Merge remote-tracking branch 'origin/geo' into geo

src/server/rerank.py

+
 from __future__ import annotations
+import threading
 from typing import Dict, Optional, Sequence
+
 from langchain_core.documents import Document
 from langchain.pydantic_v1 import Extra, root_validator
-
 from langchain.callbacks.manager import Callbacks
 from langchain.retrievers.document_compressors.base import BaseDocumentCompressor
 
@@ -13,12 +15,18 @@ class BgeRerank(BaseDocumentCompressor):
     """Model name to use for reranking."""    
     top_n: int = 10   
     """Number of documents to return."""
-    model:CrossEncoder = None
+    _model:CrossEncoder = None
     """CrossEncoder instance to use for reranking."""
+    _lock = threading.Lock()
+    """Lock to ensure thread safety."""
 
     def __init__(self, model_name: str, top_n: int = 10):
         super().__init__(model_name=model_name, top_n=top_n)
-        self.model = CrossEncoder(model_name)
+        if not BgeRerank._model:
+            with BgeRerank._lock:
+                if not BgeRerank._model:
+                    BgeRerank._model = CrossEncoder(model_name)
+        self.model = BgeRerank._model
 
     def bge_rerank(self,query,docs):
         model_inputs =  [[query, doc] for doc in docs]
@@ -30,7 +38,7 @@ class BgeRerank(BaseDocumentCompressor):
     class Config:
         """Configuration for this pydantic object."""
 
-        extra = Extra.forbid
+        extra = Extra.allow
         arbitrary_types_allowed = True
 
     def compress_documents(
@@ -61,3 +69,16 @@ class BgeRerank(BaseDocumentCompressor):
             doc.metadata["relevance_score"] = r[1]
             final_results.append(doc)
         return final_results
+    
+from abc import ABC
+import numpy as np
+
+def sigmoid(x):
+    return 1 / (1 + np.exp(-x))
+
+class Base(ABC):
+    def __init__(self, key, model_name):
+        pass
+
+    def similarity(self, query: str, texts: list):
+        raise NotImplementedError("Please implement encode method!")
\ No newline at end of file