CrewAI + Command-R7B 100 Lines of Code for Intelligent News Generation

on the basis of CrewAI With multi-intelligence collaboration and the Cohere Command-R7B Big Model, the system automates the entire process from research to writing, like having a 24-hour newsroom.

Core Functions:

1. Research and analysis: the first AI assistant is responsible for searching and organizing all information related to the topic, including news, data and expert opinion.
2. Content creation: a second AI assistant transforms the research material into fully structured articles, ensuring professionalism and readability.
3. One-Click Generation: the user simply enters the topic and the system does all the work automatically.

Technical Highlights:

• Adopting crewAI, a framework for multi-AI collaboration

• Ensure output quality with cohere, Command-R7B grand modeling

• Build a clean and easy-to-use web interface based on streamlit.

Use the process:

1. Enter the topic you want to know about in the sidebar
2. Option to adjust generation parameters (e.g. degree of creativity)
3. Click the Generate button
4. Waiting for the system to complete research and writing
5. Generated articles can be viewed or downloaded directly

The architecture diagram shown below illustrates some of the key components (intelligences/tasks/tools) and how they interact with each other!

Each component and its code is described in detail next:

Setting up the Large Language Model (LLM) and web search tools

Also create an .env file to hold their corresponding API keys:

Senior Research Analyst Intelligence

The Web Search Intelligence accepts user queries and then uses the Serper Web Search tool to fetch results from the Internet and consolidate them.

Look at this!

Research Analyst Intelligence Body Tasks

This is the research task we assigned to the Senior Research Analyst Intelligence Body and contains the task description and expected output.

Content authoring intelligences

The role of the Content Writing Intelligence is to use the collated results and turn them into a polished, publishable news article.

Content Writing Intelligent Body Tasks

This is how we describe the writing assignment, including all the details and expected output:

Set Crew, done! ✅

Start it up! 🚀

Deployment Tutorial

AI News Generator

The project builds an AI news generator using CrewAI and Cohere's Command-R:7B model!

Installation and Setup

Getting the API key::

• SQLite GUI key
• Cohere API key

Installing dependencies::
Make sure you have Python 3.11 or later installed.

pip install crewai crewai-tools

.env.example

SERPER_API_KEY=your_serper_api_key
COHERE_API_KEY=your_cohere_apikey

app.py

import os
import streamlit as st
from crewai import Agent, Task, Crew, LLM
from crewai_tools import SerperDevTool
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Streamlit page config
st.set_page_config(page_title="AI News Generator", page_icon="📰", layout="wide")

# Title and description
st.title("🤖 AI News Generator, powered by CrewAI and Cohere's Command R7B")
st.markdown("Generate comprehensive blog posts about any topic using AI agents.")

# Sidebar
with st.sidebar: st.header("Settings")
st.header("Content Settings")

# Make the text input take up more space
topic = st.text_area(
"Enter your topic",
height=100,
placeholder="Enter the topic you want to generate content about...")
)

# Add more sidebar controls if needed
st.markdown("### Advanced Settings")
temperature = st.slider("Temperature", 0.0, 1.0, 0.7)

# Add some spacing
st.markdown("----")

# Make the generate button more prominent in the sidebar
generate_button = st.button("Generate Content", type="primary", use_container_width=True)

# Add some helpful information
with st.expander("ℹ️ How to use"): st.markdown(""): st.expander("ℹ️ How to use").
st.markdown(""")
1. Enter your desired topic in the text area above
2. Adjust the temperature if needed (higher = more creative)
3. Click 'Generate Content' to start
4. Wait for the AI to generate your article
5. Download the result as a markdown file
""")

def generate_content(topic):
llm = LLM(
model="command-r",
temperature=0.7
)

search_tool = SerperDevTool(n_results=10)

