Update app.py

app.py

@@ -1,179 +1,231 @@
-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")
+import google.generativeai as genai
+from PIL import Image
+import io
+import base64
+import pandas as pd
+import zipfile
+import PyPDF2
+
+# Konfiguration der Seite
+st.set_page_config(page_title="Gemini AI Chat", layout="wide")
+
+st.title("🤖 Gemini AI Chat Interface")
 st.markdown("""
-**Willkommen im OpenRouter Minimal Chat Interface!**
-Chatte mit **kostenlosen (Free-Tier)** Modellen über die OpenRouter API. Nur Text-Chat.
+**Welcome to the Gemini AI Chat Interface!**
+Chat seamlessly with Google's advanced Gemini AI models, supporting multiple input types.
+🔗 [GitHub Profile](https://github.com/volkansah) | 
+📂 [Project Repository](https://github.com/volkansah/gemini-ai-chat) | 
+💬 [Soon](https://aicodecraft.io)
 """)
 
-# --- Session State Management ---
+# 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 {}
-
+if "uploaded_content" not in st.session_state:
+    st.session_state.uploaded_content = None
+
+# Funktionen zur Dateiverarbeitung
+def encode_image(image):
+    buffered = io.BytesIO()
+    image.save(buffered, format="JPEG")
+    return base64.b64encode(buffered.getvalue()).decode('utf-8')
+
+def process_file(uploaded_file):
+    """Verarbeitet die hochgeladene Datei und extrahiert den Inhalt."""
+    file_type = uploaded_file.name.split('.')[-1].lower()
+    
+    # Text-basierte Erweiterungen für ZIP-Verarbeitung
+    text_extensions = ('.txt', '.csv', '.py', '.html', '.js', '.css', 
+                       '.php', '.json', '.xml', '.c', '.cpp', '.java', 
+                       '.cs', '.rb', '.go', '.ts', '.swift', '.kt', '.rs', '.sh', '.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_extensions 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:
+            # Versuch, Datei als CSV oder Excel zu lesen
+            if file_type == "csv":
+                df = pd.read_csv(uploaded_file)
+            else: # xlsx
+                df = pd.read_excel(uploaded_file)
+            return {"type": "text", "content": df.to_string()}
+        except Exception as e:
+            return {"type": "error", "content": f"Failed to read tabular data: {e}"}
+    
+    if file_type == "pdf":
+        try:
+            reader = PyPDF2.PdfReader(uploaded_file)
+            return {"type": "text", "content": "".join(page.extract_text() for page in reader.pages if page.extract_text())}
+        except Exception as e:
+             return {"type": "error", "content": f"Failed to read PDF: {e}"}
+    
+    if file_type == "zip":
+        try:
+            with zipfile.ZipFile(uploaded_file) as z:
+                newline = "\n"
+                content = f"ZIP Contents (Processing text files only):{newline}"
+                
+                for file_info in z.infolist():
+                    if not file_info.is_dir():
+                        try:
+                            # Prüfen, ob die Datei eine Text-Erweiterung hat
+                            if file_info.filename.lower().endswith(text_extensions):
+                                with z.open(file_info.filename) as file:
+                                    # Decode mit 'ignore', falls es Probleme gibt
+                                    file_content = file.read().decode('utf-8', errors='ignore')
+                                    content += f"{newline}📄 {file_info.filename}:{newline}{file_content}{newline}"
+                            else:
+                                content += f"{newline}⚠️ Binärdatei/Unbekannte Datei ignoriert: {file_info.filename}{newline}"
+                        except Exception as e:
+                            content += f"{newline}❌ Fehler beim Lesen von {file_info.filename}: {str(e)}{newline}"
+                
+                return {"type": "text", "content": content}
+        except Exception as e:
+            return {"type": "error", "content": f"Failed to process ZIP: {e}"}
+    
+    return {"type": "error", "content": "Unsupported file format"}
 
-# --- Sidebar ---
+# Sidebar für Einstellungen
 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",
-        "google/gemma-2-9b-it",
-        "mistralai/mistral-7b-instruct-v0.2",
-        "qwen/qwen2-72b-instruct",
-        "nousresearch/nous-hermes-2-mixtral-8x7b-dpo",
+    api_key = st.text_input("Google AI API Key", type="password")
+    
+    # Modell-Liste bereinigt und Vision hervorgehoben
+    model_list = [
+        "gemini-1.5-flash",
+        "gemini-1.5-pro",
+        "gemini-1.5-pro-vision-latest", # Vision-Modell für Bilder
+        "gemini-1.0-pro-vision-latest",
+        "gemini-2.0-flash",
+        "gemini-2.0-flash-lite",
+        "gemini-2.0-pro-exp-02-05",
     ]
-    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) 
-
+    model = st.selectbox("Model", model_list)
+    st.caption("❗ Für Bildanalyse **(Vision)**-Modell wählen.")
+    
     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 (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,
-    }
+    max_tokens = st.slider("Max Tokens", 1, 100000, 1000)
+
+# Datei-Upload-Kontrolle
+uploaded_file = st.file_uploader("Upload File (Image/Text/PDF/ZIP)", 
+                                 type=["jpg", "jpeg", "png", "txt", "pdf", "zip", 
+                                       "csv", "xlsx", "html", "css", "php", "js", "py"])
+
+# Logik zur Dateiverarbeitung und Vorschau
+if uploaded_file and st.session_state.uploaded_content is None:
+    # Nur verarbeiten, wenn eine neue Datei hochgeladen wird und kein Inhalt im State ist
+    processed = process_file(uploaded_file)
+    st.session_state.uploaded_content = processed
+
+# Vorschau anzeigen, wenn Inhalt vorhanden
+if st.session_state.uploaded_content:
+    processed = st.session_state.uploaded_content
     
