milestone done - added project descriptions, small changes

ChatManager.py

@@ -19,8 +19,7 @@ def get_client() -> OpenAI:
 client = get_client()
 
 def send_message(message: str) -> str:
-    # hier gehts darum, die message vorzubereiten
-    # -> also nachricht aus den Chatfenster mit systemprompts und file_conntext verknüpfen
+    # Nachricht aus dem Chatfenster wird für qwen vorbereitet und mit Kontext über SystemPrompter ergänzt
     prompt = generate_prompt(message)
     response = send_prompt(prompt)
     return response

DebugLogger.py

@@ -2,7 +2,7 @@ import streamlit as st
 import subprocess
 
 def log_error(error_message):
-    #speichern wieder über session_state
+    #speichern des strukturierten outputs von qwen über session_state
     st.session_state["bugs"] = error_message
 
 
@@ -20,7 +20,6 @@ def format_debug_output(output: dict) -> str:
 
     return "\n".join(lines)
 
-#qwen
 def format_output(text: bytes) -> str:
     return text.decode('utf-8', errors='replace').strip()
 

ExecutionEngine.py

@@ -6,6 +6,8 @@ from DebugLogger import log_error, format_output, format_error
 
 
 def run_code(code: Path) -> None | str:
+    #führt Code aus angeklickter Datei im Editor aus. Sicherheitscheck über verbotene Imports und Funktionen geregelt
+
     if "code_output" in st.session_state:
         del st.session_state['code_output']
     if "code_error" in st.session_state:
@@ -29,20 +31,11 @@ def run_code(code: Path) -> None | str:
         st.session_state['code_error'] = format_error(exc)
         log_error(st.session_state['code_error'])
 
-    
-#brauchts diese Funktion noch? macht eigentlich schon run_code
-def capture_output():
-    errors = st.session_state['code_error']
-    #if errors == 0:
-    #    errors = "There are no errors"
-    return st.session_state['code_output'], errors
-
-
 
 #aus der uebungsloesung
 
 def check_code_safety(code: str) -> str | None:
-    #Analysiert den Code statisch nach verbotenen imports und builtins.
+    #analysiert den Code statisch nach verbotenen imports und builtins.
     try:
         tree = ast.parse(code)
     except SyntaxError as e:

FileManager.py

@@ -15,7 +15,7 @@ def read_file(file_path: Path) -> str:
         return file.read()
 
 def save_file(file_path: Path, content: str):
-    #wenn eine Datei im Code Editor abgeändert wird, soll die Funktion die Änderungen abspeichern
+    #wenn eine Datei im Code Editor abgeändert wird und der Save Button gedrückt wurde, speichert Funktion die Änderungen ab
     with file_path.open('w') as file:
         file.write(content)
 

SearchManager.py

@@ -1,7 +1,7 @@
 from ddgs import DDGS
-import re
 
 def perform_search(query: str) -> dict:
+    #sucht Zusatzinfos im Internet
     try:
         results = DDGS().text(query, max_results=3)
         return results
@@ -12,7 +12,8 @@ def perform_search(query: str) -> dict:
 
 
 def parse_results(results: list[dict]) -> list[dict]:
- return [
+    #Limitiert Inhalt der Suchergebnisse auf 500 Zeichen, damit qwen nicht zu langen Prompt erhält
+    return [
         {
             "url": r.get("href", ""), #
             "snippet": r.get("body", "")[:500]

SystemPrompter.py

@@ -3,7 +3,7 @@ from SearchManager import perform_search, parse_results
 
 
 def generate_prompt(user_message: str) -> str:
-
+    # der key "debug" im session_state als toggle: wenn an, dann strukturierter output mit feedbackschleife über "bugs" key
     if "debug" in st.session_state and st.session_state["debug"]:
       system_content = """\
 You are a code-review assistant. You ALWAYS respond with valid JSON and
@@ -37,10 +37,11 @@ commentary. Your entire response must be parseable by json.loads().
          context += (f" <bugs> {st.session_state['bugs']} </bugs>")
 
       prompt = system_content + task + context
-      #st.session_state["last_prompt"] = (f"{prompt}")
+      st.session_state["last_prompt"] = (f"{prompt}")
       return prompt
-      
+     
     else:
+     # ohne "debug" key im session_state: unstrukturierter output
       system_content = """\
 <persona>
   You are an experienced Python coding assistant. 
@@ -68,7 +69,7 @@ commentary. Your entire response must be parseable by json.loads().
     
