fix demo
This commit is contained in:
@@ -1,8 +1,10 @@
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import os
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import time
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import asyncio
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from lightrag import LightRAG, QueryParam
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from lightrag.llm.ollama import ollama_model_complete, ollama_embed
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from lightrag.utils import EmbeddingFunc
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from lightrag.kg.shared_storage import initialize_pipeline_status
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# Working directory and the directory path for text files
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WORKING_DIR = "./dickens"
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@@ -12,17 +14,22 @@ TEXT_FILES_DIR = "/llm/mt"
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if not os.path.exists(WORKING_DIR):
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os.mkdir(WORKING_DIR)
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# Initialize LightRAG
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rag = LightRAG(
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working_dir=WORKING_DIR,
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llm_model_func=ollama_model_complete,
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llm_model_name="qwen2.5:3b-instruct-max-context",
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embedding_func=EmbeddingFunc(
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embedding_dim=768,
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max_token_size=8192,
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func=lambda texts: ollama_embed(texts, embed_model="nomic-embed-text"),
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),
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)
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async def initialize_rag():
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# Initialize LightRAG
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rag = LightRAG(
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working_dir=WORKING_DIR,
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llm_model_func=ollama_model_complete,
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llm_model_name="qwen2.5:3b-instruct-max-context",
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embedding_func=EmbeddingFunc(
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embedding_dim=768,
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max_token_size=8192,
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func=lambda texts: ollama_embed(texts, embed_model="nomic-embed-text"),
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),
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)
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await rag.initialize_storages()
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await initialize_pipeline_status()
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return rag
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# Read all .txt files from the TEXT_FILES_DIR directory
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texts = []
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@@ -47,58 +54,65 @@ def insert_texts_with_retry(rag, texts, retries=3, delay=5):
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raise RuntimeError("Failed to insert texts after multiple retries.")
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insert_texts_with_retry(rag, texts)
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def main():
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# Initialize RAG instance
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rag = asyncio.run(initialize_rag())
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# Perform different types of queries and handle potential errors
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="naive")
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insert_texts_with_retry(rag, texts)
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# Perform different types of queries and handle potential errors
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="naive")
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)
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)
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)
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except Exception as e:
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print(f"Error performing naive search: {e}")
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except Exception as e:
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print(f"Error performing naive search: {e}")
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="local")
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="local")
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)
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)
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)
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except Exception as e:
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print(f"Error performing local search: {e}")
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except Exception as e:
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print(f"Error performing local search: {e}")
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="global")
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="global")
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)
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)
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)
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except Exception as e:
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print(f"Error performing global search: {e}")
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except Exception as e:
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print(f"Error performing global search: {e}")
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="hybrid")
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try:
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print(
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rag.query(
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"What are the top themes in this story?", param=QueryParam(mode="hybrid")
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)
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)
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)
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except Exception as e:
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print(f"Error performing hybrid search: {e}")
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except Exception as e:
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print(f"Error performing hybrid search: {e}")
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# Function to clear VRAM resources
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def clear_vram():
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os.system("sudo nvidia-smi --gpu-reset")
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# Function to clear VRAM resources
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def clear_vram():
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os.system("sudo nvidia-smi --gpu-reset")
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# Regularly clear VRAM to prevent overflow
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clear_vram_interval = 3600 # Clear once every hour
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start_time = time.time()
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# Regularly clear VRAM to prevent overflow
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clear_vram_interval = 3600 # Clear once every hour
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start_time = time.time()
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while True:
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current_time = time.time()
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if current_time - start_time > clear_vram_interval:
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clear_vram()
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start_time = current_time
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time.sleep(60) # Check the time every minute
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while True:
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current_time = time.time()
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if current_time - start_time > clear_vram_interval:
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clear_vram()
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start_time = current_time
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time.sleep(60) # Check the time every minute
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if __name__ == "__main__":
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main()
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