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| import streamlit as st | |
| from FinancialAgentOllama import FinancialAgentOllama | |
| from langchain.embeddings import HuggingFaceEmbeddings | |
| from huggingface_hub import hf_hub_download | |
| # Download the .faiss file from a model or dataset repo | |
| index_path = hf_hub_download( | |
| repo_id="mrfirdauss/FaissBhatlaBook", | |
| filename="vs_68bf713eea2c81919ac08298a05d6704/index.faiss", | |
| repo_type="dataset" | |
| ) | |
| app = FinancialAgentOllama(st, model_name="qwen3:4b", embedding=HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")) | |
| app.run() | |