from crewai import Agent, Task, Crew import gradio as gr import asyncio from typing import List, Dict, Any, Generator from langchain_openai import ChatOpenAI import queue import threading import os class AgentMessageQueue: def __init__(self): self.message_queue = queue.Queue() def add_message(self, message: Dict): self.message_queue.put(message) def get_messages(self) -> List[Dict]: messages = [] while not self.message_queue.empty(): messages.append(self.message_queue.get()) return messages class PressReleaseCrew: def __init__(self, api_key: str = None): self.api_key = api_key self.message_queue = AgentMessageQueue() self.researcher = None self.writer = None self.editor = None self.current_agent = None def initialize_agents(self, topic: str): if not self.api_key: raise ValueError("OpenAI API key is required") os.environ["OPENAI_API_KEY"] = self.api_key llm = ChatOpenAI(temperature=0.7, model="gpt-4") self.researcher = Agent( role="News Researcher", goal=f"Gather critical details and facts for a press release about {topic}", backstory="An experienced journalist who specializes in gathering news and structuring press releases.", allow_delegation=False, verbose=True, llm=llm ) self.writer = Agent( role="Press Release Writer", goal=f"Draft a compelling and structured press release about {topic}", backstory="A seasoned news writer with expertise in crafting clear and engaging press releases.", allow_delegation=False, verbose=True, llm=llm ) self.editor = Agent( role="News Editor", goal="Refine and finalize the press release for accuracy and professionalism.", backstory="A skilled editor with an eye for clarity, conciseness, and journalistic integrity.", allow_delegation=False, verbose=True, llm=llm ) def create_tasks(self, topic: str) -> List[Task]: researcher_task = Task( description=f"""As a news researcher, compile essential details for a press release on {topic} by: 1. Identifying key facts, statistics, and industry trends 2. Structuring the information into a brief, clear outline 3. Suggesting a compelling press release headline""", expected_output="A structured summary with key facts, statistics, and a proposed headline.", agent=self.researcher ) writer_task = Task( description="""Using the research provided: 1. Write a clear and engaging press release following a journalistic structure 2. Ensure it includes a compelling headline, subheading, lead paragraph, supporting details, and a boilerplate 3. Maintain a professional and neutral tone""", expected_output="A structured press release draft ready for editing.", agent=self.writer ) editor_task = Task( description="""Review and refine the press release by: 1. Checking for clarity, conciseness, and accuracy 2. Ensuring proper journalistic tone and structure 3. Correcting any grammatical or formatting issues""", expected_output="A polished, publication-ready press release.", agent=self.editor ) return [researcher_task, writer_task, editor_task] async def process_press_release(self, topic: str) -> Generator[List[Dict], None, None]: def add_agent_messages(agent_name: str, tasks: str, emoji: str = "📰"): self.message_queue.add_message({ "role": "assistant", "content": agent_name, "metadata": {"title": f"{emoji} {agent_name}"} }) self.message_queue.add_message({ "role": "assistant", "content": tasks, "metadata": {"title": f"📄 Task for {agent_name}"} }) def setup_next_agent(current_agent: str) -> None: agent_sequence = { "News Researcher": ("Press Release Writer", """Write a structured and engaging press release including: 1. A compelling headline and subheading 2. A strong lead paragraph 3. Supporting details and key statistics 4. A conclusion with a call to action or company statement"""), "Press Release Writer": ("News Editor", """Review and refine the press release for: 1. Clarity and conciseness 2. Proper journalistic tone and structure 3. Grammatical accuracy and formatting""") } if current_agent in agent_sequence: next_agent, tasks = agent_sequence[current_agent] self.current_agent = next_agent add_agent_messages(next_agent, tasks) def task_callback(task_output) -> None: raw_output = task_output.raw.strip() if self.current_agent == "News Editor": self.message_queue.add_message({ "role": "assistant", "content": "Final press release is ready!", "metadata": {"title": "📝 Final Press Release"} }) self.message_queue.add_message({ "role": "assistant", "content": raw_output }) else: self.message_queue.add_message({ "role": "assistant", "content": raw_output, "metadata": {"title": f"📰 Output from {self.current_agent}"} }) setup_next_agent(self.current_agent) def step_callback(output: Any) -> None: pass try: self.initialize_agents(topic) self.current_agent = "News Researcher" yield [{ "role": "assistant", "content": "Starting press release preparation...", "metadata": {"title": "🚀 Press Release Process Started"} }] add_agent_messages("News Researcher", """Gather essential details for a press release: 1. Identify key facts, statistics, and industry trends 2. Structure information into a brief outline 3. Suggest a compelling headline""") crew = Crew( agents=[self.researcher, self.writer, self.editor], tasks=self.create_tasks(topic), verbose=True, step_callback=step_callback, task_callback=task_callback ) def run_crew(): try: crew.kickoff() except Exception as e: self.message_queue.add_message({ "role": "assistant", "content": f"An error occurred: {str(e)}", "metadata": {"title": "❌ Error"} }) thread = threading.Thread(target=run_crew) thread.start() while thread.is_alive() or not self.message_queue.message_queue.empty(): messages = self.message_queue.get_messages() if messages: yield messages await asyncio.sleep(0.1) except Exception as e: yield [{ "role": "assistant", "content": f"An error occurred: {str(e)}", "metadata": {"title": "❌ Error"} }] def create_demo(): press_release_crew = None with gr.Blocks(theme=gr.themes.Soft()) as demo: gr.Markdown("# 📰 AI Space Launch Newsroom - Press Release Generator") openai_api_key = gr.Textbox( label='OpenAI API Key', type='password', placeholder='Enter your OpenAI API key...' ) chatbot = gr.Chatbot( label="Press Release Process", height=700, type="messages", show_label=True ) topic = gr.Textbox( label="Press Release Topic", placeholder="Enter topic..." ) btn = gr.Button("Generate Press Release", variant="primary") async def process_input(topic, history, api_key): nonlocal press_release_crew if not api_key: yield history + [{"role": "assistant", "content": "Please provide an OpenAI API key."}] return if press_release_crew is None: press_release_crew = PressReleaseCrew(api_key=api_key) async for messages in press_release_crew.process_press_release(topic): yield messages btn.click(process_input, [topic, chatbot, openai_api_key], [chatbot]) return demo if __name__ == "__main__": demo = create_demo() demo.queue() demo.launch(debug=True)