lollms-webui/app.py

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

class Gpt4AllWebUI:
    def __init__(self, _app, args) -> None:
        self.args = args
        self.current_discussion = None
        self.app = _app
        self.db_path = args.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 = ""

        # 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(
            "/update_model_params", "update_model_params", self.update_model_params, methods=["POST"]
        )

        self.add_endpoint(
            "/get_args", "get_args", self.get_args, 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):
        try:
            discussions = self.db.get_discussions()
            return jsonify(discussions)
        except Exception as ex:
            print(ex)
            return jsonify({
                "status":"Error",
                "content":                "<b style='color:red;'>Exception :<b>"
                + str(ex)
                + "<br>"
                + traceback.format_exc()
                + "<br>Please report exception"
            })


    def prepare_a_new_chatbot(self):
        # Create chatbot
        self.chatbot_bindings = self.create_chatbot()
        # Chatbot conditionning
        self.condition_chatbot()
        

    def create_chatbot(self):
        return Model(
            ggml_model=f"./models/{self.args.model}", 
            n_ctx=self.args.ctx_size, 
            seed=self.args.seed,
            )

    def condition_chatbot(self, conditionning_message = """
Instruction: Act as GPT4All. A kind and helpful AI bot built to help users solve problems.
GPT4All:Welcome! I'm here to assist you with anything you need. What can I do for you today?"""
                          ):
        self.full_message += conditionning_message +"\n"

        # self.prepare_query(conditionning_message)
        # self.chatbot_bindings.generate(
        #     conditionning_message,
        #     new_text_callback=self.new_text_callback,

        #     n_predict=len(conditionning_message),
        #     temp=self.args.temp,
        #     top_k=self.args.top_k,
        #     top_p=self.args.top_p,
        #     repeat_penalty=self.args.repeat_penalty,
        #     repeat_last_n = self.args.repeat_last_n,
        #     seed=self.args.seed,
        #     n_threads=8
        # )
        # print(f"Bot said:{self.bot_says}")        


    def prepare_query(self, message):
        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:
            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.full_message,#self.current_message,
            new_text_callback=self.new_text_callback,
            n_predict=len(self.current_message)+self.args.n_predict,
            temp=self.args.temp,
            top_k=self.args.top_k,
            top_p=self.args.top_p,
            repeat_penalty=self.args.repeat_penalty,
            repeat_last_n = self.args.repeat_last_n,
            #seed=self.args.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(
            "GPT4All", ""
        )  # 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 = "\nUser: " + message + "\nGPT4All: "
        self.full_message += self.current_message
        self.prepare_query(self.full_message)
        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)
        #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

        try:
            if self.current_discussion is None or not self.db.does_last_discussion_have_messages(
                self.db_path
            ):
                self.current_discussion = DiscussionsDB.create_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)
                )
            )
        except Exception as ex:
            print(ex)
            return (
                "<b style='color:red;'>Exception :<b>"
                + str(ex)
                + "<br>"
                + traceback.format_exc()
                + "<br>Please report exception"
            )


    def rename(self):
        data = request.get_json()
        discussion_id = data["id"]
        title = data["title"]
        Discussion.rename(self.db_path, discussion_id, title)
        return "renamed successfully"

    def restore_discussion(self, full_message):
        self.chatbot_bindings.generate(
            full_message,
            new_text_callback=self.new_text_callback,
            n_predict=0,#len(full_message),
            temp=self.args.temp,
            top_k=self.args.top_k,
            top_p=self.args.top_p,
            repeat_penalty= self.args.repeat_penalty,
            repeat_last_n = self.args.repeat_last_n,
            n_threads=8
        )

    def load_discussion(self):
        data = request.get_json()
        discussion_id = data["id"]
        self.current_discussion = Discussion(discussion_id, self.db)
        messages = self.current_discussion.get_messages()
        
        self.full_message = ""
        for message in messages:
            self.full_message += message['sender'] + ": " + message['content'] + "\n"
        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_path)
        self.current_discussion.delete_discussion()
        self.current_discussion = None
        return jsonify({})

    def update_message(self):
        try:
            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"})
        except Exception as ex:
            print(ex)
            return (
                "<b style='color:red;'>Exception :<b>"
                + str(ex)
                + "<br>"
                + traceback.format_exc()
                + "<br>Please report exception"
            )

    def new_discussion(self):
        title = request.args.get("title")
        self.current_discussion = Discussion.create_discussion(self.db_path, title)
        # Get the current timestamp
        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")

        app.config['executor'].submit(self.prepare_a_new_chatbot)
        # Return a success response
        return json.dumps({"id": self.current_discussion.discussion_id, "time": timestamp})

    def update_model_params(self):
        data = request.get_json()
        model =  str(data["model"])
        if self.args.model != model:
            print("New model selected")
            self.args.model = model
            self.prepare_a_new_chatbot()

        self.args.n_predict = int(data["nPredict"])
        self.args.seed = int(data["seed"])
        
        self.args.temp = float(data["temp"])
        self.args.top_k = int(data["topK"])
        self.args.top_p = float(data["topP"])
        self.args.repeat_penalty = int(data["repeatPenalty"])
        self.args.repeat_last_n = int(data["repeatLastN"])

        print("Parameters changed to:")
        print(f"\tTemperature:{self.args.temp}")
        print(f"\tNPredict:{self.args.n_predict}")
        print(f"\tSeed:{self.args.seed}")
        print(f"\top_k:{self.args.top_k}")
        print(f"\top_p:{self.args.top_p}")
        print(f"\trepeat_penalty:{self.args.repeat_penalty}")
        print(f"\trepeat_last_n:{self.args.repeat_last_n}")
        return jsonify({"status":"ok"})
    
    
    def get_args(self):
        return jsonify(self.args)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Start the chatbot Flask app.")
    parser.add_argument(
        "-s", "--seed", type=int, default=0, help="Force using a specific model."
    )

    parser.add_argument(
        "-m", "--model", type=str, default="gpt4all-lora-quantized-ggml.bin", help="Force using a specific model."
    )
    parser.add_argument(
        "--temp", type=float, default=0.1, help="Temperature parameter for the model."
    )
    parser.add_argument(
        "--n_predict",
        type=int,
        default=256,
        help="Number of tokens to predict at each step.",
    )
    parser.add_argument(
        "--top_k", type=int, default=40, help="Value for the top-k sampling."
    )
    parser.add_argument(
        "--top_p", type=float, default=0.95, help="Value for the top-p sampling."
    )
    parser.add_argument(
        "--repeat_penalty", type=float, default=1.3, help="Penalty for repeated tokens."
    )
    parser.add_argument(
        "--repeat_last_n",
        type=int,
        default=64,
        help="Number of previous tokens to consider for the repeat penalty.",
    )
    parser.add_argument(
        "--ctx_size",
        type=int,
        default=512,#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="localhost", help="the hostname to listen on"
    )
    parser.add_argument("--port", type=int, default=9600, help="the port to listen on")
    parser.add_argument(
        "--db_path", type=str, default="database.db", help="Database path"
    )
    parser.set_defaults(debug=False)
    args = parser.parse_args()

    executor = ThreadPoolExecutor(max_workers=2)
    app.config['executor'] = executor

    bot = Gpt4AllWebUI(app, args)

    if args.debug:
        app.run(debug=True, host=args.host, port=args.port)
    else:
        app.run(host=args.host, port=args.port)