Update rag/config.py

rag/config.py

@@ -1,44 +1,23 @@
 from dataclasses import dataclass
-from pathlib import Path
 
 @dataclass(frozen=True)
 class Settings:
-    # Data
-    dataset_path: str = "data/dataset.json"
-    index_dir: str = "data/index"
-
-    # Router (GLiNER)
+    # Router
     router_model_id: str = "urchade/gliner_small-v2.1"
-    router_threshold: float = 0.35  # soft threshold
+    router_threshold: float = 0.3
     router_labels: tuple = ("Company", "Stock Ticker")
 
-    # Retrieval model
+    # Embedding
     embed_model_id: str = "Alibaba-NLP/gte-Qwen2-7B-instruct"
-    embed_max_len: int = 2048
-    embed_batch_size: int = 1
+    embed_max_length: int = 8192
+    embed_top_k: int = 15
 
-    # Reranker model
+    # Reranker
     rerank_model_id: str = "BAAI/bge-reranker-v2-m3"
-    rerank_max_len: int = 512
-
-    # Candidate sizes
-    top_k_retrieval: int = 15
-    top_k_rerank: int = 4
-    top_k_images: int = 3
+    rerank_max_length: int = 8192
+    rerank_top_k: int = 4
 
-    # Generation model
+    # Vision
     gen_model_id: str = "Qwen/Qwen2-VL-2B-Instruct"
     max_new_tokens: int = 512
-
-    # UX / Guardrails
-    scope_companies: tuple = ("Apple", "Microsoft")
-    enforce_not_found: bool = True
-
-    def index_path(self) -> Path:
-        return Path(self.index_dir)
-
-    def doc_embeds_file(self) -> Path:
-        return self.index_path() / "doc_embeds.pt"
-
-    def doc_meta_file(self) -> Path:
-        return self.index_path() / "doc_meta.json"
+    top_k_images: int = 4  # dans ton code: tu prends 4 puis tu affiches ce que tu as; on garde