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ALwrity/lib/content_planning_calender/content_planning_agents_alwrity_crew.py

242 lines
12 KiB
Python

import os
import streamlit as st
from crewai import Agent, Task, Crew
from crewai_tools import SerperDevTool
from langchain_google_genai import ChatGoogleGenerativeAI
from crewai_tools import ScrapeWebsiteTool
from crewai_tools import FileReadTool
from ..ai_web_researcher.google_trends_researcher import do_google_trends_analysis
def create_agents(search_keywords, already_written_on):
# Tools for the agents.
search_tool = SerperDevTool()
# To enable scrapping any website it finds during it's execution
#scrape_tool = ScrapeWebsiteTool()
# To read results from a file.
# Initialize the tool to read any files the agents knows or lean the path for
# file_read_tool = FileReadTool()
# Initialize the tool with a specific file path, so the agent can only read the content of the specified file
file_read_tool = FileReadTool(file_path=os.getenv('SEARCH_SAVE_FILE'))
# The manager keeps an eye on the content already planned to give new ideas.
# TBD: Accept the user website urls and populate the file with sitemap.xml
manager_read_tool = FileReadTool(file_path=already_written_on)
# Load the google gemini api key
google_api_key = os.getenv("GEMINI_API_KEY")
# Set gemini pro as llm
llm = ChatGoogleGenerativeAI(
model="gemini-pro", verbose=True, temperature=0.7, google_api_key=google_api_key
)
content_researcher = Agent(
role = 'Senior Web Research Analyst (Content Strategy): Aisha Sharma',
goal = f"""Help Create a highly detailed 2 month-long content calender, focused around keywords: {search_keywords}.
Provide web researched titles to be used for content calender & planning to Ted XingPi""",
backstory = f"""
Your Focus: Content Opportunity Analysis & Keyword Research ({search_keywords}).
Your Skills:
1). Web Research & Content Gap Identification (Expert).
2). SEO Best Practices, Keyword Research & content planning expert (Advanced).
3). Analyzes search trends and competitor content.
4). Fuel company's content strategy with data-driven insights to attract and educate online readers.
5). Identifies high-volume, low-competition keywords relevant to {search_keywords}.
Responsibilities:
1). Recommend high-value content opportunities through in-depth web research and competitor analysis.
2). Provide your research to Senior Content Strategist & planner - Ted XingPi
""",
tools = [search_tool],
memory = True, # Enable memory
verbose = True,
max_rpm = None, # No limit on requests per minute
max_iter = 10, # Default value for maximum iterations
allow_delegation = False,
llm = llm
)
content_planner = Agent(
role = 'Senior Content Strategist & planner - Ted XingPi',
goal = f"""
Craft a series of content titles around {search_keywords} that can be expanded into 2 month-long series.
Do not repeat the blog titles, always consult the previously written blog titles from the file: {already_written_on}.""",
backstory = """You are Ted XingPi, with Experience of 15 years.
Your Skills:
1). Content Opportunity Analysis & Content calender planning (Expert).
2). AI Applications for Content Marketing (Highly Knowledgeable).
3). Content Strategy Development & keyword research for content opportunities.
Your Responsibilties:
1). Employ a balance of head terms (broad topics) and long-tail keywords (specific phrases) for optimal reach and targeting.
2). Review & Include suggestions from Content Marketing & Google Trends Specialist - Sarah Qureshi.
3). Identify content topics and keywords for {search_keywords}.
4). Senior Web Research Analyst (Content Strategy): Aisha Sharma
5). Create content calender that showcases the value proposition around {search_keywords}.
6). New content should target unique keywords to avoid competition with existing content.
7). Focus on specific aspects within a theme to differentiate semantically similar keywords for {search_keywords}.
8). Collaborate with team to identify content gaps and trending topics, relevant to given keywords.
9). Develop content calender with a focus on organic marketing to attract online customers.
10). The content calender should include, Head Term Keyword, Long-Tail Keyword and Blog Post Title.
""",
memory = True, # Enable memory
verbose = True,
tools = [manager_read_tool],
max_rpm = None, # No limit on requests per minute
max_iter = 15, # Default value for maximum iterations
allow_delegation = False,
llm = llm
)
google_trends_researcher = Agent(
role = 'Content Marketing & Google Trends Specialist - Sarah Qureshi.',
goal = f"""Help Create a highly detailed 2 month-long content calender, focused around keywords: {search_keywords}.
Analyse & provide Google trends data for content calender & planning to Ted XingPi""",
backstory = f"""You are Sarah Qureshi, with 10 years as a content writer and planner.
Your Skills:
1). Proven experience in using Google Trends for keyword research.
2). Strong understanding of SEO best practices.
3). Reading files and understanding long table with data.
Your responsibilties:
1). Collaborate on content strategy, provide keyword, titles recommendations to Ted XingPi.