       prompt = system_content + task + context
 
-      #st.session_state["last_prompt"] = (f"{prompt}")
+      st.session_state["last_prompt"] = (f"{prompt}")
 
       return prompt
 

app.py

@@ -3,28 +3,22 @@ import json
 import streamlit as st
 from pathlib import Path
 from ChatManager import send_message
-from FileManager import list_files, read_file, save_file, open_file
+from FileManager import list_files, save_file, open_file
 from ExecutionEngine import run_code
 from DebugLogger import format_debug_output, log_error
 
 
-#"Last sent prompt:", 
-#if "last_prompt" in st.session_state:
-#    st.session_state["last_prompt"]
-#if "file_content" in st.session_state:
-#    st.session_state["file_content"]
-    #type(st.session_state["file_content"])
-    #print(type(st.session_state["file_content"]))
 
 st.set_page_config(layout="wide")
 
+# Initialisierung wichtiger keys im session_state
 if not "file_content" in st.session_state:
     st.session_state["file_content"] = ""
 if not "selected_file" in st.session_state:    
     st.session_state["selected_file"] = ""
 
 with st.sidebar:
-
+# baut den Sidebar aus den vorhanden .py Dateien im Arbeitsverzeichnis
     for file in list_files():
         st.button(file.name, on_click=open_file, args=[file])
 
@@ -35,7 +29,7 @@ with col_editor_output:
     if "file_content" in st.session_state:
         text = st.text_area("Code Editor", height="stretch", key="file_content")
     
-    # Preferred pattern for editor
+    # Oberfläche erhält zusätzliche Buttons, wenn eine Datei geöffnet wird
     if st.session_state["selected_file"] != "":
         st.button("Save", on_click=save_file, args=[st.session_state["selected_file"], st.session_state["file_content"]])
         st.button("Execute Code", on_click=run_code, args=[st.session_state["selected_file"]])
@@ -55,13 +49,13 @@ with col_chat:
     if "messages" not in st.session_state:
         st.session_state.messages = []
 
-    # Display History
+    # zeigt Chatverlauf als Abschnitt mit eigenem Scrollbalken
     with st.container(border=True, height=500):
         for msg in st.session_state.messages:
             with st.chat_message(msg["role"]):
                 st.write(msg["content"])
 
-    # Input & Response
+    # regelt Verhalten bei Chat mit qwen. Nach Eingabe wird einer der Promptopitionen gewählt und fertiger Prompt sowie qwen Antwort in die messages gespeichert
     message = st.chat_input("How can qwen help you?", key="chat")
     internet = st.toggle("enable internet search", key="internet")
     if "code_output" in st.session_state or "code_error" in st.session_state:
@@ -72,7 +66,6 @@ with col_chat:
         if "debug" in st.session_state and st.session_state["debug"]:
             response = format_debug_output(json.loads(response))
             log_error(response)
-            # st.session_state["bugs"] = response
         st.session_state.messages.append({"role": "assistant", "content": response})
         st.rerun()
 

