Create app.py

app.py

@@ -0,0 +1,59 @@
+import gradio as gr
+from ebooklib import epub
+from bs4 import BeautifulSoup
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import Chroma
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.chains import RetrievalQA
+from langchain.llms import OpenAI
+
+# === EPUB-Datei verarbeiten ===
+def load_epub(epub_path):
+    book = epub.read_epub(epub_path)
+    text = []
+    for item in book.get_items():
+        if item.get_type() == epub.ITEM_DOCUMENT:
+            soup = BeautifulSoup(item.get_content(), "html.parser")
+            text.append(soup.get_text())
+    return "\n".join(text)
+
+# === Text aufteilen ===
+def split_text(text):
+    splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
+    return splitter.split_text(text)
+
+# === Vektordatenbank erstellen ===
+def create_vectorstore(texts):
+    embeddings = HuggingFaceEmbeddings(model_name="BAAI/bge-small-en")
+    return Chroma.from_texts(texts, embeddings)
+
+# === LLM (GPT-4 oder Open-Source) ===
+def load_llm():
+    return OpenAI(model_name="gpt-4")  # Nutzt GPT-4 (ersetze ggf. durch Open-Source)
+
+# === Q&A-Kette erstellen ===
+def create_qa_chain(llm, vectorstore):
+    return RetrievalQA.from_chain_type(llm, chain_type="stuff", retriever=vectorstore.as_retriever())
+
+# === Chatbot-Funktion ===
+def chatbot(epub_file, question):
+    text = load_epub(epub_file.name)
+    texts = split_text(text)
+    vectorstore = create_vectorstore(texts)
+    llm = load_llm()
+    qa_chain = create_qa_chain(llm, vectorstore)
+    return qa_chain.run(question)
+
+# === Gradio UI ===
+with gr.Blocks() as demo:
+    gr.Markdown("## 📖 E-Book Chatbot mit LangChain")
+    epub_input = gr.File(label="Lade eine EPUB-Datei hoch")
+    question_input = gr.Textbox(label="Stelle eine Frage zu deinem Buch")
+    answer_output = gr.Textbox(label="Antwort", interactive=False)
+    submit_button = gr.Button("Frage stellen")
+    
+    submit_button.click(chatbot, inputs=[epub_input, question_input], outputs=answer_output)
+
+# === App starten ===
+if __name__ == "__main__":
+    demo.launch()