-    res = requests.post(f"{OPENROUTER_API_BASE}/chat/completions", headers=headers, data=json.dumps(payload))
+    st.subheader("Current File Attachment:")
     
-    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}")
+    if processed["type"] == "image":
+        st.image(processed["content"], caption="Attached Image", use_container_width=False, width=300)
+    elif processed["type"] == "text":
+        st.text_area("File Preview", processed["content"], height=150)
+    elif processed["type"] == "error":
+         st.error(f"Error processing file: {processed['content']}")
+    
+    # NEU: Clear Button
+    if st.button("❌ Clear Uploaded File Attachment"):
+        st.session_state.uploaded_content = None
+        # Da st.file_uploader selbst nicht einfach resettet,
+        # informieren wir den Nutzer, dass der Zustand gelöscht ist.
+        st.info("Attachment cleared! Reload the page to reset the upload field completely.")
+
 
+# Chat-Historie anzeigen
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
 
-# --- Chat Input ---
-if prompt := st.chat_input("Deine Nachricht..."):
+# Chat-Eingabe verarbeiten
+if prompt := st.chat_input("Your message..."):
     if not api_key:
-        st.warning("Bitte trage deinen OpenRouter API Key in der Sidebar ein.")
+        st.warning("API Key benötigt!")
         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)}"})
+    
+    # NEU: Spinner hinzugefügt
+    with st.spinner("Gemini is thinking..."):
+        try:
+            # API konfigurieren
+            genai.configure(api_key=api_key)
+            
+            # Modell auswählen
+            model_instance = genai.GenerativeModel(model)
+            
+            # Inhalt vorbereiten
+            content = [{"text": prompt}]
+            
+            # Dateiinhalt hinzufügen
+            if st.session_state.uploaded_content:
+                if st.session_state.uploaded_content["type"] == "image":
+                    # Überprüfung, ob ein Vision-Modell ausgewählt ist
+                    if "vision" not in model.lower() and "pro" not in model.lower():
+                        st.error("Bitte ein Vision- oder Pro-Modell für Bilder auswählen!")
+                        st.stop()
+                    
+                    content.append({
+                        "inline_data": {
+                            "mime_type": "image/jpeg",
+                            "data": encode_image(st.session_state.uploaded_content["content"])
+                        }
+                    })
+                elif st.session_state.uploaded_content["type"] == "text":
+                    # Text-Inhalt dem Prompt hinzufügen
+                    content[0]["text"] += f"\n\n[Attached File Content]\n{st.session_state.uploaded_content['content']}"
+            
+            # Nachricht zur Historie hinzufügen und anzeigen
+            st.session_state.messages.append({"role": "user", "content": prompt})
+            with st.chat_message("user"):
+                st.markdown(prompt)
+            
+            # Antwort generieren
+            response = model_instance.generate_content(
+                content,
+                generation_config=genai.types.GenerationConfig(
+                    temperature=temperature,
+                    max_output_tokens=max_tokens
+                )
+            )
+            
+            # Überprüfen, ob die Antwort gültig ist
+            if not response.candidates:
+                st.error("API Error: Keine gültige Antwort erhalten. Überprüfe die Eingabe oder das Modell.")
+            else:
+                # Antwort anzeigen und zur Historie hinzufügen
+                response_text = response.text
+                with st.chat_message("assistant"):
+                    st.markdown(response_text)
+                st.session_state.messages.append({"role": "assistant", "content": response_text})
+            
+        except Exception as e:
+            st.error(f"API Error: {str(e)}")
+            # Zusätzliche Überprüfung für Visionsfehler
+            if st.session_state.uploaded_content and st.session_state.uploaded_content["type"] == "image" and "vision" not in model.lower() and "pro" not in model.lower():
+                st.error("Detail-Fehler: Für Bilder MUSS ein Vision-fähiger Modell (z.B. 1.5 Pro) ausgewählt werden.")
+
+# Instructions in the sidebar
+with st.sidebar:
+    st.markdown("""
+    ---
+    ## 📝 Instructions:
+    1. Enter your Google AI API key
+    2. Select a model (use **Pro/Vision** models for image analysis)
+    3. Adjust parameters (Temperature/Tokens)
+    4. Upload a file (optional, supports **Image, Text, PDF, ZIP, CSV/XLSX**)
+    5. Type your message and press Enter
+    
+    ### About
+    🔗 [GitHub Profile](https://github.com/volkansah) | 
+    📂 [Project Repository](https://github.com/volkansah/gemini-ai-chat) | 
+    💬 [Soon](https://aicodecraft.io)
+    """)