# First Agent: Senior Research Analyst
senior_research_analyst = Agent(
role="Senior Research Analyst", goal=f "Research, analyze

backstory="You're an expert research analyst with advanced web research skills. "
"You excel at finding, analyzing, and synthesizing information from "
You're skilled at " "distinguishing reliable sources from unreliable sources."
"distinguishing reliable sources from unreliable ones,"
You're skilled at " "distinguishing reliable sources from unreliable ones," " "fact-checking, cross-referencing information, and " "identifying key patterns and insights."
" "identifying key patterns and insights.
" "well-organized research briefs with proper citations " "and source verification.
Your analysis includes both " "raw data and interpreted insights.
" "raw data and interpreted insights, making complex " "information accessible and actionable.
" "information accessible and actionable.",
allow_delegation=False, verbose=True, " "and source verification.
verbose=True, tools=[search_tools][search_tools][search_tools], and
tools=[search_tool],
llm=llm
)

# Second Agent: Content Writer
content_writer = Agent(
role="Content Writer", goal="Transform research findings into engaging blog posts while maintaining accuracy", content_writer = Agent(
goal="Transform research findings into engaging blog posts while maintaining accuracy",
backstory="You're a skilled content writer specialized in creating "
"engaging, accessible content from technical research."
"You work closely with the Senior Research Analyst and excel at maintaining the perfect " "balance between informative and entertaining content.
"balance between informative and entertaining writing, "
" "while ensuring all facts and citations from the research " "are properly incorporated.
You have a talent for making " "complex topics approachable without oversimplifying.
You have a talent for making " "complex topics approachable without oversimplifying them.", " "while ensuring all facts and citations from the research " "are properly incorporated.
You have a talent for making " "complex topics approachable without oversimplifying them.", allow_delegation=False, verbose=True, verbose=True, verbose=True.
You have a talent for making " "complex topics approachable without oversimplifying them.
llm=llm
)

# Research Task
research_task = Task(
description=("""
1. Conduct comprehensive research on {topic} including.
- Recent developments and news
- Key industry trends and innovations
- Expert opinions and analyses
- Expert opinions and analyses
2. Evaluate source credibility and fact-check all information
3. Organize findings into a structured research brief
4. Include all relevant citations and sources
"""), expected_output="""), expected_output=""")
expected_output="""A detailed research report containing.
- Executive summary of key findings
- Comprehensive analysis of current trends and developments
- List of verified facts and statistics
- All citations and links to original sources
- Clear categorization of main themes and patterns
Please format with clear sections and bullet points for easy reference.""","","
Please format with clear sections and bullet points for easy reference.""", agent=senior_research_analyst
)

# Writing Task
writing_task = Task(
description=("""
Using the research brief provided, create an engaging blog post that.
1. Transforms technical information into accessible content
2. Maintains all factual accuracy and citations from the research
3. Includes.
- Attention-grabbing introduction
- Well-structured body sections with clear headings
- Includes: Attention-grabbing introduction Well-structured body sections with clear headings
4. Preserves all source citations in [Source: URL] format
5. Includes a References section at the end
Includes a References section at the end """), expected_output="""), and
expected_output="""A polished blog post in markdown format that.
- Engages readers while maintaining accuracy
- Contains properly structured sections
- Includes Inline citations hyperlinked to the original source url
- Presents information in an accessible yet informative way
- Follows proper markdown formatting, use H1 for the title and H3 for the sub-sections""","","
agent=content_writer
)

# Create Crew
crew = Crew(
agents=[senior_research_analyst, content_writer],
tasks=[research_task, writing_task], verbose=True
verbose=True
)

return crew.kickoff(inputs={"topic": topic})

# Main content area
if generate_button.
with st.spinner('Generating content... This may take a moment.').
This may take a moment.'): try.
result = generate_content(topic)
st.markdown("### Generated Content")
st.markdown(result)

# Add download button
st.download_button(
label="Download Content",
data=result.raw, file_name=f"{topic.lower()
file_name=f"{topic.lower().replace(' ', '_')}_article.md",
mime="text/markdown"
)
except Exception as e.
st.error(f "An error occurred: {str(e)}")

# Footer
st.markdown("---")
st.markdown("Built with CrewAI, Streamlit and powered by Cohere's Command R7B")

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