This is the code..
import streamlit as st
import os
import json
from crewai import Agent, Task, Crew, Process
from crewai_tools import SerperDevTool
from datetime import datetime
from groq import Groq
import sqlite3
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Set up environment variables
os.environ["SERPER_API_KEY"] = os.getenv("SERPER_API_KEY")
os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")
# Initialize tools with error handling
try:
search_tool = SerperDevTool()
except Exception as e:
st.error(f"Error initializing SerperDevTool: {str(e)}")
search_tool = None
# Initialize Groq client
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
def perform_groq_chat_completion(prompt):
try:
chat_completion = client.chat.completions.create(
messages=[
{"role": "user", "content": prompt}
],
model="llama-3.1-70b-versatile",
)
return chat_completion.choices[0].message.content
except Exception as e:
st.error(f"Error performing Groq chat completion: {str(e)}")
return None
# Database setup
def init_db():
conn = sqlite3.connect('crewai_results.db')
c = conn.cursor()
c.execute('''CREATE TABLE IF NOT EXISTS results
(id INTEGER PRIMARY KEY AUTOINCREMENT,
crew_name TEXT,
result TEXT,
timestamp TEXT)''')
conn.commit()
conn.close()
def save_result(crew_name, result):
conn = sqlite3.connect('crewai_results.db')
c = conn.cursor()
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
c.execute("INSERT INTO results (crew_name, result, timestamp) VALUES (?, ?, ?)",
(crew_name, result, timestamp))
conn.commit()
conn.close()
def get_results():
conn = sqlite3.connect('crewai_results.db')
c = conn.cursor()
c.execute("SELECT * FROM results ORDER BY timestamp DESC")
results = c.fetchall()
conn.close()
return results
# AI-assisted agent creation
def ai_create_agent(description):
prompt = f"Parse the following agent description into a role, goal, and backstory. Respond in the format 'Role: [role]\nGoal: [goal]\nBackstory: [backstory]':\n\n{description}"
response = perform_groq_chat_completion(prompt)
if not response:
return None
# Initialize default values
agent_info = {
"role": "Undefined Role",
"goal": "Undefined Goal",
"backstory": "Undefined Backstory"
}
# Parse the response
for line in response.split('\n'):
if ':' in line:
key, value = line.split(':', 1)
key = key.strip().lower()
value = value.strip()
if key == 'role':
agent_info['role'] = value
elif key == 'goal':
agent_info['goal'] = value
elif key == 'backstory':
agent_info['backstory'] = value
return agent_info
# AI-generated task
def ai_create_task(description):
prompt = f"Generate a formal task description and expected output based on this natural language description. Respond in the format 'Description: [description]\nExpected Output: [expected output]':\n\n{description}"
response = perform_groq_chat_completion(prompt)
st.write("Debug - AI Response:", response) # Debug line
if not response:
return None
# Initialize default values
task_info = {
"description": "Undefined Description",
"expected_output": "Undefined Expected Output"
}
# Parse the response
for line in response.split('\n'):
if ':' in line:
key, value = line.split(':', 1)
key = key.strip().lower()
value = value.strip()
if key == 'description':
task_info['description'] = value
elif key == 'expected output':
task_info['expected_output'] = value
st.write("Debug - Parsed Task Info:", task_info) # Debug line
return task_info
# Streamlit app
st.set_page_config(page_title="CrewAI Crew Builder", layout="wide")
# Custom CSS for improved styling and readability
st.markdown("""
<style>
.stApp {
background-color: #2E3440;
color: #D8DEE9;
}
.stButton>button {
background-color: #5E81AC;
color: #ECEFF4;
}
.stTextInput>div>div>input {
background-color: #3B4252;
color: #E5E9F0;
}
.stTextArea>div>div>textarea {
background-color: #3B4252;
color: #E5E9F0;
}
.stExpander {
background-color: #434C5E;
}
.stExpander > div > div > div > div > div > p {
color: #E5E9F0;
}
h1, h2, h3 {
color: #88C0D0;
}
.stSidebar {
background-color: #3B4252;
}
.stSidebar [data-testid="stSidebarNav"] {
background-color: #2E3440;
}
</style>
""", unsafe_allow_html=True)
st.title("Enhanced CrewAI Crew Builder")
# Initialize session state
if 'agents' not in st.session_state:
st.session_state.agents = []
if 'tasks' not in st.session_state:
st.session_state.tasks = []
if 'crew_name' not in st.session_state:
st.session_state.crew_name = ""
if 'result' not in st.session_state:
st.session_state.result = None
# Sidebar for adding agents and tasks
st.sidebar.header("Crew Configuration")
st.session_state.crew_name = st.sidebar.text_input("Crew Name", st.session_state.crew_name)
# AI-generated agent
with st.sidebar.expander("Add Agent (AI-Assisted)"):
agent_description = st.text_area("Describe your agent")
if st.button("Generate Agent"):
if agent_description:
agent_info = ai_create_agent(agent_description)
if agent_info:
st.session_state.agents.append(agent_info)
st.success("Agent added successfully!")
else:
st.error("Failed to generate agent. Please try again.")
else:
st.error("Please provide a description for the agent.")
# AI-generated task
with st.sidebar.expander("Add Task (AI-Generated)"):
task_description = st.text_area("Describe your task")
if st.button("Generate Task"):
if task_description:
task_info = ai_create_task(task_description)
if task_info:
st.session_state.tasks.append(task_info)
st.success("Task added successfully!")
st.write("Debug - Tasks after adding:", st.session_state.tasks) # Debug line
st.rerun() # Use st.rerun() instead of st.experimental_rerun()
else:
st.error("Failed to generate task. Please try again.")
else:
st.error("Please provide a description for the task.")
