Update app.py

app.py

@@ -1,43 +1,13 @@
+# config.py
 import os
-import sys
-import subprocess
-import streamlit as st
 from huggingface_hub import InferenceClient
-import gradio as gr
-import random
-import prompts
-from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
-import black
-from pylint import lint
-from io import StringIO
-
-# Initialize the InferenceClient for Mixtral-8x7B-Instruct-v0.1
-client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
-
-# Initialize the pipeline for Llama-3-8B-Instruct-Coder-GGUF
-pipe = pipeline("text-generation", model="bartowski/Llama-3-8B-Instruct-Coder-GGUF")
-
-HUGGING_FACE_REPO_URL = "https://huggingface.co/spaces/acecalisto3/DevToolKit"
-PROJECT_ROOT = "projects"
-AGENT_DIRECTORY = "agents"
-
-# Global state management
-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': {}
-    }
-
-# Define the agents
-agents = [
+from transformers import pipeline
+
+# Initialize clients and models
+MIXTRAL_CLIENT = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
+LLAMA_PIPELINE = pipeline("text-generation", model="bartowski/Llama-3-8B-Instruct-Coder-GGUF")
+
+AGENTS = [
     "WEB_DEV",
     "AI_SYSTEM_PROMPT",
     "PYTHON_CODE_DEV",
@@ -47,177 +17,197 @@ agents = [
     "HUGGINGFACE_FILE_DEV",
 ]
 
+# ai_agent.py
+import random
+from typing import List, Dict, Tuple
+
 class AIAgent:
-    def __init__(self, name, description, skills):
+    def __init__(self, name: str, description: str, skills: List[str]):
         self.name = name
         self.description = description
         self.skills = skills
 
-    def create_agent_prompt(self):
+    def create_agent_prompt(self) -> str:
         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):
+        return 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.
+        """
+
+    def autonomous_build(self, chat_history: List[Tuple[str, str]], workspace_projects: Dict[str, Dict]) -> Tuple[str, str]:
         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 format_prompt(message, history):
+# utils.py
+import os
+import subprocess
+from typing import List, Tuple
+
+def format_prompt(message: str, history: List[Tuple[str, str]]) -> str:
     prompt = "<s>"
     for user_prompt, bot_response in history:
-        prompt += f"[INST] {user_prompt} [/INST]"
-        prompt += f" {bot_response}</s> "
+        prompt += f"[INST] {user_prompt} [/INST] {bot_response}</s> "
     prompt += f"[INST] {message} [/INST]"
     return prompt
 
-def generate(prompt, history, agent_name=agents[0], sys_prompt="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
+def generate(prompt: str, history: List[Tuple[str, str]], agent_name: str = AGENTS[0], sys_prompt: str = "", 
+             temperature: float = 0.9, max_new_tokens: int = 256, top_p: float = 0.95, repetition_penalty: float = 1.0):
     seed = random.randint(1, 1111111111111111)
-    agent = getattr(prompts, agent_name, prompts.WEB_DEV_SYSTEM_PROMPT)
-    system_prompt = agent
-
     generate_kwargs = dict(
-        temperature=float(temperature),
+        temperature=temperature,
         max_new_tokens=max_new_tokens,
-        top_p=float(top_p),
+        top_p=top_p,
         repetition_penalty=repetition_penalty,
         do_sample=True,
         seed=seed,
     )
-
-    formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    formatted_prompt = format_prompt(f"{sys_prompt}, {prompt}", history)
+    stream = MIXTRAL_CLIENT.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
     output = ""
-
     for response in stream:
         output += response.token.text
         yield output
     return output
 
-def chat_interface(chat_input):
-    response = generate(chat_input, st.session_state.chat_history)
-    return response
-
-def chat_interface_with_agent(chat_input, agent_name):
-    agent_prompt = getattr(prompts, agent_name, prompts.WEB_DEV_SYSTEM_PROMPT)
-    response = generate(chat_input, st.session_state.chat_history, agent_name=agent_name, sys_prompt=agent_prompt)
-    return response
-
-def terminal_interface(command, project_name):
-    # Implement terminal functionality here
-    return f"Executed command: {command} in project: {project_name}"
-
-def add_code_to_workspace(project_name, code, file_name):
-    if project_name not in st.session_state.workspace_projects:
-        st.session_state.workspace_projects[project_name] = {'files': []}
-    st.session_state.workspace_projects[project_name]['files'].append(file_name)
+def terminal_interface(command: str, project_name: str) -> str:
+    try:
+        result = subprocess.run(command, shell=True, capture_output=True, text=True, cwd=project_name)
+        return result.stdout if result.returncode == 0 else result.stderr
+    except Exception as e:
+        return str(e)
+
+def add_code_to_workspace(project_name: str, code: str, file_name: str) -> str:
+    project_path = os.path.join(os.getcwd(), project_name)
+    os.makedirs(project_path, exist_ok=True)
+    file_path = os.path.join(project_path, file_name)
+    with open(file_path, 'w') as file:
+        file.write(code)
     return f"Added {file_name} to {project_name}"
 
