SimpleHTTPRequestHandler):
sys_version = ""
server_version = "ConcedoLlamaForKoboldServer"
def __init__(self, addr, port, embedded_kailite):
self.addr = addr
self.port = port
self.embedded_kailite = embedded_kailite
def __call__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def log_message(self, format, *args):
global showdebug
if showdebug:
super().log_message(format, *args)
pass
async def generate_text(self, newprompt, genparams, basic_api_flag, stream_flag):
def run_blocking():
if basic_api_flag:
return generate(
prompt=newprompt,
max_length=genparams.get('max', 50),
temperature=genparams.get('temperature', 0.8),
top_k=int(genparams.get('top_k', 120)),
top_a=genparams.get('top_a', 0.0),
top_p=genparams.get('top_p', 0.85),
typical_p=genparams.get('typical', 1.0),
tfs=genparams.get('tfs', 1.0),
rep_pen=genparams.get('rep_pen', 1.1),
rep_pen_range=genparams.get('rep_pen_range', 128),
mirostat=genparams.get('mirostat', 0),
mirostat_tau=genparams.get('mirostat_tau', 5.0),
mirostat_eta=genparams.get('mirostat_eta', 0.1),
sampler_order=genparams.get('sampler_order', [6,0,1,3,4,2,5]),
seed=genparams.get('sampler_seed', -1),
stop_sequence=genparams.get('stop_sequence', []),
use_default_badwordsids=genparams.get('use_default_badwordsids', True),
stream_sse=stream_flag)
else:
return generate(prompt=newprompt,
max_context_length=genparams.get('max_context_length', maxctx),
max_length=genparams.get('max_length', 50),
temperature=genparams.get('temperature', 0.8),
top_k=genparams.get('top_k', 120),
top_a=genparams.get('top_a', 0.0),
top_p=genparams.get('top_p', 0.85),
typical_p=genparams.get('typical', 1.0),
tfs=genparams.get('tfs', 1.0),
rep_pen=genparams.get('rep_pen', 1.1),
rep_pen_range=genparams.get('rep_pen_range', 128),
mirostat=genparams.get('mirostat', 0),
mirostat_tau=genparams.get('mirostat_tau', 5.0),
mirostat_eta=genparams.get('mirostat_eta', 0.1),
sampler_order=genparams.get('sampler_order', [6,0,1,3,4,2,5]),
seed=genparams.get('sampler_seed', -1),
stop_sequence=genparams.get('stop_sequence', []),
use_default_badwordsids=genparams.get('use_default_badwordsids', True),
stream_sse=stream_flag)
recvtxt = ""
if stream_flag:
loop = asyncio.get_event_loop()
executor = ThreadPoolExecutor()
recvtxt = await loop.run_in_executor(executor, run_blocking)
else:
recvtxt = run_blocking()
if args.debugmode!=-1:
utfprint("\nOutput: " + recvtxt)
res = {"data": {"seqs":[recvtxt]}} if basic_api_flag else {"results": [{"text": recvtxt}]}
try:
return res
except Exception as e:
print(f"Generate: Error while generating: {e}")
async def send_sse_event(self, event, data):
self.wfile.write(f'event: {event}\n'.encode())
self.wfile.write(f'data: {data}\n\n'.encode())
async def handle_sse_stream(self):
self.send_response(200)
self.send_header("Cache-Control", "no-cache")
self.send_header("Connection", "keep-alive")
self.end_headers()
current_token = 0
incomplete_token_buffer = bytearray()
while not handle.has_finished():
streamcount = handle.get_stream_count()
while current_token < streamcount:
token = handle.new_token(current_token)
if token is None: # Token isnt ready yet, received nullpointer
break
current_token += 1
newbyte = ctypes.string_at(token)
incomplete_token_buffer += bytearray(newbyte)
tokenStr = incomplete_token_buffer.decode("UTF-8","ignore")
if tokenStr!="":
incomplete_token_buffer.clear()
event_data = {"token": tokenStr}
event_str = json.dumps(event_data)
await self.send_sse_event("message", event_str)
await asyncio.sleep(0.02) #this should keep things responsive
# flush buffers, sleep a bit to make sure all data sent, and then force close the connection
self.wfile.flush()
await asyncio.sleep(0.1)
self.close_connection = True
async def handle_request(self, genparams, newprompt, basic_api_flag, stream_flag):
tasks = []
if stream_flag:
tasks.append(self.handle_sse_stream())
generate_task = asyncio.create_task(self.generate_text(newprompt, genparams, basic_api_flag, stream_flag))
tasks.append(generate_task)
try:
await asyncio.gather(*tasks)
generate_result = generate_task.result()
return generate_result
except Exception as e:
print(e)
def do_GET(self):
global maxctx, maxhordelen, friendlymodelname, KcppVersion, streamLock
self.path = self.path.rstrip('/')
response_body = None
if self.path in ["", "/?"] or self.path.startswith(('/?','?')): #it's possible for the root url to have ?params without /
if args.stream and not "streaming=1" in self.path:
self.path = self.path.replace("streaming=0","")
if self.path.startswith(('/?','?')):
self.path += "&streaming=1"
else:
self.path = self.path + "?streaming=1"
self.send_response(302)
self.send_header("Location", self.path)
self.end_headers()
print("Force redirect to streaming mode, as --stream is set.")
