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@@ -18,8 +18,9 @@ fine-tuned using **Unsloth** on an expanded dataset of financial questions and a
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  quantized and augmented with a 4bit QLoRa. \
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  \
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  Prompt analysis and model registry is handled by **Comet LLM**, and finance news is streamed via **Bytewax** using an \
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- **Alpaca API**, and then sent as a vector embedding to **Qdrant**'s serverless vector store. **LangChain** chains the prompt and \
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- most relevant news article with real-time finance information, **contextualizing the output**. \
 
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  \
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  **#TODO:** Add citations to output to show end-user which article has been used to generate the output.
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  quantized and augmented with a 4bit QLoRa. \
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  \
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  Prompt analysis and model registry is handled by **Comet LLM**, and finance news is streamed via **Bytewax** using an \
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+ **Alpaca API**, then parsed, cleaned, and chunked with **unstructured**, and finally sent as a vector embedding to \
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+ **Qdrant**'s serverless vector store. **LangChain** chains the prompt and most relevant news article with real-time \
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+ finance information, **contextualizing the output**. \
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  \
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  **#TODO:** Add citations to output to show end-user which article has been used to generate the output.
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