koboldcpp/koboldcpp.py
2023-04-03 10:35:18 +08:00

366 lines
15 KiB
Python

# A hacky little script from Concedo that exposes llama.cpp function bindings
# allowing it to be used via a simulated kobold api endpoint
# it's not very usable as there is a fundamental flaw with llama.cpp
# which causes generation delay to scale linearly with original prompt length.
import ctypes
import os
import psutil
import argparse
import json, http.server, threading, socket, sys, time
class load_model_inputs(ctypes.Structure):
_fields_ = [("threads", ctypes.c_int),
("max_context_length", ctypes.c_int),
("batch_size", ctypes.c_int),
("f16_kv", ctypes.c_bool),
("model_filename", ctypes.c_char_p),
("n_parts_overwrite", ctypes.c_int)]
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_p", ctypes.c_float),
("rep_pen", ctypes.c_float),
("rep_pen_range", ctypes.c_int)]
class generation_outputs(ctypes.Structure):
_fields_ = [("status", ctypes.c_int),
("text", ctypes.c_char * 16384)]
handle = None
use_blas = False # if true, uses OpenBLAS for acceleration. libopenblas.dll must exist in the same dir.
def init_library():
global handle, use_blas
libname = ""
if use_blas:
libname = "koboldcpp_blas.dll"
else:
libname = "koboldcpp.dll"
print("Initializing dynamic library: " + libname)
dir_path = os.path.dirname(os.path.realpath(__file__))
#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
def load_model(model_filename,batch_size=8,max_context_length=512,n_parts_overwrite=-1,threads=6):
inputs = load_model_inputs()
inputs.model_filename = model_filename.encode("UTF-8")
inputs.batch_size = batch_size
inputs.max_context_length = max_context_length #initial value to use for ctx, can be overwritten
inputs.threads = threads
inputs.n_parts_overwrite = n_parts_overwrite
inputs.f16_kv = True
ret = handle.load_model(inputs)
return ret
def generate(prompt,max_length=20, max_context_length=512,temperature=0.8,top_k=100,top_p=0.85,rep_pen=1.1,rep_pen_range=128,seed=-1):
inputs = generation_inputs()
outputs = ctypes.create_unicode_buffer(ctypes.sizeof(generation_outputs))
inputs.prompt = prompt.encode("UTF-8")
inputs.max_context_length = max_context_length # this will resize the context buffer if changed
inputs.max_length = max_length
inputs.temperature = temperature
inputs.top_k = top_k
inputs.top_p = top_p
inputs.rep_pen = rep_pen
inputs.rep_pen_range = rep_pen_range
inputs.seed = seed
ret = handle.generate(inputs,outputs)
if(ret.status==1):
return ret.text.decode("UTF-8","ignore")
return ""
#################################################################
### 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
maxlen = 128
modelbusy = False
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 do_GET(self):
global maxctx, maxlen, friendlymodelname
if self.path in ["/", "/?"] or self.path.startswith(('/?','?')): #it's possible for the root url to have ?params without /
response_body = ""
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
self.send_response(200)
self.send_header('Content-Length', str(len(response_body)))
self.end_headers()
self.wfile.write(response_body)
return
self.path = self.path.rstrip('/')
if self.path.endswith(('/api/v1/model', '/api/latest/model')):
self.send_response(200)
self.end_headers()
result = {'result': friendlymodelname }
self.wfile.write(json.dumps(result).encode())
return
if self.path.endswith(('/api/v1/config/max_length', '/api/latest/config/max_length')):
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps({"value": maxlen}).encode())
return
if self.path.endswith(('/api/v1/config/max_context_length', '/api/latest/config/max_context_length')):
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps({"value": maxctx}).encode())
return
if self.path.endswith(('/api/v1/config/soft_prompt', '/api/latest/config/soft_prompt')):
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps({"value":""}).encode())
return
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())
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
self.path = self.path.rstrip('/')
if modelbusy:
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
if self.path.endswith('/request'):
basic_api_flag = True
if self.path.endswith(('/api/v1/generate', '/api/latest/generate')):
kai_api_flag = True
if basic_api_flag or kai_api_flag:
genparams = None
try:
genparams = json.loads(body)
except ValueError as e:
self.send_response(503)
self.end_headers()
return
print("\nInput: " + json.dumps(genparams))
modelbusy = True
if kai_api_flag:
fullprompt = genparams.get('prompt', "")
else:
fullprompt = genparams.get('text', "")
newprompt = fullprompt
recvtxt = ""
if kai_api_flag:
recvtxt = 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', 200),
top_p=genparams.get('top_p', 0.85),
rep_pen=genparams.get('rep_pen', 1.1),
rep_pen_range=genparams.get('rep_pen_range', 128),
