app.py

import os

import sys

import subprocess

import streamlit as st

from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer

import black

from pylint import lint

from io import StringIO

import openai




# Set your OpenAI API key here

openai.api_key = "YOUR_OPENAI_API_KEY"




HUGGING_FACE_REPO_URL = "https://huggingface.co/spaces/acecalisto3/DevToolKit"

PROJECT_ROOT = "projects"

AGENT_DIRECTORY = "agents"




# 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 = []

if 'current_state' not in st.session_state:

    st.session_state.current_state = {

        'toolbox': {},

        'workspace_chat': {}

    }




class AIAgent:

    def __init__(self, name, description, skills):

        self.name = name

        self.description = description

        self.skills = skills




    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):

        """

        Autonomous build logic that continues based on the state of chat history and workspace projects.

        """

        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 save_agent_to_file(agent):

    """Saves the agent's prompt to a file locally and then commits to the Hugging Face repository."""

    if not os.path.exists(AGENT_DIRECTORY):

        os.makedirs(AGENT_DIRECTORY)

    file_path = os.path.join(AGENT_DIRECTORY, f"{agent.name}.txt")

    config_path = os.path.join(AGENT_DIRECTORY, f"{agent.name}Config.txt")

    with open(file_path, "w") as file:

        file.write(agent.create_agent_prompt())

    with open(config_path, "w") as file:

        file.write(f"Agent Name: {agent.name}\nDescription: {agent.description}")

    st.session_state.available_agents.append(agent.name)




    commit_and_push_changes(f"Add agent {agent.name}")




def load_agent_prompt(agent_name):

    """Loads an agent prompt from a file."""

    file_path = os.path.join(AGENT_DIRECTORY, f"{agent_name}.txt")

    if os.path.exists(file_path):

        with open(file_path, "r") as file:

            agent_prompt = file.read()

        return agent_prompt

    else:

        return None




def create_agent_from_text(name, text):

    skills = text.split('\n')

    agent = AIAgent(name, "AI agent created from text input.", skills)

    save_agent_to_file(agent)

    return agent.create_agent_prompt()




# Chat interface using a selected agent

def chat_interface_with_agent(input_text, agent_name):

    agent_prompt = load_agent_prompt(agent_name)

    if agent_prompt is None:

        return f"Agent {agent_name} not found."




    # Load the GPT-2 model which is compatible with AutoModelForCausalLM

    model_name = "gpt2"

    try:

        model = AutoModelForCausalLM.from_pretrained(model_name)

        tokenizer = AutoTokenizer.from_pretrained(model_name)

        generator = pipeline("text-generation", model=model, tokenizer=tokenizer)

    except EnvironmentError as e:

        return f"Error loading model: {e}"




    # Combine the agent prompt with user input

    combined_input = f"{agent_prompt}\n\nUser: {input_text}\nAgent:"

    

    # Truncate input text to avoid exceeding the model's maximum length

    max_input_length = 900

    input_ids = tokenizer.encode(combined_input, return_tensors="pt")

    if input_ids.shape[1] > max_input_length:

        input_ids = input_ids[:, :max_input_length]




    # Generate chatbot response

    outputs = model.generate(

        input_ids, max_new_tokens=50, num_return_sequences=1, do_sample=True, pad_token_id=tokenizer.eos_token_id # Set pad_token_id to eos_token_id

    )

    response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    return response




def workspace_interface(project_name):

    project_path = os.path.join(PROJECT_ROOT, project_name)

    if not os.path.exists(PROJECT_ROOT):

        os.makedirs(PROJECT_ROOT)

    if not os.path.exists(project_path):

        os.makedirs(project_path)

        st.session_state.workspace_projects[project_name] = {"files": []}

        st.session_state.current_state['workspace_chat']['project_name'] = project_name

        commit_and_push_changes(f"Create project {project_name}")

        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 os.path.exists(project_path):

        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)

        st.session_state.current_state['workspace_chat']['added_code'] = {"file_name": file_name, "code": code}

        commit_and_push_changes(f"Add code to {file_name} in project {project_name}")

        return f"Code added to {file_name} in project {project_name} successfully."

    else:

        return f"Project {project_name} does not exist."




def terminal_interface(command, project_name=None):

    if project_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."

