Preparation for automatic message classification
This commit is contained in:
parent
bf23771989
commit
2fb607310d
14 changed files with 228 additions and 42 deletions
|
@ -21,7 +21,8 @@ from nio import (
|
|||
EncryptionError,
|
||||
RoomMessageText,
|
||||
RoomSendResponse,
|
||||
SyncResponse
|
||||
SyncResponse,
|
||||
RoomMessageNotice
|
||||
)
|
||||
from nio.crypto import Olm
|
||||
|
||||
|
@ -55,6 +56,8 @@ class GPTBot:
|
|||
logger: Optional[Logger] = Logger()
|
||||
chat_api: Optional[OpenAI] = None
|
||||
image_api: Optional[OpenAI] = None
|
||||
classification_api: Optional[OpenAI] = None
|
||||
operator: Optional[str] = None
|
||||
|
||||
@classmethod
|
||||
def from_config(cls, config: ConfigParser):
|
||||
|
@ -76,6 +79,7 @@ class GPTBot:
|
|||
|
||||
# Override default values
|
||||
if "GPTBot" in config:
|
||||
bot.operator = config["GPTBot"].get("Operator", bot.operator)
|
||||
bot.default_room_name = config["GPTBot"].get(
|
||||
"DefaultRoomName", bot.default_room_name)
|
||||
bot.default_system_message = config["GPTBot"].get(
|
||||
|
@ -83,7 +87,8 @@ class GPTBot:
|
|||
bot.force_system_message = config["GPTBot"].getboolean(
|
||||
"ForceSystemMessage", bot.force_system_message)
|
||||
|
||||
bot.chat_api = bot.image_api = OpenAI(config["OpenAI"]["APIKey"], config["OpenAI"].get("Model"), bot.logger)
|
||||
bot.chat_api = bot.image_api = bot.classification_api = OpenAI(
|
||||
config["OpenAI"]["APIKey"], config["OpenAI"].get("Model"), bot.logger)
|
||||
bot.max_tokens = config["OpenAI"].getint("MaxTokens", bot.max_tokens)
|
||||
bot.max_messages = config["OpenAI"].getint(
|
||||
"MaxMessages", bot.max_messages)
|
||||
|
@ -158,10 +163,10 @@ class GPTBot:
|
|||
self.logger.log(
|
||||
f"Could not decrypt message {event.event_id} in room {room_id}", "error")
|
||||
continue
|
||||
if isinstance(event, RoomMessageText):
|
||||
if isinstance(event, (RoomMessageText, RoomMessageNotice)):
|
||||
if event.body.startswith("!gptbot ignoreolder"):
|
||||
break
|
||||
if not event.body.startswith("!"):
|
||||
if (not event.body.startswith("!")) or (event.body.startswith("!gptbot")):
|
||||
messages.append(event)
|
||||
|
||||
self.logger.log(f"Found {len(messages)} messages (limit: {n})")
|
||||
|
@ -230,14 +235,15 @@ class GPTBot:
|
|||
|
||||
await COMMANDS.get(command, COMMANDS[None])(room, event, self)
|
||||
|
||||
async def event_callback(self,room: MatrixRoom, event: Event):
|
||||
async def event_callback(self, room: MatrixRoom, event: Event):
|
||||
self.logger.log("Received event: " + str(event.event_id), "debug")
|
||||
try:
|
||||
for eventtype, callback in EVENT_CALLBACKS.items():
|
||||
if isinstance(event, eventtype):
|
||||
await callback(room, event, self)
|
||||
except Exception as e:
|
||||
self.logger.log(f"Error in event callback for {event.__class__}: {e}", "error")
|
||||
self.logger.log(
|
||||
f"Error in event callback for {event.__class__}: {e}", "error")
|
||||
|
||||
async def response_callback(self, response: Response):
|
||||
for response_type, callback in RESPONSE_CALLBACKS.items():
|
||||
|
@ -347,6 +353,30 @@ class GPTBot:
|
|||
|
||||
return await self.matrix_client._send(RoomSendResponse, method, path, data, (room.room_id,))
|
||||
|
||||
def log_api_usage(self, message: Event | str, room: MatrixRoom | int, api: str, tokens: int):
|
||||
"""Log API usage to the database.
