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import os

# Set your OpenAI API key
os.environ["OPENAI_API_KEY"] = "your_openai_api_key"

class Agent:
 def __init__(self, name):
 self.name = name

 def perceive(self, input_data):
 """Receive input from the environment."""
 raise NotImplementedError("Perceive method must be implemented.")

 def decide(self):
 """Make decisions based on perceived input."""
 raise NotImplementedError("Decide method must be implemented.")

 def act(self):
 """Perform an action based on the decision."""
 raise NotImplementedError("Act method must be implemented.")

class InputAgent(Agent):
 def perceive(self, input_data):
 self.topic = input_data

 def decide(self):
 return f"Proceeding with research on: {self.topic}"

 def act(self):
 print(self.decide())
 return self.topic

class RetrievalAgent(Agent):
 def __init__(self, name, api_url):
 super().__init__(name)
 self.api_url = api_url

 def perceive(self, topic):
 self.topic = topic

 def decide(self):
 query_params = {"q": self.topic, "apiKey": "your_api_key"}
 return requests.get(self.api_url, params=query_params)

 def act(self):
 response = self.decide()
 if response.status_code == 200:
 articles = response.json().get("articles", [])
 print(f"Retrieved {len(articles)} articles.")
 return articles
 else:
 print("Failed to retrieve articles.")
 return []

import openai

class SummarizationAgent(Agent):
 def perceive(self, articles):
 self.articles = articles

 def decide(self):
 summaries = []
 for article in self.articles:
 prompt = f"Summarize the following article:\n\n{article['content']}"
 response = openai.Completion.create(
 model="text-davinci-003",
 prompt=prompt,
 max_tokens=100
 )
 summaries.append(response.choices[0].text.strip())
 return summaries

 def act(self):
 summaries = self.decide()
 for idx, summary in enumerate(summaries):
 print(f"Summary {idx + 1}: {summary}")
 return summaries

class Workflow:
 def __init__(self, agents):
 self.agents = agents

 def run(self, input_data):
 current_data = input_data
 for agent in self.agents:
 agent.perceive(current_data)
 current_data = agent.act()
 print("Workflow completed.")

# Define the API URL for article retrieval
api_url = "https://newsapi.org/v2/everything"

# Create agents
input_agent = InputAgent(name="InputAgent")
retrieval_agent = RetrievalAgent(name="RetrievalAgent", api_url=api_url)
summarization_agent = SummarizationAgent(name="SummarizationAgent")

# Orchestrate workflow
agents = [input_agent, retrieval_agent, summarization_agent]
research_workflow = Workflow(agents)

# Run the workflow
topic = "AI in Healthcare"
research_workflow.run(topic)

class FileStorageAgent(Agent):
 def perceive(self, summaries):
 self.summaries = summaries

 def decide(self):
 return "Summaries saved to research_summaries.txt."

 def act(self):
 with open("research_summaries.txt", "w") as file:
 for summary in self.summaries:
 file.write(summary + "\n\n")
 print(self.decide())

file_storage_agent = FileStorageAgent(name="FileStorageAgent")
agents.append(file_storage_agent)