app.py

"""app.py"""
import os
import autogen
import autogen.runtime_logging
import autogen.types
import dotenv
import agentops

from autogen import UserProxyAgent
from story_book_agents import agent_manager_instance, story_draft_groupchat, storyboard_groupchat

import story_book_agents


# prepare the LLM configurations
dotenv.load_dotenv(override=True)

gpt_config_list_default = [{
    "model": os.environ.get("MODEL"),
    "api_key": os.environ.get("API_KEY"),
    "base_url": os.environ.get("BASE_URL"),
    "api_type": os.environ.get("API_TYPE","azure"),
    "api_version": os.environ.get("API_VERSION","2024-06-01"),
}]

dalle_config = {
    "config_list": [{
        "model": os.environ.get("DALLE_MODEL"),
        "api_key": os.environ.get("DALLE_API_KEY"),
        "base_url": os.environ.get("DALLE_BASE_URL"),
        "api_type": os.environ.get("DALLE_API_TYPE"),
        "api_version": os.environ.get("DALLE_API_VERSION"),
    }],
    "timeout": 120,
    "temperature": 0.7,
    "max_tokens": 2000

}

# toggle this line if you don't use agentops
#agentops.init(api_key=os.environ.get("AGENTOPS_API_KEY"))

story_book_agents.init_agents(gpt_config_list_default)
# create a UserProxyAgent instance
user_agent = UserProxyAgent(
    name="User",
    llm_config=False,
    human_input_mode="ALWAYS",
    code_execution_config=False,
)


def main():
    """Main function."""
    preliminary_story_requirements = "给我讲一个故事吧"
    chat_results = autogen.agentchat.initiate_chats([
        # Obtain preliminary requirements through the conversation with the Receptionist agent.
        {
            "sender": user_agent,
            "recipient": agent_manager_instance.default_receptionist_agent,
            "message": preliminary_story_requirements,
            "max_turns": 10,
            "summary_method": "reflection_with_llm",
            "summary_args": {
                "summary_prompt": """
Summarize the key points from the conversation without any introductory phrases. 

1. The summary must be in the same language as the user's specified language for the picture book if explicitly mentioned. 
2. If the user did not specify a language, use the main language used by the user throughout the conversation.
3. Ensure that the summary reflects the language used predominantly in the conversation, regardless of any predefined commands like "exit." 
4. The summary should clearly reflect the user's requirements and preferences discussed during the conversation.
"""
            }
        },
        # The Story Draft Group includes agents such as the Story Editor, Story Critic, Producer, and IT Assistant.
        # They communicate through a group chat to create, review, and store the story content.
        story_draft_groupchat.set_story_draft_chat()
    ])
    story_id = chat_results[1].summary
    print("Story ID: " + story_id)
    chat_results2 = autogen.agentchat.initiate_chats(
        [
            # in this storyboard chatgroup, the agents create/critic/save the storyboard base on the story content.
            storyboard_groupchat.set_storyboard_chat(story_id)
        ]
    )
    print(chat_results2[0].summary)


# entry point
if __name__ == '__main__':
    main()