|
||||
|
||||
Args:
|
||||
message (Event): The event that triggered the API usage.
|
||||
room (MatrixRoom | int): The room the event was sent in.
|
||||
api (str): The API that was used.
|
||||
tokens (int): The number of tokens used.
|
||||
"""
|
||||
|
||||
if not self.database:
|
||||
return
|
||||
|
||||
if isinstance(message, Event):
|
||||
message = message.event_id
|
||||
|
||||
if isinstance(room, MatrixRoom):
|
||||
room = room.room_id
|
||||
|
||||
self.database.execute(
|
||||
"INSERT INTO token_usage (message_id, room_id, tokens, api, timestamp) VALUES (?, ?, ?, ?, ?)",
|
||||
(message, room, tokens, api, datetime.now())
|
||||
)
|
||||
|
||||
async def run(self):
|
||||
"""Start the bot."""
|
||||
|
||||
|
@ -410,7 +440,8 @@ class GPTBot:
|
|||
# Set up callbacks
|
||||
|
||||
self.matrix_client.add_event_callback(self.event_callback, Event)
|
||||
self.matrix_client.add_response_callback(self.response_callback, Response)
|
||||
self.matrix_client.add_response_callback(
|
||||
self.response_callback, Response)
|
||||
|
||||
# Accept pending invites
|
||||
|
||||
|
@ -454,7 +485,8 @@ class GPTBot:
|
|||
chat_messages, self.max_tokens - 1, system_message=system_message)
|
||||
|
||||
try:
|
||||
response, tokens_used = await self.generate_chat_response(truncated_messages)
|
||||
response, tokens_used = self.chat_api.generate_chat_response(
|
||||
chat_messages, user=room.room_id)
|
||||
except Exception as e:
|
||||
self.logger.log(f"Error generating response: {e}", "error")
|
||||
await self.send_message(
|
||||
|
@ -462,40 +494,22 @@ class GPTBot:
|
|||
return
|
||||
|
||||
if response:
|
||||
self.log_api_usage(event, room, f"{self.chat_api.api_code}-{self.chat_api.chat_api}", tokens_used)
|
||||
|
||||
self.logger.log(f"Sending response to room {room.room_id}...")
|
||||
|
||||
# Convert markdown to HTML
|
||||
|
||||
message = await self.send_message(room, response)
|
||||
|
||||
if self.database:
|
||||
self.logger.log("Storing record of tokens used...")
|
||||
|
||||
with self.database.cursor() as cursor:
|
||||
cursor.execute(
|
||||
"INSERT INTO token_usage (message_id, room_id, tokens, timestamp) VALUES (?, ?, ?, ?)",
|
||||
(message.event_id, room.room_id, tokens_used, datetime.now()))
|
||||
self.database.commit()
|
||||
else:
|
||||
# Send a notice to the room if there was an error
|
||||
self.logger.log("Didn't get a response from GPT API", "error")
|
||||
send_message(
|
||||
await send_message(
|
||||
room, "Something went wrong. Please try again.", True)
|
||||
|
||||
await self.matrix_client.room_typing(room.room_id, False)
|
||||
|
||||
async def generate_chat_response(self, messages: List[Dict[str, str]]) -> Tuple[str, int]:
|
||||
"""Generate a response to a chat message.
|
||||
|
||||
Args:
|
||||
messages (List[Dict[str, str]]): A list of messages to use as context.
|
||||
|
||||
Returns:
|
||||
Tuple[str, int]: The response text and the number of tokens used.