seed=-1
)
print("\nOutput: " + recvtxt)
res = {"results": [{"text": recvtxt}]}
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps(res).encode())
else:
recvtxt = generate(
prompt=newprompt,
max_length=genparams.get('max', 50),
temperature=genparams.get('temperature', 0.8),
top_k=genparams.get('top_k', 200),
top_p=genparams.get('top_p', 0.85),
rep_pen=genparams.get('rep_pen', 1.1),
rep_pen_range=genparams.get('rep_pen_range', 128),
seed=-1
)
print("\nOutput: " + recvtxt)
res = {"data": {"seqs":[recvtxt]}}
self.send_response(200)
self.end_headers()
self.wfile.write(json.dumps(res).encode())
modelbusy = False
return
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:
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):
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):
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):
self.httpd.server_close()
sys.exit(0)
finally:
self.httpd.server_close()
sys.exit(0)
def stop(self):
self.httpd.server_close()
numThreads = 5
threadArr = []
for i in range(numThreads):
threadArr.append(Thread(i))
while 1:
try:
time.sleep(10)
except KeyboardInterrupt:
for i in range(numThreads):
threadArr[i].stop()
sys.exit(0)
def main(args):
global use_blas
if not os.path.exists(os.path.join(os.path.dirname(os.path.realpath(__file__)), "libopenblas.dll")) or not os.path.exists(os.path.join(os.path.dirname(os.path.realpath(__file__)), "koboldcpp_blas.dll")):
print("Warning: libopenblas.dll or koboldcpp_blas.dll not found. Non-BLAS library will be used. Ignore this if you have manually linked with OpenBLAS.")
use_blas = False
elif os.name != 'nt':
print("Prebuilt OpenBLAS binaries only available for windows. Please manually build/link libopenblas from makefile with LLAMA_OPENBLAS=1")
use_blas = False
elif not args.noblas:
print("Attempting to use OpenBLAS library for faster prompt ingestion. A compatible libopenblas.dll will be required.")
use_blas = True
init_library() # Note: if blas does not exist and is enabled, program will crash.
ggml_selected_file = args.model_file
embedded_kailite = None
if not ggml_selected_file:
#give them a chance to pick a file
print("Please manually select ggml file:")
from tkinter.filedialog import askopenfilename
ggml_selected_file = askopenfilename (title="Select ggml model .bin files")
if not ggml_selected_file:
print("\nNo ggml model file was selected. Exiting.")
time.sleep(1)
sys.exit(2)
if not os.path.exists(ggml_selected_file):
print(f"Cannot find model file: {ggml_selected_file}")
time.sleep(1)
sys.exit(2)
mdl_nparts = sum(1 for n in range(1, 9) if os.path.exists(f"{ggml_selected_file}.{n}")) + 1
modelname = os.path.abspath(ggml_selected_file)
print(f"Loading model: {modelname} \n[Parts: {mdl_nparts}, Threads: {args.threads}]")
loadok = load_model(modelname,8,maxctx,mdl_nparts,args.threads)
print("Load Model OK: " + str(loadok))
if not loadok:
print("Could not load model: " + modelname)
time.sleep(1)
sys.exit(3)
try:
basepath = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(basepath, "klite.embd"), mode='rb') as f:
embedded_kailite = f.read()
print("Embedded Kobold Lite loaded.")
except:
print("Could not find Kobold Lite. Embedded Kobold Lite will not be available.")
print(f"Starting Kobold HTTP Server on port {args.port}")
epurl = ""
if args.host=="":
epurl = f"http://localhost:{args.port}" + ("?streaming=1" if args.stream else "")
else:
epurl = f"http://{args.host}:{args.port}?host={args.host}" + ("&streaming=1" if args.stream else "")
print(f"Please connect to custom endpoint at {epurl}")
RunServerMultiThreaded(args.host, args.port, embedded_kailite)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Kobold llama.cpp server')
parser.add_argument("model_file", help="Model file to load", nargs="?")
portgroup = parser.add_mutually_exclusive_group() #we want to be backwards compatible with the unnamed positional args
portgroup.add_argument("--port", help="Port to listen on", default=5001, type=int)
portgroup.add_argument("port", help="Port to listen on", default=5001, nargs="?", type=int)
parser.add_argument("--host", help="Host IP to listen on. If empty, all routable interfaces are accepted.", default="")
physical_core_limit = psutil.cpu_count(logical=False)
# logical_core_limit = (os.cpu_count() if os.cpu_count()<=4 else max(4,os.cpu_count()-4))
default_threads = (physical_core_limit if physical_core_limit<=4 else max(4,physical_core_limit-1))
parser.add_argument("--threads", help="Use a custom number of threads if specified. Otherwise, uses an amount based on CPU cores", type=int, default=default_threads)
parser.add_argument("--stream", help="Uses pseudo streaming", action='store_true')
parser.add_argument("--noblas", help="Do not use OpenBLAS for accelerated prompt ingestion", action='store_true')
args = parser.parse_args()
main(args)