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configs/rerankers/llm.py

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+from typing import Optional
+from pydantic import Field
+
+from mem0.configs.rerankers.base import BaseRerankerConfig
+
+
+class LLMRerankerConfig(BaseRerankerConfig):
+    """
+    Configuration for LLM-based reranker.
+    
+    Attributes:
+        model (str): LLM model to use for reranking. Defaults to "gpt-4o-mini".
+        api_key (str): API key for the LLM provider.
+        provider (str): LLM provider. Defaults to "openai".
+        top_k (int): Number of top documents to return after reranking.
+        temperature (float): Temperature for LLM generation. Defaults to 0.0 for deterministic scoring.
+        max_tokens (int): Maximum tokens for LLM response. Defaults to 100.
+        scoring_prompt (str): Custom prompt template for scoring documents.
+    """
+    
+    model: str = Field(
+        default="gpt-4o-mini",
+        description="LLM model to use for reranking"
+    )
+    api_key: Optional[str] = Field(
+        default=None,
+        description="API key for the LLM provider"
+    )
+    provider: str = Field(
+        default="openai",
+        description="LLM provider (openai, anthropic, etc.)"
+    )
+    top_k: Optional[int] = Field(
+        default=None,
+        description="Number of top documents to return after reranking"
+    )
+    temperature: float = Field(
+        default=0.0,
+        description="Temperature for LLM generation"
+    )
+    max_tokens: int = Field(
+        default=100,
+        description="Maximum tokens for LLM response"
+    )
+    scoring_prompt: Optional[str] = Field(
+        default=None,
+        description="Custom prompt template for scoring documents"
+    )