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syshin0116syshin0116
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fix(examples): use openai_embed.func to prevent double EmbeddingFunc wrapping
openai_embed is an EmbeddingFunc instance (decorated with @wrap_embedding_func_with_attrs). Wrapping it inside a lambda and passing it to another EmbeddingFunc causes double invocation of EmbeddingFunc.__call__, which doubles the returned vector count and raises "Vector count mismatch: expected N vectors but got 2N vectors". Using openai_embed.func accesses the unwrapped async function directly, as documented in lightrag-hku's own codebase. Fixes the root cause of HKUDS/LightRAG#2549.
1 parent 5c53c4c commit d29b81a

5 files changed

Lines changed: 11 additions & 11 deletions

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‎README.md‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -409,7 +409,7 @@ async def main():
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embedding_func = EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,
@@ -485,7 +485,7 @@ async def process_multimodal_content():
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embedding_func=EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,
@@ -711,7 +711,7 @@ async def load_existing_lightrag():
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embedding_func=EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,
@@ -874,7 +874,7 @@ async def insert_content_list_example():
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embedding_func = EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,

‎README_zh.md‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -389,7 +389,7 @@ async def main():
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embedding_func = EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,
@@ -467,7 +467,7 @@ async def process_multimodal_content():
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embedding_func=EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,
@@ -692,7 +692,7 @@ async def load_existing_lightrag():
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embedding_func=EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,
@@ -855,7 +855,7 @@ async def insert_content_list_example():
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embedding_func = EmbeddingFunc(
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embedding_dim=3072,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model="text-embedding-3-large",
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api_key=api_key,

‎examples/insert_content_list_example.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -252,7 +252,7 @@ def vision_model_func(
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embedding_func = EmbeddingFunc(
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embedding_dim=embedding_dim,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model=embedding_model,
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api_key=api_key,

‎examples/modalprocessors_example.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -175,7 +175,7 @@ async def initialize_rag(api_key: str, base_url: str = None):
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embedding_func=EmbeddingFunc(
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embedding_dim=embedding_dim,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model=embedding_model,
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api_key=api_key,

‎examples/raganything_example.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -189,7 +189,7 @@ def vision_model_func(
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embedding_func = EmbeddingFunc(
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embedding_dim=embedding_dim,
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max_token_size=8192,
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func=lambda texts: openai_embed(
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func=lambda texts: openai_embed.func(
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texts,
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model=embedding_model,
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api_key=api_key,

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