import json import streamlit as st import os import subprocess from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer from huggingface_hub import HfApi try: huggingface_json = st.secrets["hf_token"] huggingface_data = json.loads("huggingface_json") huggingface_token = huggingface_data["huggingface_json"] except Exception as e: st.error(f"Unable to load secrets: {str(e)}") raise PROJECT_ROOT = "projects" AGENT_DIRECTORY = "agents" AVAILABLE_CODE_GENERATIVE_MODELS = ["bigcode/starcoder", "Salesforce/codegen-350M-mono", "microsoft/CodeGPT-small"] # Global state to manage communication between Tool Box and Workspace Chat App if 'chat_history' not in st.session_state: st.session_state.chat_history = [] if 'terminal_history' not in st.session_state: st.session_state.terminal_history = [] if 'workspace_projects' not in st.session_state: st.session_state.workspace_projects = {} if 'available_agents' not in st.session_state: st.session_state.available_agents = [] # AI Guide Toggle ai_guide_level = st.sidebar.radio("AI Guide Level", ["Full Assistance", "Partial Assistance", "No Assistance"]) class AIAgent: def __init__(self, name, description, skills): self.name = name self.description = description self.skills = skills self._hf_api = HfApi(token=huggingface_token) def create_agent_prompt(self): skills_str = '\n'.join([f"* {skill}" for skill in self.skills]) agent_prompt = f""" As an elite expert developer, my name is {self.name}. I possess a comprehensive understanding of the following areas: {skills_str} I am confident that I can leverage my expertise to assist you in developing and deploying cutting-edge web applications. Please feel free to ask any questions or present any challenges you may encounter. """ return agent_prompt def autonomous_build(self, chat_history, workspace_projects, project_name, selected_model, hf_token): summary = "Chat History:\n" + "\n".join([f"User: {u}\nAgent: {a}" for u, a in chat_history]) summary += "\n\nWorkspace Projects:\n" + "\n".join([f"{p}: {details}" for p, details in workspace_projects.items()]) next_step = "Based on the current state, the next logical step is to implement the main application logic." return summary, next_step def deploy_built_space_to_hf(self): # Implement logic to deploy the built space to Hugging Face Spaces pass def has_valid_hf_token(self): return self._hf_api.whoami() is not None def process_input(input_text): chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium", tokenizer="microsoft/DialoGPT-medium") response = chatbot(input_text, max_length=50, num_return_sequences=1)[0]['generated_text'] return response def run_code(code): try: result = subprocess.run(code, shell=True, capture_output=True, text=True) return result.stdout except Exception as e: return str(e) def workspace_interface(project_name): project_path = os.path.join(PROJECT_ROOT, project_name) if not os.path.exists(project_path): os.makedirs(project_path) st.session_state.workspace_projects[project_name] = {'files': []} return f"Project '{project_name}' created successfully." else: return f"Project '{project_name}' already exists." def add_code_to_workspace(project_name, code, file_name): project_path = os.path.join(PROJECT_ROOT, project_name) if not os.path.exists(project_path): return f"Project '{project_name}' does not exist." file_path = os.path.join(project_path, file_name) with open(file_path, "w") as file: file.write(code) st.session_state.workspace_projects[project_name]['files'].append(file_name) return f"Code added to '{file_name}' in project '{project_name}'." def display_chat_history(chat_history): return "\n".join([f"User: {u}\nAgent: {a}" for u, a in chat_history]) def display_workspace_projects(workspace_projects): return "\n".join([f"{p}: {details}" for p, details in workspace_projects.items()]) if __name__ == "__main__": st.set_page_config(layout="wide", page_title="AI-Powered Development Platform") # Sidebar st.sidebar.title("AI Development Platform") st.sidebar.header("Tool Box") st.sidebar.subheader("Workspace Management") project_name_input = st.sidebar.text_input("Project Name:") create_project_button = st.sidebar.button("Create Project") if create_project_button: st.sidebar.write(workspace_interface(project_name_input)) st.sidebar.subheader("Code Generation") selected_model = st.sidebar.selectbox("Select Code Model", AVAILABLE_CODE_GENERATIVE_MODELS) code_input = st.sidebar.text_area("Enter Code Prompt:") generate_code_button = st.sidebar.button("Generate Code") if generate_code_button: if selected_model: tokenizer = AutoTokenizer.from_pretrained(selected_model) model = AutoModelForCausalLM.from_pretrained(selected_model) code_generator = pipeline("text-generation", model=model, tokenizer=tokenizer) generated_code = code_generator(code_input, max_length=500, num_return_sequences=1)[0]['generated_text'] st.sidebar.code(generated_code) else: st.sidebar.error("Please select a code model.") st.sidebar.subheader("Terminal") command = st.sidebar.text_input("Enter a command:") if command: output, error = run_code(command) if error: st.sidebar.error(f"Error executing command: {error}") else: st.sidebar.code(output) # Main Content st.title("AI-Powered Development Platform") st.header("Workspace") st.subheader("Chat with an AI Agent") chat_input = st.text_input("Enter your message:") if chat_input: st.session_state.chat_history.append((chat_input, process_input(chat_input))) st.markdown("## Chat History ##") st.markdown(display_chat_history(st.session_state.chat_history)) st.subheader("Available Agents") for agent_name in st.session_state.available_agents: st.write(f"**{agent_name}**") st.subheader("Project Management") st.markdown(display_workspace_projects(st.session_state.workspace_projects)) # AI Guide if ai_guide_level == "Full Assistance": st.markdown("## AI Guide: Full Assistance ##") st.write("**Recommended Action:**") st.write("Create a new project and then generate some code.") elif ai_guide_level == "Partial Assistance": st.markdown("## AI Guide: Partial Assistance ##") st.write("**Tips:**") st.write("Use the chat interface to ask questions about your project.") st.write("Use the code generation tool to generate code snippets.") else: st.markdown("## AI Guide: No Assistance ##") st.write("You are on your own!") # Autonomous Build if st.button("Autonomous Build"): project_name = project_name_input selected_model = selected_model agent = AIAgent("Code Architect", "I am an expert in code generation and deployment.", ["Code Generation", "Deployment"]) summary, next_step = agent.autonomous_build(st.session_state.chat_history, st.session_state.workspace_projects, project_name, selected_model, huggingface_token) st.write("Autonomous Build Summary:") st.write(summary) st.write("Next Step:") st.write(next_step) if agent._hf_api and agent.has_valid_hf_token(): repository = agent.deploy_built_space_to_hf() st.markdown("## Congratulations! Successfully deployed Space �� ##") st.markdown("[Check out your new Space here](hf.co/" + repository.name + ")") # CSS for styling st.markdown(""" """, unsafe_allow_html=True)