return None
if self.embedded_kailite is None:
response_body = (f"Embedded Kobold Lite is not found.<br>You will have to connect via the main KoboldAI client, or <a href='https://lite.koboldai.net?local=1&port={self.port}'>use this URL</a> to connect.").encode()
else:
response_body = self.embedded_kailite
elif self.path.endswith(('/api/v1/model', '/api/latest/model')):
response_body = (json.dumps({'result': friendlymodelname }).encode())
elif self.path.endswith(('/api/v1/config/max_length', '/api/latest/config/max_length')):
response_body = (json.dumps({"value": maxhordelen}).encode())
elif self.path.endswith(('/api/v1/config/max_context_length', '/api/latest/config/max_context_length')):
response_body = (json.dumps({"value": min(maxctx,maxhordectx)}).encode())
elif self.path.endswith(('/api/v1/config/soft_prompt', '/api/latest/config/soft_prompt')):
response_body = (json.dumps({"value":""}).encode())
elif self.path.endswith(('/api/v1/config/soft_prompts_list', '/api/latest/config/soft_prompts_list')):
response_body = (json.dumps({"values": []}).encode())
elif self.path.endswith(('/api/v1/info/version', '/api/latest/info/version')):
response_body = (json.dumps({"result":"1.2.4"}).encode())
elif self.path.endswith(('/api/extra/version')):
response_body = (json.dumps({"result":"KoboldCpp","version":KcppVersion}).encode())
elif self.path.endswith(('/api/extra/perf')):
lastp = handle.get_last_process_time()
laste = handle.get_last_eval_time()
lastc = handle.get_last_token_count()
stopreason = handle.get_last_stop_reason()
response_body = (json.dumps({"last_process":lastp,"last_eval":laste,"last_token_count":lastc, "stop_reason":stopreason, "idle":(0 if modelbusy.locked() else 1)}).encode())
if response_body is None:
self.send_response(404)
self.end_headers()
rp = 'Error: HTTP Server is running, but this endpoint does not exist. Please check the URL.'
self.wfile.write(rp.encode())
else:
self.send_response(200)
self.send_header('Content-Length', str(len(response_body)))
self.end_headers()
self.wfile.write(response_body)
return
def do_POST(self):
global modelbusy
content_length = int(self.headers['Content-Length'])
body = self.rfile.read(content_length)
basic_api_flag = False
kai_api_flag = False
kai_sse_stream_flag = False
self.path = self.path.rstrip('/')
if self.path.endswith(('/api/extra/tokencount')):
try:
genparams = json.loads(body)
countprompt = genparams.get('prompt', "")
count = handle.token_count(countprompt.encode("UTF-8"))
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps({"value": count}).encode())
except ValueError as e:
utfprint("Count Tokens - Body Error: " + str(e))
self.send_response(400)
self.end_headers()
self.wfile.write(json.dumps({"value": -1}).encode())
return
if self.path.endswith('/api/extra/abort'):
ag = handle.abort_generate()
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps({"success": ("true" if ag else "false")}).encode())
print("\nGeneration Aborted")
return
if self.path.endswith('/api/extra/generate/check'):
pendtxt = handle.get_pending_output()
pendtxtStr = ctypes.string_at(pendtxt).decode("UTF-8","ignore")
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps({"results": [{"text": pendtxtStr}]}).encode())
return
if not modelbusy.acquire(blocking=False):
self.send_response(503)
self.end_headers()
self.wfile.write(json.dumps({"detail": {
"msg": "Server is busy; please try again later.",
"type": "service_unavailable",
}}).encode())
return
try:
if self.path.endswith('/request'):
basic_api_flag = True
if self.path.endswith(('/api/v1/generate', '/api/latest/generate')):
kai_api_flag = True
if self.path.endswith('/api/extra/generate/stream'):
kai_api_flag = True
kai_sse_stream_flag = True
if basic_api_flag or kai_api_flag:
genparams = None
try:
genparams = json.loads(body)
except ValueError as e:
utfprint("Body Err: " + str(body))
return self.send_response(503)
if args.debugmode!=-1:
utfprint("\nInput: " + json.dumps(genparams))
if kai_api_flag:
fullprompt = genparams.get('prompt', "")
else:
fullprompt = genparams.get('text', "")
newprompt = fullprompt
gen = asyncio.run(self.handle_request(genparams, newprompt, basic_api_flag, kai_sse_stream_flag))
try:
# Headers are already sent when streaming
if not kai_sse_stream_flag:
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps(gen).encode())
except:
print("Generate: The response could not be sent, maybe connection was terminated?")
