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Functions463 in github.com/circlemind-ai/fast-graphrag

⨍ Functions 463◇ Types & classes 132↳ Endpoints 50
↓ 17 callersMethodencode
Get the embedding representation of the input text. Args: texts (str): The input text to embed. model (str): The name of the mode
fast_graphrag/_llm/_base.py:134
↓ 17 callersMethodget_load_path
(self)
fast_graphrag/_storage/_namespace.py:54
↓ 15 callersMethod_insert_start
Prepare the storage for inserting.
fast_graphrag/_storage/_base.py:91
↓ 14 callersMethodget
(self)
fast_graphrag/_storage/_base.py:117
↓ 11 callersMethod_query_start
Prepare the storage for querying.
fast_graphrag/_storage/_base.py:100
↓ 9 callersFunctiondump_to_csv
( data: Iterable[object], fields: List[str], separator: str = "\t", with_header: bool = False,
fast_graphrag/_models.py:43
↓ 9 callersFunctionextract_sorted_scores
Take a sparse row vector and return a list of non-zero (index, score) pairs sorted by score.
fast_graphrag/_utils.py:67
↓ 8 callersFunctionformat_and_send_prompt
Get a prompt, format it with the supplied args, and send it to the LLM. If a system prompt is provided (i.e. PROMPTS contains a key named '{promp
fast_graphrag/_llm/_base.py:18
↓ 8 callersFunctionget_event_loop
()
fast_graphrag/_utils.py:56
↓ 8 callersMethodget_save_path
(self)
fast_graphrag/_storage/_namespace.py:61
↓ 8 callersMethodset_in_progress
(self, in_progress: bool)
fast_graphrag/_storage/_base.py:32
↓ 8 callersMethodwith_checkpoints
(self, fn: Callable[[], Any])
fast_graphrag/_storage/_namespace.py:89
↓ 7 callersFunctioncsr_from_indices_list
Create a CSR matrix from a list of lists.
fast_graphrag/_utils.py:95
↓ 7 callersMethodmake_for
(self, namespace: str)
fast_graphrag/_storage/_namespace.py:51
↓ 6 callersMethod_insert_done
Commit the storage operations after inserting.
fast_graphrag/_storage/_base.py:95
↓ 6 callersMethodencode
(self, texts: list[str], model: Optional[str] = None)
fast_graphrag/_llm/_llm_openai.py:190
↓ 6 callersMethodget_node
(self, node: Union[GTNode, GTId])
fast_graphrag/_storage/_base.py:211
↓ 6 callersMethodsend_message
Send a message to the language model and receive a response. Args: prompt (str): The input message to send to the language model.
fast_graphrag/_llm/_llm_openai.py:87
↓ 6 callersMethodto_dataclass
(pydantic: "TGraph.Model")
fast_graphrag/_types.py:242
↓ 5 callersFunctiondump_to_reference_list
(data: Iterable[object], separator: str = "\n=====\n\n")
fast_graphrag/_models.py:67
↓ 5 callersMethodextract
Extract unique chunks from the given data.
fast_graphrag/_services/_base.py:36
↓ 5 callersMethodinsert
( self, content: Union[str, List[str]], metadata: Union[List[Optional[Dict[str, Any]]]
fast_graphrag/_graphrag.py:69
↓ 5 callersMethodquery_start
Load the storage for querying.
benchmarks/vdb_benchmark.py:73
↓ 5 callersMethodsend_message
Send a message to the language model and receive a response. Args: prompt (str): The input message to send to the language model.
fast_graphrag/_llm/_base.py:93
↓ 5 callersMethodto_dict
( cls, obj: Optional["TSerializable"] = None, objs: Optional[Iterable["TSerializable"]] = None,
fast_graphrag/_types.py:22
↓ 5 callersMethodupsert
Add or update embeddings in the storage.
benchmarks/vdb_benchmark.py:58
↓ 4 callersMethodasync_query
Query the graph with a given input. Args: query (str): The query string to search for in the graph. params (QueryPara
fast_graphrag/_graphrag.py:160
↓ 4 callersMethodedge_count
(self)
fast_graphrag/_storage/_base.py:208
↓ 4 callersMethodget_knn
( self, embeddings: Iterable[GTEmbedding], top_k: int )
fast_graphrag/_storage/_base.py:172
↓ 4 callersMethodinsert_edges
( self, edges: Optional[Iterable[GTEdge]] = None, indices: Optional[Iterable[Tuple[TIn
fast_graphrag/_storage/_base.py:239
↓ 4 callersMethodinsert_start
Prepare the storage for inserting.
benchmarks/vdb_benchmark.py:99
↓ 4 callersMethodquery_done
Finish querying the storage.
