youngkingdom/dify
1
0
Fork 0
mirror of https://github.com/langgenius/dify.git synced 2026-05-04 01:18:05 +08:00
Code Issues Packages Projects Releases Wiki Activity

refactor(workflow): inject credential/model access ports into LLM nodes (#32569)

Browse Source 
Signed-off-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
-LAN-
2026-02-27 14:36:41 +08:00
committed by GitHub
parent d20880d102
commit a694533fc9
38 changed files with 676 additions and 179 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
api/core/rag/embedding/cached_embedding.py
View File

@ -35,7 +35,9 @@ class CacheEmbedding(Embeddings):
embedding = (
db.session.query(Embedding)
.filter_by(
model_name=self._model_instance.model, hash=hash, provider_name=self._model_instance.provider
model_name=self._model_instance.model_name,
hash=hash,
provider_name=self._model_instance.provider,
)
.first()
)
@ -52,7 +54,7 @@ class CacheEmbedding(Embeddings):
try:
model_type_instance = cast(TextEmbeddingModel, self._model_instance.model_type_instance)
model_schema = model_type_instance.get_model_schema(
self._model_instance.model, self._model_instance.credentials
self._model_instance.model_name, self._model_instance.credentials
)
max_chunks = (
model_schema.model_properties[ModelPropertyKey.MAX_CHUNKS]
@ -87,7 +89,7 @@ class CacheEmbedding(Embeddings):
hash = helper.generate_text_hash(texts[i])
if hash not in cache_embeddings:
embedding_cache = Embedding(
model_name=self._model_instance.model,
model_name=self._model_instance.model_name,
hash=hash,
provider_name=self._model_instance.provider,
embedding=pickle.dumps(n_embedding, protocol=pickle.HIGHEST_PROTOCOL),
@ -114,7 +116,9 @@ class CacheEmbedding(Embeddings):
embedding = (
db.session.query(Embedding)
.filter_by(
model_name=self._model_instance.model, hash=file_id, provider_name=self._model_instance.provider
model_name=self._model_instance.model_name,
hash=file_id,
provider_name=self._model_instance.provider,
)
.first()
)
@ -131,7 +135,7 @@ class CacheEmbedding(Embeddings):
try:
model_type_instance = cast(TextEmbeddingModel, self._model_instance.model_type_instance)
model_schema = model_type_instance.get_model_schema(
self._model_instance.model, self._model_instance.credentials
self._model_instance.model_name, self._model_instance.credentials
)
max_chunks = (
model_schema.model_properties[ModelPropertyKey.MAX_CHUNKS]
@ -168,7 +172,7 @@ class CacheEmbedding(Embeddings):
file_id = multimodel_documents[i]["file_id"]
if file_id not in cache_embeddings:
embedding_cache = Embedding(
model_name=self._model_instance.model,
model_name=self._model_instance.model_name,
hash=file_id,
provider_name=self._model_instance.provider,
embedding=pickle.dumps(n_embedding, protocol=pickle.HIGHEST_PROTOCOL),
@ -190,7 +194,7 @@ class CacheEmbedding(Embeddings):
"""Embed query text."""
# use doc embedding cache or store if not exists
hash = helper.generate_text_hash(text)
embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model}_{hash}"
embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model_name}_{hash}"
embedding = redis_client.get(embedding_cache_key)
if embedding:
redis_client.expire(embedding_cache_key, 600)
@ -233,7 +237,7 @@ class CacheEmbedding(Embeddings):
"""Embed multimodal documents."""
# use doc embedding cache or store if not exists
file_id = multimodel_document["file_id"]
embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model}_{file_id}"
embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model_name}_{file_id}"
embedding = redis_client.get(embedding_cache_key)
if embedding:
redis_client.expire(embedding_cache_key, 600)