return
finally:
modelbusy.release()
self.send_response(404)
self.end_headers()
def do_OPTIONS(self):
self.send_response(200)
self.end_headers()
def do_HEAD(self):
self.send_response(200)
self.end_headers()
def end_headers(self):
self.send_header('Access-Control-Allow-Origin', '*')
self.send_header('Access-Control-Allow-Methods', '*')
self.send_header('Access-Control-Allow-Headers', '*')
if "/api" in self.path:
if self.path.endswith("/stream"):
self.send_header('Content-type', 'text/event-stream')
self.send_header('Content-type', 'application/json')
else:
self.send_header('Content-type', 'text/html')
return super(ServerRequestHandler, self).end_headers()
def RunServerMultiThreaded(addr, port, embedded_kailite = None):
global exitcounter
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
sock.bind((addr, port))
sock.listen(5)
class Thread(threading.Thread):
def __init__(self, i):
threading.Thread.__init__(self)
self.i = i
self.daemon = True
self.start()
def run(self):
global exitcounter
handler = ServerRequestHandler(addr, port, embedded_kailite)
with http.server.HTTPServer((addr, port), handler, False) as self.httpd:
try:
self.httpd.socket = sock
self.httpd.server_bind = self.server_close = lambda self: None
self.httpd.serve_forever()
except (KeyboardInterrupt,SystemExit):
exitcounter = 999
self.httpd.server_close()
sys.exit(0)
finally:
exitcounter = 999
self.httpd.server_close()
sys.exit(0)
def stop(self):
global exitcounter
exitcounter = 999
self.httpd.server_close()
numThreads = 8
threadArr = []
for i in range(numThreads):
threadArr.append(Thread(i))
while 1:
try:
time.sleep(10)
except KeyboardInterrupt:
exitcounter = 999
for i in range(numThreads):
threadArr[i].stop()
sys.exit(0)
# note: customtkinter-5.2.0
def show_new_gui():
from tkinter.filedialog import askopenfilename
from tkinter.filedialog import asksaveasfile
# if args received, launch
if len(sys.argv) != 1:
import tkinter as tk
root = tk.Tk() #we dont want the useless window to be visible, but we want it in taskbar
root.attributes("-alpha", 0)
args.model_param = askopenfilename(title="Select ggml model .bin or .gguf files")
root.destroy()
if not args.model_param:
print("\nNo ggml model file was selected. Exiting.")