benchmarks/vdb_benchmark.py:88
↓ 4 callersMethodsize
(self)
fast_graphrag/_storage/_base.py:169
↓ 4 callersMethodupsert_node
(self, node: GTNode, node_index: Union[TIndex, None])
fast_graphrag/_storage/_base.py:233
↓ 3 callersMethod_query_done
Release the storage after querying.
fast_graphrag/_storage/_base.py:104
↓ 3 callersMethodasync_insert
Insert a new memory or memories into the graph. Args: content (str | list[str]): The data to be inserted. Can be a single string
fast_graphrag/_graphrag.py:78
↓ 3 callersMethodget
(self, keys: Iterable[GTKey])
fast_graphrag/_storage/_ikv_pickle.py:26
↓ 3 callersMethodget_edge_by_index
(self, index: TIndex)
fast_graphrag/_storage/_base.py:230
↓ 3 callersMethodget_entities_to_relationships_map
(self)
fast_graphrag/_storage/_base.py:253
↓ 3 callersMethodget_node_by_index
(self, index: TIndex)
fast_graphrag/_storage/_base.py:227
↓ 3 callersMethodget_relationships_attrs
(self, key: str)
fast_graphrag/_storage/_base.py:259
↓ 3 callersMethodinsert_done
Finish inserting into the storage.
benchmarks/vdb_benchmark.py:114
↓ 3 callersMethodnode_count
(self)
fast_graphrag/_storage/_base.py:205
↓ 3 callersMethodscore_all
Score all embeddings against the given queries. Return a (#queries, #all_embeddings) matrix containing the relevancy scores of each embedding
fast_graphrag/_storage/_base.py:185
↓ 3 callersMethodscore_nodes
Score nodes based on the initial weights.
fast_graphrag/_storage/_base.py:262
↓ 3 callersMethodset
(self, blob: GTBlob)
fast_graphrag/_storage/_base.py:120
↓ 2 callersMethod__init__
(self, message: str = "Invalid storage operation")
fast_graphrag/_exceptions.py:4
↓ 2 callersFunction_execute_with_inner_retries
Executes an asynchronous operation with a specified number of inner retry attempts. Args: operation: An async callable representing the API c
fast_graphrag/_llm/_llm_genai.py:65
↓ 2 callersMethod_extract_chunks
(self, data: TDocument)
fast_graphrag/_services/_chunk_extraction.py:63
↓ 2 callersMethod_score_entities_by_vectordb
( self, query_embeddings: Iterable[TEmbedding], top_k: int = 1, threshold: Optional[float] = None
fast_graphrag/_services/_state_manager.py:266
↓ 2 callersMethod_upsert_edge
( self, llm: BaseLLMService, target: BaseGraphStorage[GTNode, TRelation, TId],
fast_graphrag/_policies/_graph_upsert.py:227
↓ 2 callersMethoddelete_edges_by_index
(self, indices: Iterable[TIndex])
fast_graphrag/_storage/_base.py:250
↓ 2 callersMethodextract_entities_from_query
Extract entities from the given query.
fast_graphrag/_services/_base.py:58
↓ 2 callersMethodget_by_index
(self, indices: Iterable[TIndex])
fast_graphrag/_storage/_base.py:137
↓ 2 callersMethodget_edges
( self, source_node: Union[GTId, TIndex], target_node: Union[GTId, TIndex] )
fast_graphrag/_storage/_base.py:217
↓ 2 callersMethodget_index
(self, keys: Iterable[GTKey])
fast_graphrag/_storage/_base.py:140
↓ 2 callersMethodget_path
(working_dir: str, checkpoint: Optional[int] = None)
fast_graphrag/_storage/_namespace.py:16
↓ 2 callersMethodmask_new
(self, keys: Iterable[GTKey])
fast_graphrag/_storage/_base.py:155
↓ 2 callersMethodnew
(working_dir: str, checkpoint: int = 0, keep_n: int = 0)
fast_graphrag/_storage/_namespace.py:12
↓ 2 callersMethodquery_done
(self)
fast_graphrag/_storage/_base.py:81
↓ 2 callersMethodquery_start
(self)
fast_graphrag/_storage/_base.py:53
↓ 2 callersMethodto_attrs
(edge: Optional[Any] = None, edges: Optional[Iterable[Any]] = None, **kwargs: Any)
fast_graphrag/_types.py:68
↓ 2 callersMethodtruncate
Genearate a tabular representation of the context. Truncate the tables to the maximum number of assigned tokens.
