Fixed retry strategy, message history and inference params; Cleaned up Bedrock example

examples/lightrag_bedrock_demo.py

@@ -3,46 +3,39 @@ LightRAG meets Amazon Bedrock ⛰️
 """
 
 import os
+import logging
 
 from lightrag import LightRAG, QueryParam
 from lightrag.llm import bedrock_complete, bedrock_embedding
 from lightrag.utils import EmbeddingFunc
 
-WORKING_DIR = "./dickens"
+logging.getLogger("aiobotocore").setLevel(logging.WARNING)
 
+WORKING_DIR = "./dickens"
 if not os.path.exists(WORKING_DIR):
     os.mkdir(WORKING_DIR)
 
 rag = LightRAG(
     working_dir=WORKING_DIR,
     llm_model_func=bedrock_complete,
-    llm_model_name="anthropic.claude-3-haiku-20240307-v1:0",
-    node2vec_params = {
-        'dimensions': 1024,
-        'num_walks': 10,
-        'walk_length': 40,
-        'window_size': 2,
-        'iterations': 3,
-        'random_seed': 3
-    },
+    llm_model_name="Anthropic Claude 3 Haiku // Amazon Bedrock",
     embedding_func=EmbeddingFunc(
         embedding_dim=1024,
         max_token_size=8192,
-        func=lambda texts: bedrock_embedding(texts)
+        func=bedrock_embedding
     )
 )
 
-with open("./book.txt") as f:
+with open("./book.txt", 'r', encoding='utf-8') as f:
     rag.insert(f.read())
 
-# Naive search
-print(rag.query("What are the top themes in this story?", param=QueryParam(mode="naive")))
-
-# Local search
-print(rag.query("What are the top themes in this story?", param=QueryParam(mode="local")))
-
-# Global search
-print(rag.query("What are the top themes in this story?", param=QueryParam(mode="global")))
-
-# Hybrid search
-print(rag.query("What are the top themes in this story?", param=QueryParam(mode="hybrid")))
+for mode in ["naive", "local", "global", "hybrid"]:
+    print("\n+-" + "-" * len(mode) + "-+")
+    print(f"| {mode.capitalize()} |")
+    print("+-" + "-" * len(mode) + "-+\n")
+    print(
+        rag.query(
+            "What are the top themes in this story?",
+            param=QueryParam(mode=mode)
+        )
+    )