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from collections import Counter | |
import asyncio | |
from tqdm.asyncio import tqdm as tqdm_async | |
from graphgen.utils.format import split_string_by_multi_markers | |
from graphgen.utils import logger, detect_main_language | |
from graphgen.models import TopkTokenModel, Tokenizer | |
from graphgen.models.storage.base_storage import BaseGraphStorage | |
from graphgen.templates import KG_SUMMARIZATION_PROMPT, KG_EXTRACTION_PROMPT | |
async def _handle_kg_summary( | |
entity_or_relation_name: str, | |
description: str, | |
llm_client: TopkTokenModel, | |
tokenizer_instance: Tokenizer, | |
max_summary_tokens: int = 200 | |
) -> str: | |
""" | |
处理实体或关系的描述信息 | |
:param entity_or_relation_name | |
:param description | |
:param llm_client | |
:param tokenizer_instance | |
:param max_summary_tokens | |
:return: new description | |
""" | |
language = detect_main_language(description) | |
if language == "en": | |
language = "English" | |
else: | |
language = "Chinese" | |
KG_EXTRACTION_PROMPT["FORMAT"]["language"] = language | |
tokens = tokenizer_instance.encode_string(description) | |
if len(tokens) < max_summary_tokens: | |
return description | |
use_description = tokenizer_instance.decode_tokens(tokens[:max_summary_tokens]) | |
prompt = KG_SUMMARIZATION_PROMPT[language]["TEMPLATE"].format( | |
entity_name=entity_or_relation_name, | |
description_list=use_description.split('<SEP>'), | |
**KG_SUMMARIZATION_PROMPT["FORMAT"] | |
) | |
new_description = await llm_client.generate_answer(prompt) | |
logger.info("Entity or relation %s summary: %s", entity_or_relation_name, new_description) | |
return new_description | |
async def merge_nodes( | |
nodes_data: dict, | |
kg_instance: BaseGraphStorage, | |
llm_client: TopkTokenModel, | |
tokenizer_instance: Tokenizer, | |
max_concurrent: int = 1000 | |
): | |
""" | |
Merge nodes | |
:param nodes_data | |
:param kg_instance | |
:param llm_client | |
:param tokenizer_instance | |
:param max_concurrent | |
:return | |
""" | |
semaphore = asyncio.Semaphore(max_concurrent) | |
async def process_single_node(entity_name: str, node_data: list[dict]): | |
async with semaphore: | |
entity_types = [] | |
source_ids = [] | |
descriptions = [] | |
node = await kg_instance.get_node(entity_name) | |
if node is not None: | |
entity_types.append(node["entity_type"]) | |
source_ids.extend( | |
split_string_by_multi_markers(node["source_id"], ['<SEP>']) | |
) | |
descriptions.append(node["description"]) | |
# 统计当前节点数据和已有节点数据的entity_type出现次数,取出现次数最多的entity_type | |
entity_type = sorted( | |
Counter( | |
[dp["entity_type"] for dp in node_data] + entity_types | |
).items(), | |
key=lambda x: x[1], | |
reverse=True, | |
)[0][0] | |
description = '<SEP>'.join( | |
sorted(set([dp["description"] for dp in node_data] + descriptions)) | |
) | |
description = await _handle_kg_summary( | |
entity_name, description, llm_client, tokenizer_instance | |
) | |
source_id = '<SEP>'.join( | |
set([dp["source_id"] for dp in node_data] + source_ids) | |
) | |
node_data = { | |
"entity_type": entity_type, | |
"description": description, | |
"source_id": source_id | |
} | |
await kg_instance.upsert_node( | |
entity_name, | |
node_data=node_data | |
) | |
node_data["entity_name"] = entity_name | |
return node_data | |
logger.info("Inserting entities into storage...") | |
entities_data = [] | |
for result in tqdm_async( | |
asyncio.as_completed( | |
[process_single_node(k, v) for k, v in nodes_data.items()] | |
), | |
total=len(nodes_data), | |
desc="Inserting entities into storage", | |
unit="entity", | |
): | |
try: | |
entities_data.append(await result) | |
except Exception as e: # pylint: disable=broad-except | |
logger.error("Error occurred while inserting entities into storage: %s", e) | |
async def merge_edges( | |
edges_data: dict, | |
kg_instance: BaseGraphStorage, | |
llm_client: TopkTokenModel, | |
tokenizer_instance: Tokenizer, | |
max_concurrent: int = 1000 | |
): | |
""" | |
Merge edges | |
:param edges_data | |
:param kg_instance | |
:param llm_client | |
:param tokenizer_instance | |
:param max_concurrent | |
:return | |
""" | |
semaphore = asyncio.Semaphore(max_concurrent) | |
async def process_single_edge(src_id: str, tgt_id: str, edge_data: list[dict]): | |
async with semaphore: | |
source_ids = [] | |
descriptions = [] | |
edge = await kg_instance.get_edge(src_id, tgt_id) | |
if edge is not None: | |
source_ids.extend( | |
split_string_by_multi_markers(edge["source_id"], ['<SEP>']) | |
) | |
descriptions.append(edge["description"]) | |
description = '<SEP>'.join( | |
sorted(set([dp["description"] for dp in edge_data] + descriptions)) | |
) | |
source_id = '<SEP>'.join( | |
set([dp["source_id"] for dp in edge_data] + source_ids) | |
) | |
for insert_id in [src_id, tgt_id]: | |
if not await kg_instance.has_node(insert_id): | |
await kg_instance.upsert_node( | |
insert_id, | |
node_data={ | |
"source_id": source_id, | |
"description": description, | |
"entity_type": "UNKNOWN" | |
} | |
) | |
description = await _handle_kg_summary( | |
f"({src_id}, {tgt_id})", description, llm_client, tokenizer_instance | |
) | |
await kg_instance.upsert_edge( | |
src_id, | |
tgt_id, | |
edge_data={ | |
"source_id": source_id, | |
"description": description | |
} | |
) | |
edge_data = { | |
"src_id": src_id, | |
"tgt_id": tgt_id, | |
"description": description | |
} | |
return edge_data | |
logger.info("Inserting relationships into storage...") | |
relationships_data = [] | |
for result in tqdm_async( | |
asyncio.as_completed( | |
[process_single_edge(src_id, tgt_id, v) for (src_id, tgt_id), v in edges_data.items()] | |
), | |
total=len(edges_data), | |
desc="Inserting relationships into storage", | |
unit="relationship", | |
): | |
try: | |
relationships_data.append(await result) | |
except Exception as e: # pylint: disable=broad-except | |
logger.error("Error occurred while inserting relationships into storage: %s", e) | |