ollama test

examples/lightrag_ollama_demo.py

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+import os
+
+from lightrag import LightRAG, QueryParam
+from lightrag.llm import ollama_model_complete, ollama_embedding
+from lightrag.utils import EmbeddingFunc
+
+WORKING_DIR = "./dickens"
+
+if not os.path.exists(WORKING_DIR):
+    os.mkdir(WORKING_DIR)
+
+rag = LightRAG(
+    working_dir=WORKING_DIR,
+    llm_model_func=ollama_model_complete,  
+    llm_model_name='your_model_name',
+    embedding_func=EmbeddingFunc(
+        embedding_dim=768,
+        max_token_size=8192,
+        func=lambda texts: ollama_embedding(
+            texts, 
+            embed_model="nomic-embed-text"
+        )
+    ),
+)
+
+
+with open("./book.txt") 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")))