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import os
import streamlit as st
from langchain_community.utilities import GoogleSearchAPIWrapper
from langchain_google_generativeai import GoogleGenerativeAI
from langchain.llms import GooglePalm
from langchain.chains import ConversationChain
from langchain.memory import ConversationBufferMemory
import subprocess
import git
import logging
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# API Key Input
if "GOOGLE_API_KEY" not in st.session_state:
st.session_state.GOOGLE_API_KEY = ""
st.header("Enter your Google Search API Key")
st.session_state.GOOGLE_API_KEY = st.text_input("API Key:", value=st.session_state.GOOGLE_API_KEY, type="password")
# Initialize Google Search API Wrapper (only if API key is provided)
if st.session_state.GOOGLE_API_KEY:
search = GoogleSearchAPIWrapper(google_api_key=st.session_state.GOOGLE_API_KEY)
# Agents
agents = {
"WEB_DEV": {
"description": "Expert in web development technologies and frameworks.",
"skills": ["HTML", "CSS", "JavaScript", "React", "Vue.js", "Flask", "Django", "Node.js", "Express.js"],
"system_prompt": "You are a web development expert. Your goal is to assist the user in building and deploying web applications. Provide code snippets, explanations, and guidance on best practices.",
},
"AI_SYSTEM_PROMPT": {
"description": "Expert in designing and implementing AI systems.",
"skills": ["Machine Learning", "Deep Learning", "Natural Language Processing", "Computer Vision", "Reinforcement Learning"],
"system_prompt": "You are an AI system expert. Your goal is to assist the user in designing and implementing AI systems. Provide code snippets, explanations, and guidance on best practices.",
},
"PYTHON_CODE_DEV": {
"description": "Expert in Python programming and development.",
"skills": ["Python", "Data Structures", "Algorithms", "Object-Oriented Programming", "Functional Programming"],
"system_prompt": "You are a Python code development expert. Your goal is to assist the user in writing and debugging Python code. Provide code snippets, explanations, and guidance on best practices.",
},
"CODE_REVIEW_ASSISTANT": {
"description": "Expert in code review and quality assurance.",
"skills": ["Code Style", "Best Practices", "Security", "Performance", "Maintainability"],
"system_prompt": "You are a code review expert. Your goal is to assist the user in reviewing and improving their code. Provide feedback on code quality, style, and best practices.",
},
}
# Session State
if "workspace_projects" not in st.session_state:
st.session_state.workspace_projects = {}
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
if "active_agent" not in st.session_state:
st.session_state.active_agent = None
if "selected_agents" not in st.session_state:
st.session_state.selected_agents = []
if "current_project" not in st.session_state:
st.session_state.current_project = None
# Helper Functions
def add_code_to_workspace(project_name: str, code: str, file_name: str):
if project_name in st.session_state.workspace_projects:
st.session_state.workspace_projects[project_name]['files'].append({'file_name': file_name, 'code': code})
return f"Added code to {file_name} in project {project_name}"
else:
return f"Project {project_name} does not exist"
def terminal_interface(command: str, project_name: str):
try:
if project_name in st.session_state.workspace_projects:
result = subprocess.run(command, cwd=project_name, shell=True, capture_output=True, text=True)
return result.stdout + result.stderr
else:
return f"Project {project_name} does not exist"
except FileNotFoundError:
return f"Error: Command not found. Please check your command."
except Exception as e:
logging.error(f"An error occurred: {e}")
return f"An unexpected error occurred while running the command."
def get_agent_response(message: str, system_prompt: str):
llm = GoogleGenerativeAI(google_api_key=st.session_state.GOOGLE_API_KEY) # Use GoogleGenerativeAI
memory = ConversationBufferMemory()
conversation = ConversationChain(llm=llm, memory=memory)
full_prompt = f"{system_prompt}\n{message}"
response = conversation.run(full_prompt)
return response
def display_agent_info(agent_name: str):
agent = agents[agent_name]
st.sidebar.subheader(f"Active Agent: {agent_name}")
st.sidebar.write(f"Description: {agent['description']}")
st.sidebar.write(f"Skills: {', '.join(agent['skills'])}")
def display_workspace_projects():
st.subheader("Workspace Projects")
for project_name, project_data in st.session_state.workspace_projects.items():
with st.expander(project_name):
for file in project_data['files']:
st.text(file['file_name'])
st.code(file['code'], language="python")
def display_chat_history():
st.subheader("Chat History")
for message in st.session_state.chat_history:
st.text(message)
def run_autonomous_build(selected_agents: list[str], project_name: str):
st.info("Starting autonomous build process...")
for agent in selected_agents:
st.write(f"Agent {agent} is working on the project...")
prompt = f"Generate Python code for a simple web application using Flask framework in project {project_name}. Include instructions for running the application."
code = get_agent_response(prompt, agents[agent]['system_prompt'])
add_code_to_workspace(project_name, code, f"{agent.lower()}_app.py")
st.write(f"Agent {agent} has completed its task.")
st.success("Autonomous build process completed!")
def collaborative_agent_example(selected_agents: list[str], project_name: str, task: str):
st.info(f"Starting collaborative task: {task}")
responses = {}
for agent in selected_agents:
st.write(f"Agent {agent} is working on the task...")
