yangdx
commited on
Commit
·
d0221a9
1
Parent(s):
78289f5
Fix doc_status error
Browse files- lightrag/lightrag.py +24 -28
lightrag/lightrag.py
CHANGED
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@@ -408,17 +408,8 @@ class LightRAG:
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self.graph_storage_cls, global_config=global_config
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)
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embedding_func=None,
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)
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self.llm_response_cache = self.key_string_value_json_storage_cls(
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namespace=make_namespace(
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self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
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),
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embedding_func=self.embedding_func,
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)
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# Check if Oracle storage implementation is used
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if (
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@@ -528,7 +519,7 @@ class LightRAG:
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self.kv_storage == "PGKVStorage"
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or self.vector_storage == "PGVectorStorage"
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or self.graph_storage == "PGGraphStorage"
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or self.
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):
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# Read configuration file
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config_parser = configparser.ConfigParser()
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@@ -578,12 +569,16 @@ class LightRAG:
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self.vector_db_storage_cls.db = postgres_db
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if self.graph_storage == "PGGraphStorage":
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self.graph_storage_cls.db = postgres_db
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if self.
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self.
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####
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# Add embedding function by walter
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####
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self.full_docs: BaseKVStorage = self.key_string_value_json_storage_cls(
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namespace=make_namespace(
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self.namespace_prefix, NameSpace.KV_STORE_FULL_DOCS
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@@ -602,9 +597,6 @@ class LightRAG:
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),
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embedding_func=self.embedding_func,
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)
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####
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# End of adding embedding function by walter
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####
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self.entities_vdb = self.vector_db_storage_cls(
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namespace=make_namespace(
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@@ -627,6 +619,7 @@ class LightRAG:
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embedding_func=self.embedding_func,
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)
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if self.llm_response_cache and hasattr(
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self.llm_response_cache, "global_config"
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):
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@@ -639,6 +632,17 @@ class LightRAG:
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embedding_func=self.embedding_func,
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)
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self.llm_model_func = limit_async_func_call(self.llm_model_max_async)(
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partial(
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self.llm_model_func,
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@@ -647,14 +651,6 @@ class LightRAG:
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)
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)
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# Initialize document status storage
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self.doc_status_storage_cls = self._get_storage_class(self.doc_status_storage)
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self.doc_status: DocStatusStorage = self.doc_status_storage_cls(
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namespace=make_namespace(self.namespace_prefix, NameSpace.DOC_STATUS),
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global_config=global_config,
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embedding_func=None,
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)
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async def get_graph_labels(self):
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text = await self.chunk_entity_relation_graph.get_all_labels()
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return text
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self.graph_storage_cls, global_config=global_config
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)
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+
# Initialize document status storage
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self.doc_status_storage_cls = self._get_storage_class(self.doc_status_storage)
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# Check if Oracle storage implementation is used
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if (
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self.kv_storage == "PGKVStorage"
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or self.vector_storage == "PGVectorStorage"
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or self.graph_storage == "PGGraphStorage"
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or self.doc_status_storage == "PGDocStatusStorage"
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):
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# Read configuration file
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config_parser = configparser.ConfigParser()
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self.vector_db_storage_cls.db = postgres_db
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if self.graph_storage == "PGGraphStorage":
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self.graph_storage_cls.db = postgres_db
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if self.doc_status_storage == "OracleGraphStorage":
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self.doc_status_storage_cls = postgres_db
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self.llm_response_cache = self.key_string_value_json_storage_cls(
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namespace=make_namespace(
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self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
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),
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embedding_func=self.embedding_func,
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)
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self.full_docs: BaseKVStorage = self.key_string_value_json_storage_cls(
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namespace=make_namespace(
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self.namespace_prefix, NameSpace.KV_STORE_FULL_DOCS
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),
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embedding_func=self.embedding_func,
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)
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self.entities_vdb = self.vector_db_storage_cls(
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namespace=make_namespace(
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embedding_func=self.embedding_func,
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)
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# What's for, Is this nessisary ?
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if self.llm_response_cache and hasattr(
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self.llm_response_cache, "global_config"
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):
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embedding_func=self.embedding_func,
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)
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# self.json_doc_status_storage = self.key_string_value_json_storage_cls(
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# namespace=self.namespace_prefix + "json_doc_status_storage",
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# embedding_func=None,
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# )
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self.doc_status: DocStatusStorage = self.doc_status_storage_cls(
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namespace=make_namespace(self.namespace_prefix, NameSpace.DOC_STATUS),
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global_config=global_config,
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embedding_func=None,
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)
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self.llm_model_func = limit_async_func_call(self.llm_model_max_async)(
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partial(
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self.llm_model_func,
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)
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)
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async def get_graph_labels(self):
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text = await self.chunk_entity_relation_graph.get_all_labels()
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return text
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