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app.py
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import argparse
import json
import re
import random
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, _app, args) -> None:
self.args = args
self.current_discussion = None
self.app = _app
self.db_path = args.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"]
)
# 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.
Start by welcoming the user then stop sending text.
GPT4All:Welcome! I'm here to assist you with anything you need. What can I do for you today?"""
):
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="")
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 = "\nUser: " + message + "\nGPT4All: "
self.prepare_query(self.current_message)
self.chatbot_bindings.generate(
self.current_message,
new_text_callback=self.new_text_callback,
n_predict=len(self.current_message)+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.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()
full_message = ""
for message in messages:
full_message += message['sender'] + ": " + message['content'] + "\n"
self.chatbot_bindings.generate(
full_message,
new_text_callback=self.new_text_callback,
n_predict=len(messages),
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,
)
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")
# Create chatbot
self.chatbot_bindings = self.create_chatbot()
# Chatbot conditionning
self.condition_chatbot()
# 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(
"-s", "--seed", type=int, default=0, help="Force using a specific model."
)
parser.add_argument(
"-m", "--model", type=str, default="gpt4all-lora-quantized.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,#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=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()
check_discussion_db(args.db_path)
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)