|
||||
"""
|
||||
|
||||
return self.chat_api.generate_chat_response(messages)
|
||||
|
||||
def get_system_message(self, room: MatrixRoom | int) -> str:
|
||||
default = self.default_system_message
|
||||
|
||||
|
|
|
@ -1,21 +1,34 @@
|
|||
import openai
|
||||
import requests
|
||||
|
||||
import json
|
||||
|
||||
from .logging import Logger
|
||||
|
||||
from typing import Dict, List, Tuple, Generator
|
||||
from typing import Dict, List, Tuple, Generator, Optional
|
||||
|
||||
class OpenAI:
|
||||
api_key: str
|
||||
chat_model: str = "gpt-3.5-turbo"
|
||||
logger: Logger
|
||||
|
||||
api_code: str = "openai"
|
||||
|
||||
@property
|
||||
def chat_api(self) -> str:
|
||||
return self.chat_model
|
||||
|
||||
classification_api = chat_api
|
||||
image_api: str = "dalle"
|
||||
|
||||
operator: str = "OpenAI ([https://openai.com](https://openai.com))"
|
||||
|
||||
def __init__(self, api_key, chat_model=None, logger=None):
|
||||
self.api_key = api_key
|
||||
self.chat_model = chat_model or self.chat_model
|
||||
self.logger = logger or Logger()
|
||||
|
||||
def generate_chat_response(self, messages: List[Dict[str, str]]) -> Tuple[str, int]:
|
||||
def generate_chat_response(self, messages: List[Dict[str, str]], user: Optional[str] = None) -> Tuple[str, int]:
|
||||
"""Generate a response to a chat message.
|
||||
|
||||
Args:
|
||||
|
@ -30,7 +43,8 @@ class OpenAI:
|
|||
response = openai.ChatCompletion.create(
|
||||
model=self.chat_model,
|
||||
messages=messages,
|
||||
api_key=self.api_key
|
||||
api_key=self.api_key,
|
||||
user = user
|
||||
)
|
||||
|
||||
result_text = response.choices[0].message['content']
|
||||
|
@ -38,7 +52,50 @@ class OpenAI:
|
|||
self.logger.log(f"Generated response with {tokens_used} tokens.")
|
||||
return result_text, tokens_used
|
||||
|
||||
def generate_image(self, prompt: str) -> Generator[bytes, None, None]:
|
||||
def classify_message(self, query: str, user: Optional[str] = None) -> Tuple[Dict[str, str], int]:
|
||||
system_message = """You are a classifier for different types of messages. You decide whether an incoming message is meant to be a prompt for an AI chat model, an image generation AI, or a calculation for WolframAlpha. You respond with a JSON object like this:
|
||||
|
||||
{ "type": event_type, "prompt": prompt }
|
||||
|
||||
- If the message you received is meant for the AI chat model, the event_type is "chat", and the prompt is the literal content of the message you received. This is also the default if none of the other options apply.
|
||||
- If it is a prompt for a calculation that can be answered better by WolframAlpha than an AI chat bot, the event_type is "calculate". Optimize the message you received for input to WolframAlpha, and return it as the prompt attribute.
|
||||
- If it is a prompt for an AI image generation, the event_type is "imagine". Optimize the message you received for use with DALL-E, and return it as the prompt attribute.
|
||||
- If for any reason you are unable to classify the message (for example, if it infringes on your terms of service), the event_type is "error", and the prompt is a message explaining why you are unable to process the message.
|
||||
|
||||
Only the event_types mentioned above are allowed, you must not respond in any other way."""