time.sleep(3)
sys.exit(2)
return
import customtkinter as ctk
nextstate = 0 #0=exit, 1=launch, 2=oldgui
windowwidth = 530
windowheight = 500
ctk.set_appearance_mode("dark")
root = ctk.CTk()
root.geometry(str(windowwidth) + "x" + str(windowheight))
root.title("KoboldCpp v"+KcppVersion)
root.resizable(False,False)
tabs = ctk.CTkFrame(root, corner_radius = 0, width=windowwidth, height=windowheight-50)
tabs.grid(row=0, stick="nsew")
tabnames= ["Quick Launch", "Hardware", "Tokens", "Model", "Network"]
navbuttons = {}
navbuttonframe = ctk.CTkFrame(tabs, width=100, height=int(tabs.cget("height")))
navbuttonframe.grid(row=0, column=0, padx=2,pady=2)
navbuttonframe.grid_propagate(False)
tabcontentframe = ctk.CTkFrame(tabs, width=windowwidth - int(navbuttonframe.cget("width")), height=int(tabs.cget("height")))
tabcontentframe.grid(row=0, column=1, sticky="nsew", padx=2, pady=2)
tabcontentframe.grid_propagate(False)
tabcontent = {}
lib_option_pairs = [
(lib_openblas, "Use OpenBLAS"),
(lib_clblast, "Use CLBlast"),
(lib_cublas, "Use CuBLAS/hipBLAS"),
(lib_default, "Use No BLAS"),
(lib_noavx2, "NoAVX2 Mode (Old CPU)"),
(lib_failsafe, "Failsafe Mode (Old CPU)")]
openblas_option, clblast_option, cublas_option, default_option, noavx2_option, failsafe_option = (opt if file_exists(lib) or (os.name == 'nt' and file_exists(opt + ".dll")) else None for lib, opt in lib_option_pairs)
# slider data
blasbatchsize_values = ["-1", "32", "64", "128", "256", "512", "1024", "2048"]
blasbatchsize_text = ["Don't Batch BLAS","32","64","128","256","512","1024","2048"]
contextsize_text = ["512", "1024", "2048", "3072", "4096", "6144", "8192", "12288", "16384"]
runopts = [opt for lib, opt in lib_option_pairs if file_exists(lib)]
antirunopts = [opt.replace("Use ", "") for lib, opt in lib_option_pairs if not (opt in runopts)]
if not any(runopts):
show_gui_warning("No Backend Available")
def tabbuttonaction(name):
for t in tabcontent:
if name == t:
tabcontent[t].grid(row=0, column=0)
navbuttons[t].configure(fg_color="#6f727b")
else:
tabcontent[t].grid_forget()
navbuttons[t].configure(fg_color="transparent")
# Dynamically create tabs + buttons based on values of [tabnames]
for idx, name in enumerate(tabnames):
tabcontent[name] = ctk.CTkFrame(tabcontentframe, width=int(tabcontentframe.cget("width")), height=int(tabcontentframe.cget("height")), fg_color="transparent")
tabcontent[name].grid_propagate(False)
if idx == 0:
tabcontent[name].grid(row=idx, sticky="nsew")
ctk.CTkLabel(tabcontent[name], text= name, font=ctk.CTkFont(None, 14, 'bold')).grid(row=0, padx=12, pady = 5, stick='nw')
navbuttons[name] = ctk.CTkButton(navbuttonframe, text=name, width = 100, corner_radius=0 , command = lambda d=name:tabbuttonaction(d), hover_color="#868a94" )
navbuttons[name].grid(row=idx)
tabbuttonaction(tabnames[0])
# helper functions
def makecheckbox(parent, text, variable=None, row=0, column=0, command=None, onvalue=1, offvalue=0):
temp = ctk.CTkCheckBox(parent, text=text,variable=variable, onvalue=onvalue, offvalue=offvalue)
if command is not None and variable is not None:
variable.trace("w", command)
temp.grid(row=row,column=column, padx=8, pady=1, stick="nw")
return temp
def makelabel(parent, text, row, column=0):
temp = ctk.CTkLabel(parent, text=text)
temp.grid(row=row, column=column, padx=8, pady=1, stick="nw")
return temp
def makeslider(parent, label, options, var, from_ , to, row=0, width=160, height=10, set=0):
sliderLabel = makelabel(parent, options[set], row + 1, 1)
makelabel(parent, label, row)
def sliderUpdate(a,b,c):
sliderLabel.configure(text = options[int(var.get())])
var.trace("w", sliderUpdate)
slider = ctk.CTkSlider(parent, from_=from_, to=to, variable = var, width = width, height=height, border_width=5,number_of_steps=len(options) - 1)
