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fix annotation query exception (#1771)

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Co-authored-by: jyong <jyong@dify.ai>
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Jyong 2023-12-18 16:48:34 +08:00 committed by GitHub
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1 changed files with 59 additions and 55 deletions
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114
api/core/completion.py
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@ -341,66 +341,70 @@ class Completion:
app = conversation_message_task.app
annotation_reply = app_model_config.annotation_reply_dict
if annotation_reply['enabled']:
score_threshold = annotation_reply.get('score_threshold', 1)
embedding_provider_name = annotation_reply['embedding_model']['embedding_provider_name']
embedding_model_name = annotation_reply['embedding_model']['embedding_model_name']
# get embedding model
embedding_model = ModelFactory.get_embedding_model(
tenant_id=app.tenant_id,
model_provider_name=embedding_provider_name,
model_name=embedding_model_name
)
embeddings = CacheEmbedding(embedding_model)
try:
score_threshold = annotation_reply.get('score_threshold', 1)
embedding_provider_name = annotation_reply['embedding_model']['embedding_provider_name']
embedding_model_name = annotation_reply['embedding_model']['embedding_model_name']
# get embedding model
embedding_model = ModelFactory.get_embedding_model(
tenant_id=app.tenant_id,
model_provider_name=embedding_provider_name,
model_name=embedding_model_name
)
embeddings = CacheEmbedding(embedding_model)
dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding(
embedding_provider_name,
embedding_model_name,
'annotation'
)
dataset_collection_binding = DatasetCollectionBindingService.get_dataset_collection_binding(
embedding_provider_name,
embedding_model_name,
'annotation'
)
dataset = Dataset(
id=app.id,
tenant_id=app.tenant_id,
indexing_technique='high_quality',
embedding_model_provider=embedding_provider_name,
embedding_model=embedding_model_name,
collection_binding_id=dataset_collection_binding.id
)
dataset = Dataset(
id=app.id,
tenant_id=app.tenant_id,
indexing_technique='high_quality',
embedding_model_provider=embedding_provider_name,
embedding_model=embedding_model_name,
collection_binding_id=dataset_collection_binding.id
)
vector_index = VectorIndex(
dataset=dataset,
config=current_app.config,
embeddings=embeddings
)
vector_index = VectorIndex(
dataset=dataset,
config=current_app.config,
embeddings=embeddings
)
documents = vector_index.search(
conversation_message_task.query,
search_type='similarity_score_threshold',
search_kwargs={
'k': 1,
'score_threshold': score_threshold,
'filter': {
'group_id': [dataset.id]
documents = vector_index.search(
conversation_message_task.query,
search_type='similarity_score_threshold',
search_kwargs={
'k': 1,
'score_threshold': score_threshold,
'filter': {
'group_id': [dataset.id]
}
}
}
)
if documents:
annotation_id = documents[0].metadata['annotation_id']
score = documents[0].metadata['score']
annotation = AppAnnotationService.get_annotation_by_id(annotation_id)
if annotation:
conversation_message_task.annotation_end(annotation.content, annotation.id, annotation.account.name)
# insert annotation history
AppAnnotationService.add_annotation_history(annotation.id,
app.id,
annotation.question,
annotation.content,
conversation_message_task.query,
conversation_message_task.user.id,
conversation_message_task.message.id,
from_source,
score)
return True
)
if documents:
annotation_id = documents[0].metadata['annotation_id']
score = documents[0].metadata['score']
annotation = AppAnnotationService.get_annotation_by_id(annotation_id)
if annotation:
conversation_message_task.annotation_end(annotation.content, annotation.id, annotation.account.name)
# insert annotation history
AppAnnotationService.add_annotation_history(annotation.id,
app.id,
annotation.question,
annotation.content,
conversation_message_task.query,
conversation_message_task.user.id,
conversation_message_task.message.id,
from_source,
score)
return True
except Exception as e:
logging.warning(f'Query annotation failed, exception: {str(e)}.')
return False
return False
@classmethod