app.py

import streamlit as st
import requests
import json
from PIL import Image
import io
import base64
import pandas as pd
import zipfile
import PyPDF2
import os

# --- Konfiguration ---
st.set_page_config(page_title="OpenRouter Free Interface", layout="wide", initial_sidebar_state="expanded")
OPENROUTER_API_BASE = "https://openrouter.ai/api/v1"

# --- Page Title ---
st.title("💸 OpenRouter Free-Tier Interface")
st.markdown("""
**Willkommen im All-OpenRouter-Free-Interface Deluxe!**
Chatte mit **kostenlosen (Free-Tier)** Modellen über die OpenRouter API.
Alle Modelle unterliegen den OpenRouter-Ratenbegrenzungen.
""")

# --- Session State Management ---
if "messages" not in st.session_state:
    st.session_state.messages = []
if "uploaded_content" not in st.session_state:
    st.session_state.uploaded_content = None


# --- Datei-Verarbeitung ---
def encode_image(image):
    buf = io.BytesIO()
    image.save(buf, format="JPEG")
    return base64.b64encode(buf.getvalue()).decode("utf-8")


def process_file(uploaded_file):
    # Ihr robuster File Manager ist perfekt
    file_type = uploaded_file.name.split('.')[-1].lower()
    text_exts = ('.txt', '.csv', '.py', '.html', '.js', '.css', '.json', '.xml', '.sql', '.xlsx')

    if file_type in ["jpg", "jpeg", "png"]:
        return {"type": "image", "content": Image.open(uploaded_file).convert('RGB')}

    if file_type in ["txt"] + [ext.strip('.') for ext in text_exts if ext not in ('.csv', '.xlsx')]:
        return {"type": "text", "content": uploaded_file.read().decode("utf-8", errors="ignore")}

    if file_type in ["csv", "xlsx"]:
        try:
            df = pd.read_csv(uploaded_file) if file_type == "csv" else pd.read_excel(uploaded_file)
            return {"type": "text", "content": df.to_string()}
        except Exception as e:
            return {"type": "error", "content": f"Fehler beim Lesen der Tabelle: {e}"}

    if file_type == "pdf":
        try:
            reader = PyPDF2.PdfReader(uploaded_file)
            return {"type": "text", "content": "".join(page.extract_text() or "" for page in reader.pages)}
        except Exception as e:
            return {"type": "error", "content": f"PDF Fehler: {e}"}

    if file_type == "zip":
        try:
            with zipfile.ZipFile(uploaded_file) as z:
                content = "ZIP Contents:\n"
                for f in z.infolist():
                    if not f.is_dir() and f.filename.lower().endswith(text_exts):
                        content += f"\n📄 {f.filename}:\n"
                        content += z.read(f.filename).decode("utf-8", errors="ignore")
                return {"type": "text", "content": content or "ZIP enthält keine lesbaren Textdateien."}
        except Exception as e:
            return {"type": "error", "content": f"ZIP Fehler: {e}"}

    return {"type": "error", "content": "Nicht unterstütztes Dateiformat."}


# --- Context-Length Fetch (MIT CACHING) ---
@st.cache_data(ttl=3600) # Caching für 1 Stunde, um API-Calls zu sparen
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")

    # Free Modelle (Fallback)
    FREE_MODEL_LIST = [
        "cognitivecomputations/dolphin-mistral-24b-venice-edition:free",
        "deepseek/deepseek-chat-v3",
        "google/gemma-2-9b-it",
        "mistralai/mistral-7b-instruct-v0.2",
        "qwen/qwen2-72b-instruct",
        "nousresearch/nous-hermes-2-mixtral-8x7b-dpo",
    ]

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

    # Context automatisch anpassen (durch Caching nur bei Bedarf neu geladen)
    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, 32000), 
        min(512, default_ctx)
    )
    st.caption(f"🔢 Model Context Length: {default_ctx}")
    
    st.markdown("---")

    # Verbesserter Reset-Button
    if st.button("🔄 Chat Reset (Full)"):
        st.session_state.messages = []
        st.session_state.uploaded_content = None
        # Rerun, um st.file_uploader zu leeren und die App in den Startzustand zu versetzen
        st.experimental_rerun() 

    st.markdown("""
    ---
    🧠 **Hinweis:** Dein API-Key wird nur **lokal** verwendet, um Anfragen an OpenRouter zu authentifizieren.
    """)


# --- Datei Upload & Preview Logik ---
uploaded_file = st.file_uploader("Upload File (optional)",
                                 type=["jpg", "jpeg", "png", "txt", "pdf", "zip", "csv", "xlsx", "html", "css", "js", "py"])

# NEUE/KORRIGIERTE LOGIK: Nur verarbeiten, wenn eine neue Datei hochgeladen wird und KEIN Inhalt im State ist
if uploaded_file and st.session_state.uploaded_content is None:
    st.session_state.uploaded_content = process_file(uploaded_file)
    # KEIN st.experimental_rerun() hier! Streamlit rendert die Vorschau beim nächsten regulären Durchlauf.
    # Siehe Gemini Code: Dort fehlt dieser Rerun auch.

if st.session_state.uploaded_content:
    processed = st.session_state.uploaded_content
    st.subheader("📎 Current Attachment:")
    if processed["type"] == "image":
        st.image(processed["content"], caption="Attached Image", width=300)
    elif processed["type"] == "text":
        st.text_area("File Preview", processed["content"], height=150)
    elif processed["type"] == "error":
        st.error(processed["content"])
        
    # Anhang einzeln entfernen
    if st.button("❌ Remove Attachment"):
        st.session_state.uploaded_content = None
        st.experimental_rerun() # Hier ist der Rerun notwendig, um den uploader zu leeren


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


# --- API Call Funktion ---
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-Free-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()

    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)

    messages = [{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]

    if st.session_state.uploaded_content:
        content = st.session_state.uploaded_content
        if content["type"] == "image":
            base64_img = encode_image(content["content"])
            # OpenRouter Multimodalität (OpenAI-Schema)
            messages[-1]["content"] = [
                {"type": "text", "text": prompt},
                {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_img}"}}
            ]
        elif content["type"] == "text":
            # Text-Dateien einfach dem letzten Prompt anhängen
            messages[-1]["content"] += f"\n\n[Attached File Content]\n{content['content']}"

    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)}"})