README.md

---
title: Financial Bot
emoji: 🚀
colorFrom: red
colorTo: green
sdk: gradio
sdk_version: 4.16.0
app_file: app.py
pinned: false
license: mit
---

# Friendly Fincancial Bot

This is the Inference module of a 3-part **prod-ready** FTI feature-training-inference **RAG-framework LLMOps** course. \
In this iteration, I've **replaced Falcon 7B Instruct** with the **currently-SoTa (Jan'24) Mistral-7B-Instruct-v0.2**, \
fine-tuned using **Unsloth** on financial questions and answers generated with the help of GPT-4, quantized \
and augmented with a 4bit QLoRa. \
\
Prompt analysis and model registry is handled by **Comet LLM**, and finance news is streamed via **Bytewax** using an \
**Alpaca API**, and then sent as a vector embedding to **Qdrant**'s serverless vector store. **LangChain** chains the prompt and \
most relevant news article to provide answers with real-time finance information embedded within the output. \
\
**#TODO:** Add citations to output to show end-user which article has been used to generate the output.

I have contributed to the original MIT licensed (ka-ching!) course which can be found here:\
[https://medium.com/decoding-ml/the-llms-kit-build-a-production-ready-real-time-financial-advisor-system-using-streaming-ffdcb2b50714]