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This is a comprehensive stock management system that integrates AI-powered tools for stock analysis, trade requests, and client activity tracking. It includes a backend built with Python, a frontend with HTML, and services for PDF processing, stock queries, and real-time communication.

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shahalam22/stock-flow-ai

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Installation Guide

Setup Process

Backend Setup

  1. Navigate to the backend folder:
  • cd backend
  1. Install required dependencies:
  • pip install -r requirements.txt
  1. Configure environment variables:

    • Create a .env file in the backend directory
      • Here setup alphavantage api
      • Example:

{width="5.459095581802274in" height="1.2085017497812773in"}

  • Create a config.py in backend/app directory
    • Here setup gemini api
    • Example

{width="3.9172134733158357in" height="4.042230971128609in"}

  • Add your database connection details

Qdrant Database Setup

  1. Run Qdrant database using Docker:
  • docker run -p 6333:6333 -p 6334:6334 qdrant/qdrant
  1. Update your .env file with the Qdrant port configuration

Launch the Application

  1. Start the backend server:
    • cd backend

      • python –m venv venv

      • .\vevn\Scripts\activate

      • uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

    The backend will run on localhost:8000

  1. Start the frontend:
  • Simply run the frontend through vscode live server

    The frontend will be available at localhost:5500

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This is a comprehensive stock management system that integrates AI-powered tools for stock analysis, trade requests, and client activity tracking. It includes a backend built with Python, a frontend with HTML, and services for PDF processing, stock queries, and real-time communication.

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