lollms-webui/app.py
Saifeddine ALOUI 7e5cbfdc15 Upgraded code
2023-04-13 21:40:46 +02:00

540 lines
18 KiB
Python

######
# Project : GPT4ALL-UI
# Author : ParisNeo with the help of the community
# Supported by Nomic-AI
# Licence : Apache 2.0
# Description :
# A front end Flask application for llamacpp models.
# The official GPT4All Web ui
# Made by the community for the community
######
import argparse
import json
import re
import traceback
from datetime import datetime
from concurrent.futures import ThreadPoolExecutor
import sys
from db import DiscussionsDB, Discussion
from flask import (
Flask,
Response,
jsonify,
render_template,
request,
stream_with_context,
send_from_directory
)
from pyllamacpp.model import Model
from queue import Queue
from pathlib import Path
import gc
app = Flask("GPT4All-WebUI", static_url_path="/static", static_folder="static")
import time
from config import load_config
class Gpt4AllWebUI:
def __init__(self, _app, config:dict, personality:dict) -> None:
self.config = config
self.personality = personality
self.current_discussion = None
self.current_message_id = 0
self.app = _app
self.db_path = config["db_path"]
self.db = DiscussionsDB(self.db_path)
# If the database is empty, populate it with tables
self.db.populate()
# workaround for non interactive mode
self.full_message = ""
self.full_message_list = []
self.prompt_message = ""
# This is the queue used to stream text to the ui as the bot spits out its response
self.text_queue = Queue(0)
self.add_endpoint(
"/list_models", "list_models", self.list_models, methods=["GET"]
)
self.add_endpoint(
"/list_discussions", "list_discussions", self.list_discussions, methods=["GET"]
)
self.add_endpoint("/", "", self.index, methods=["GET"])
self.add_endpoint("/export_discussion", "export_discussion", self.export_discussion, methods=["GET"])
self.add_endpoint("/export", "export", self.export, methods=["GET"])
self.add_endpoint(
"/new_discussion", "new_discussion", self.new_discussion, methods=["GET"]
)
self.add_endpoint("/bot", "bot", self.bot, methods=["POST"])
self.add_endpoint("/rename", "rename", self.rename, methods=["POST"])
self.add_endpoint(
"/load_discussion", "load_discussion", self.load_discussion, methods=["POST"]
)
self.add_endpoint(
"/delete_discussion",
"delete_discussion",
self.delete_discussion,
methods=["POST"],
)
self.add_endpoint(
"/update_message", "update_message", self.update_message, methods=["GET"]
)
self.add_endpoint(
"/message_rank_up", "message_rank_up", self.message_rank_up, methods=["GET"]
)
self.add_endpoint(
"/message_rank_down", "message_rank_down", self.message_rank_down, methods=["GET"]
)
self.add_endpoint(
"/delete_message", "delete_message", self.delete_message, methods=["GET"]
)
self.add_endpoint(
"/update_model_params", "update_model_params", self.update_model_params, methods=["POST"]
)
self.add_endpoint(
"/get_config", "get_config", self.get_config, methods=["GET"]
)
self.add_endpoint(
"/extensions", "extensions", self.extensions, methods=["GET"]
)
self.add_endpoint(
"/training", "training", self.training, methods=["GET"]
)
self.add_endpoint(
"/main", "main", self.main, methods=["GET"]
)
self.add_endpoint(
"/settings", "settings", self.settings, methods=["GET"]
)
self.add_endpoint(
"/help", "help", self.help, methods=["GET"]
)
self.prepare_a_new_chatbot()
def list_models(self):
models_dir = Path('./models') # replace with the actual path to the models folder
models = [f.name for f in models_dir.glob('*.bin')]
return jsonify(models)
def list_discussions(self):
discussions = self.db.get_discussions()
return jsonify(discussions)
def prepare_a_new_chatbot(self):
# Create chatbot
self.chatbot_bindings = self.create_chatbot()
def create_chatbot(self):
return Model(
ggml_model=f"./models/{self.config['model']}",
n_ctx=self.config['ctx_size'],
seed=self.config['seed'],
)
def condition_chatbot(self, conditionning_message):
if self.current_discussion is None:
self.current_discussion = self.db.load_last_discussion()
message_id = self.current_discussion.add_message(
"conditionner",
conditionning_message,
DiscussionsDB.MSG_TYPE_CONDITIONNING,
0,
self.current_message_id
)
self.current_message_id = message_id
if self.personality["welcome_message"]!="":
message_id = self.current_discussion.add_message(
self.personality["name"], self.personality["welcome_message"],
DiscussionsDB.MSG_TYPE_NORMAL,
0,
self.current_message_id
)
self.current_message_id = message_id
return message_id
def prepare_query(self):
self.bot_says = ""
self.full_text = ""
self.is_bot_text_started = False
#self.current_message = message
def new_text_callback(self, text: str):
print(text, end="")
sys.stdout.flush()
self.full_text += text
if self.is_bot_text_started:
self.bot_says += text
self.full_message += text
self.text_queue.put(text)
#if self.current_message in self.full_text:
if len(self.prompt_message) <= len(self.full_text):
self.is_bot_text_started = True
def add_endpoint(