-# 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 not in st.session_state.workspace_projects:
-        st.session_state.workspace_projects[project_name] = {'files': []}
-        st.success(f"Created project: {project_name}")
-    else:
-        st.warning(f"Project {project_name} already exists")
-
-# Code Addition
-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
-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
-st.subheader("Chat with DevToolKit 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"DevToolKit: {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"DevToolKit: {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", 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)
-
-# Gradio Interface
-additional_inputs = [
-    gr.Dropdown(label="Agents", choices=[s for s in agents], value=agents[0], interactive=True),
-    gr.Textbox(label="System Prompt", max_lines=1, interactive=True),
-    gr.Slider(label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs"),
-    gr.Slider(label="Max new tokens", value=1048*10, minimum=0, maximum=1000*10, step=64, interactive=True, info="The maximum numbers of new tokens"),
-    gr.Slider(label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens"),
-    gr.Slider(label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens"),
-]
+# main.py
+import streamlit as st
+import gradio as gr
+from config import AGENTS
+from ai_agent import AIAgent
+from utils import generate, terminal_interface, add_code_to_workspace
 
-examples = [
-    ["Create a simple web application using Flask", agents[0], None, None, None, None, ],
-    ["Generate a Python script to perform a linear regression analysis", agents[2], None, None, None, None, ],
-    ["Create a Dockerfile for a Node.js application", agents[1], None, None, None, None, ],
-    # Add more examples as needed
-]
+# Streamlit UI
+def main():
+    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 not in st.session_state.workspace_projects:
+            st.session_state.workspace_projects[project_name] = {'files': []}
+            st.success(f"Created project: {project_name}")
+        else:
+            st.warning(f"Project {project_name} already exists")
+
+    # Code Addition
+    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
+    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
+    st.subheader("Chat with DevToolKit for Guidance")
+    chat_input = st.text_area("Enter your message for guidance:")
+    if st.button("Get Guidance"):
+        chat_response = next(generate(chat_input, st.session_state.chat_history))
+        st.session_state.chat_history.append((chat_input, chat_response))
+        st.write(f"DevToolKit: {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"DevToolKit: {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", AGENTS)
+    agent_chat_input = st.text_area("Enter your message for the agent:")
+    if st.button("Send to Agent"):
+        agent_chat_response = next(generate(agent_chat_input, st.session_state.chat_history, agent_name=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)
+
+if __name__ == "__main__":
+    main()
+
+# gradio_interface.py
+import gradio as gr
+from config import AGENTS
+from utils import generate
+
+def create_gradio_interface():
+    additional_inputs = [
+        gr.Dropdown(label="Agents", choices=[s for s in AGENTS], value=AGENTS[0], interactive=True),
+        gr.Textbox(label="System Prompt", max_lines=1, interactive=True),
+        gr.Slider(label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs"),
+        gr.Slider(label="Max new tokens", value=1048*10, minimum=0, maximum=1000*10, step=64, interactive=True, info="The maximum numbers of new tokens"),
+        gr.Slider(label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens"),
+        gr.Slider(label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens"),
+    ]
+
+    examples = [
+        ["Create a simple web application using Flask", AGENTS[0], None, None, None, None],
+        ["Generate a Python script to perform a linear regression analysis", AGENTS[2], None, None, None, None],
+        ["Create a Dockerfile for a Node.js application", AGENTS[1], None, None, None, None],
+    ]
+
+    return gr.ChatInterface(
+        fn=generate,
+        chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
+        additional_inputs=additional_inputs,
+        title="DevToolKit AI Assistant",
+        examples=examples,
+        concurrency_limit=20,
+    )
 
-gr.ChatInterface(
-    fn=generate,
-    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
-    additional_inputs=additional_inputs,
-    title="DevToolKit AI Assistant",
-    examples=examples,
-    concurrency_limit=20,
-).launch(show_api=True)
+if __name__ == "__main__":
+    interface = create_gradio_interface()
+    interface.launch(show_api=True)