Files
pipecat/services/open_ai_service.py
Moishe Lettvin e724720e76 Getting started
2023-12-25 19:09:11 -05:00

58 lines
1.9 KiB
Python

from services.ai_service import AIService
import requests
from PIL import Image
import io
import openai
import os
import time
import json
class OpenAIService(AIService):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def run_llm(self, messages, latest_user_message=None, stream = True):
local_messages = messages.copy()
if latest_user_message:
local_messages.append({"role": "user", "content": latest_user_message})
messages_for_log = json.dumps(local_messages, indent=2)
self.logger.info(f"==== generating chat via openai: {messages_for_log}")
model = os.getenv("OPEN_AI_MODEL")
if not model:
model = "gpt-4"
response = openai.ChatCompletion.create(
api_type = 'openai',
api_version = '2020-11-07',
api_base = "https://api.openai.com/v1",
api_key = os.getenv("OPEN_AI_KEY"),
model=model,
stream=stream,
messages=local_messages
)
return response
def run_image_gen(self, sentence):
self.logger.info("🖌️ generating openai image async for ", sentence)
start = time.time()
image = openai.Image.create(
api_type = 'openai',
api_version = '2020-11-07',
api_base = "https://api.openai.com/v1",
api_key = os.getenv("OPEN_AI_KEY"),
prompt=f'{sentence} in the style of {self.image_style}',
n=1,
size=f"1024x1024",
)
image_url = image["data"][0]["url"]
self.logger.info("🖌️ generated image from url", image["data"][0]["url"])
response = requests.get(image_url)
self.logger.info("🖌️ got image from url", response)
dalle_stream = io.BytesIO(response.content)
dalle_im = Image.open(dalle_stream)
self.logger.info("🖌️ total time", time.time() - start)
return (image_url, dalle_im)