slider.grid(row=row+1, column=0, padx = 8, stick="w")
slider.set(set)
return slider
def makelabelentry(parent, text, var, row=0, width= 50):
label = makelabel(parent, text, row)
entry = ctk.CTkEntry(parent, width=width, textvariable=var) #you cannot set placeholder text for SHARED variables
entry.grid(row=row, column=1, padx= 8, stick="nw")
return entry, label
def makefileentry(parent, text, searchtext, var, row=0, width=250):
makelabel(parent, text, row)
def getfilename(var, text):
var.set(askopenfilename(title=text))
entry = ctk.CTkEntry(parent, width, textvariable=var)
entry.grid(row=row+1, column=0, padx=8, stick="nw")
button = ctk.CTkButton(parent, 50, text="Browse", command= lambda a=var,b=searchtext:getfilename(a,b))
button.grid(row=row+1, column=1, stick="nw")
return
def show_tooltip(event, tooltip_text=None):
if hasattr(show_tooltip, "_tooltip"):
tooltip = show_tooltip._tooltip
else:
tooltip = ctk.CTkToplevel(root)
tooltip.configure(fg_color="#ffffe0")
tooltip.withdraw()
tooltip.overrideredirect(True)
tooltip_label = ctk.CTkLabel(tooltip, text=tooltip_text, text_color="#000000", fg_color="#ffffe0")
tooltip_label.pack(expand=True, padx=2, pady=1)
show_tooltip._tooltip = tooltip
x, y = root.winfo_pointerxy()
tooltip.wm_geometry(f"+{x + 10}+{y + 10}")
tooltip.deiconify()
def hide_tooltip(event):
if hasattr(show_tooltip, "_tooltip"):
tooltip = show_tooltip._tooltip
tooltip.withdraw()
def setup_backend_tooltip(parent):
num_backends_built = makelabel(parent, str(len(runopts)) + "/6", 5, 2)
num_backends_built.grid(row=1, column=2, padx=0, pady=0)
num_backends_built.configure(text_color="#00ff00")
# Bind the backend count label with the tooltip function
num_backends_built.bind("<Enter>", lambda event: show_tooltip(event, f"This is the number of backends you have built and available." + (f"\nMissing: {', '.join(antirunopts)}" if len(runopts) != 6 else "")))
num_backends_built.bind("<Leave>", hide_tooltip)
# Vars - should be in scope to be used by multiple widgets
gpulayers_var = ctk.StringVar(value="0")
threads_var = ctk.StringVar(value=str(default_threads))
runopts_var = ctk.StringVar()
gpu_choice_var = ctk.StringVar(value="1")
launchbrowser = ctk.IntVar(value=1)
highpriority = ctk.IntVar()
disablemmap = ctk.IntVar()
psutil = ctk.IntVar()
usemlock = ctk.IntVar()
debugmode = ctk.IntVar()
lowvram_var = ctk.IntVar()
mmq_var = ctk.IntVar(value=1)
blas_threads_var = ctk.StringVar()
blas_size_var = ctk.IntVar()
version_var =ctk.StringVar(value="0")
stream = ctk.IntVar()
smartcontext = ctk.IntVar()
unbantokens = ctk.IntVar()
usemirostat = ctk.IntVar()
mirostat_var = ctk.StringVar(value="2")
mirostat_tau = ctk.StringVar(value="5.0")
mirostat_eta = ctk.StringVar(value="0.1")
context_var = ctk.IntVar()
customrope_var = ctk.IntVar()
customrope_scale = ctk.StringVar(value="1.0")
customrope_base = ctk.StringVar(value="10000")
model_var = ctk.StringVar()
lora_var = ctk.StringVar()
lora_base_var = ctk.StringVar()
port_var = ctk.StringVar(value=defaultport)
host_var = ctk.StringVar(value="")
horde_name_var = ctk.StringVar(value="koboldcpp")
horde_gen_var = ctk.StringVar(value=maxhordelen)
horde_context_var = ctk.StringVar(value=maxhordectx)
horde_apikey_var = ctk.StringVar(value="")
horde_workername_var = ctk.StringVar(value="")
usehorde_var = ctk.IntVar()
# Quick Launch Tab
quick_tab = tabcontent["Quick Launch"]
def changerunmode(a,b,c):
index = runopts_var.get()
if index == "Use CLBlast" or index == "Use CuBLAS/hipBLAS":
gpu_selector_label.grid(row=3, column=0, padx = 8, pady=1, stick="nw")
quick_gpu_selector_label.grid(row=3, column=0, padx = 8, pady=1, stick="nw")
if index == "Use CLBlast":
gpu_selector_box.grid(row=3, column=1, padx=8, pady=1, stick="nw")
quick_gpu_selector_box.grid(row=3, column=1, padx=8, pady=1, stick="nw")
