Update app.py

app.py

@@ -1,13 +1,16 @@
+import streamlit as st
 import os
 import subprocess
-import streamlit as st
 from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 import black
 from pylint import lint
 from io import StringIO
 import openai
+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"
 
@@ -20,11 +23,6 @@ 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):
@@ -48,30 +46,19 @@ 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()])
 
-        # Implement more sophisticated logic here based on chat history and workspace projects
-        # For example, you could:
-        # - Analyze the chat history to identify the user's goals and suggest relevant actions.
-        # - Check the workspace projects for missing files or dependencies and suggest adding them.
-        # - Use a language model to generate code based on the user's requests.
-
         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."""
+    """Saves the agent's prompt to a file."""
     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")
@@ -88,13 +75,11 @@ def create_agent_from_text(name, text):
     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)
@@ -103,31 +88,27 @@ def chat_interface_with_agent(input_text, agent_name):
     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")
+    max_input_length = 900
     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
+        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)
+    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": []}
-        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."
@@ -139,8 +120,6 @@ def add_code_to_workspace(project_name, code, 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."
@@ -153,58 +132,42 @@ def terminal_interface(command, project_name=None):
         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()
+
+    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]
 
-# ... [rest of the translate_code function, but remove the OpenAI API call and replace it with your own logic] ...
-
-def generate_code(code_idea):
-    # Replace this with a call to a Hugging Face model or your own logic
-    # For example, using a text-generation pipeline:
-    generator = pipeline('text-generation', model='gpt4o')
-    generated_code = generator(code_idea, max_length=10000, num_return_sequences=1)[0]['generated_text']
-    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}"}
-        ]
-    st.session_state.current_state['toolbox']['generated_code'] = generated_code
-    
-    return generated_code
-    
-def translate_code(code, input_language, output_language):
-    # Define a dictionary to map programming languages to their corresponding file extensions
-    language_extensions = {
-        
-    }
-
-    # 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}"
+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=[
@@ -212,12 +175,7 @@ def translate_code(code, input_language, output_language):
             {"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
+    return response.choices[0].message['content'].strip()
 
 def generate_code(code_idea):
     response = openai.ChatCompletion.create(
@@ -227,32 +185,14 @@ def generate_code(code_idea):
             {"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
+    return response.choices[0].message['content'].strip()
 
-# 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")
@@ -264,23 +204,20 @@ 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:]  # Extract agent_name from @agent_name
-            chat_input = " ".join(chat_input.split(" ")[1:])  # Remove agent_name from input
+            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(chat_input)
+            chat_response = "Chat interface function not provided."
         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"):
@@ -288,7 +225,6 @@ 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"):
@@ -296,21 +232,18 @@ 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'):")
@@ -319,14 +252,12 @@ elif app_mode == "Tool Box":
         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')",
@@ -341,17 +272,14 @@ elif app_mode == "Tool Box":
         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'):")
@@ -359,59 +287,55 @@ elif app_mode == "Workspace Chat App":
         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)
+        chat_response = "Chat interface function not provided."
         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
+    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.")
+
     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 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.")