wehub-resource-sync
44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
from pydantic import BaseModel
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class IndexUpdate(BaseModel):
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base_index_name: str
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base_endpoint_name: str
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qa_index_name: str | None
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qa_endpoint_name: str | None
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firestore_db_name: str | None
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firestore_namespace: str | None
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class PromptUpdate(BaseModel):
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prompt_name: str
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new_content: str
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class RAGConfig(BaseModel):
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llm_name: str = "gemini-2.0-flash"
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temperature: float = 0.2
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similarity_top_k: int = 5
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retrieval_strategy: str = "auto_merging"
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use_hyde: bool = True
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use_refine: bool = True
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use_node_rerank: bool = True
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use_react: bool = True
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qa_followup: bool = True
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hybrid_retrieval: bool = True
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class RAGRequest(RAGConfig):
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query: str = "What were Google's Q1 Earnings?"
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evaluate_response: bool
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eval_model_name: str | None = "gemini-2.0-flash"
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embedding_model_name: str | None = "text-embedding-005"
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class EvalRequest(RAGConfig):
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eval_model_name: str = "gemini-2.0-flash"
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embedding_model_name: str | None = "text-embedding-005"
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input_eval_dataset_bucket_uri: str = "test_rag_questions/test_ground_truth.csv"
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bq_eval_results_table_id: str = "eval_results.eval_results_table"
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ragas_metrics: list[str] = ["faithfulness", "answer_relevancy"]
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