lollms-webui/app.py

import argparse
import json
import re
import sqlite3
import traceback
from datetime import datetime

from flask import (
    Flask,
    Response,
    jsonify,
    render_template,
    request,
    stream_with_context,
)
from pyllamacpp.model import Model


# =================================== Database ==================================================================
class Discussion:
    def __init__(self, discussion_id, db_path="database.db"):
        self.discussion_id = discussion_id
        self.db_path = db_path

    @staticmethod
    def create_discussion(db_path="database.db", title="untitled"):
        with sqlite3.connect(db_path) as conn:
            cur = conn.cursor()
            cur.execute("INSERT INTO discussion (title) VALUES (?)", (title,))
            discussion_id = cur.lastrowid
            conn.commit()
        return Discussion(discussion_id, db_path)

    @staticmethod
    def get_discussion(db_path="database.db", discussion_id=0):
        return Discussion(discussion_id, db_path)

    def add_message(self, sender, content):
        with sqlite3.connect(self.db_path) as conn:
            cur = conn.cursor()
            cur.execute(
                "INSERT INTO message (sender, content, discussion_id) VALUES (?, ?, ?)",
                (sender, content, self.discussion_id),
            )
            message_id = cur.lastrowid
            conn.commit()
        return message_id

    @staticmethod
    def get_discussions(db_path):
        with sqlite3.connect(db_path) as conn:
            cursor = conn.cursor()
            cursor.execute("SELECT * FROM discussion")
            rows = cursor.fetchall()
        return [{"id": row[0], "title": row[1]} for row in rows]

    @staticmethod
    def rename(db_path, discussion_id, title):
        with sqlite3.connect(db_path) as conn:
            cursor = conn.cursor()
            cursor.execute(
                "UPDATE discussion SET title=? WHERE id=?", (title, discussion_id)
            )
            conn.commit()

    def delete_discussion(self):
        with sqlite3.connect(self.db_path) as conn:
            cur = conn.cursor()
            cur.execute(
                "DELETE FROM message WHERE discussion_id=?", (self.discussion_id,)
            )
            cur.execute("DELETE FROM discussion WHERE id=?", (self.discussion_id,))
            conn.commit()

    def get_messages(self):
        with sqlite3.connect(self.db_path) as conn:
            cur = conn.cursor()
            cur.execute(
                "SELECT * FROM message WHERE discussion_id=?", (self.discussion_id,)
            )
            rows = cur.fetchall()
        return [{"sender": row[1], "content": row[2], "id": row[0]} for row in rows]

    def update_message(self, message_id, new_content):
        with sqlite3.connect(self.db_path) as conn:
            cur = conn.cursor()
            cur.execute(
                "UPDATE message SET content = ? WHERE id = ?", (new_content, message_id)
            )
            conn.commit()

    def remove_discussion(self):
        with sqlite3.connect(self.db_path) as conn:
            conn.cursor().execute(
                "DELETE FROM discussion WHERE id=?", (self.discussion_id,)
            )
            conn.commit()


def last_discussion_has_messages(db_path="database.db"):
    with sqlite3.connect(db_path) as conn:
        cursor = conn.cursor()
        cursor.execute("SELECT * FROM message ORDER BY id DESC LIMIT 1")
        last_message = cursor.fetchone()
    return last_message is not None


def export_to_json(db_path="database.db"):
    with sqlite3.connect(db_path) as conn:
        cur = conn.cursor()
        cur.execute("SELECT * FROM discussion")
        discussions = []
        for row in cur.fetchall():
            discussion_id = row[0]
            discussion = {"id": discussion_id, "messages": []}
            cur.execute("SELECT * FROM message WHERE discussion_id=?", (discussion_id,))
            for message_row in cur.fetchall():
                discussion["messages"].append(
                    {"sender": message_row[1], "content": message_row[2]}
                )
            discussions.append(discussion)
        return discussions


def remove_discussions(db_path="database.db"):
    with sqlite3.connect(db_path) as conn:
        cur = conn.cursor()
        cur.execute("DELETE FROM message")
        cur.execute("DELETE FROM discussion")
        conn.commit()