        result = subprocess.run(command, cwd=project_path, shell=True, capture_output=True, text=True)

    else:

        result = subprocess.run(command, shell=True, capture_output=True, text=True)

    if result.returncode == 0:

        st.session_state.current_state['toolbox']['terminal_output'] = result.stdout

        return result.stdout

    else:

        st.session_state.current_state['toolbox']['terminal_output'] = result.stderr

        return result.stderr




def code_editor_interface(code):

    try:

        formatted_code = black.format_str(code, mode=black.FileMode())

    except black.NothingChanged:

        formatted_code = code

    result = StringIO()

    sys.stdout = result

    sys.stderr = result

    (pylint_stdout, pylint_stderr) = lint.py_run(code, return_std=True)

    sys.stdout = sys.__stdout__

    sys.stderr = sys.__stderr__

    lint_message = pylint_stdout.getvalue() + pylint_stderr.getvalue()

    st.session_state.current_state['toolbox']['formatted_code'] = formatted_code

    st.session_state.current_state['toolbox']['lint_message'] = lint_message

    return formatted_code, lint_message




def summarize_text(text):

    summarizer = pipeline("summarization")

    summary = summarizer(text, max_length=50, min_length=25, do_sample=False)

    st.session_state.current_state['toolbox']['summary'] = summary[0]['summary_text']

    return summary[0]['summary_text']




def sentiment_analysis(text):

    analyzer = pipeline("sentiment-analysis")

    sentiment = analyzer(text)

    st.session_state.current_state['toolbox']['sentiment'] = sentiment[0]

    return sentiment[0]




def translate_code(code, input_language, output_language):

    # Define a dictionary to map programming languages to their corresponding file extensions

    language_extensions = {

        # ignore the specific languages right now, and continue to EOF

    }




    # Add code to handle edge cases such as invalid input and unsupported programming languages

    if input_language not in language_extensions:

        raise ValueError(f"Invalid input language: {input_language}")

    if output_language not in language_extensions:

        raise ValueError(f"Invalid output language: {output_language}")




    # Use the dictionary to map the input and output languages to their corresponding file extensions

    input_extension = language_extensions[input_language]

    output_extension = language_extensions[output_language]




    # Translate the code using the OpenAI API

    prompt = f"Translate this code from {input_language} to {output_language}:\n\n{code}"

    response = openai.ChatCompletion.create(

        model="gpt-4",

        messages=[

            {"role": "system", "content": "You are an expert software developer."},

            {"role": "user", "content": prompt}

        ]

    )

    translated_code = response.choices[0].message['content'].strip()




    # Return the translated code

    translated_code = response.choices[0].message['content'].strip()

    st.session_state.current_state['toolbox']['translated_code'] = translated_code

    return translated_code




def generate_code(code_idea):

    response = openai.ChatCompletion.create(

        model="gpt-4",

        messages=[

            {"role": "system", "content": "You are an expert software developer."},

            {"role": "user", "content": f"Generate a Python code snippet for the following idea:\n\n{code_idea}"}

        ]

    )

    generated_code = response.choices[0].message['content'].strip()

    st.session_state.current_state['toolbox']['generated_code'] = generated_code

    return generated_code




def commit_and_push_changes(commit_message):

    """Commits and pushes changes to the Hugging Face repository."""

    commands = [

        "git add .",

        f"git commit -m '{commit_message}'",

        "git push"

    ]

    for command in commands:

        result = subprocess.run(command, shell=True, capture_output=True, text=True)

        if result.returncode != 0:

            st.error(f"Error executing command '{command}': {result.stderr}")

            break




# Streamlit App

st.title("AI Agent Creator")




# Sidebar navigation

st.sidebar.title("Navigation")

app_mode = st.sidebar.selectbox("Choose the app mode", ["AI Agent Creator", "Tool Box", "Workspace Chat App"])




if app_mode == "AI Agent Creator":

    # AI Agent Creator

    st.header("Create an AI Agent from Text")




    st.subheader("From Text")

    agent_name = st.text_input("Enter agent name:")

    text_input = st.text_area("Enter skills (one per line):")

    if st.button("Create Agent"):

        agent_prompt = create_agent_from_text(agent_name, text_input)

        st.success(f"Agent '{agent_name}' created and saved successfully.")

        st.session_state.available_agents.append(agent_name)




elif app_mode == "Tool Box":

    # Tool Box

    st.header("AI-Powered Tools")




    # Chat Interface

    st.subheader("Chat with CodeCraft")

    chat_input = st.text_area("Enter your message:")

    if st.button("Send"):

        if chat_input.startswith("@"):

            agent_name = chat_input.split(" ")[0][1:]  # Extract agent_name from @agent_name

            chat_input = " ".join(chat_input.split(" ")[1:])  # Remove agent_name from input

            chat_response = chat_interface_with_agent(chat_input, agent_name)

        else:

            chat_response = chat_interface(chat_input)

        st.session_state.chat_history.append((chat_input, chat_response))

        st.write(f"CodeCraft: {chat_response}")




    # Terminal Interface

    st.subheader("Terminal")

    terminal_input = st.text_input("Enter a command:")

    if st.button("Run"):

        terminal_output = terminal_interface(terminal_input)

        st.session_state.terminal_history.append((terminal_input, terminal_output))

        st.code(terminal_output, language="bash")




    # Code Editor Interface

    st.subheader("Code Editor")

    code_editor = st.text_area("Write your code:", height=300)

    if st.button("Format & Lint"):

        formatted_code, lint_message = code_editor_interface(code_editor)

        st.code(formatted_code, language="python")

        st.info(lint_message)




