import streamlit as st from streamlit_ace import st_ace from transformers import pipeline, AutoTokenizer import os import subprocess import black from pylint import lint from io import StringIO import sys import re from typing import List, Dict from streamlit_jupyter import StreamlitPatcher, tqdm from .agents import ( TextGenerationTool, AIAgent, process_input, run_code, workspace_interface, add_code_to_workspace, display_chat_history, display_workspace_projects, generate_space_content, analyze_code, get_code_completion, lint_code, format_code ) # This line should be at the top of your script StreamlitPatcher().jupyter() # This patches Streamlit to work in Jupyter # Access Hugging Face API key from secrets hf_token = st.secrets["hf_token"] if not hf_token: st.error("Hugging Face API key not found. Please make sure it is set in the secrets.") HUGGING_FACE_REPO_URL = "https://huggingface.co/spaces/acecalisto3/0shotTest" 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"]) # Load the CodeGPT tokenizer explicitly code_generator_tokenizer = AutoTokenizer.from_pretrained("microsoft/CodeGPT-small-py", clean_up_tokenization_spaces=True) # Load the CodeGPT model for code completion code_generator = pipeline("text-generation", model="microsoft/CodeGPT-small-py", tokenizer=code_generator_tokenizer) def main(): st.title("Streamlit Workspace") # Load agents from the agent directory agent_files = [f for f in os.listdir(AGENT_DIRECTORY) if f.endswith(".py")] for agent_file in agent_files: agent_module = __import__(f"{AGENT_DIRECTORY}.{os.path.splitext(agent_file)[0]}") agent_class = getattr(agent_module, os.path.splitext(agent_file)[0]) agent_instance = agent_class() st.session_state.available_agents.append(agent_instance) # Display the available agents st.subheader("Available Agents") for agent in st.session_state.available_agents: st.write(f"**{agent.name}**: {agent.description}") # Select an agent selected_agent = st.selectbox("Select an Agent", [agent.name for agent in st.session_state.available_agents]) current_agent = next((agent for agent in st.session_state.available_agents if agent.name == selected_agent), None) # Display the agent's prompt if current_agent: st.subheader(f"{current_agent.name} Prompt") st.write(current_agent.create_agent_prompt()) # Workspace Tab st.subheader("Workspace") workspace_tabs = st.tabs(["Chat", "Tool Box", "Projects"]) with workspace_tabs[0]: # Chat Tab st.subheader("Chat with your Agent") user_input = st.text_input("Enter your message:") if user_input: st.session_state.chat_history.append((user_input, current_agent.generate_agent_response(user_input))) user_input = "" # Clear the input field # Display chat history st.markdown(display_chat_history(st.session_state.chat_history)) # AI Guide if ai_guide_level != "No Assistance": st.subheader("AI Guide") guide_chat_history = [] if ai_guide_level == "Full Assistance": guide_chat_history.append(( "I'm building a Streamlit app to display data from a CSV file.", "Great! Let's start by creating a new project in the workspace." )) guide_chat_history.append(( "Create a new project called 'data_app'.", "Okay, I've created the project 'data_app'. What would you like to name the main file?" )) guide_chat_history.append(( "Name it 'app.py'.", "Alright, I've added an empty 'app.py' file to the 'data_app' project. Now, let's add some code to read the CSV file." )) guide_chat_history.append(( "Add the following code to 'app.py':\n```python\nimport pandas as pd\nimport streamlit as st\n\ndata = pd.read_csv('data.csv')\nst.write(data)\n```", "Excellent! Now you can run this code to see the data from your CSV file in the Streamlit app." )) elif ai_guide_level == "Partial Assistance": guide_chat_history.append(( "I'm building a Streamlit app to display data from a CSV file.", "Great! Let's start by creating a new project in the workspace." )) display_ai_guide_chat(guide_chat_history) with workspace_tabs[1]: # Tool Box Tab st.subheader("Tool Box") code_input = st_ace(language='python', theme='monokai', key='code_input') if st.button("Run Code"): output = run_code(code_input) st.text_area("Output", output, height=200) if st.button("Analyze Code"): hints = analyze_code(code_input) st.text_area("Hints", "\n".join(hints), height=200) if st.button("Format Code"): formatted_code = format_code(code_input) st_ace(value=formatted_code, language='python', theme='monokai', key='formatted_code') if st.button("Lint Code"): lint_messages = lint_code(code_input) st.text_area("Lint Messages", "\n".join(lint_messages), height=200) if st.button("Get Code Completion"): completion = get_code_completion(code_input) st_ace(value=completion, language='python', theme='monokai', key='code_completion') with workspace_tabs[2]: # Projects Tab st.subheader("Projects") project_name = st.text_input("Project Name") if st.button("Create Project"): message = workspace_interface(project_name) st.write(message) file_name = st.text_input("File Name") code_content = st_ace(language='python', theme='monokai', key='code_content') if st.button("Add Code to Project"): message = add_code_to_workspace(project_name, code_content, file_name) st.write(message) st.subheader("Workspace Projects") st.markdown(display_workspace_projects(st.session_state.workspace_projects)) if __name__ == "__main__": main()