small changes

README.md

@@ -171,10 +171,12 @@ vorausgefüllten Debug-Nachricht.
 Zwei sich gegenseitig ausschliessende Ansichten, umgeschaltet via `st.toggle("Agent Mode")`:
 
 **Normaler Chat** (`render_normal_chat()`):
-- Websuch-Panel oben — öffnet sich automatisch, wenn Suchergebnisse aktiv sind.
+- Kompakte 4-spaltige Toolbar direkt über dem Chat-Input:
+  `[● Agent Mode]` `[🔍 Search]` `[🗑️ Clear]` `[⚙️ Settings]`
+  — Web-Suche und Einstellungen jeweils als `st.popover`, Clear öffnet einen Bestätigungs-Dialog.
 - System-Prompt wird vor jeder ausgehenden Nachricht neu generiert (`_set_system_prompt()`).
 - Unterstützt Slash-Befehle `/search <Abfrage>` und `/search clear`.
-- Einstellungs-Expander: Dateikontext-Toggle, Modell-Auswahl, Max-Token-Slider,
+- Settings-Popover: Dateikontext-Toggle, Modell-Auswahl, Max-Token-Slider,
   benutzerdefinierter System-Prompt.
 - «Mit KI debuggen»-Nachrichten vom Editor werden über `pending_debug_message` im
   Session-State weitergeleitet.
@@ -228,7 +230,9 @@ Generiert kontextbewusste System-Prompts. Signatur:
 SystemPrompter.generate_prompt(
     user_message="",
     file_context=None,      # {"name": str, "content": str}
-    search_context=None,    # reserviert, noch nicht verdrahtet
+    search_context=None,    # list[{"title", "url", "snippet"}] — in system_prompter.py implementiert,
+                            # aber in chat.py nicht verwendet: dort wird Search-Kontext direkt
+                            # als <search_context>-Block vor die Nachricht eingefügt
     task_type="default",    # "debug" | "explain" | "optimize" | "default"
 )
 ```
@@ -241,7 +245,7 @@ Funktion oder Klasse zurückzugeben, nach der der Benutzer fragt, anstatt die ge
 ### `execution_engine.py`
 Führt Dateien in einem Subprocess mit `capture_output=True`, `text=True` und einem
 `RUN_TIMEOUT` von 30 Sekunden aus. Aktuell unterstützt:
-- `.py` — via `py`-Launcher (Windows) / `sys.executable`
+- `.py` — via `sys.executable` (plattformübergreifend; zeigt auf den aktuell aktiven Python-Interpreter)
 - `.tex` — via `pdflatex -interaction=nonstopmode` (erfordert pdflatex im PATH)
 
 Rückgabe: `{"stdout": str, "stderr": str, "rc": int}`.
@@ -297,7 +301,7 @@ Wichtige Methoden:
 | `start_task(task)` | Setzt den gesamten Zustand zurück, befüllt History mit System + Aufgabe |
 | `propose_next_action()` | Ruft das LLM auf, parst JSON, speichert als `pending_action` |
 | `approve()` | Führt das ausstehende Tool via `dispatch_tool()` aus, loggt Ergebnis |
-| `reject(feedback)` | Injiziert Feedback + Replan-Tag; schlägt neue Aktion vor |
+| `reject(feedback)` | Injiziert Feedback + Replan-Tag in die History; `propose_next_action()` wird danach separat aufgerufen |
 | `follow_up(question)` | Fügt nach «done» eine Folgefrage ein, setzt Schleife fort |
 
 Hilfsfunktionen (Modul-Ebene):
@@ -308,7 +312,7 @@ Hilfsfunktionen (Modul-Ebene):
 | `trim_messages(msgs)` | Entfernt alte Turns, wenn History `MAX_HISTORY_CHARS` (80 000 Zeichen) überschreitet; System-Nachricht + Original-Aufgabe bleiben immer erhalten |
 | `_strip_code_fences(text)` | Entfernt ` ```json `- / ` ``` `-Wrapper aus LLM-Antworten |
 | `dispatch_tool(name, arguments)` | Leitet weiter an `MCPToolAdapter.call_tool()` |
-| `get_tool_descriptions()` | Erstellt eine menschenlesbare Tool-Liste für den System-Prompt |
+| `build_all_tool_description()` | Erstellt eine menschenlesbare Tool-Liste für den System-Prompt |
 
 ### `mcp_server_adapter.py`
 Liest `mcp_server_config.json`, startet jeden Server als stdio-Subprocess (immer mit
@@ -335,12 +339,11 @@ Alle drei Server sind FastMCP-Applikationen, die über stdio kommunizieren.