if gpu_choice_var.get()=="All":
gpu_choice_var.set("1")
elif index == "Use CuBLAS/hipBLAS":
CUDA_gpu_selector_box.grid(row=3, column=1, padx=8, pady=1, stick="nw")
CUDA_quick_gpu_selector_box.grid(row=3, column=1, padx=8, pady=1, stick="nw")
else:
gpu_selector_label.grid_forget()
gpu_selector_box.grid_forget()
CUDA_gpu_selector_box.grid_forget()
quick_gpu_selector_label.grid_forget()
quick_gpu_selector_box.grid_forget()
CUDA_quick_gpu_selector_box.grid_forget()
if index == "Use CuBLAS/hipBLAS":
lowvram_box.grid(row=4, column=0, padx=8, pady=1, stick="nw")
quick_lowvram_box.grid(row=4, column=0, padx=8, pady=1, stick="nw")
mmq_box.grid(row=4, column=1, padx=8, pady=1, stick="nw")
quick_mmq_box.grid(row=4, column=1, padx=8, pady=1, stick="nw")
else:
lowvram_box.grid_forget()
quick_lowvram_box.grid_forget()
mmq_box.grid_forget()
quick_mmq_box.grid_forget()
if index == "Use CLBlast" or index == "Use CuBLAS/hipBLAS":
gpu_layers_label.grid(row=5, column=0, padx = 8, pady=1, stick="nw")
gpu_layers_entry.grid(row=5, column=1, padx=8, pady=1, stick="nw")
quick_gpu_layers_label.grid(row=5, column=0, padx = 8, pady=1, stick="nw")
quick_gpu_layers_entry.grid(row=5, column=1, padx=8, pady=1, stick="nw")
else:
gpu_layers_label.grid_forget()
gpu_layers_entry.grid_forget()
quick_gpu_layers_label.grid_forget()
quick_gpu_layers_entry.grid_forget()
# presets selector
makelabel(quick_tab, "Presets:", 1)
runoptbox = ctk.CTkComboBox(quick_tab, values=runopts, width=180,variable=runopts_var, state="readonly")
runoptbox.grid(row=1, column=1,padx=8, stick="nw")
runoptbox.set(runopts[0]) # Set to first available option
# Tell user how many backends are available
setup_backend_tooltip(quick_tab)
# gpu options
quick_gpu_selector_label = makelabel(quick_tab, "GPU ID:", 3)
quick_gpu_selector_box = ctk.CTkComboBox(quick_tab, values=["1","2","3"], width=60, variable=gpu_choice_var, state="readonly")
CUDA_quick_gpu_selector_box = ctk.CTkComboBox(quick_tab, values=["1","2","3","All"], width=60, variable=gpu_choice_var, state="readonly")
quick_gpu_layers_entry,quick_gpu_layers_label = makelabelentry(quick_tab,"GPU Layers:", gpulayers_var, 5, 50)
quick_lowvram_box = makecheckbox(quick_tab, "Low VRAM", lowvram_var, 4,0)
quick_mmq_box = makecheckbox(quick_tab, "Use QuantMatMul (mmq)", mmq_var, 4,1)
# threads
makelabelentry(quick_tab, "Threads:" , threads_var, 8, 50)
# blas batch size
makeslider(quick_tab, "BLAS Batch Size:", blasbatchsize_text, blas_size_var, 0, 7, 12, set=5)
# quick boxes
quick_boxes = {"Launch Browser": launchbrowser , "High Priority" : highpriority, "Streaming Mode":stream, "Use SmartContext":smartcontext, "Unban Tokens":unbantokens, "Disable MMAP":disablemmap,}
for idx, name, in enumerate(quick_boxes):
makecheckbox(quick_tab, name, quick_boxes[name], int(idx/2) +20, idx%2)
# context size
makeslider(quick_tab, "Context Size:", contextsize_text, context_var, 0, len(contextsize_text)-1, 30, set=2)
# load model
makefileentry(quick_tab, "Model:", "Select GGML Model File", model_var, 40, 170)
# Hardware Tab
hardware_tab = tabcontent["Hardware"]
# presets selector
makelabel(hardware_tab, "Presets:", 1)
runoptbox = ctk.CTkComboBox(hardware_tab, values=runopts, width=180,variable=runopts_var, state="readonly")
runoptbox.grid(row=1, column=1,padx=8, stick="nw")
runoptbox.set(runopts[0]) # Set to first available option
# Tell user how many backends are available
setup_backend_tooltip(hardware_tab)
# gpu options
gpu_selector_label = makelabel(hardware_tab, "GPU ID:", 3)
gpu_selector_box = ctk.CTkComboBox(hardware_tab, values=["1","2","3"], width=60, variable=gpu_choice_var, state="readonly")
CUDA_gpu_selector_box = ctk.CTkComboBox(hardware_tab, values=["1","2","3", "All"], width=60, variable=gpu_choice_var, state="readonly")