commit

app.py

@@ -1,6 +1,6 @@
 # app.py
 import os
-from typing import List, Dict, Tuple
+from typing import List, Tuple
 
 import gradio as gr
 from langchain_core.documents import Document
@@ -12,9 +12,7 @@ from load_documents import load_documents
 from speech_io import transcribe_audio, synthesize_speech
 
 
-# ===============================
-# 1. Documents Laden
-# ===============================
+# ========== 1. Lade Dokumente ==========
 print("🔹 Lade Dokumente aus Supabase …")
 docs: List[Document] = load_documents()
 print("✔ DOCUMENTS LOADED:", len(docs))
@@ -40,9 +38,7 @@ llm = ChatOpenAI(
 )
 
 
-# ===============================
-# 2. RAG Engine
-# ===============================
+# ========== 2. RAG ==========
 def build_context(docs: List[Document]) -> str:
     parts = []
     for i, d in enumerate(docs, 1):
@@ -61,60 +57,53 @@ def build_context(docs: List[Document]) -> str:
     return "\n\n".join(parts)
 
 
-def rag_answer(query: str, mode: str) -> Tuple[str, List[Document]]:
+def rag_answer(query: str, mode: str):
     retrieved = retriever.invoke(query)
     ctx = build_context(retrieved)
 
     modes = {
         "Kurz": "Antworte sehr kurz (max. 3 Sätze).",
-        "Standard": "Antworte ausführlich und gut verständlich.",
-        "Juristisch Präzise": "Antworte fachlich-präzise mit juristischer Struktur.",
+        "Standard": "Antworte ausführlich und verständlich.",
+        "Juristisch Präzise": "Formuliere juristisch präzise.",
     }
 
     messages = [
-        {"role": "system",
-         "content": "Du bist ein Chatbot für Prüfungsrecht. Antworte NUR auf Deutsch."},
-        {"role": "user",
-         "content": f"FRAGE:\n{query}\n\nKONTEXT:\n{ctx}\n\n{modes[mode]}"}
+        {
+            "role": "system",
+            "content": "Du bist ein Chatbot für Prüfungsrecht. Antworte nur auf Deutsch."
+        },
+        {
+            "role": "user",
+            "content": f"FRAGE:\n{query}\n\nKONTEXT:\n{ctx}\n\n{modes[mode]}"
+        }
     ]
 
-    response = llm.invoke(messages)
-    answer = response.content
-    return answer, retrieved
+    resp = llm.invoke(messages)
+    return resp.content, retrieved
 
 
-# ===============================
-# 3. Chatbot Funktionen (GRADIO v6 FORMAT!)
-# ===============================
-def chatbot_text(user_input: str, history: List[Dict], mode: str):
+# ========== 3. Chatbot Funktionen (GRADIO 4.x – TUPLES) ==========
+def chatbot_text(user_input: str, history: List[Tuple[str, str]], mode: str):
     answer, _ = rag_answer(user_input, mode)
-    history = history + [
-        {"role": "user", "content": user_input},
-        {"role": "assistant", "content": answer},
-    ]
+    history = history + [(user_input, answer)]
     return history, history
 
 
-def chatbot_voice(audio_file: str, history: List[Dict], mode: str, language_hint: str):
-    user_text = transcribe_audio(audio_file, language=language_hint or None)
+def chatbot_voice(audio_file: str, history: List[Tuple[str, str]], mode: str, language_hint: str):
+    user_text = transcribe_audio(audio_file, language_hint or None)
     answer, _ = rag_answer(user_text, mode)
     audio_out = synthesize_speech(answer)
 
-    history = history + [
-        {"role": "user", "content": user_text},
-        {"role": "assistant", "content": answer},
-    ]
+    history = history + [(user_text, answer)]
     return history, audio_out, user_text, history
 
 
-# ===============================
-# 4. UI
-# ===============================
+# ========== 4. UI ==========
 with gr.Blocks(title="Prüfungsrechts-Chatbot") as demo:
 
     with gr.Tab("💬 Text-Chat"):
         mode = gr.Radio(["Kurz", "Standard", "Juristisch Präzise"], value="Standard")
-        chat = gr.Chatbot(type="messages")
+        chat = gr.Chatbot()
         state = gr.State([])
         inp = gr.Textbox(label="Frage eingeben")
         send = gr.Button("Senden")
@@ -123,19 +112,19 @@ with gr.Blocks(title="Prüfungsrechts-Chatbot") as demo:
 
     with gr.Tab("🎙️ Sprach-Chat"):
         mode_v = gr.Radio(["Kurz", "Standard", "Juristisch Präzise"], value="Standard")
-        chat_v = gr.Chatbot(type="messages")
+        chat_v = gr.Chatbot()
         state_v = gr.State([])
 
         mic = gr.Audio(sources=["microphone"], type="filepath")
-        lang_hint = gr.Textbox(label="Sprache (optional: de/en/vi)")
-        out_audio = gr.Audio(label="Antwort (TTS)")
-        trans_box = gr.Textbox(label="Transkript")
+        lang = gr.Textbox(label="Sprache (optional: de/en/vi)")
+        out_audio = gr.Audio()
+        transcript = gr.Textbox(label="Transkript")
 
         btn = gr.Button("Sprechen")
         btn.click(
             chatbot_voice,
-            [mic, state_v, mode_v, lang_hint],
-            [chat_v, out_audio, trans_box, state_v]
+            [mic, state_v, mode_v, lang],
+            [chat_v, out_audio, transcript, state_v]
         )
 
 if __name__ == "__main__":