import gradio as gr
import os
from huggingface_hub import InferenceClient
from langchain_community.document_loaders import PyMuPDFLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_huggingface import HuggingFaceEmbeddings
from langchain_community.vectorstores import FAISS

# 1. Ayarlar ve İstemci
hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
client = InferenceClient("google/gemma-2-9b-it", token=hf_token)

# 2. PDF Hafızası Oluşturma
def initialize_hemdem():
    if not os.path.exists("kulliyat.pdf"):
        return None
    try:
        loader = PyMuPDFLoader("kulliyat.pdf")
        docs = loader.load()
        text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
        split_docs = text_splitter.split_documents(docs)
        embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
        vector_db = FAISS.from_documents(split_docs, embeddings)
        return vector_db
    except Exception as e:
        print(f"Hata: {e}")
        return None

vector_db = initialize_hemdem()

# 3. Sohbet Fonksiyonu
def chat(message, history):
    if vector_db is None:
        return "Sistem hatası: 'kulliyat.pdf' bulunamadı."
    
    # İlgili parçaları bul
    related_docs = vector_db.similarity_search(message, k=3)
    context = "\n".join([doc.page_content for doc in related_docs])
    
    # Gemma 2 için Mesaj Formatı (Conversational Task uyumlu)
    messages = [
        {"role": "system", "content": f"Sen Hemdem-i Gemini-yi Emre'sin. Emre'nin külliyatına dayanarak cevap ver. Dökümanlar: {context}"},
        {"role": "user", "content": message}
    ]
    
    try:
        response = ""
        # Chat Completion metodunu kullanarak 'conversational' hatasını aşıyoruz
        for message in client.chat_completion(
            messages,
            max_tokens=1024,
            stream=True,
        ):
            token = message.choices[0].delta.content
            response += token
        return response
    except Exception as e:
        return f"Bağlantı Hatası: {str(e)}"

# 4. Arayüz
demo = gr.ChatInterface(
    fn=chat,
    title="💜 Hemdem-i Şir",
    description="Gemma 2 destekli Emre Külliyat Rehberi",
)

if __name__ == "__main__":
    demo.launch()