 - Beide Tools nutzen SSRF-Schutz (gleiche URL-Validierung wie `search_manager.py`)
 
 **`mcp_server_code_execution.py`** — Sandbox-Python-Analyse:
-- `check_code_safety(code)` — statische Analyse; blockiert gefährliche Imports/Builtins
 - `analyse_structure(code)` — AST-basierte Strukturzusammenfassung
 - `lint_code(code)` — pyflakes-Analyse
 - `python_code_validation(code)` — Sicherheits- + Syntaxprüfung ohne Ausführung
 - `run_python_sandboxed(code)` — Ausführung in einem Subprocess mit `PYTHONIOENCODING=utf-8`,
-  10 s Timeout, Output begrenzt auf `MAX_OUTPUT_LENGTH`
+  15 s Timeout, Output begrenzt auf `MAX_OUTPUT_LENGTH`
 
 ---
 

backend/agent/coding_agent.py

@@ -167,6 +167,7 @@ Example:
   - After validation passes, run it with run_python to verify correctness.
   - If an error occurs, analyse it and try to fix it (up to 3 retries).
   - Stay within the workspace directory.
+  - Never use emojis, umlauts (ä, ö, ü, Ä, Ö, Ü, ß), or any non-ASCII characters in string literals or print() calls — the execution environment uses cp1252 encoding which cannot handle them.
   - When the task is fully complete, call the "done" tool.
   - If you receive a <human_message>, acknowledge it and adjust your plan.
   - If you receive a <replan> tag, revise your plan before choosing the next tool.

backend/managers/execution_engine.py

@@ -6,6 +6,7 @@ processes from blocking the UI indefinitely.
 """
 
 import subprocess
+import sys
 from pathlib import Path
 
 from backend.managers.debug_logger import get_logger
@@ -40,7 +41,7 @@ class ExecutionEngine:
 
         # Build the shell command depending on file type
         if suffix == ".py":
-            cmd = ["py", active_file.name]
+            cmd = [sys.executable, active_file.name]
         elif suffix == ".tex":
             # pdflatex in non-interactive mode so it never waits for input
             cmd = [

backend/managers/system_prompter.py

@@ -9,26 +9,38 @@ logger = get_logger(__name__)
 MAX_FILE_CHARS = 4000
 
 # Per-task base prompts — selected via the task_type parameter.
+# Appended to every prompt — ensures generated code is safe to run on Windows
+# where the console encoding is cp1252 and cannot handle emojis or non-ASCII chars.
+_CODE_SAFETY_NOTE = (
+    " When writing or suggesting code, never use emojis, umlauts (ä, ö, ü, Ä, Ö, Ü, ß), "
+    "or any non-ASCII characters in string literals or print statements, "
+    "as the execution environment uses cp1252 encoding which cannot handle them."
+)
+
 _TASK_PROMPTS: dict[str, str] = {
     "debug": (
         "You are a debugging expert integrated into a lightweight code editor. "
         "Focus on identifying and fixing errors. "
         "Be concise and precise. Use markdown and fenced code blocks where appropriate."
+        + _CODE_SAFETY_NOTE
     ),
     "explain": (
         "You are a code explainer integrated into a lightweight code editor. "
         "Use simple language and examples. "
         "Be concise and precise. Use markdown and fenced code blocks where appropriate."
+        + _CODE_SAFETY_NOTE
     ),
     "optimize": (
         "You are a code optimization expert integrated into a lightweight code editor. "
         "Focus on performance and readability. "
         "Be concise and precise. Use markdown and fenced code blocks where appropriate."
+        + _CODE_SAFETY_NOTE
     ),
     "default": (
         "You are an expert code assistant integrated into a lightweight code editor. "
         "Help the user with code suggestions, debugging, explanations, and improvements. "
         "Be concise and precise. Use markdown and fenced code blocks where appropriate."
+        + _CODE_SAFETY_NOTE
     ),
 }
 

frontend/chat.py

@@ -368,7 +368,7 @@ def _clear_chat_dialog():
 # ── Normal Chat ───────────────────────────────────────────────────────────────
 
 def _render_search_panel():
-    """Render the collapsible web search panel above the chat history.
+    """Render the collapsible web search panel above the chat toolbar.
