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YangQianli92 2024-04-18 11:42:20 +08:00 • committed by GitHub
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12
examples/rag_bm.py
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@ -15,7 +15,7 @@ from metagpt.rag.schema import (
BM25RetrieverConfig,
FAISSIndexConfig,
FAISSRetrieverConfig,
FlagEmbeddingConfig,
BGERerankConfig,
LLMRankerConfig,
CohereRerankConfig,
ColbertRerankConfig,
@ -54,8 +54,8 @@ class RAGExample:
if "all" in dataset_name or dataset.name in dataset_name:
output_dir = DATA_PATH / f"{dataset.name}"
if os.path.exists(output_dir):
logger.info("Loading Exists index!")
if output_dir.exists():
logger.info("Loading Existed index!")
logger.info(f"Index Path:{output_dir}")
self.engine = SimpleEngine.from_index(
index_config=FAISSIndexConfig(persist_path=output_dir),
@ -63,7 +63,7 @@ class RAGExample:
retriever_configs=[FAISSRetrieverConfig(), BM25RetrieverConfig()],
)
else:
logger.info("Loading index from document!")
logger.info("Loading index from documents!")
self.engine = SimpleEngine.from_docs(
input_files=dataset.document_files,
retriever_configs=[FAISSRetrieverConfig()],
@ -81,7 +81,7 @@ class RAGExample:
logger.info(f"=====The {dataset.name} Benchmark dataset assessment is complete!=====")
self._print_bm_result(results)
write_json_file((EXAMPLE_BENCHMARK_PATH \ dataset.name \ "bm_result.json").as_posix()), results, "utf-8")
write_json_file((EXAMPLE_BENCHMARK_PATH / dataset.name / "bm_result.json").as_posix(), results, "utf-8")
async def rag_evaluate_single(self, question, reference, ground_truth, print_title=True):
"""This example run rag pipeline, use faiss&bm25 retriever and llm ranker, will print something like:
@ -126,7 +126,7 @@ class RAGExample:
except Exception as e:
logger.error(e)
return self.benchmark._set_metrics(
return self.benchmark.set_metrics(
generated_text=LLM_ERROR, ground_truth_text=ground_truth, question=question
)