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114 lines
4.5 KiB
Python
114 lines
4.5 KiB
Python
import argparse
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import asyncio
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import logging
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import os
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import sys
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import openai
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from agnext.application import SingleThreadedAgentRuntime
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from agnext.components.models import OpenAIChatCompletionClient, SystemMessage
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from agnext.core import AgentRuntime
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sys.path.append(os.path.abspath(os.path.dirname(__file__)))
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sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
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from common.agents import ChatCompletionAgent, ImageGenerationAgent
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from common.memory import BufferedChatMemory
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from common.patterns._group_chat_manager import GroupChatManager
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from utils import TextualChatApp, TextualUserAgent, start_runtime
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def illustrator_critics(runtime: AgentRuntime, app: TextualChatApp) -> None:
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runtime.register(
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"User",
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lambda: TextualUserAgent(
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description="A user looking for illustration.",
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app=app,
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),
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)
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descriptor = runtime.register_and_get_proxy(
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"Descriptor",
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lambda: ChatCompletionAgent(
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description="An AI agent that provides a description of the image.",
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system_messages=[
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SystemMessage(
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"You create short description for image. \n"
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"In this conversation, you will be given either: \n"
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"1. Request for new image. \n"
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"2. Feedback on some image created. \n"
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"In both cases, you will provide a description of a new image to be created. \n"
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"Only provide the description of the new image and nothing else. \n"
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"Be succinct and precise."
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),
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],
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memory=BufferedChatMemory(buffer_size=10),
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model_client=OpenAIChatCompletionClient(model="gpt-4-turbo", max_tokens=500),
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),
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)
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illustrator = runtime.register_and_get_proxy(
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"Illustrator",
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lambda: ImageGenerationAgent(
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description="An AI agent that generates images.",
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client=openai.AsyncOpenAI(),
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model="dall-e-3",
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memory=BufferedChatMemory(buffer_size=1),
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),
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)
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critic = runtime.register_and_get_proxy(
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"Critic",
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lambda: ChatCompletionAgent(
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description="An AI agent that provides feedback on images given user's requirements.",
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system_messages=[
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SystemMessage(
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"You are an expert in image understanding. \n"
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"In this conversation, you will judge an image given the description and provide feedback. \n"
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"Pay attention to the details like the spelling of words and number of objects. \n"
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"Use the following format in your response: \n"
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"Number of each object type in the image: <Type 1 (e.g., Husky Dog)>: 1, <Type 2>: 2, ...\n"
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"Feedback: <Your feedback here> \n"
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"Approval: <APPROVE or REVISE> \n"
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),
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],
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memory=BufferedChatMemory(buffer_size=2),
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model_client=OpenAIChatCompletionClient(model="gpt-4-turbo"),
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),
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)
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runtime.register(
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"GroupChatManager",
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lambda: GroupChatManager(
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description="A chat manager that handles group chat.",
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memory=BufferedChatMemory(buffer_size=5),
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participants=[illustrator.id, critic.id, descriptor.id],
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termination_word="APPROVE",
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),
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)
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app.welcoming_notice = f"""You are now in a group chat with the following agents:
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1. 🤖 {descriptor.metadata['name']}: {descriptor.metadata.get('description')}
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2. 🤖 {illustrator.metadata['name']}: {illustrator.metadata.get('description')}
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3. 🤖 {critic.metadata['name']}: {critic.metadata.get('description')}
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Provide a prompt for the illustrator to generate an image.
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"""
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async def main() -> None:
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runtime = SingleThreadedAgentRuntime()
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app = TextualChatApp(runtime, user_name="You")
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illustrator_critics(runtime, app)
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asyncio.create_task(start_runtime(runtime))
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await app.run_async()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Illustrator-critics pattern for image generation demo.")
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parser.add_argument("--verbose", action="store_true", help="Enable verbose logging.")
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args = parser.parse_args()
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if args.verbose:
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logging.basicConfig(level=logging.WARNING)
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logging.getLogger("agnext").setLevel(logging.DEBUG)
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handler = logging.FileHandler("illustrator_critics.log")
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logging.getLogger("agnext").addHandler(handler)
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asyncio.run(main())
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