    # Text Summarization Tool

    st.subheader("Summarize Text")

    text_to_summarize = st.text_area("Enter text to summarize:")

    if st.button("Summarize"):

        summary = summarize_text(text_to_summarize)

        st.write(f"Summary: {summary}")




    # Sentiment Analysis Tool

    st.subheader("Sentiment Analysis")

    sentiment_text = st.text_area("Enter text for sentiment analysis:")

    if st.button("Analyze Sentiment"):

        sentiment = sentiment_analysis(sentiment_text)

        st.write(f"Sentiment: {sentiment}")




    # Text Translation Tool (Code Translation)

    st.subheader("Translate Code")

    code_to_translate = st.text_area("Enter code to translate:")

    source_language = st.text_input("Enter source language (e.g. 'Python'):")

    target_language = st.text_input("Enter target language (e.g. 'JavaScript'):")

    if st.button("Translate Code"):

        translated_code = translate_code(code_to_translate, source_language, target_language)

        st.code(translated_code, language=target_language.lower())




    # Code Generation

    st.subheader("Code Generation")

    code_idea = st.text_input("Enter your code idea:")

    if st.button("Generate Code"):

        generated_code = generate_code(code_idea)

        st.code(generated_code, language="python")




    # Display Preset Commands

    st.subheader("Preset Commands")

    preset_commands = {

        "Create a new project": "create_project('project_name')",

        "Add code to workspace": "add_code_to_workspace('project_name', 'code', 'file_name')",

        "Run terminal command": "terminal_interface('command', 'project_name')",

        "Generate code": "generate_code('code_idea')",

        "Summarize text": "summarize_text('text')",

        "Analyze sentiment": "sentiment_analysis('text')",

        "Translate code": "translate_code('code', 'source_language', 'target_language')",

    }

    for command_name, command in preset_commands.items():

        st.write(f"{command_name}: `{command}`")




elif app_mode == "Workspace Chat App":

    # Workspace Chat App

    st.header("Workspace Chat App")




    # Project Workspace Creation

    st.subheader("Create a New Project")

    project_name = st.text_input("Enter project name:")

    if st.button("Create Project"):

        workspace_status = workspace_interface(project_name)

        st.success(workspace_status)




    # Add Code to Workspace

    st.subheader("Add Code to Workspace")

    code_to_add = st.text_area("Enter code to add to workspace:")

    file_name = st.text_input("Enter file name (e.g. 'app.py'):")

    if st.button("Add Code"):

        add_code_status = add_code_to_workspace(project_name, code_to_add, file_name)

        st.success(add_code_status)




    # Terminal Interface with Project Context

    st.subheader("Terminal (Workspace Context)")

    terminal_input = st.text_input("Enter a command within the workspace:")

    if st.button("Run Command"):

        terminal_output = terminal_interface(terminal_input, project_name)

        st.code(terminal_output, language="bash")




    # Chat Interface for Guidance

    st.subheader("Chat with CodeCraft for Guidance")

    chat_input = st.text_area("Enter your message for guidance:")

    if st.button("Get Guidance"):

        chat_response = chat_interface(chat_input)

        st.session_state.chat_history.append((chat_input, chat_response))

        st.write(f"CodeCraft: {chat_response}")




    # Display Chat History

    st.subheader("Chat History")

    for user_input, response in st.session_state.chat_history:

        st.write(f"User: {user_input}")

        st.write(f"CodeCraft: {response}")




    # Display Terminal History

    st.subheader("Terminal History")

    for command, output in st.session_state.terminal_history:

        st.write(f"Command: {command}")

        st.code(output, language="bash")




    # Display Projects and Files

    st.subheader("Workspace Projects")

    for project, details in st.session_state.workspace_projects.items():

        st.write(f"Project: {project}")

        for file in details['files']:

            st.write(f"  - {file}")




    # Chat with AI Agents

    st.subheader("Chat with AI Agents")

    selected_agent = st.selectbox("Select an AI agent", st.session_state.available_agents)

    agent_chat_input = st.text_area("Enter your message for the agent:")

    if st.button("Send to Agent"):

        agent_chat_response = chat_interface_with_agent(agent_chat_input, selected_agent)

        st.session_state.chat_history.append((agent_chat_input, agent_chat_response))

        st.write(f"{selected_agent}: {agent_chat_response}")




    # Automate Build Process

    st.subheader("Automate Build Process")

    if st.button("Automate"):

        agent = AIAgent(selected_agent, "", [])  # Load the agent without skills for now

        summary, next_step = agent.autonomous_build(st.session_state.chat_history, st.session_state.workspace_projects)

        st.write("Autonomous Build Summary:")

        st.write(summary)

        st.write("Next Step:")

        st.write(next_step)




# Display current state for debugging

st.sidebar.subheader("Current State")

st.sidebar.json(st.session_state.current_state)