self,
endpoint=None,
endpoint_name=None,
handler=None,
methods=["GET"],
*args,
**kwargs,
):
self.app.add_url_rule(
endpoint, endpoint_name, handler, methods=methods, *args, **kwargs
)
def index(self):
return render_template("chat.html")
def format_message(self, message):
# Look for a code block within the message
pattern = re.compile(r"(```.*?```)", re.DOTALL)
match = pattern.search(message)
# If a code block is found, replace it with a <code> tag
if match:
code_block = match.group(1)
message = message.replace(code_block, f"<code>{code_block[3:-3]}</code>")
# Return the formatted message
return message
def export(self):
return jsonify(self.db.export_to_json())
def export_discussion(self):
return jsonify(self.full_message)
def generate_message(self):
self.generating=True
self.text_queue=Queue()
gc.collect()
self.chatbot_bindings.generate(
self.prompt_message,#self.full_message,#self.current_message,
new_text_callback=self.new_text_callback,
n_predict=len(self.current_message)+self.config['n_predict'],
temp=self.config['temp'],
top_k=self.config['top_k'],
top_p=self.config['top_p'],
repeat_penalty=self.config['repeat_penalty'],
repeat_last_n = self.config['repeat_last_n'],
#seed=self.config['seed'],
n_threads=8
)
self.generating=False
@stream_with_context
def parse_to_prompt_stream(self, message, message_id):
bot_says = ""
self.stop = False
# send the message to the bot
print(f"Received message : {message}")
# First we need to send the new message ID to the client
response_id = self.current_discussion.add_message(
self.personality["name"], ""
) # first the content is empty, but we'll fill it at the end
yield (
json.dumps(
{
"type": "input_message_infos",
"message": message,
"id": message_id,
"response_id": response_id,
}
)
)
self.current_message = self.personality["message_prefix"] + message + self.personality["message_suffix"]
self.full_message += self.current_message
self.full_message_list.append(self.current_message)
if len(self.full_message_list) > self.config["nb_messages_to_remember"]:
self.prompt_message = self.personality["personality_conditionning"]+ '\n'.join(self.full_message_list[-self.config["nb_messages_to_remember"]:])
else:
self.prompt_message = self.full_message
self.prepare_query()
self.generating = True
app.config['executor'].submit(self.generate_message)
while self.generating or not self.text_queue.empty():
try:
value = self.text_queue.get(False)
yield value
except :
time.sleep(1)
self.current_discussion.update_message(response_id, self.bot_says)
self.full_message_list.append(self.bot_says)
#yield self.bot_says# .encode('utf-8').decode('utf-8')
# TODO : change this to use the yield version in order to send text word by word
return "\n".join(bot_says)
def bot(self):
self.stop = True
if self.current_discussion is None:
if self.db.does_last_discussion_have_messages():
self.current_discussion = self.db.create_discussion()
else:
self.current_discussion = self.db.load_last_discussion()
message_id = self.current_discussion.add_message(
"user", request.json["message"]
)
message = f"{request.json['message']}"
# Segmented (the user receives the output as it comes)
# We will first send a json entry that contains the message id and so on, then the text as it goes
return Response(
stream_with_context(
self.parse_to_prompt_stream(message, message_id)
)
)
def rename(self):
data = request.get_json()
title = data["title"]
self.current_discussion.rename(title)
return "renamed successfully"
def restore_discussion(self, full_message):
self.prompt_message = full_message
if len(self.full_message_list)>5:
self.prompt_message = "\n".join(self.full_message_list[-5:])
self.chatbot_bindings.generate(
self.prompt_message,#full_message,
new_text_callback=self.new_text_callback,
n_predict=0,#len(full_message),
temp=self.config['temp'],
top_k=self.config['top_k'],
top_p=self.config['top_p'],
repeat_penalty= self.config['repeat_penalty'],
repeat_last_n = self.config['repeat_last_n'],
n_threads=8
)
def load_discussion(self):
data = request.get_json()
if "id" in data:
discussion_id = data["id"]
self.current_discussion = Discussion(discussion_id, self.db)
else:
if self.current_discussion is not None:
discussion_id = self.current_discussion.discussion_id
self.current_discussion = Discussion(discussion_id, self.db)
else:
self.current_discussion = self.db.create_discussion()
messages = self.current_discussion.get_messages()
self.full_message = ""
self.full_message_list = []
for message in messages:
if message['sender']!="conditionner":
self.full_message += message['sender'] + ": " + message['content'] + "\n"
self.full_message_list.append(message['sender'] + ": " + message['content'])
self.current_message_id=message['id']
app.config['executor'].submit(self.restore_discussion, self.full_message)
return jsonify(messages)
def delete_discussion(self):
data = request.get_json()
discussion_id = data["id"]
self.current_discussion = Discussion(discussion_id, self.db)
