This commit is contained in:
Michael Yang 2023-06-27 12:19:34 -07:00
parent 8750e9889f
commit 1ae91f75f0
7 changed files with 196 additions and 216 deletions

219
ollama.py
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import json
import os
import threading
import click
from tqdm import tqdm
from pathlib import Path
from llama_cpp import Llama
from flask import Flask, Response, stream_with_context, request
from flask_cors import CORS
from template import template
app = Flask(__name__)
CORS(app) # enable CORS for all routes
# llms tracks which models are loaded
llms = {}
lock = threading.Lock()
def models_directory():
home_dir = Path.home()
models_dir = home_dir / ".ollama/models"
if not models_dir.exists():
models_dir.mkdir(parents=True)
return models_dir
def load(model):
"""
Load a model.
Args:
model (str): The name or path of the model to load.
Returns:
str or None: The name of the model
dict or None: If the model cannot be loaded, a dictionary with an 'error' key is returned.
If the model is successfully loaded, None is returned.
"""
with lock:
load_from = ""
if os.path.exists(model) and model.endswith(".bin"):
# model is being referenced by path rather than name directly
path = os.path.abspath(model)
base = os.path.basename(path)
load_from = path
name = os.path.splitext(base)[0] # Split the filename and extension
else:
# model is being loaded from the ollama models directory
dir = models_directory()
# TODO: download model from a repository if it does not exist
load_from = str(dir / f"{model}.bin")
name = model
if load_from == "":
return None, {"error": "Model not found."}
if not os.path.exists(load_from):
return None, {"error": f"The model {load_from} does not exist."}
if name not in llms:
llms[name] = Llama(model_path=load_from)
return name, None
def unload(model):
"""
Unload a model.
Remove a model from the list of loaded models. If the model is not loaded, this is a no-op.
Args:
model (str): The name of the model to unload.
"""
llms.pop(model, None)
def generate(model, prompt):
# auto load
name, error = load(model)
if error is not None:
return error
generated = llms[name](
str(prompt), # TODO: optimize prompt based on model
max_tokens=4096,
stop=["Q:", "\n"],
stream=True,
)
for output in generated:
yield json.dumps(output)
def models():
dir = models_directory()
all_files = os.listdir(dir)
bin_files = [
file.replace(".bin", "") for file in all_files if file.endswith(".bin")
]
return bin_files
@app.route("/load", methods=["POST"])
def load_route_handler():
data = request.get_json()
model = data.get("model")
if not model:
return Response("Model is required", status=400)
error = load(model)
if error is not None:
return error
return Response(status=204)
@app.route("/unload", methods=["POST"])
def unload_route_handler():
data = request.get_json()
model = data.get("model")
if not model:
return Response("Model is required", status=400)
unload(model)
return Response(status=204)
@app.route("/generate", methods=["POST"])
def generate_route_handler():
data = request.get_json()
model = data.get("model")
prompt = data.get("prompt")
prompt = template(model, prompt)
if not model:
return Response("Model is required", status=400)
if not prompt:
return Response("Prompt is required", status=400)
if not os.path.exists(f"{model}"):
return {"error": "The model does not exist."}, 400
return Response(
stream_with_context(generate(model, prompt)), mimetype="text/event-stream"
)
@app.route("/models", methods=["GET"])
def models_route_handler():
bin_files = models()
return Response(json.dumps(bin_files), mimetype="application/json")
@click.group(invoke_without_command=True)
@click.pass_context
def cli(ctx):
# allows the script to respond to command line input when executed directly
if ctx.invoked_subcommand is None:
click.echo(ctx.get_help())
@cli.command()
@click.option("--port", default=7734, help="Port to run the server on")
@click.option("--debug", default=False, help="Enable debug mode")
def serve(port, debug):
print("Serving on http://localhost:{port}")
app.run(host="0.0.0.0", port=port, debug=debug)
@cli.command(name="load")
@click.argument("model")
@click.option("--file", default=False, help="Indicates that a file path is provided")
def load_cli(model, file):
if file:
error = load(path=model)
else:
error = load(model)
if error is not None:
print(error)
return
print("Model loaded")
@cli.command(name="generate")
@click.argument("model")
@click.option("--prompt", default="", help="The prompt for the model")
def generate_cli(model, prompt):
if prompt == "":
prompt = input("Prompt: ")
output = ""
prompt = template(model, prompt)
for generated in generate(model, prompt):
generated_json = json.loads(generated)
text = generated_json["choices"][0]["text"]
output += text
print(f"\r{output}", end="", flush=True)
@cli.command(name="models")
def models_cli():
print(models())
@cli.command(name="pull")
@click.argument("model")
def pull_cli(model):
print("not implemented")
@cli.command(name="import")
@click.argument("model")
def import_cli(model):
print("not implemented")
if __name__ == "__main__":
cli()
from ollama.cmd.cli import main
if __name__ == '__main__':
main()

