Update crew.py

crew.py

@@ -1,21 +1,55 @@
-from crewai import Crew, Process
-from langchain_openai import ChatOpenAI
+import os
 
-from agents import get_researcher_agent, get_writer_agent
-from tasks import get_research_task, get_write_task
-
-LLM_MANAGER="o4-mini"
-LLM_AGENT="gpt-4o-mini"
-
-VERBOSE = True
+from crewai import Agent, Task, Crew
+from crewai_tools import (
+    DirectoryReadTool,
+    FileReadTool,
+    SerperDevTool,
+    WebsiteSearchTool
+)
 
 def get_crew():
+    # Instantiate tools
+    docs_tool = DirectoryReadTool(directory='./blog-posts')
+    file_tool = FileReadTool()
+    search_tool = SerperDevTool()
+    web_rag_tool = WebsiteSearchTool()
+    
+    # Create agents
+    researcher = Agent(
+        role='Market Research Analyst',
+        goal='Provide up-to-date market analysis of the AI industry',
+        backstory='An expert analyst with a keen eye for market trends.',
+        tools=[search_tool, web_rag_tool],
+        verbose=True
+    )
+    
+    writer = Agent(
+        role='Content Writer',
+        goal='Craft engaging blog posts about the AI industry',
+        backstory='A skilled writer with a passion for technology.',
+        tools=[docs_tool, file_tool],
+        verbose=True
+    )
+    
+    # Define tasks
+    research = Task(
+        description='Research the latest trends in the AI industry and provide a summary.',
+        expected_output='A summary of the top 3 trending developments in the AI industry with a unique perspective on their significance.',
+        agent=researcher
+    )
+    
+    write = Task(
+        description='Write an engaging blog post about the AI industry, based on the research analyst's summary. Draw inspiration from the latest blog posts in the directory.',
+        expected_output='A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.',
+        agent=writer,
+        output_file='blog-posts/new_post.md'  # The final blog post will be saved here
+    )
+    
+    # Assemble a crew with planning enabled
     return Crew(
-        agents=[get_researcher_agent(LLM_AGENT, VERBOSE), 
-                get_writer_agent(LLM_AGENT, VERBOSE)],
-        tasks=[get_research_task(LLM_AGENT, VERBOSE), 
-               get_write_task(LLM_AGENT, VERBOSE)],
-        manager_llm=ChatOpenAI(model=LLM_MANAGER),
-        process=Process.sequential,
-        verbose=VERBOSE
+        agents=[researcher, writer],
+        tasks=[research, write],
+        verbose=True,
+        planning=True,  # Enable planning feature
     )