2). Recommend high-volume, low-competition keywords, titles with strong user intent.
3). Recommend, Rising search queries related to {search_keywords}.
4). Recommend keywords, blog titles for preparing/planning the content calender.
5). Provide your research to Senior Content Strategist & planner - Ted XingPi
""",
memory = True, # Enable memory
tools = [file_read_tool],
verbose = True,
max_rpm = None, # No limit on requests per minute
max_iter = 15, # Default value for maximum iterations
allow_delegation = False,
llm = llm
)
content_marketing_manager = Agent(
role="Content Marketing Manager - Diksha Yuj",
goal=f"""Create highly detailed 2 month-long content calender, focused around keywords: {search_keywords}.
Use insights and context from team members: Sarah Qureshi, Ted XingPi and Aisha Sharma""",
backstory="""
Content Marketing Manager: Diksha Yuj
Experience: Digital Marketing Veteran (15+ years)
Mission: Supercharge organic growth of the company, with content marketing.
Responsibilities:
1). Ensures that content titles are not repeated & No keyword cannabilization.
2). Maintains and consults a file for all previous written titles({already_written_on}).
3). Develops a content calendar aligned and optimized around {search_keywords}.
4). Keenly follows & learns the research and communication of other team members.
5). The content calender should include, Head Term Keyword, Long-Tail Keyword and Blog Post Title.
6). Use insights and context from team members: Sarah Qureshi, Ted XingPi and Aisha Sharma
""",
memory=True, # Enable memory
verbose=True,
tools = [manager_read_tool],
max_rpm=None, # No limit on requests per minute
max_iter=10, # Default value for maximum iterations
allow_delegation=False,
llm=llm
)
return [content_researcher, google_trends_researcher, content_planner, content_marketing_manager]
def create_tasks(agents, search_keywords, already_written_on):
research_task = Task(
description=f"""Conduct web analysis on "{search_keywords}",for content calender.
Set the input parameter 'search_query' to query""",
expected_output=f"""Provide comprehensive content calender ideas to Senior Content Strategist & planner - Ted XingPi""",
agent=agents[0] # Assign to the researcher agent
)
google_trends_task = Task(
description=f"""Conduct Google Trends analysis, on keywords: {search_keywords}, from the file({os.getenv('SEARCH_SAVE_FILE')}).
Suggest blog titles for content calender. Recommend high-volume, low-competition keywords with strong user intent.
Set the input parameter 'file_path' to {os.getenv('SEARCH_SAVE_FILE')}""",
expected_output=f"Provide comprehensive content calender ideas to Senior Content Strategist & planner - Ted XingPi",
agent=agents[1] # Assign to the researcher agent
)
planner_task = Task(
description=f"""Develop a content calendar for {search_keywords}, based team member's.
New content should target unique keywords to avoid competition with existing content.
Use context & insights from Aisha Sharma & Sarah Qureshi.
Set the input parameter file_path to {already_written_on}""",
expected_output=f"""A Highly detailed content calender that positions {search_keywords} as a must-read for industry insiders and newcomers alike. Final content calender for the next 2 months. Targeting 5 articles per week.
""",
#human_input=True,
agent=agents[2] # Assign to the outliner agent
)
marketing_manager_task = Task(
description=f"""Make sure the content calender is optimised for keywords: '{search_keywords}'.
Make sure the titles are unique, semantically unique and mitigate keyword cannabilization.
Use context & insights from Aisha Sharma, Ted XingPi & Sarah Qureshi.
Set the input parameter 'file_path' to {already_written_on}
""",
expected_output=f"""Final content calender for the next 2 months. Targeting 5 articles per week.
Make sure to present the content calender in tabular format. Include details of how to use the content calender.
""",
agent=agents[3] # Assign to the reviewer agent
)
return [research_task, google_trends_task, planner_task, marketing_manager_task]
def execute_tasks(agents, tasks):
""" WIP """
result = None
crew = Crew(
agents=agents,
tasks=tasks,
verbose=2, # You can set it to 1 or 2 for different logging levels
#process=Process.sequential,
#memory=True,
language="en"
)
try:
result = crew.kickoff()
return result
except Exception as err:
print(err)
def ai_agents_content_planner(search_keywords):
already_written_on = os.path.join(os.getcwd(), "lib", "content_planning_calender", "content_already_planned.txt")
do_google_trends_analysis(search_keywords)
result = None
#setup_environment()
try:
agents = create_agents(search_keywords, already_written_on)
except Exception as err:
st.error(f"Failed in Creating in Agents: {err}")
try:
tasks = create_tasks(agents, search_keywords, already_written_on)
except Exception as err:
st.error(f"Failed to Create Agent Tasks: {err}")
try:
result = execute_tasks(agents, tasks)
except Exception as err:
st.error(f"Failed to execute Agent Tasks: {err}")
st.markdown("### Final Content Calender:")
st.markdown(result)