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Makes OpenAI calls awaitable

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This commit is contained in:
Justin 2023-05-19 12:43:19 -05:00
parent a546e969cc
commit f118a23714
4 changed files with 58 additions and 62 deletions
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24
classes/bot.py
View file

@ -746,8 +746,14 @@ class GPTBot:
await self.matrix_client.room_read_markers(room.room_id, event.event_id)
if (not from_chat_command) and self.room_uses_classification(room):
classification, tokens = self.classification_api.classify_message(
event.body, room.room_id)
try:
classification, tokens = await self.classification_api.classify_message(
event.body, room.room_id)
except Exception as e:
self.logger.log(f"Error classifying message: {e}", "error")
await self.send_message(
room, "Something went wrong. Please try again.", True)
return
self.log_api_usage(
event, room, f"{self.classification_api.api_code}-{self.classification_api.classification_api}", tokens)
@ -781,18 +787,8 @@ class GPTBot:
chat_messages, self.max_tokens - 1, system_message=system_message)
try:
loop = asyncio.get_event_loop()
except Exception as e:
self.logger.log(f"Error getting event loop: {e}", "error")
await self.send_message(
room, "Something went wrong. Please try again.", True)
return
try:
chat_partial = functools.partial(self.chat_api.generate_chat_response, truncated_messages, user=room.room_id)
response, tokens_used = await loop.run_in_executor(None, chat_partial)
# response, tokens_used = self.chat_api.generate_chat_response(
# chat_messages, user=room.room_id)
response, tokens_used = await 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(

68
classes/openai.py
View file

@ -1,6 +1,8 @@
import openai
import requests
import asyncio
import functools
import json
from .logging import Logger
@ -17,7 +19,7 @@ class OpenAI:
@property
def chat_api(self) -> str:
return self.chat_model
classification_api = chat_api
image_api: str = "dalle"
@ -28,7 +30,7 @@ class OpenAI:
self.chat_model = chat_model or self.chat_model
self.logger = logger or Logger()
def generate_chat_response(self, messages: List[Dict[str, str]], user: Optional[str] = None) -> Tuple[str, int]:
async 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:
@ -37,22 +39,29 @@ class OpenAI:
Returns:
Tuple[str, int]: The response text and the number of tokens used.
"""
try:
loop = asyncio.get_event_loop()
except Exception as e:
self.logger.log(f"Error getting event loop: {e}", "error")
return
self.logger.log(f"Generating response to {len(messages)} messages using {self.chat_model}...")
response = openai.ChatCompletion.create(
model=self.chat_model,
messages=messages,
api_key=self.api_key,
user = user
chat_partial = functools.partial(
openai.ChatCompletion.create,
model=self.chat_model,
messages=messages,
api_key=self.api_key,
user = user
)
response = await loop.run_in_executor(None, chat_partial)
result_text = response.choices[0].message['content']
tokens_used = response.usage["total_tokens"]
self.logger.log(f"Generated response with {tokens_used} tokens.")
return result_text, tokens_used
def classify_message(self, query: str, user: Optional[str] = None) -> Tuple[Dict[str, str], int]:
async 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, or meant for a different API. You respond with a JSON object like this:
{ "type": event_type, "prompt": prompt }
@ -66,10 +75,15 @@ class OpenAI:
- 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."""
try:
loop = asyncio.get_event_loop()
except Exception as e:
self.logger.log(f"Error getting event loop: {e}", "error")
return
messages = [
{
"role": "system",
"role": "system",
"content": system_message
},
{
@ -80,12 +94,14 @@ Only the event_types mentioned above are allowed, you must not respond in any ot
self.logger.log(f"Classifying message '{query}'...")
response = openai.ChatCompletion.create(
model=self.chat_model,
messages=messages,
api_key=self.api_key,
user = user
chat_partial = functools.partial(
openai.ChatCompletion.create,
model=self.chat_model,
messages=messages,
api_key=self.api_key,
user=user
)
response = await loop.run_in_executor(None, chat_partial)
try:
result = json.loads(response.choices[0].message['content'])
@ -98,7 +114,7 @@ Only the event_types mentioned above are allowed, you must not respond in any ot
return result, tokens_used
def generate_image(self, prompt: str, user: Optional[str] = None) -> Generator[bytes, None, None]:
async def generate_image(self, prompt: str, user: Optional[str] = None) -> Generator[bytes, None, None]:
"""Generate an image from a prompt.
Args:
@ -107,16 +123,24 @@ Only the event_types mentioned above are allowed, you must not respond in any ot
Yields:
bytes: The image data.
"""
try:
loop = asyncio.get_event_loop()
except Exception as e:
self.logger.log(f"Error getting event loop: {e}", "error")
return
self.logger.log(f"Generating image from prompt '{prompt}'...")
response = openai.Image.create(
prompt=prompt,
n=1,
api_key=self.api_key,
size="1024x1024",
user = user
image_partial = functools.partial(
openai.Image.create,
prompt=prompt,
n=1,
api_key=self.api_key,
size="1024x1024",
user = user
)
response = await loop.run_in_executor(None, image_partial)
images = []
@ -124,4 +148,4 @@ Only the event_types mentioned above are allowed, you must not respond in any ot
image = requests.get(image.url).content
images.append(image)
return images, len(images)
return images, len(images)

14
commands/classify.py
View file

@ -1,6 +1,3 @@
import asyncio
import functools
from nio.events.room_events import RoomMessageText
from nio.rooms import MatrixRoom
@ -12,16 +9,7 @@ async def command_classify(room: MatrixRoom, event: RoomMessageText, bot):
bot.logger.log("Classifying message...")
try:
loop = asyncio.get_event_loop()
except Exception as e:
bot.logger.log(f"Error getting event loop: {e}", "error")
await bot.send_message(
room, "Something went wrong. Please try again.", True)
return
try:
classify_partial = functools.partial(bot.classification_api.classify_message, prompt, user=room.room_id)
response, tokens_used = await loop.run_in_executor(None, classify_partial)
response, tokens_used = await bot.classification_api.classify_message(prompt, user=room.room_id)
except Exception as e:
bot.logger.log(f"Error classifying message: {e}", "error")
await bot.send_message(room, "Sorry, I couldn't classify the message. Please try again later.", True)

14
commands/imagine.py
View file

@ -1,6 +1,3 @@
import asyncio
import functools
from nio.events.room_events import RoomMessageText
from nio.rooms import MatrixRoom
@ -12,16 +9,7 @@ async def command_imagine(room: MatrixRoom, event: RoomMessageText, bot):
bot.logger.log("Generating image...")
try:
loop = asyncio.get_event_loop()
except Exception as e:
bot.logger.log(f"Error getting event loop: {e}", "error")
await bot.send_message(
room, "Something went wrong. Please try again.", True)
return
try:
image_partial = functools.partial(bot.image_api.generate_image, prompt, user=room.room_id)
images, tokens_used = await loop.run_in_executor(None, image_partial)
images, tokens_used = await bot.image_api.generate_image(prompt, user=room.room_id)
except Exception as e:
bot.logger.log(f"Error generating image: {e}", "error")
await bot.send_message(room, "Sorry, I couldn't generate an image. Please try again later.", True)