# Template Library
with st.sidebar.expander("Template Library"):
template_type = st.selectbox("Select template type", ["Agent", "Task"])
if template_type == "Agent":
agent_templates = {
"Researcher": {"role": "Researcher", "goal": "Gather and analyze information", "backstory": "Experienced academic with a passion for discovery"},
"Writer": {"role": "Writer", "goal": "Create engaging content", "backstory": "Published author with a flair for storytelling"},
"Data Analyst": {"role": "Data Analyst", "goal": "Extract insights from data", "backstory": "Statistical expert with a keen eye for patterns"},
}
selected_template = st.selectbox("Select an agent template", list(agent_templates.keys()))
if st.button("Use Template"):
st.session_state.agents.append(agent_templates[selected_template])
st.success(f"{selected_template} template added!")
else:
task_templates = {
"Market Research": {"description": "Conduct market research on a specific product", "expected_output": "Comprehensive market analysis report"},
"Content Creation": {"description": "Write a blog post on a given topic", "expected_output": "1500-word SEO-optimized blog post"},
"Data Analysis": {"description": "Analyze sales data for the past quarter", "expected_output": "Executive summary with key insights and visualizations"},
}
selected_template = st.selectbox("Select a task template", list(task_templates.keys()))
if st.button("Use Template"):
st.session_state.tasks.append(task_templates[selected_template])
st.success(f"{selected_template} template added!")
# Main content area
col1, col2 = st.columns(2)
# Display and edit agents
with col1:
st.header("Agents")
for i, agent in enumerate(st.session_state.agents):
with st.expander(f"Agent {i+1}: {agent['role']}"):
agent['role'] = st.text_input("Role", agent['role'], key=f"agent_role_{i}")
agent['goal'] = st.text_area("Goal", agent['goal'], key=f"agent_goal_{i}")
agent['backstory'] = st.text_area("Backstory", agent['backstory'], key=f"agent_backstory_{i}")
if st.button(f"Remove Agent {i+1}"):
st.session_state.agents.pop(i)
st.experimental_rerun()
# Display and edit tasks
with col2:
st.header("Tasks")
if not st.session_state.tasks:
st.write("No tasks added yet.")
for i, task in enumerate(st.session_state.tasks):
with st.expander(f"Task {i+1}"):
task['description'] = st.text_area("Description", task['description'], key=f"task_desc_{i}")
task['expected_output'] = st.text_area("Expected Output", task['expected_output'], key=f"task_output_{i}")
if st.button(f"Remove Task {i+1}"):
st.session_state.tasks.pop(i)
st.rerun() # Use st.rerun() here as well
# Visualization of crew structure
if st.session_state.agents and st.session_state.tasks:
st.header("Crew Structure Visualization")
crew_structure = {
"name": st.session_state.crew_name,
"children": [
{"name": "Agents", "children": [{"name": agent["role"]} for agent in st.session_state.agents]},
{"name": "Tasks", "children": [{"name": task["description"][:30] + "..."} for task in st.session_state.tasks]}
]
}
st.json(crew_structure) # This is a simple JSON representation; you could use a proper visualization library for a more interactive display
# Run the crew
if st.button("Run Crew"):
if st.session_state.crew_name and len(st.session_state.agents) > 0 and len(st.session_state.tasks) > 0:
if search_tool is None:
st.error("SerperDevTool is not initialized. Please check your API keys and try again.")
else:
# Create Agent and Task objects
agents = [Agent(
role=a['role'],
goal=a['goal'],
backstory=a['backstory'],
verbose=True,
allow_delegation=True,
tools=[search_tool]
) for a in st.session_state.agents]
tasks = [Task(
description=t['description'],
agent=agents[i % len(agents)],
expected_output=t['expected_output']
) for i, t in enumerate(st.session_state.tasks)]
# Create and run the crew
crew = Crew(
agents=agents,
tasks=tasks,
process=Process.sequential,
verbose=True,
max_delegation_depth=2
)
with st.spinner("Running crew..."):
try:
st.session_state.result = crew.kickoff()
st.success("Crew execution completed successfully!")
st.write(st.session_state.result)
# Save result to database
init_db()
save_result(st.session_state.crew_name, str(st.session_state.result))
except Exception as e:
st.error(f"An error occurred during crew execution: {str(e)}")
else:
st.error("Please provide a crew name and add at least one agent and one task before running the crew.")
# View saved results
if st.button("View Saved Results"):
results = get_results()
for result in results:
with st.expander(f"Crew: {result[1]} - {result[3]}"):
st.write(result[2])
# Export configuration
if st.sidebar.button("Export Configuration"):
config_data = {
"crew_name": st.session_state.crew_name,
"agents": st.session_state.agents,
"tasks": st.session_state.tasks
}
st.sidebar.download_button(
label="Download Configuration",
data=json.dumps(config_data, indent=2),
file_name=f"{st.session_state.crew_name}_config.json",
mime="application/json"
)
# AI Suggestions
if st.button("Get AI Suggestions"):
crew_info = json.dumps({"agents": st.session_state.agents, "tasks": st.session_state.tasks})
prompt = f"Analyze this crew configuration and provide suggestions for improvement:\n\n{crew_info}"
suggestions = perform_groq_chat_completion(prompt)
st.write("AI Suggestions:", suggestions)
# Initialize the database
init_db()This is the Output to the first run of the app..
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