fix:rename knowledge_init.py

rename knowledge_init.py

tools/knowledge_init.py

@@ -0,0 +1,51 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+import argparse
+import os
+import sys
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
+
+from pilot.configs.config import Config
+from pilot.configs.model_config import (
+    DATASETS_DIR,
+    LLM_MODEL_CONFIG,
+)
+from pilot.source_embedding.knowledge_embedding import KnowledgeEmbedding
+
+CFG = Config()
+
+
+class LocalKnowledgeInit:
+    embeddings: object = None
+
+    def __init__(self, vector_store_config) -> None:
+        self.vector_store_config = vector_store_config
+        self.model_name = LLM_MODEL_CONFIG["text2vec"]
+
+    def knowledge_persist(self, file_path):
+        """knowledge persist"""
+        for root, _, files in os.walk(file_path, topdown=False):
+            for file in files:
+                filename = os.path.join(root, file)
+                # docs = self._load_file(filename)
+                ke = KnowledgeEmbedding(
+                    file_path=filename,
+                    model_name=self.model_name,
+                    vector_store_config=self.vector_store_config,
+                )
+                client = ke.init_knowledge_embedding()
+                client.source_embedding()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--vector_name", type=str, default="default")
+    args = parser.parse_args()
+    vector_name = args.vector_name
+    store_type = CFG.VECTOR_STORE_TYPE
+    vector_store_config = {"vector_store_name": vector_name}
+    print(vector_store_config)
+    kv = LocalKnowledgeInit(vector_store_config=vector_store_config)
+    kv.knowledge_persist(file_path=DATASETS_DIR)
+    print("your knowledge embedding success...")