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ollama/__init__.py Normal file
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from ollama.model import models
from ollama.engine import generate, load, unload
__all__ = [
'models',
'generate',
'load',
'unload',
]

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ollama/cmd/__init__.py Normal file
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ollama/cmd/cli.py Normal file
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import json
from pathlib import Path
from argparse import ArgumentParser
from ollama import model, engine
from ollama.cmd import server
def main():
parser = ArgumentParser()
parser.add_argument('--models-home', default=Path.home() / '.ollama' / 'models')
subparsers = parser.add_subparsers()
server.set_parser(subparsers.add_parser('serve'))
list_parser = subparsers.add_parser('list')
list_parser.set_defaults(fn=list)
generate_parser = subparsers.add_parser('generate')
generate_parser.add_argument('model')
generate_parser.add_argument('prompt')
generate_parser.set_defaults(fn=generate)
args = parser.parse_args()
args = vars(args)
fn = args.pop('fn')
fn(**args)
def list(*args, **kwargs):
for m in model.models(*args, **kwargs):
print(m)
def generate(*args, **kwargs):
for output in engine.generate(*args, **kwargs):
output = json.loads(output)
choices = output.get('choices', [])
if len(choices) > 0:
print(choices[0].get('text', ''), end='')

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ollama/cmd/server.py Normal file
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from aiohttp import web
from ollama import engine
def set_parser(parser):
parser.add_argument('--host', default='127.0.0.1')
parser.add_argument('--port', default=7734)
parser.set_defaults(fn=serve)
def serve(models_home='.', *args, **kwargs):
app = web.Application()
app.add_routes([
web.post('/load', load),
web.post('/unload', unload),
web.post('/generate', generate),
])
app.update({
'llms': {},
'models_home': models_home,
})
web.run_app(app, **kwargs)
async def load(request):
body = await request.json()
model = body.get('model')
if not model:
raise web.HTTPBadRequest()
kwargs = {
'llms': request.app.get('llms'),
'models_home': request.app.get('models_home'),
}
engine.load(model, **kwargs)
return web.Response()
async def unload(request):
body = await request.json()
model = body.get('model')
if not model:
raise web.HTTPBadRequest()
engine.unload(model, llms=request.app.get('llms'))
return web.Response()
async def generate(request):
body = await request.json()
model = body.get('model')
if not model:
raise web.HTTPBadRequest()
prompt = body.get('prompt')
if not prompt:
raise web.HTTPBadRequest()
response = web.StreamResponse()
await response.prepare(request)
kwargs = {
'llms': request.app.get('llms'),
'models_home': request.app.get('models_home'),
}
for output in engine.generate(model, prompt, **kwargs):
await response.write(output.encode('utf-8'))
await response.write(b'\n')
return response

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ollama/engine.py Normal file
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import os
import json
import sys
from contextlib import contextmanager
from llama_cpp import Llama as LLM
import ollama.model
@contextmanager
def suppress_stderr():
stderr = os.dup(sys.stderr.fileno())
with open(os.devnull, 'w') as devnull:
os.dup2(devnull.fileno(), sys.stderr.fileno())
yield
os.dup2(stderr, sys.stderr.fileno())
def generate(model, prompt, models_home='.', llms={}, *args, **kwargs):
llm = load(model, models_home=models_home, llms=llms)
if 'max_tokens' not in kwargs:
kwargs.update({'max_tokens': 16384})
if 'stop' not in kwargs:
kwargs.update({'stop': ['Q:', '\n']})
if 'stream' not in kwargs:
kwargs.update({'stream': True})
for output in llm(prompt, *args, **kwargs):
yield json.dumps(output)
def load(model, models_home='.', llms={}):
llm = llms.get(model, None)
if not llm:
model_path = {
name: path
for name, path in ollama.model.models(models_home)
}.get(model, None)
if model_path is None:
raise ValueError('Model not found')
# suppress LLM's output
with suppress_stderr():
llm = LLM(model_path, verbose=False)
llms.update({model: llm})
return llm
def unload(model, llms={}):
if model in llms:
llms.pop(model)

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ollama/model.py Normal file
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from os import walk, path
def models(models_home='.', *args, **kwargs):
for root, _, files in walk(models_home):
for file in files:
base, ext = path.splitext(file)
if ext == '.bin':
yield base, path.join(root, file)