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	fix bug
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				| @ -3,6 +3,7 @@ import sys | |||||||
| 
 | 
 | ||||||
| from lightrag import LightRAG, QueryParam | from lightrag import LightRAG, QueryParam | ||||||
| from lightrag.llm import hf_model_complete, hf_embedding | from lightrag.llm import hf_model_complete, hf_embedding | ||||||
|  | from lightrag.utils import EmbeddingFunc | ||||||
| from transformers import AutoModel,AutoTokenizer | from transformers import AutoModel,AutoTokenizer | ||||||
| 
 | 
 | ||||||
| WORKING_DIR = "./dickens" | WORKING_DIR = "./dickens" | ||||||
| @ -14,9 +15,13 @@ rag = LightRAG( | |||||||
|     working_dir=WORKING_DIR, |     working_dir=WORKING_DIR, | ||||||
|     llm_model_func=hf_model_complete,   |     llm_model_func=hf_model_complete,   | ||||||
|     llm_model_name='meta-llama/Llama-3.1-8B-Instruct', |     llm_model_name='meta-llama/Llama-3.1-8B-Instruct', | ||||||
|     embedding_func=hf_embedding,   |     embedding_func=EmbeddingFunc( | ||||||
|     tokenizer=AutoTokenizer.from_pretrained("sentence-transformers/all-MiniLM-L6-v2"), |         tokenizer=AutoTokenizer.from_pretrained("sentence-transformers/all-MiniLM-L6-v2"), | ||||||
|     embed_model=AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2") |         embed_model=AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2"), | ||||||
|  |         embedding_dim=384, | ||||||
|  |         max_token_size=5000, | ||||||
|  |         func=hf_embedding | ||||||
|  |     ), | ||||||
| ) | ) | ||||||
| 
 | 
 | ||||||
| 
 | 
 | ||||||
|  | |||||||
| @ -5,15 +5,15 @@ from lightrag import LightRAG, QueryParam | |||||||
| from lightrag.llm import gpt_4o_mini_complete, gpt_4o_complete | from lightrag.llm import gpt_4o_mini_complete, gpt_4o_complete | ||||||
| from transformers import AutoModel,AutoTokenizer | from transformers import AutoModel,AutoTokenizer | ||||||
| 
 | 
 | ||||||
| WORKING_DIR = "./dickens" | WORKING_DIR = "/home/zrguo/code/myrag/agriculture" | ||||||
| 
 | 
 | ||||||
| if not os.path.exists(WORKING_DIR): | if not os.path.exists(WORKING_DIR): | ||||||
|     os.mkdir(WORKING_DIR) |     os.mkdir(WORKING_DIR) | ||||||
| 
 | 
 | ||||||
| rag = LightRAG( | rag = LightRAG( | ||||||
|     working_dir=WORKING_DIR, |     working_dir=WORKING_DIR, | ||||||
|     llm_model_func=gpt_4o_complete |     llm_model_func=gpt_4o_mini_complete | ||||||
|     # llm_model_func=gpt_4o_mini_complete |     # llm_model_func=gpt_4o_complete | ||||||
| ) | ) | ||||||
| 
 | 
 | ||||||
| 
 | 
 | ||||||
|  | |||||||
| @ -76,12 +76,8 @@ class LightRAG: | |||||||
|         } |         } | ||||||
|     ) |     ) | ||||||
| 
 | 
 | ||||||
|     # text embedding |  | ||||||
|     tokenizer: Any = None |  | ||||||
|     embed_model: Any = None |  | ||||||
| 
 |  | ||||||
|     # embedding_func: EmbeddingFunc = field(default_factory=lambda:hf_embedding) |     # embedding_func: EmbeddingFunc = field(default_factory=lambda:hf_embedding) | ||||||
|     embedding_func: EmbeddingFunc = field(default_factory=lambda:openai_embedding)#  |     embedding_func: EmbeddingFunc = field(default_factory=lambda:openai_embedding) | ||||||
|     embedding_batch_num: int = 32 |     embedding_batch_num: int = 32 | ||||||
|     embedding_func_max_async: int = 16 |     embedding_func_max_async: int = 16 | ||||||
| 
 | 
 | ||||||
| @ -103,13 +99,6 @@ class LightRAG: | |||||||
|     convert_response_to_json_func: callable = convert_response_to_json |     convert_response_to_json_func: callable = convert_response_to_json | ||||||
| 
 | 
 | ||||||
|     def __post_init__(self):         |     def __post_init__(self):         | ||||||
|         if callable(self.embedding_func) and self.embedding_func.__name__ == 'hf_embedding': |  | ||||||
|             if self.tokenizer is None: |  | ||||||
|                 self.tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/all-MiniLM-L6-v2") |  | ||||||
|             if self.embed_model is None: |  | ||||||
|                 self.embed_model = AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2") |  | ||||||
| 
 |  | ||||||
| 
 |  | ||||||
|         log_file = os.path.join(self.working_dir, "lightrag.log") |         log_file = os.path.join(self.working_dir, "lightrag.log") | ||||||
|         set_logger(log_file) |         set_logger(log_file) | ||||||
|         logger.info(f"Logger initialized for working directory: {self.working_dir}") |         logger.info(f"Logger initialized for working directory: {self.working_dir}") | ||||||
| @ -139,10 +128,9 @@ class LightRAG: | |||||||
|         self.chunk_entity_relation_graph = self.graph_storage_cls( |         self.chunk_entity_relation_graph = self.graph_storage_cls( | ||||||
|             namespace="chunk_entity_relation", global_config=asdict(self) |             namespace="chunk_entity_relation", global_config=asdict(self) | ||||||
|         ) |         ) | ||||||
|  | 
 | ||||||
|         self.embedding_func = limit_async_func_call(self.embedding_func_max_async)( |         self.embedding_func = limit_async_func_call(self.embedding_func_max_async)( | ||||||
|             lambda texts: self.embedding_func(texts, self.tokenizer, self.embed_model)  |             self.embedding_func | ||||||
|             if callable(self.embedding_func) and self.embedding_func.__name__ == 'hf_embedding' |  | ||||||
|             else self.embedding_func(texts) |  | ||||||
|         ) |         ) | ||||||
| 
 | 
 | ||||||
|         self.entities_vdb = ( |         self.entities_vdb = ( | ||||||
|  | |||||||
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