streamlit-crewai-process-output 0.1.1

A component for displaying CrewAI agent process outputs in Streamlit applications

Streamlit CrewAI Process Output

A Streamlit component for beautifully displaying CrewAI's process output in real-time. This component makes it easy to create engaging Streamlit apps with CrewAI by providing:

• 🎨 Beautiful, formatted output with emojis
• ⚡ Real-time streaming updates
• 🔍 Automatic detection of different output types (agents, tasks, thoughts)
• 🧩 Simple integration with just a few lines of code

Installation

pip install streamlit-crewai-process-output

This will automatically install all required dependencies:

• crewai>=0.95.0
• crewai-tools>=0.25.8
• streamlit>=1.41.0

Compatible with Python 3.7 through 3.12.

Quick Start

Here's a complete, working example you can copy and run:

import streamlit as st
from crewai import Agent, Task, Crew, Process
from crewai_tools import SerperDevTool
from streamlit_crewai_process_output import CrewAIProcessOutput
import os

st.title("CrewAI Research Assistant")

# API Keys in sidebar
with st.sidebar:
    st.markdown("### ⚙️ Configuration")
    with st.expander("🔑 API Keys", expanded=True):
        st.info("API keys are stored temporarily in memory and cleared when you close the browser.")
        
        openai_api_key = st.text_input("OpenAI API Key", type="password")
        if openai_api_key:
            os.environ["OPENAI_API_KEY"] = openai_api_key
            
        serper_api_key = st.text_input("SerperDev API Key", type="password")
        if serper_api_key:
            os.environ["SERPER_API_KEY"] = serper_api_key

# Check if API keys are set
if not os.getenv("OPENAI_API_KEY") or not os.getenv("SERPER_API_KEY"):
    st.warning("⚠️ Please enter your API keys in the sidebar to get started")
    st.stop()

# Research task input
task_description = st.text_area(
    "What would you like to research?",
    value="Research the latest developments in AI and summarize the key trends."
)

if st.button("Start Research"):
    with st.status("🤖 Researching...", expanded=True):
        try:
            # Set up CrewAI process output
            output_container = st.container()
            with CrewAIProcessOutput.capture(output_container):
                # Create the researcher agent
                researcher = Agent(
                    role='Research Analyst',
                    goal='Conduct thorough research on given topics',
                    backstory='Expert at analyzing and summarizing complex information',
                    tools=[SerperDevTool()],
                    verbose=True
                )

                # Create and run the crew
                crew = Crew(
                    agents=[researcher],
                    tasks=[Task(
                        description=task_description,
                        expected_output="Summary of the research findings",
                        agent=researcher
                    )],
                    verbose=True,
                    process=Process.sequential
                )

                # Run and get result
                result = crew.kickoff()
            
        except Exception as e:
            st.error(f"An error occurred: {str(e)}")
            return

    # Display final result in markdown
    st.markdown("---")
    st.markdown("### 🏁 Final Result")
    st.markdown(result)
            

Save this as app.py and run it with:

streamlit run app.py

You'll need:

1. An OpenAI API key from OpenAI
2. A SerperDev API key from SerperDev

Why Use This Component?

1. Better User Experience: Instead of raw console output, your users see a beautifully formatted, real-time stream of what CrewAI is doing.

2. Zero Configuration: The component automatically detects and formats different types of output (agents, tasks, thoughts) with appropriate emojis and styling.

3. Simple Integration: Just wrap your CrewAI code in a with statement - no need to handle stdout redirection or process different output types manually.

4. Real-time Updates: Users can see exactly what's happening as CrewAI works, making your app more engaging and informative.

5. Clean Code: Keep your Streamlit app code clean and focused on business logic instead of output formatting.

Contributing

We welcome contributions! Feel free to open issues or submit pull requests on our GitHub repository.

Made with ❤️ by Tony Kipkemboi.