app.py

import os
import streamlit as st
import tempfile
import requests
import json
# Entfernte Imports: PIL.Image, io, base64, pandas, zipfile, PyPDF2
# Da kein File Manager mehr benötigt wird.

# ----------------------------------------------------
# 🚨 KRITISCHE FIXES FÜR DEN PERMISSION ERROR
# Zwingt Streamlit, seine temporären/Konfigurationsdateien
# in den beschreibbaren /tmp-Bereich zu schreiben.
# ----------------------------------------------------

# 1. Temporären, beschreibbaren Pfad erstellen
TEMP_STREAMLIT_HOME = os.path.join(tempfile.gettempdir(), "st_config_workaround")
os.makedirs(TEMP_STREAMLIT_HOME, exist_ok=True)

# 2. Umgebungsvariablen setzen
os.environ["STREAMLIT_HOME"] = TEMP_STREAMLIT_HOME
os.environ["STREAMLIT_GATHER_USAGE_STATS"] = "false"

# 3. Minimale config.toml erstellen, um Schreibversuche zu unterbinden
CONFIG_PATH = os.path.join(TEMP_STREAMLIT_HOME, "config.toml")
CONFIG_CONTENT = """
[browser]
gatherUsageStats = false
"""

if not os.path.exists(CONFIG_PATH):
    try:
        with open(CONFIG_PATH, "w") as f:
            f.write(CONFIG_CONTENT)
    except Exception as e:
        print(f"WARNUNG: Konnte config.toml nicht schreiben: {e}")

# ----------------------------------------------------
# Ende der Workarounds
# ----------------------------------------------------

# --- Konfiguration ---
# Hinweis: Layout-Einstellung 'wide' bleibt erhalten
st.set_page_config(page_title="OpenRouter Minimal Chat UI", layout="wide")
OPENROUTER_API_BASE = "https://openrouter.ai/api/v1"

# --- Page Title ---
st.title("💸 OpenRouter Minimal Chat Interface")
st.markdown("""
**Willkommen im OpenRouter Minimal Chat Interface!**
Chatte mit **kostenlosen (Free-Tier)** Modellen über die OpenRouter API. Nur Text-Chat.
""")

# --- Session State Management ---
if "messages" not in st.session_state:
    st.session_state.messages = []
# st.session_state.uploaded_content wurde entfernt.

# --- Context-Length Fetch (Wird beibehalten, da für den Slider wichtig) ---
def fetch_model_contexts(api_key):
    """Lädt alle Modelle + deren context_length."""
    if not api_key:
        return {}
    headers = {"Authorization": f"Bearer {api_key}"}
    try:
        res = requests.get(f"{OPENROUTER_API_BASE}/models", headers=headers, timeout=10)
        contexts = {}
        if res.status_code == 200:
            for m in res.json().get("data", []):
                mid = m.get("id")
                ctx = m.get("context_length", 4096)
                contexts[mid] = ctx
        return contexts
    except Exception as e:
        return {}


# --- Sidebar ---
with st.sidebar:
    st.header("⚙️ API Settings")
    api_key = st.text_input("OpenRouter API Key", type="password")

    # --- Manuelle Modelle ---
    FREE_MODEL_LIST = [
        "cognitivecomputations/dolphin-mistral-24b-venice-edition:free",
        "deepseek/deepseek-chat-v3.1:free",
        "nvidia/nemotron-nano-9b-v2:free",
        "google/gemma-3-27b-it:free",
        "openai/gpt-oss-20b:free",
        "qwen/qwen3-coder:free",
        "qwen/qwen2.5-vl-72b-instruct:free",
        "nousresearch/deephermes-3-llama-3-8b-preview:free",

    ]
    model = st.selectbox("Wähle ein Modell", FREE_MODEL_LIST, index=0)

    # Kontextlänge holen (mit Fallback)
    model_contexts = fetch_model_contexts(api_key)
    default_ctx = model_contexts.get(model, 4096) 

    temperature = st.slider("Temperature", 0.0, 1.0, 0.7)
    max_tokens = st.slider(
        f"Max Output Tokens (max {default_ctx})", 
        1, 
        min(default_ctx, 128000), 
        min(512, default_ctx)
    )
    st.caption(f"🔢 Model Context Length (Fallback 4096): {default_ctx}")

    if st.button("🔄 Chat Reset"):
        st.session_state.messages = []
        st.success("Chat-Verlauf gelöscht.")
        st.experimental_rerun()

    st.markdown("""
    ---
    **Minimal UI:** Nur Text-Chat.
    """)

# --- Datei Upload Sektion komplett entfernt ---


# --- Chat Verlauf anzeigen ---
for msg in st.session_state.messages:
    with st.chat_message(msg["role"]):
        st.markdown(msg["content"])


# --- API Request Funktion (Unverändert) ---
def call_openrouter(model, messages, temp, max_tok, key):
    headers = {
        "Authorization": f"Bearer {key}",
        "Content-Type": "application/json",
        "Referer": "https://aicodecraft.io",
        "X-Title": "OpenRouter-Minimal-Interface",
    }
    payload = {
        "model": model,
        "messages": messages,
        "temperature": temp,
        "max_tokens": max_tok,
    }
    
    res = requests.post(f"{OPENROUTER_API_BASE}/chat/completions", headers=headers, data=json.dumps(payload))
    
    if res.status_code == 200:
        try:
            return res.json()["choices"][0]["message"]["content"]
        except (KeyError, IndexError):
            raise Exception("Fehlerhafte API-Antwort: Konnte Antworttext nicht extrahieren.")
    else:
        try:
            err = res.json()
            msg = err.get("error", {}).get("message", res.text)
        except:
            msg = res.text
        raise Exception(f"API Error {res.status_code}: {msg}")


# --- Chat Input ---
if prompt := st.chat_input("Deine Nachricht..."):
    if not api_key:
        st.warning("Bitte trage deinen OpenRouter API Key in der Sidebar ein.")
        st.stop()

    # Nachricht hinzufügen und anzeigen
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)

    # API Nachrichten vorbereiten (für Chatverlauf)
    messages = [{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]

    # Antwort generieren
    with st.chat_message("assistant"):
        with st.spinner(f"Fragend {model}..."):
            try:
                reply = call_openrouter(model, messages, temperature, max_tokens, api_key)
                st.markdown(reply)
                st.session_state.messages.append({"role": "assistant", "content": reply})
            except Exception as e:
                st.error(str(e))
                st.session_state.messages.append({"role": "assistant", "content": f"❌ {str(e)}"})