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": system_message
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": query
|
||||
}
|
||||
]
|
||||
|
||||
self.logger.log(f"Classifying message '{query}'...")
|
||||
|
||||
response = openai.ChatCompletion.create(
|
||||
model=self.chat_model,
|
||||
messages=messages,
|
||||
api_key=self.api_key,
|
||||
user = user
|
||||
)
|
||||
|
||||
try:
|
||||
result = json.loads(response.choices[0].message['content'])
|
||||
except:
|
||||
result = {"type": "chat", "prompt": query}
|
||||
|
||||
tokens_used = response.usage["total_tokens"]
|
||||
|
||||
self.logger.log(f"Classified message as {result['type']} with {tokens_used} tokens.")
|
||||
|
||||
return result, tokens_used
|
||||
|
||||
def generate_image(self, prompt: str, user: Optional[str] = None) -> Generator[bytes, None, None]:
|
||||
"""Generate an image from a prompt.
|
||||
|
||||
Args:
|
||||
|
@ -54,9 +111,14 @@ class OpenAI:
|
|||
prompt=prompt,
|
||||
n=1,
|
||||
api_key=self.api_key,
|
||||
size="1024x1024"
|
||||
size="1024x1024",
|
||||
user = user
|
||||
)
|
||||
|
||||
images = []
|
||||
|
||||
for image in response.data:
|
||||
image = requests.get(image.url).content
|
||||
yield image
|
||||
images.append(image)
|
||||
|
||||
return images, len(images)
|
|
@ -10,17 +10,33 @@ class WolframAlpha:
|
|||
logger: Logger
|
||||
client: wolframalpha.Client
|
||||
|
||||
api_code: str = "wolfram"
|
||||
calculation_api: str = "alpha"
|
||||
|
||||
operator: str = "Wolfram ([https://www.wolfram.com](https://www.wolfram.com))"
|
||||
|
||||
def __init__(self, api_key: str, logger: Optional[Logger] = None):
|
||||
self.api_key: str = api_key
|
||||
self.logger: Logger = logger or Logger()
|
||||
self.client = wolframalpha.Client(self.api_key)
|
||||
|
||||
def generate_calculation_response(self, query: str, text: Optional[bool] = False, results_only: Optional[bool] = False) -> Generator[str | bytes, None, None]:
|
||||
def generate_calculation_response(self, query: str, text: Optional[bool] = False, results_only: Optional[bool] = False, user: Optional[str] = None) -> Generator[str | bytes, None, None]:
|
||||
self.logger.log(f"Querying WolframAlpha for {query}")
|
||||
|
||||
response: wolframalpha.Result = self.client.query(query)
|
||||
|
||||
for pod in response.pods if not results_only else response.results:
|
||||
if not response.success:
|
||||
yield "Could not process your query."
|
||||
|
||||
if response.didyoumeans:
|
||||
yield "Did you mean: " + response.didyoumeans["didyoumean"][0]["#text"]
|
||||
|
||||
return
|
||||
|
||||
if response.error:
|
||||
self.logger.log("Error in query to WolframAlpha: " + response.error, "error")
|
||||
|
||||
for pod in response.pods if not results_only else (response.results if len(list(response.results)) else response.pods):
|
||||
self.logger.log(pod.keys(), "debug")
|
||||
if pod.title:
|
||||
yield "*" + pod.title + "*"
|
||||
|
|
|
@ -8,6 +8,8 @@ from .ignoreolder import command_ignoreolder
|
|||
from .systemmessage import command_systemmessage
|
||||
from .imagine import command_imagine
|
||||
from .calculate import command_calculate
|
||||
from .classify import command_classify
|
||||
from .chat import command_chat
|
||||
|
||||
COMMANDS = {
|
||||
"help": command_help,
|
||||
|
@ -19,5 +21,7 @@ COMMANDS = {
|
|||
"systemmessage": command_systemmessage,
|
||||
"imagine": command_imagine,
|
||||
"calculate": command_calculate,
|
||||
"classify": command_classify,
|
||||
"chat": command_chat,
|
||||
None: command_unknown,
|
||||
}
|
||||
|
|
|
@ -20,15 +20,17 @@ async def command_calculate(room: MatrixRoom, event: RoomMessageText, bot):
|
|||
prompt = " ".join(prompt)
|
||||
|
||||
if prompt:
|
||||
bot.logger.log("Querying WolframAlpha")
|
||||
bot.logger.log("Querying calculation API...")
