Delete rag_pipeline.py

rag_pipeline.py

@@ -1,43 +0,0 @@
-from sentence_transformers import SentenceTransformer
-from transformers import pipeline
-import faiss
-import numpy as np
-from config import MODEL_CONFIG
-
-class ArabicRAGSystem:
-    def __init__(self):
-        self.embedder = SentenceTransformer(MODEL_CONFIG["embedding_model"])
-        self.llm = pipeline("text-generation", model=MODEL_CONFIG["llm"])
-        self.index = None
-        self.documents = []
-        
-    def build_index(self, chunks: List[str]):
-        """Create FAISS index from document chunks"""
-        self.documents = chunks
-        embeddings = self.embedder.encode(chunks, show_progress_bar=True)
-        self.index = faiss.IndexFlatIP(embeddings.shape[1])
-        self.index.add(embeddings)
-        
-    def retrieve(self, query: str, k: int = 3) -> List[str]:
-        """Retrieve relevant document chunks"""
-        query_embedding = self.embedder.encode([query])
-        distances, indices = self.index.search(query_embedding, k)
-        return [self.documents[i] for i in indices[0]]
-    
-    def generate_answer(self, question: str, context: List[str]) -> str:
-        """Generate answer using LLM with retrieved context"""
-        prompt = f"""استخدم المعلومات التالية للإجابة على السؤال:
-        
-        السياق:
-        {'\n'.join(context)}
-        
-        السؤال: {question}
-        الإجابة:"""
-        
-        result = self.llm(
-            prompt,
-            max_new_tokens=256,
-            temperature=0.7,
-            do_sample=True
-        )
-        return result[0]["generated_text"].replace(prompt, "")