# create database schema
def check_discussion_db(db_path):
    print("Checking discussions database...")
    with sqlite3.connect(db_path) as conn:
        cur = conn.cursor()
        cur.execute(
            """
            CREATE TABLE IF NOT EXISTS discussion (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                title TEXT
            )
        """
        )
        cur.execute(
            """
            CREATE TABLE IF NOT EXISTS message (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                sender TEXT NOT NULL,
                content TEXT NOT NULL,
                discussion_id INTEGER NOT NULL,
                FOREIGN KEY (discussion_id) REFERENCES discussion(id)
            )
        """
        )
        conn.commit()

    print("Ok")


# ========================================================================================================================


app = Flask("GPT4All-WebUI", static_url_path="/static", static_folder="static")


class Gpt4AllWebUI:
    def __init__(self, chatbot_bindings, _app, db_path="database.db") -> None:
        self.current_discussion = None
        self.chatbot_bindings = chatbot_bindings
        self.app = _app
        self.db_path = db_path
        self.add_endpoint("/", "", self.index, 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(
            "/discussions", "discussions", self.discussions, methods=["GET"]
        )
        self.add_endpoint("/rename", "rename", self.rename, methods=["POST"])
        self.add_endpoint(
            "/get_messages", "get_messages", self.get_messages, 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"]
        )

        conditionning_message = """
Instruction: Act as GPT4All. A kind and helpful AI bot built to help users solve problems.
Start by welcoming the user then stop sending text.
GPT4All:"""
        self.prepare_query(conditionning_message)
        chatbot_bindings.generate(
            conditionning_message,
            n_predict=55,
            new_text_callback=self.new_text_callback,
            n_threads=8,
        )
        print(f"Bot said:{self.bot_says}")
        # Chatbot conditionning
        # response = self.chatbot_bindings.prompt("This is a discussion between A user and an AI. AI responds to user questions in a helpful manner. AI is not allowed to lie or deceive. AI welcomes the user\n### Response:")
        # print(response)

    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="")
        self.full_text += text
        if self.is_bot_text_started:
            self.bot_says += text
        if self.current_message in self.full_text:
            self.is_bot_text_started = True

    def new_text_callback_with_yield(self, text: str):
        """
        To do , fix the problem with yield to be able to show interactive response as text comes
        """
        print(text, end="")
        self.full_text += text
        if self.is_bot_text_started:
            self.bot_says += text
        if self.current_message in self.full_text:
            self.is_bot_text_started = True
        yield text

    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(export_to_json(self.db_path))

    @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 = "User: " + message + "\nGPT4All:"
        self.prepare_query(self.current_message)
        chatbot_model_bindings.generate(
            self.current_message,
            n_predict=55,
            new_text_callback=self.new_text_callback,
            n_threads=8,
        )

        self.current_discussion.update_message(response_id, self.bot_says)
        yield self.bot_says
        # 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 last_discussion_has_messages(
                self.db_path
            ):
                self.current_discussion = Discussion.create_discussion(self.db_path)

            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 discussions(self):
        try:
            discussions = Discussion.get_discussions(self.db_path)
            return jsonify(discussions)
        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 get_messages(self):
        data = request.get_json()
        discussion_id = data["id"]
        self.current_discussion = Discussion(discussion_id, self.db_path)
        messages = self.current_discussion.get_messages()
        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")

        # add a new discussion
        # self.chatbot_bindings.close()
        # self.chatbot_bindings.open()

        # Return a success response
        return json.dumps({"id": self.current_discussion.discussion_id, "time": timestamp})


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Start the chatbot Flask app.")

    parser.add_argument(
        "--temp", type=float, default=0.1, help="Temperature parameter for the model."
    )
    parser.add_argument(
        "--n_predict",
        type=int,
        default=128,
        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=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()

    chatbot_model_bindings = Model(
        ggml_model="./models/gpt4all-lora-quantized-ggml.bin", n_ctx=512
    )

    # Old Code
    # GPT4All(decoder_config = {
    #     'temp': args.temp,
    #     'n_predict':args.n_predict,
    #     'top_k':args.top_k,
    #     'top_p':args.top_p,
    #     #'color': True,#"## Instruction",
    #     'repeat_penalty': args.repeat_penalty,
    #     'repeat_last_n':args.repeat_last_n,
    #     'ctx_size': args.ctx_size
    # })
    check_discussion_db(args.db_path)
    bot = Gpt4AllWebUI(chatbot_model_bindings, app, args.db_path)

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