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refactor(api): continue decoupling dify_graph from API concerns (#33580)

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Signed-off-by: -LAN- <laipz8200@outlook.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: WH-2099 <wh2099@pm.me>
This commit is contained in:
-LAN-
2026-03-25 20:32:24 +08:00
committed by GitHub
parent b7b9b003c9
commit 56593f20b0
487 changed files with 17999 additions and 9186 deletions
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10
api/core/rag/embedding/cached_embedding.py
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@ -21,9 +21,8 @@ logger = logging.getLogger(__name__)
class CacheEmbedding(Embeddings):
def __init__(self, model_instance: ModelInstance, user: str | None = None):
def __init__(self, model_instance: ModelInstance):
self._model_instance = model_instance
self._user = user
def embed_documents(self, texts: list[str]) -> list[list[float]]:
"""Embed search docs in batches of 10."""
@ -65,7 +64,7 @@ class CacheEmbedding(Embeddings):
batch_texts = embedding_queue_texts[i : i + max_chunks]
embedding_result = self._model_instance.invoke_text_embedding(
texts=batch_texts, user=self._user, input_type=EmbeddingInputType.DOCUMENT
texts=batch_texts, input_type=EmbeddingInputType.DOCUMENT
)
for vector in embedding_result.embeddings:
@ -147,7 +146,6 @@ class CacheEmbedding(Embeddings):
embedding_result = self._model_instance.invoke_multimodal_embedding(
multimodel_documents=batch_multimodel_documents,
user=self._user,
input_type=EmbeddingInputType.DOCUMENT,
)
@ -202,7 +200,7 @@ class CacheEmbedding(Embeddings):
return [float(x) for x in decoded_embedding]
try:
embedding_result = self._model_instance.invoke_text_embedding(
texts=[text], user=self._user, input_type=EmbeddingInputType.QUERY
texts=[text], input_type=EmbeddingInputType.QUERY
)
embedding_results = embedding_result.embeddings[0]
@ -245,7 +243,7 @@ class CacheEmbedding(Embeddings):
return [float(x) for x in decoded_embedding]
try:
embedding_result = self._model_instance.invoke_multimodal_embedding(
multimodel_documents=[multimodel_document], user=self._user, input_type=EmbeddingInputType.QUERY
multimodel_documents=[multimodel_document], input_type=EmbeddingInputType.QUERY
)
embedding_results = embedding_result.embeddings[0]