self.current_discussion.delete_discussion()
self.current_discussion = None
return jsonify({})
def update_message(self):
discussion_id = request.args.get("id")
new_message = request.args.get("message")
self.current_discussion.update_message(discussion_id, new_message)
return jsonify({"status": "ok"})
def message_rank_up(self):
discussion_id = request.args.get("id")
new_rank = self.current_discussion.message_rank_up(discussion_id)
return jsonify({"new_rank": new_rank})
def message_rank_down(self):
discussion_id = request.args.get("id")
new_rank = self.current_discussion.message_rank_down(discussion_id)
return jsonify({"new_rank": new_rank})
def delete_message(self):
discussion_id = request.args.get("id")
new_rank = self.current_discussion.delete_message(discussion_id)
return jsonify({"new_rank": new_rank})
def new_discussion(self):
title = request.args.get("title")
self.current_discussion = self.db.create_discussion(title)
# Get the current timestamp
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
app.config['executor'].submit(self.prepare_a_new_chatbot)
self.full_message =""
# Chatbot conditionning
self.condition_chatbot(self.personality["personality_conditionning"])
# Return a success response
return json.dumps({"id": self.current_discussion.discussion_id, "time": timestamp, "welcome_message":self.personality["welcome_message"]})
def update_model_params(self):
data = request.get_json()
model = str(data["model"])
if self.config['model'] != model:
print("New model selected")
self.config['model'] = model
self.prepare_a_new_chatbot()
self.config['n_predict'] = int(data["nPredict"])
self.config['seed'] = int(data["seed"])
self.config['temp'] = float(data["temp"])
self.config['top_k'] = int(data["topK"])
self.config['top_p'] = float(data["topP"])
self.config['repeat_penalty'] = float(data["repeatPenalty"])
self.config['repeat_last_n'] = int(data["repeatLastN"])
print("Parameters changed to:")
print(f"\tTemperature:{self.config['temp']}")
print(f"\tNPredict:{self.config['n_predict']}")
print(f"\tSeed:{self.config['seed']}")
print(f"\top_k:{self.config['top_k']}")
print(f"\top_p:{self.config['top_p']}")
print(f"\trepeat_penalty:{self.config['repeat_penalty']}")
print(f"\trepeat_last_n:{self.config['repeat_last_n']}")
return jsonify({"status":"ok"})
def get_config(self):
return jsonify(self.config)
def main(self):
return render_template("main.html")
def settings(self):
return render_template("settings.html")
def help(self):
return render_template("help.html")
def training(self):
return render_template("training.html")
def extensions(self):
return render_template("extensions.html")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Start the chatbot Flask app.")
parser.add_argument(
"-c", "--config", type=str, default="default", help="Sets the configuration file to be used."
)
parser.add_argument(
"-p", "--personality", type=str, default=None, help="Selects the personality to be using."
)
parser.add_argument(
"-s", "--seed", type=int, default=None, help="Force using a specific seed value."
)
parser.add_argument(
"-m", "--model", type=str, default=None, help="Force using a specific model."
)
parser.add_argument(
"--temp", type=float, default=None, help="Temperature parameter for the model."
)
parser.add_argument(
"--n_predict",
type=int,
default=None,
help="Number of tokens to predict at each step.",
)
parser.add_argument(
"--top_k", type=int, default=None, help="Value for the top-k sampling."
)
parser.add_argument(
"--top_p", type=float, default=None, help="Value for the top-p sampling."
)
parser.add_argument(
"--repeat_penalty", type=float, default=None, help="Penalty for repeated tokens."
)
parser.add_argument(
"--repeat_last_n",
type=int,
default=None,
help="Number of previous tokens to consider for the repeat penalty.",
)
parser.add_argument(
"--ctx_size",
type=int,
default=None,#2048,
help="Size of the context window for the model.",
)
parser.add_argument(
"--debug",
dest="debug",
action="store_true",
help="launch Flask server in debug mode",
)
parser.add_argument(
"--host", type=str, default=None, help="the hostname to listen on"
)
parser.add_argument("--port", type=int, default=None, help="the port to listen on")
parser.add_argument(
"--db_path", type=str, default=None, help="Database path"
)
parser.set_defaults(debug=False)
args = parser.parse_args()
config_file_path = f"configs/{args.config}.yaml"
config = load_config(config_file_path)
# Override values in config with command-line arguments
for arg_name, arg_value in vars(args).items():
if arg_value is not None:
config[arg_name] = arg_value
personality = load_config(f"personalities/{config['personality']}.yaml")
executor = ThreadPoolExecutor(max_workers=2)
app.config['executor'] = executor
bot = Gpt4AllWebUI(app, config, personality)
if config["debug"]:
app.run(debug=True, host=config["host"], port=config["port"])
else:
app.run(host=config["host"], port=config["port"])