|
||||
|
||||
for subpod in bot.calculation_api.generate_calculation_response(prompt, text, results_only):
|
||||
for subpod in bot.calculation_api.generate_calculation_response(prompt, text, results_only, user=room.room_id):
|
||||
bot.logger.log(f"Sending subpod...")
|
||||
if isinstance(subpod, bytes):
|
||||
await bot.send_image(room, subpod)
|
||||
else:
|
||||
await bot.send_message(room, subpod, True)
|
||||
|
||||
bot.log_api_usage(event, room, f"{self.calculation_api.api_code}-{self.calculation_api.calculation_api}", tokens_used)
|
||||
|
||||
return
|
||||
|
||||
await bot.send_message(room, "You need to provide a prompt.", True)
|
15
commands/chat.py
Normal file
15
commands/chat.py
Normal file
|
@ -0,0 +1,15 @@
|
|||
from nio.events.room_events import RoomMessageText
|
||||
from nio.rooms import MatrixRoom
|
||||
|
||||
|
||||
async def command_chat(room: MatrixRoom, event: RoomMessageText, bot):
|
||||
prompt = " ".join(event.body.split()[2:])
|
||||
|
||||
if prompt:
|
||||
bot.logger.log("Sending chat message...")
|
||||
event.body = prompt
|
||||
await bot.process_query(room, event)
|
||||
|
||||
return
|
||||
|
||||
await bot.send_message(room, "You need to provide a prompt.", True)
|
24
commands/classify.py
Normal file
24
commands/classify.py
Normal file
|
@ -0,0 +1,24 @@
|
|||
from nio.events.room_events import RoomMessageText
|
||||
from nio.rooms import MatrixRoom
|
||||
|
||||
|
||||
async def command_classify(room: MatrixRoom, event: RoomMessageText, bot):
|
||||
prompt = " ".join(event.body.split()[2:])
|
||||
|
||||
if prompt:
|
||||
bot.logger.log("Classifying message...")
|
||||
|
||||
response, tokens_used = bot.classification_api.classify_message(prompt, user=room.room_id)
|
||||
|
||||
message = f"The message you provided seems to be of type: {response['type']}."
|
||||
|
||||
if not prompt == response["prompt"]:
|
||||
message += f"\n\nPrompt: {response['prompt']}."
|
||||
|
||||
await bot.send_message(room, message, True)
|
||||
|
||||
bot.log_api_usage(event, room, f"{self.classification_api.api_code}-{self.classification_api.classification_api}", tokens_used)
|
||||
|
||||
return
|
||||
|
||||
await bot.send_message(room, "You need to provide a prompt.", True)
|
|
@ -14,6 +14,9 @@ async def command_help(room: MatrixRoom, event: RoomMessageText, bot):
|
|||
- !gptbot systemmessage \<message\> - Get or set the system message for this room
|
||||
- !gptbot imagine \<prompt\> - Generate an image from a prompt
|
||||
- !gptbot calculate [--text] [--details] \<query\> - Calculate a result to a calculation, optionally forcing text output instead of an image, and optionally showing additional details like the input interpretation
|
||||
- !gptbot privacy - Show privacy information
|
||||
- !gptbot chat \<message\> - Send a message to the chat API
|
||||
- !gptbot classify \<message\> - Classify a message using the classification API
|
||||
"""
|
||||
|
||||
await bot.send_message(room, body, True)
|
|
@ -8,10 +8,14 @@ async def command_imagine(room: MatrixRoom, event: RoomMessageText, bot):
|
|||
if prompt:
|
||||
bot.logger.log("Generating image...")
|
||||
|
||||
for image in bot.image_api.generate_image(prompt):
|
||||
images, tokens_used = bot.image_api.generate_image(prompt, user=room.room_id)
|
||||
|
||||
for image in images:
|
||||
bot.logger.log(f"Sending image...")
