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68 lines
2.0 KiB
Python
68 lines
2.0 KiB
Python
import os
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from dotenv import load_dotenv
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from aworld.core.memory import MemoryConfig, EmbeddingsConfig, VectorDBConfig, \
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MemoryLLMConfig
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from aworld.memory.db.postgres import PostgresMemoryStore
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from aworld.memory.main import MemoryFactory
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def init_memory():
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load_dotenv()
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MemoryFactory.init(
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config=MemoryConfig(
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provider="aworld",
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llm_config=MemoryLLMConfig(
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provider="openai",
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model_name=os.environ["LLM_MODEL_NAME"],
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api_key=os.environ["LLM_API_KEY"],
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base_url=os.environ["LLM_BASE_URL"]
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),
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embedding_config=EmbeddingsConfig(
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provider="ollama",
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base_url="http://localhost:11434",
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model_name="nomic-embed-text"
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),
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vector_store_config=VectorDBConfig(
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provider="chroma",
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config=
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{
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"chroma_data_path": "./chroma_db",
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"collection_name": "aworld",
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}
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)
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))
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def init_postgres_memory():
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load_dotenv()
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postgres_memory_store = PostgresMemoryStore(db_url=os.getenv("MEMORY_STORE_POSTGRES_DSN"))
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MemoryFactory.init(
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custom_memory_store=postgres_memory_store,
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config=MemoryConfig(
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provider="aworld",
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llm_config=MemoryLLMConfig(
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provider="openai",
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model_name=os.environ["LLM_MODEL_NAME"],
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api_key=os.environ["LLM_API_KEY"],
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base_url=os.environ["LLM_BASE_URL"]
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),
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embedding_config=EmbeddingsConfig(
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provider="ollama",
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base_url="http://localhost:11434",
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model_name="nomic-embed-text"
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),
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vector_store_config=VectorDBConfig(
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provider="chroma",
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config=
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{
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"chroma_data_path": "./chroma_db",
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"collection_name": "aworld",
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}
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)
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))
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