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View All on GitHubQuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance.
AI Summary: Integrate an embedding model using LiteLLM into the QuantMind framework. This involves creating an `embedding.py` file, unit tests, an `EmbeddingConfig` class, and a usage example demonstrating the integration.
QuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance.
AI Summary: This task requires building a Quant Paper Agent that fetches research papers from arXiv, parses them using an LLM-based parser, tags them with relevant financial topics using another LLM, generates summaries, and saves the structured data as a `Knowledge` object. This involves connecting existing components (ArxivSource, LocalStorage) and creating new ones (LlamaParser, LLMTagger, SummaryFlow) to form a complete knowledge extraction pipeline.
QuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance.