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enhanced the query engines with max_retries parameter #19

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Merged
pavanjava merged 1 commit into from
Sep 10, 2024
Merged

enhanced the query engines with max_retries parameter #19

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9 changes: 6 additions & 3 deletions bootstraprag/templates/llamaindex/rag_with_self_correction/self_correction_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,8 @@ class SelfCorrectingRAG:
]

def __init__(self, input_dir: str, similarity_top_k: int = 3, chunk_size: int = 128,
chunk_overlap: int = 100, show_progress: bool = False, no_of_retries: int = 5, required_exts: list[str] = ['.pdf', '.txt']):
chunk_overlap: int = 100, show_progress: bool = False, no_of_retries: int = 5,
required_exts: list[str] = ['.pdf', '.txt']):

self.input_dir = input_dir
self.similarity_top_k = similarity_top_k
Expand Down Expand Up @@ -108,7 +109,8 @@ def query_with_retry_query_engine(self, query: str) -> RESPONSE_TYPE:
# source nodes for the query based on llm node evaluation.
def query_with_source_query_engine(self, query: str) -> RESPONSE_TYPE:
retry_source_query_engine = RetrySourceQueryEngine(self.base_query_engine,
self.query_response_evaluator)
self.query_response_evaluator,
max_retries=self.no_of_retries)
retry_source_response = retry_source_query_engine.query(query)
return retry_source_response

Expand All @@ -121,6 +123,7 @@ def query_with_guideline_query_engine(self, query: str) -> RESPONSE_TYPE:
"The response should try to summarize where possible.\n"
) # just for example
retry_guideline_query_engine = RetryGuidelineQueryEngine(self.base_query_engine,
guideline_eval, resynthesize_query=True)
guideline_eval, resynthesize_query=True,
max_retries=self.no_of_retries)
retry_guideline_response = retry_guideline_query_engine.query(query)
return retry_guideline_response
5 changes: 3 additions & 2 deletions .../templates/llamaindex/rag_with_self_correction_with_observability/self_correction_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
from llama_index.llms.ollama import Ollama
from llama_index.embeddings.ollama import OllamaEmbedding
from llama_index.vector_stores.qdrant import QdrantVectorStore
from llama_index. core. base. base_query_engine import BaseQueryEngine
from llama_index.core.base.response.schema import Response, StreamingResponse, AsyncStreamingResponse, PydanticResponse
from llama_index.core.query_engine import RetryQueryEngine, RetrySourceQueryEngine, RetryGuidelineQueryEngine
from llama_index.core.evaluation import RelevancyEvaluator, GuidelineEvaluator
Expand Down Expand Up @@ -68,8 +69,8 @@ def __init__(self, input_dir: str, similarity_top_k: int = 3, chunk_size: int =
api_key=os.environ['DB_API_KEY'])
self.vector_store = QdrantVectorStore(client=self.client, collection_name=os.environ['COLLECTION_NAME'])
self.query_response_evaluator = RelevancyEvaluator()
self.base_query_engine = None
self._index = None
self.base_query_engine: BaseQueryEngine = None
self._index: VectorStoreIndex = None

self._load_data_and_create_engine()

Expand Down