The program runs into an infinite loop and cannot be stopped.

[Cherries-Man]

I run lightrag_hf_demo.py, but there is no response after running it. Does anyone know what is going on?

My code is as follows:

import os

from lightrag import LightRAG, QueryParam
from lightrag.llm import hf_model_complete, hf_embedding
from lightrag.utils import EmbeddingFunc
from transformers import AutoModel, AutoTokenizer

WORKING_DIR = "./dickens"

if not os.path.exists(WORKING_DIR):
    os.mkdir(WORKING_DIR)

rag = LightRAG(
    working_dir=WORKING_DIR,
    llm_model_func=hf_model_complete,
    # llm_model_name="meta-llama/Llama-3.1-8B-Instruct",
    llm_model_name="/data1/yfman/hf_models/Llama-3.1-8B-Instruct",
    embedding_func=EmbeddingFunc(
        embedding_dim=384,
        max_token_size=5000,
        func=lambda texts: hf_embedding(
            texts,
            tokenizer=AutoTokenizer.from_pretrained(
                "sentence-transformers/all-MiniLM-L6-v2"
            ),
            embed_model=AutoModel.from_pretrained(
                "sentence-transformers/all-MiniLM-L6-v2"
            ),
        ),
    ),
)


# with open("./book.txt", "r", encoding="utf-8") as f:
with open("/home/yfman/LightRAG/book.txt", "r", encoding="utf-8") as f:
    rag.insert(f.read())

# Perform naive search
print(
    rag.query("What are the top themes in this story?", param=QueryParam(mode="naive"))
)

# Perform local search
print(
    rag.query("What are the top themes in this story?", param=QueryParam(mode="local"))
)

# Perform global search
print(
    rag.query("What are the top themes in this story?", param=QueryParam(mode="global"))
)

# Perform hybrid search
print(
    rag.query("What are the top themes in this story?", param=QueryParam(mode="hybrid"))
)

The program output is as follows:

(base) yfman@amax406:~$  cd /home/yfman ; /usr/bin/env /data0/yfman/.conda/envs/lightrag/bin/python /home/yfman/.vscode-server/extensions/ms-python.debugpy-2024.12.0-linux-x64/bundled/libs/debugpy/adapter/../../debugpy/launcher 41889 -- /home/yfman/LightRAG/examples/lightrag_hf_demo.py 
INFO:lightrag:Logger initialized for working directory: ./dickens
INFO:lightrag:Load KV llm_response_cache with 0 data
INFO:lightrag:Load KV full_docs with 0 data
INFO:lightrag:Load KV text_chunks with 0 data
INFO:nano-vectordb:Init {'embedding_dim': 384, 'metric': 'cosine', 'storage_file': './dickens/vdb_entities.json'} 0 data
INFO:nano-vectordb:Init {'embedding_dim': 384, 'metric': 'cosine', 'storage_file': './dickens/vdb_relationships.json'} 0 data
INFO:nano-vectordb:Init {'embedding_dim': 384, 'metric': 'cosine', 'storage_file': './dickens/vdb_chunks.json'} 0 data
INFO:lightrag:[New Docs] inserting 1 docs
INFO:lightrag:[New Chunks] inserting 42 chunks
INFO:lightrag:Inserting 42 vectors to chunks
INFO:lightrag:[Entity Extraction]...
Loading checkpoint shards: 100%|██████████████████████████████████| 4/4 [00:09<00:00,  2.27s/it]
/data0/yfman/.conda/envs/lightrag/lib/python3.9/site-packages/transformers/generation/configuration_utils.py:638: UserWarning: `num_beams` is set to 1. However, `early_stopping` is set to `True` -- this flag is only used in beam-based generation modes. You should set `num_beams>1` or unset `early_stopping`.
  warnings.warn(
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.)
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.d)
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.

Thank you!