fast_graphrag/_types.py:258
↓ 2 callersMethodupsert_edge
(self, edge: GTEdge, edge_index: Union[TIndex, None])
fast_graphrag/_storage/_base.py:236
↓ 1 callersMethod_count_tokens
(self, messages: List[dict[str, str]])
examples/gemini_vertexai_llm.py:169
↓ 1 callersMethod_embedding_request
Get embeddings for a batch of texts. Args: input_texts (List[str]): Batch of texts to embed model (str): Model name
examples/gemini_vertexai_llm.py:114
↓ 1 callersMethod_embedding_request
(self, input: List[str], model: str)
fast_graphrag/_llm/_llm_voyage.py:78
↓ 1 callersMethod_embedding_request
(self, input: List[str], model: str)
fast_graphrag/_llm/_llm_openai.py:226
↓ 1 callersMethod_embedding_request
Makes an embedding request for a batch of input texts. Applies internal retry logic and rate limiting to ensure a valid response is obtained.
fast_graphrag/_llm/_llm_genai.py:411
↓ 1 callersMethod_enforce_overlap
(self, chunks: List[List[Tuple[str, int]]])
fast_graphrag/_services/_chunk_extraction.py:121
↓ 1 callersMethod_extract
Extract both entities and relationships from the given chunks.
fast_graphrag/_services/_information_extraction.py:58
↓ 1 callersMethod_extract_from_chunk
Extract entities and relationships from the given chunk.
fast_graphrag/_services/_information_extraction.py:121
↓ 1 callersMethod_extract_retry_time
(self, error_message: str)
examples/gemini_vertexai_llm.py:162
↓ 1 callersMethod_get_edge_indices
( self, source_node: Union[GTId, TIndex], target_node: Union[GTId, TIndex] )
fast_graphrag/_storage/_base.py:222
↓ 1 callersMethod_get_edge_indices
( self, source_node: Union[GTId, TIndex], target_node: Union[GTId, TIndex] )
fast_graphrag/_storage/_gdb_igraph.py:70
↓ 1 callersMethod_get_entities_to_num_docs
(self)
fast_graphrag/_services/_state_manager.py:263
↓ 1 callersMethod_gleaning
Do gleaning steps until the llm says we are done or we reach the max gleaning steps.
fast_graphrag/_services/_information_extraction.py:76
↓ 1 callersMethod_merge
Merge the given graphs into a single graph storage.
fast_graphrag/_services/_information_extraction.py:150
↓ 1 callersMethod_merge_similar_edges
Merge similar edges between the same pair of nodes. Args: llm (BaseLLMService): The language model that is called to determine th
fast_graphrag/_policies/_graph_upsert.py:249
↓ 1 callersMethod_merge_splits
(self, splits: List[str])
fast_graphrag/_services/_chunk_extraction.py:88
↓ 1 callersFunction_query_task
(query: Query)
benchmarks/graph_benchmark.py:114
↓ 1 callersFunction_query_task
(query: Query, mode: str)
benchmarks/nano_benchmark.py:114
↓ 1 callersFunction_query_task
(query: Query, mode: str)
benchmarks/lightrag_benchmark.py:116
↓ 1 callersFunction_query_task
(query: Query)
benchmarks/vdb_benchmark.py:273
↓ 1 callersMethod_rollback
(self)
fast_graphrag/_storage/_namespace.py:75
↓ 1 callersFunction_run
()
benchmarks/graph_benchmark.py:128
↓ 1 callersFunction_run
(mode: str)
benchmarks/nano_benchmark.py:133
↓ 1 callersFunction_run
(mode: str)
benchmarks/lightrag_benchmark.py:133
↓ 1 callersFunction_run_benchmark
()
benchmarks/vdb_benchmark.py:276
↓ 1 callersFunction_run_create
()
benchmarks/vdb_benchmark.py:265
↓ 1 callersMethod_score_chunks_by_relations
(self, relationships_score: csr_matrix)
fast_graphrag/_services/_state_manager.py:304
↓ 1 callersMethod_score_entities_by_graph
(self, entity_scores: Optional[csr_matrix])
fast_graphrag/_services/_state_manager.py:291
↓ 1 callersMethod_score_relationships_by_entities
(self, entity_scores: csr_matrix)
fast_graphrag/_services/_state_manager.py:296
↓ 1 callersMethod_split_text
(self, text: str)
fast_graphrag/_services/_chunk_extraction.py:85
↓ 1 callersMethodare_neighbours
(self, source_node: Union[GTId, TIndex], target_node: Union[GTId, TIndex])
fast_graphrag/_storage/_base.py:247
↓ 1 callersMethodask_query
Ask a query to the LLM.
benchmarks/vdb_benchmark.py:153
↓ 1 callersMethodcount_tokens
Returns the number of tokens for a given text using the encoding appropriate for the model.
fast_graphrag/_llm/_base.py:80
↓ 1 callersMethoddelete
(self, keys: Iterable[GTKey])
fast_graphrag/_storage/_base.py:149
↓ 1 callersFunctiondump_to_reference_list
Convert list of chunks to a string.
benchmarks/vdb_benchmark.py:39
↓ 1 callersMethodedge_count
(self)
fast_graphrag/_storage/_gdb_igraph.py:43
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