response = get_agent_response(task, agents[agent]['system_prompt'])
responses[agent] = response
combined_response = combine_and_process_responses(responses, task)
st.success("Collaborative task completed!")
st.write(combined_response)
def combine_and_process_responses(responses: dict[str, str], task: str) -> str:
combined = "\n\n".join([f"{agent}: {response}" for agent, response in responses.items()])
return f"Combined response for task '{task}':\n\n{combined}"
# Streamlit UI
st.title("DevToolKit: AI-Powered Development Environment")
# Project Management
st.header("Project Management")
project_name = st.text_input("Enter project name:")
if st.button("Create Project"):
if project_name and project_name not in st.session_state.workspace_projects:
st.session_state.workspace_projects[project_name] = {'files': []}
st.success(f"Created project: {project_name}")
os.makedirs(project_name, exist_ok=True)
elif project_name in st.session_state.workspace_projects:
st.warning(f"Project {project_name} already exists")
else:
st.warning("Please enter a project name")
# Code Editor
st.subheader("Code Editor")
if st.session_state.workspace_projects:
selected_project = st.selectbox("Select project", list(st.session_state.workspace_projects.keys()))
if selected_project:
files = [file['file_name'] for file in st.session_state.workspace_projects[selected_project]['files']]
selected_file = st.selectbox("Select file to edit", files) if files else None
if selected_file:
file_content = next((file['code'] for file in st.session_state.workspace_projects[selected_project]['files']
if file['file_name'] == selected_file), "")
edited_code = st.text_area("Edit code", value=file_content, height=300)
if st.button("Save Changes"):
for file in st.session_state.workspace_projects[selected_project]['files']:
if file['file_name'] == selected_file:
file['code'] = edited_code
file_path = os.path.join(selected_project, selected_file)
with open(file_path, "w") as f:
f.write(edited_code)
st.success("Changes saved successfully!")
break
else:
st.info("No files in the project. Use the chat interface to generate code.")
else:
st.info("No projects created yet. Create a project to start coding.")
# Terminal Interface
st.subheader("Terminal (Workspace Context)")
if st.session_state.workspace_projects:
selected_project = st.selectbox("Select project for terminal",
list(st.session_state.workspace_projects.keys()),
key="terminal_project_select")
terminal_input = st.text_input("Enter a command within the workspace:")
if st.button("Run Command"):
terminal_output = terminal_interface(terminal_input, selected_project)
st.code(terminal_output, language="bash")
else:
st.info("No projects created yet. Create a project to use the terminal.")
# Chat Interface
st.subheader("Chat with AI Agents")
selected_agents = st.multiselect("Select AI agents", list(agents.keys()), key="agent_select")
st.session_state.selected_agents = selected_agents
agent_chat_input = st.text_area("Enter your message for the agents:", key="agent_input")
if st.button("Send to Agents", key="agent_send"):
if selected_agents and agent_chat_input:
responses = {}
for agent in selected_agents:
response = get_agent_response(agent_chat_input, agents[agent]['system_prompt'])
responses[agent] = response
st.session_state.chat_history.append(f"User: {agent_chat_input}")
for agent, response in responses.items():
st.session_state.chat_history.append(f"{agent}: {response}")
st.text_area("Chat History", value='\n'.join(st.session_state.chat_history), height=300)
else:
st.warning("Please select at least one agent and enter a message.")
# Agent Control
st.subheader("Agent Control")
for agent_name in agents:
agent = agents[agent_name]
with st.expander(f"{agent_name} ({agent['description']})"):
if st.button(f"Activate {agent_name}", key=f"activate_{agent_name}"):
st.session_state.active_agent = agent_name
st.success(f"{agent_name} activated.")
if st.button(f"Deactivate {agent_name}", key=f"deactivate_{agent_name}"):
st.session_state.active_agent = None
st.success(f"{agent_name} deactivated.")
# Automate Build Process
st.subheader("Automate Build Process")
if st.button("Automate"):
if st.session_state.selected_agents and project_name:
run_autonomous_build(st.session_state.selected_agents, project_name)
else:
st.warning("Please select at least one agent and create a project.")
# Version Control
st.subheader("Version Control")
repo_url = st.text_input("Enter repository URL:")
if st.button("Clone Repository"):
if repo_url and project_name:
try:
git.Repo.clone_from(repo_url, project_name)
st.success(f"Repository cloned successfully to {project_name}")
except git.GitCommandError as e:
st.error(f"Error cloning repository: {e}")
else:
st.warning("Please enter a repository URL and create a project.")
# Collaborative Agent Example
st.subheader("Collaborative Agent Example")
collab_agents = st.multiselect("Select AI agents for collaboration",
list(agents.keys()),
key="collab_agent_select")
collab_project = st.text_input("Enter project name for collaboration:")
collab_task = st.text_input("Enter collaborative task:")
if st.button("Start Collaborative Task"):
if collab_agents and collab_project and collab_task:
collaborative_agent_example(collab_agents, collab_project, collab_task)
else:
st.warning("Please select agents, enter a project name, and a task.")
else:
st.warning("Please enter your Google Search API Key to continue.")