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@ -8,13 +8,13 @@ class FinancialSituationMemory:
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def __init__(self, name, config):
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self.client = OpenAI(base_url=config["backend_url"], api_key=config.get("api_key"))
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# 根據 backend 決定 embedding 策略
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# Based on llm_provider to select embeddings
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if config["llm_provider"] == "ollama":
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self.embedding = "nomic-embed-text"
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self.embedding_client = OpenAI(base_url="http://localhost:11434/v1")
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self.use_local_embedding = False
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elif config["llm_provider"] == "xai":
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# Grok - 使用本地 Hugging Face 模型
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# Grok - use local Hugging Face model
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self.embedding_model = SentenceTransformer('all-MiniLM-L6-v2')
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self.use_local_embedding = True
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else:
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@ -29,10 +29,10 @@ class FinancialSituationMemory:
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def get_embedding(self, text):
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"""Get embedding for a text"""
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if self.use_local_embedding:
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# 使用本地 Hugging Face 模型
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# use local Hugging Face model
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return self.embedding_model.encode(text).tolist()
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else:
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# 使用 API
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# use API
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response = self.embedding_client.embeddings.create(
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model=self.embedding,
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input=text
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