|
||||
await bot.send_image(room, image)
|
||||
|
||||
bot.log_api_usage(event, room, f"{self.image_api.api_code}-{self.image_api.image_api}", tokens_used)
|
||||
|
||||
return
|
||||
|
||||
await bot.send_message(room, "You need to provide a prompt.", True)
|
17
commands/privacy.py
Normal file
17
commands/privacy.py
Normal file
|
@ -0,0 +1,17 @@
|
|||
from nio.events.room_events import RoomMessageText
|
||||
from nio.rooms import MatrixRoom
|
||||
|
||||
|
||||
async def command_privacy(room: MatrixRoom, event: RoomMessageText, bot):
|
||||
body = "**Privacy**\n\nIf you use this bot, note that your messages will be sent to the following recipients:\n\n"
|
||||
|
||||
body += "- The bot's operator" + (f"({bot.operator})" if bot.operator else "") + "\n"
|
||||
|
||||
if bot.chat_api:
|
||||
body += "- For chat requests: " + f"{bot.chat_api.operator}" + "\n"
|
||||
if bot.image_api:
|
||||
body += "- For image generation requests (!gptbot imagine): " + f"{bot.image_api.operator}" + "\n"
|
||||
if bot.calculate_api:
|
||||
body += "- For calculation requests (!gptbot calculate): " + f"{bot.calculate_api.operator}" + "\n"
|
||||
|
||||
await bot.send_message(room, body, True)
|
|
@ -15,7 +15,7 @@ async def command_systemmessage(room: MatrixRoom, event: RoomMessageText, bot):
|
|||
system_message, event.server_timestamp)
|
||||
)
|
||||
|
||||
bot.send_message(room, f"Alright, I've stored the system message: '{system_message}'.", True)
|
||||
await bot.send_message(room, f"Alright, I've stored the system message: '{system_message}'.", True)
|
||||
return
|
||||
|
||||
bot.logger.log("Retrieving system message...")
|
||||
|
|
|
@ -68,6 +68,11 @@ AccessToken = syt_yoursynapsetoken
|
|||
|
||||
[GPTBot]
|
||||
|
||||
# Some way for the user to contact you.
|
||||
# Ideally, either your personal user ID or a support room
|
||||
#
|
||||
Operator = Contact details not set
|
||||
|
||||
# The default room name used by the !newroom command
|
||||
# Defaults to GPTBot if not set
|
||||
#
|
||||
|
|
|
@ -6,12 +6,14 @@ from duckdb import DuckDBPyConnection
|
|||
from .migration_1 import migration as migration_1
|
||||
from .migration_2 import migration as migration_2
|
||||
from .migration_3 import migration as migration_3
|
||||
from .migration_4 import migration as migration_4
|
||||
|
||||
MIGRATIONS = OrderedDict()
|
||||
|
||||
MIGRATIONS[1] = migration_1
|
||||
MIGRATIONS[2] = migration_2
|
||||
MIGRATIONS[3] = migration_3
|
||||
MIGRATIONS[4] = migration_4
|
||||
|
||||
def get_version(db: DuckDBPyConnection) -> int:
|
||||
"""Get the current database version.
|
||||
|
|
18
migrations/migration_4.py
Normal file
18
migrations/migration_4.py
Normal file
|
@ -0,0 +1,18 @@
|
|||
# Migration to add API column to token usage table
|
||||
|
||||
from datetime import datetime
|
||||
|
||||
def migration(conn):
|
||||
with conn.cursor() as cursor:
|
||||
cursor.execute(
|
||||
"""
|
||||
ALTER TABLE token_usage ADD COLUMN api TEXT DEFAULT 'openai'
|
||||
"""
|
||||
)
|
||||
|
||||
cursor.execute(
|
||||
"INSERT INTO migrations (id, timestamp) VALUES (4, ?)",
|
||||
(datetime.now(),)
|
||||
)
|
||||
|
||||
conn.commit()
|
Loading…
Reference in a new issue