File size: 1,966 Bytes
75922df 0553d6a 75922df 390c21a 75922df |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
import os
from lightrag import LightRAG, QueryParam
from lightrag.llm.ollama import ollama_embed, openai_complete_if_cache
from lightrag.utils import EmbeddingFunc
# WorkingDir
ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
WORKING_DIR = os.path.join(ROOT_DIR, "myKG")
if not os.path.exists(WORKING_DIR):
os.mkdir(WORKING_DIR)
print(f"WorkingDir: {WORKING_DIR}")
# redis
os.environ["REDIS_URI"] = "redis://localhost:6379"
# neo4j
BATCH_SIZE_NODES = 500
BATCH_SIZE_EDGES = 100
os.environ["NEO4J_URI"] = "bolt://117.50.173.35:7687"
os.environ["NEO4J_USERNAME"] = "neo4j"
os.environ["NEO4J_PASSWORD"] = "12345678"
# milvus
os.environ["MILVUS_URI"] = "http://117.50.173.35:19530"
os.environ["MILVUS_USER"] = "root"
os.environ["MILVUS_PASSWORD"] = "Milvus"
os.environ["MILVUS_DB_NAME"] = "lightrag"
async def llm_model_func(
prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs
) -> str:
return await openai_complete_if_cache(
"deepseek-chat",
prompt,
system_prompt=system_prompt,
history_messages=history_messages,
api_key="sk-91d0b59f25554251aa813ed756d79a6d",
base_url="https://api.deepseek.com",
**kwargs,
)
embedding_func = EmbeddingFunc(
embedding_dim=768,
max_token_size=512,
func=lambda texts: ollama_embed(
texts, embed_model="shaw/dmeta-embedding-zh", host="http://117.50.173.35:11434"
),
)
rag = LightRAG(
working_dir=WORKING_DIR,
llm_model_func=llm_model_func,
llm_model_max_token_size=32768,
embedding_func=embedding_func,
chunk_token_size=512,
chunk_overlap_token_size=256,
kv_storage="RedisKVStorage",
graph_storage="Neo4JStorage",
vector_storage="MilvusVectorDBStorge",
doc_status_storage="RedisKVStorage",
)
file = "../book.txt"
with open(file, "r", encoding="utf-8") as f:
rag.insert(f.read())
print(rag.query("谁会3D建模 ？", param=QueryParam(mode="mix")))
|