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Hotfix/fix documents index mismatch error in rerank (#1662)

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Co-authored-by: baomi.wbm <baomi.wbm@dtwave-inc.com>
This commit is contained in:
WangBooth 2023-11-30 22:03:20 +08:00 committed by GitHub
parent 0423775687
commit 22bc9ddc73
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2 changed files with 14 additions and 6 deletions
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15
api/core/model_providers/models/reranking/cohere_reranking.py
View File

@ -1,14 +1,15 @@
import logging
from typing import Optional, List
from typing import List, Optional
import cohere
import openai
from langchain.schema import Document
from core.model_providers.error import LLMBadRequestError, LLMAPIConnectionError, LLMAPIUnavailableError, \
LLMRateLimitError, LLMAuthorizationError
from core.model_providers.error import (LLMAPIConnectionError,
LLMAPIUnavailableError,
LLMAuthorizationError,
LLMBadRequestError, LLMRateLimitError)
from core.model_providers.models.reranking.base import BaseReranking
from core.model_providers.providers.base import BaseModelProvider
from langchain.schema import Document
class CohereReranking(BaseReranking):
@ -26,10 +27,14 @@ class CohereReranking(BaseReranking):
def rerank(self, query: str, documents: List[Document], score_threshold: Optional[float], top_k: Optional[int]) -> Optional[List[Document]]:
docs = []
doc_id = []
unique_documents = []
for document in documents:
if document.metadata['doc_id'] not in doc_id:
doc_id.append(document.metadata['doc_id'])
docs.append(document.page_content)
unique_documents.append(document)
documents = unique_documents
results = self.client.rerank(query=query, documents=docs, model=self.name, top_n=top_k)
rerank_documents = []

5
api/core/model_providers/models/reranking/xinference_reranking.py
View File

@ -23,11 +23,14 @@ class XinferenceReranking(BaseReranking):
def rerank(self, query: str, documents: List[Document], score_threshold: Optional[float], top_k: Optional[int]) -> Optional[List[Document]]:
docs = []
doc_id = []
unique_documents = []
for document in documents:
if document.metadata['doc_id'] not in doc_id:
doc_id.append(document.metadata['doc_id'])
docs.append(document.page_content)
unique_documents.append(document)
documents = unique_documents
model = self.client.get_model(self.credentials['model_uid'])
response = model.rerank(query=query, documents=docs, top_n=top_k)
rerank_documents = []