Update app.py

app.py

@@ -1,6 +1,6 @@
-import streamlit as st
 import os
 import subprocess
+import streamlit as st
 from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 import black
 from pylint import lint
@@ -11,6 +11,7 @@ import sys
 # 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"
 
@@ -23,6 +24,11 @@ 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):
@@ -35,6 +41,7 @@ class AIAgent:
         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
@@ -46,6 +53,17 @@ I am confident that I can leverage my expertise to assist you in developing and
         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()])
 
+        # Analyze chat history and workspace projects to suggest actions
+        # Example:
+        # - Check if the user has requested to create a new file
+        # - Check if the user has requested to install a package
+        # - Check if the user has requested to run a command
+        # - Check if the user has requested to generate code
+        # - Check if the user has requested to translate code
+        # - Check if the user has requested to summarize text
+        # - Check if the user has requested to analyze sentiment
+
+        # Generate a response based on the analysis
         next_step = "Based on the current state, the next logical step is to implement the main application logic."
 
         return summary, next_step
@@ -82,7 +100,7 @@ def chat_interface_with_agent(input_text, agent_name):
 
     model_name = "Bin12345/AutoCoder_S_6.7B"
     try:
-    pipe = pipeline("text-generation", model="Bin12345/AutoCoder_S_6.7B")
+        model = AutoModelForCausalLM.from_pretrained(model_name)
         tokenizer = AutoTokenizer.from_pretrained(model_name)
         generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
     except EnvironmentError as e:
@@ -102,42 +120,18 @@ def chat_interface_with_agent(input_text, agent_name):
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response
 
-def workspace_interface(project_name):
-    if not os.path.exists(PROJECT_ROOT):
-        os.makedirs(PROJECT_ROOT)
-    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 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)
-        return f"Code added to {file_name} in project {project_name} successfully."
-    else:
-        return f"Project {project_name} does not exist."
-
+# Terminal interface
 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)
+        result = subprocess.run(command, shell=True, capture_output=True, text=True, cwd=project_path)
     else:
         result = subprocess.run(command, shell=True, capture_output=True, text=True)
-    
-    if result.returncode == 0:
-        return result.stdout
-    else:
-        return result.stderr
+    return result.stdout
 
+# Code editor interface
 def code_editor_interface(code):
     try:
         formatted_code = black.format_str(code, mode=black.FileMode())
@@ -156,43 +150,69 @@ def code_editor_interface(code):
 
     return formatted_code, lint_message
 
+# Text summarization tool
 def summarize_text(text):
     summarizer = pipeline("summarization")
-    summary = summarizer(text, max_length=50, min_length=25, do_sample=False)
+    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
     return summary[0]['summary_text']
 
+# Sentiment analysis tool
 def sentiment_analysis(text):
     analyzer = pipeline("sentiment-analysis")
-    sentiment = analyzer(text)
-    return sentiment[0]
+    result = analyzer(text)
+    return result[0]['label']
 
+# Text translation tool (code translation)
 def translate_code(code, source_language, target_language):
-    prompt = f"Translate this code from {source_language} to {target_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}
-        ]
-    )
-    return response.choices[0].message['content'].strip()
+    # Use a Hugging Face translation model instead of OpenAI
+    translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-es")  # Example: English to Spanish
+    translated_code = translator(code, target_lang=target_language)[0]['translation_text']
+    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}"}
-        ]
-    )
-    return response.choices[0].message['content'].strip()
+    # Use a Hugging Face code generation model instead of OpenAI
+    generator = pipeline('text-generation', model='bigcode/starcoder')
+    generated_code = generator(code_idea, max_length=1000, num_return_sequences=1)[0]['generated_text']
+    return generated_code
+
+def chat_interface(input_text):
+    """Handles general chat interactions with the user."""
+    # Use a Hugging Face chatbot model or your own logic
+    chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
+    response = chatbot(input_text, max_length=50, num_return_sequences=1)[0]['generated_text']
+    return response
 
+# Workspace interface
+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."
+
+# Add code to workspace
+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}'."
+
+# 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")
@@ -204,20 +224,18 @@ if app_mode == "AI Agent Creator":
         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:]
-            chat_input = " ".join(chat_input.split(" ")[1:])
-            chat_response = chat_interface_with_agent(chat_input, agent_name)
-        else:
-            chat_response = "Chat interface function not provided."
+        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"):
@@ -225,6 +243,7 @@ elif app_mode == "Tool Box":
         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"):
@@ -232,110 +251,104 @@ elif app_mode == "Tool Box":
         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'):")
+    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")
 
-    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'):")
+    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 function not provided."
+        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")
-    if st.session_state.available_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}")
-    else:
-        st.write("No agents available. Please create an agent first.")
-
+    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"):
-        if st.session_state.available_agents:
-            selected_agent = st.session_state.available_agents[0]
-            agent = AIAgent(selected_agent, "", []) 
-            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)
-        else:
-            st.write("No agents available. Please create an agent first.")
+        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)