 
     Stores results in session_state.search_results so they are automatically
     injected as context into the next message the user sends.
@@ -424,9 +424,6 @@ def render_normal_chat():
     logger.info("Chat mode")
     chat_manager: ChatManager = st.session_state.chat_manager
 
-    # Search panel always rendered at the top — expands automatically when results are active.
-    _render_search_panel()
-
     # Apply model/token overrides from the Settings panel before any API call.
     if st.session_state.get("selected_model"):
         chat_manager.model = st.session_state.selected_model
@@ -456,7 +453,58 @@ def render_normal_chat():
         with st.chat_message(message["role"]):
             st.markdown(message["content"])
 
-    # Chat input — Enter to send, no extra button needed.
+    # ── Toolbar — directly above the sticky chat input ────────────────────────
+    # In Streamlit, st.chat_input is a fixed footer. Elements placed BEFORE it
+    # in code appear in the scrollable content area right above the input bar.
+    _render_search_panel()
+
+    col_clear, col_agent, col_settings = st.columns([1, 1, 1])
+    with col_clear:
+        if st.button("🗑️ Clear Chat", use_container_width=True):
+            _clear_chat_dialog()
+    with col_agent:
+        st.toggle("Agent Mode", key="agent_mode")
+    with col_settings:
+        with st.popover("⚙️ Settings", use_container_width=True):
+            st.toggle(
+                "Include current file as context",
+                key="include_file_context",
+                value=True,
+            )
+
+            st.divider()
+
+            default_model = chat_manager.model or ""
+            model_options = [default_model] if default_model else []
+            for m in [
+                "claude-3-5-sonnet-20241022",
+                "claude-3-haiku-20240307",
+                "gpt-4o",
+                "gpt-4o-mini",
+            ]:
+                if m not in model_options:
+                    model_options.append(m)
+            st.selectbox("Model", model_options, key="selected_model")
+
+            st.slider(
+                "Max Response Tokens",
+                min_value=256,
+                max_value=8000,
+                value=chat_manager.max_tokens,
+                step=256,
+                key="chat_max_tokens",
+            )
+
+            st.divider()
+
+            st.text_area(
+                "Custom System Prompt (overrides default if set)",
+                key="custom_system_prompt",
+                height=120,
+                placeholder="Leave empty to use the default assistant prompt with optional file context.",
+            )
+
+    # Chat input — sticky footer, always at the very bottom of the viewport.
     # Supports /search <query> and /search clear as special commands.
     user_input = st.chat_input("Type a message or /search <query>...")
     if user_input:
@@ -535,43 +583,6 @@ def render_normal_chat():
         st.session_state.chat_history.append({"role": "assistant", "content": ai_response})
         st.rerun()
 
-    # 5d — Clear Chat opens a confirmation dialog instead of deleting immediately.
-    if st.button("🗑️ Clear Chat"):
-        _clear_chat_dialog()
-
-    # Toggle to switch to Agent Mode (render_normal_chat and render_agent_mode are
-    # mutually exclusive, so the same key here causes no DuplicateWidgetID conflict).
-    st.toggle("Agent Mode", key="agent_mode")
-
-    # 5h — Settings expander: file context toggle, model, token limit, custom prompt.
-    with st.expander("⚙️ Settings", expanded=False):
-        st.toggle("Include current file as context", key="include_file_context", value=True)
-
-        st.divider()
-
-        default_model = chat_manager.model or ""
-        model_options = [default_model] if default_model else []
-        for m in ["claude-3-5-sonnet-20241022", "claude-3-haiku-20240307", "gpt-4o", "gpt-4o-mini"]:
-            if m not in model_options:
-                model_options.append(m)
-        st.selectbox("Model", model_options, key="selected_model")
-
-        st.slider(
-            "Max Response Tokens",
-            min_value=256, max_value=8000,
-            value=chat_manager.max_tokens,
-            step=256, key="chat_max_tokens",
-        )
-
-        st.divider()
-
-        st.text_area(
-            "Custom System Prompt (overrides default if set)",
-            key="custom_system_prompt",
-            height=120,
-            placeholder="Leave empty to use the default assistant prompt with optional file context.",
-        )
-
 
 # ── Entry point ───────────────────────────────────────────────────────────────
 

requirements.txt

@@ -1,5 +1,5 @@
 # Core Framework
-streamlit>=1.28.0
+streamlit==1.57.0
 streamlit_arborist>=0.1.0
 
 # AI/LLM Integration