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Trending Media Chatbot (1).pdf
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Binary file (5.7 kB). View file
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Trending Media Chatbot App.py
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import gradio as gr
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from langchain.document_loaders import PyPDFLoader
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.embeddings import HuggingFaceEmbeddings
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from langchain.vectorstores import FAISS
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from langchain.chains import RetrievalQA
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from langchain.llms import CTransformers
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# Lade und verarbeite das PDF beim Start
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loader = PyPDFLoader("TrendingMedia_ChatbotBasis_FINAL.pdf")
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documents = loader.load()
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splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
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texts = splitter.split_documents(documents)
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embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
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db = FAISS.from_documents(texts, embeddings)
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retriever = db.as_retriever(search_kwargs={"k": 2})
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llm = CTransformers(
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model="TheBloke/TinyLlama-1.1B-Chat-v1-GGUF",
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model_file="tinyllama-1.1b-chat-v1.Q4_K_M.gguf",
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config={'max_new_tokens': 512, 'temperature': 0.5}
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)
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qa_chain = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever)
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# Frage-Antwort-Logik
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def ask_question(user_input):
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if user_input.lower() in ["start", "hallo", "hi", "hey"]:
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return "👋 Willkommen bei Trending Media! Wie kann ich dir behilflich sein?"
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response = qa_chain.run(user_input)
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if response.strip() == "" or "I'm sorry" in response or len(response.split()) < 5:
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if "kontakt" in user_input.lower() or "erreichen" in user_input.lower():
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return (
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"📬 Du kannst uns direkt über dieses Formular kontaktieren:\n\n"
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"**Vorname & Nachname:**\n[_________]\n\n"
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"**E-Mail:**\n[_________]\n\n"
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"**Nachricht:**\n[__________________________]\n\n"
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"*Oder direkt über:* [📨 Kontaktformular](https://trendingmedia.ch/kontakt)"
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)
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else:
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return "❌ Das kann ich dir leider nicht beantworten. Ich bin auf Informationen aus unserem PDF spezialisiert."
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return response
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# Gradio UI
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with gr.Blocks() as demo:
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gr.Markdown("## 🤖 TrendingBot\nWillkommen bei Trending Media! Stelle mir deine Frage.")
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user_input = gr.Textbox(label="Deine Frage", placeholder="Frag mich etwas über unsere Lösungen...")
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bot_response = gr.Textbox(label="TrendingBot antwortet")
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user_input.submit(ask_question, inputs=user_input, outputs=bot_response)
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demo.launch()
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