project_description.md

@@ -0,0 +1,135 @@
+**Lightweight Code Editor with AI integration**
+
+##1. Introduction
+
+This code editor was made as a project for the course Artificial Intelligence in Software Engineering I at FH Graubuenden.
+Its purpose is to help with coding questions and debugging.
+
+
+##2. Requirements
+
+streamlit
+openai
+ddgs
+dotenv
+
+##3. Installation
+
+- install requirements through pip
+- aquire the environment variables thourgh FHGR
+- connect to the FHGR VPN to get access to the AI model.
+- run the app via terminal with "streamlit run app.py". A browser window will open.
+
+##4. Architecture
+
+The code is split up into frontend (app.py) and backend modules (FileManager, ChatManager, SystemPrompter, ExecutionEngine, DebugLogger and SearchManager).
+A lot of functionality is realized through the use of the session_state from streamlit. 
+Since the streamlit app is rerun after each action the session_state is used to keep track of relevant information.
+
+# 4.1 app.py
+
+This module is the entrypoint for the streamlit functionality. It contains all elements that are visible when the program is run. 
+
+
+	- sidebar:
+		The sidebar shows all python files within the working directory through fuctions found in the FileManager. Each file is represented by a clickable button.
+		There is no functionality to add or delete files from within the program. To change the available files the user has to manually add them to the directory.
+		Interacts with FileManger
+		
+	- code editor:
+		The code editor shows the contents of the opened file. The contents can be changed, saved and also executed. 
+		Interacts with FileManager, ExecutionEngine
+		
+	- chat:
+		This element consists of an input area to send messages to the AI, two toggles to enable different modes as well as a scrollable history.
+		The first toggle is "enable internet search". This appends the results of an internet search to the prompt that is sent to the AI.
+		This means the results from the search are not primarily for the user, but for the AI to use recent information before responing to the user.
+		The second toggle "debug with qwen" appears only when a file was executed. This mode uses more structured output which is also sent to the next prompt for the AI.
+		With this feedback the AI can help with a more focused approach to find and fix bugs in the code. The user has to implement the fixes themself since the AI cannot change the contents of the file.
+		Interacts with ChatManager, Debuglogger
+	
+# 4.2 FileManager.py
+
+This module manages the access to the working directory. It uses Path objects.
+The open_file function is only used as a helper function to save the file path and contents to the session_state.
+
+# 4.3 ChatManager.py
+
+The environment variables are located in a .env file which is excluded from the gitea upload.
+The qwen AI is accessed through the openai API client.
+While this module sends the messages to the AI it is heavily dependend on the SystemPrompter to supply the relevant context for the finished prompt.
+Interacts with SystemPrompter
+
+# 4.4 SystemPrompter.py
+
+This module handles all the context to add to the user message sent via the ChatManager. The instructions for the AI are structured with xml tags.
+There are two modes which are chosen with a toggle. Both modes differ in the system component and sent context.
+When the toggle is off the generated prompt includes system instructions which make the AI act as a coding assistant who gives short responses.
+With the toggle on the output is structured with json and focussed on finding bugs in the provided code. The AI's response is also loaded into the session_state.
+This means that subsequent messages to the AI keep its own responses therefore having the ability to iterate on them.
+Interacts with SearchManager
+
+# 4.5 ExecutionEngine.py
+
+With this module the program can execute the opened file after clicking the corresponding button in the streamlit app. 
+There is a safety check before the subprocess is called to make sure no malicious actions can be made from within the program.
+Interacts with Debuglogger
+
+# 4.6 DebugLogger.py
+
+This module handles making all outputs from various other module more readable and useable.
+It saves the AI's response in the session_state to be able to send it with the next prompt when using the debug toggle.
+
+# 4.7 SearchManager.py
+
+This modules uses the duckduckgosearch API to make searching the internet possible. 
+The user does not directly see the search, but the result is sent with the prompt to the AI.
+
+
+##5. Usage
+
+The following examples illustrate how to use this program.
+
+*I want to ask the AI about something in my file*
+	**user actions**:		- click on button with name of the file
+							- write message to AI
+							- wait for response
+							- implement suggestions from AI
+							
+	**interaction flow**:	- st.sidebar uses list_files() to generate Buttons
+							- on_click uses open_file() to load content and file Path into session_state
+							- send_message() uses generate_prompt() to add system_prompt and context = file_content to the user_message
+							- response is displayed by st.session_state.messages
+							
+
+*I want to ask the AI about somehting in my file, but the AI has outdated info about the topic*
+	**user actions**:		- click on button with name of the file
+							- activate "enable internet search" toggle
+							- write message to AI
+							- wait for response
+							- implement suggestions from AI
+							
+	**interaction flow**:	- st.sidebar uses list_files() to generate Buttons
+							- on_click uses open_file() to load content and file Path into session_state
+							- send_message() uses generate_prompt() to add system_prompt and context = file_content and results from perform_search() to the user_message
+							- response is displayed by st.session_state.messages
+							
+							
+*I want to debug my code* 
+	**user actions**:		- click on button with name of the file
+							- click the "execute code" button
+							- write message to AI
+							- wait for response
+							- implement suggestions from AI
+							- write message to AI
+							- implement suggestions from AI
+							
+	**interaction flow**:	- st.sidebar uses list_files() to generate Buttons
+							- on_click uses open_file() to load content and file Path into session_state
+							- on_click uses run_code() to execute the file, results are formatted by format_output() or format_error()
+							- code_output or code_error are loaded into seassion_state
+							- send_message() uses generate_prompt() to add system_prompt which detects the "debug" toggle and adds context = file_content and code_output / code_error to the user_message
+							- response is displayed by st.session_state.messages
+							- send_message() uses generate_prompt() to add system_prompt which detects the "debug" toggle and adds context = file_content and code_output / code_error and debug response to the user_message
+							- response is displayed by st.session_state.messages
+