/VentureBuddy

An AI-powered advisor for everyone interested in Entrepreneurship dedicated for the Moroccan public

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Mokawil .AI 🤖💼🇲🇦

Problem

Starting and managing a business in Morocco is challenging for entrepreneurs and aspiring business owners due to a lack of access to reliable information. Many struggle with the complexities of setting up a company, understanding tax requirements, and grasping Morocco-specific business terminology. Business failures in Morcco skyrocketed in 2022, rising by 17.4% compared to 2021.

Intorducing Mokawil.AI

Mokawil .AI is the first-of-its-kind GenAI-powered chatbot designed to assist entrepreneurs and aspiring entrepreneurs in starting their businesses in Morocco. It has access to specific information covering everything from creating a company, running it, understanding when and how much to pay taxes, business terminology in Morocco, and much more.

Approach:

We utilized the Retrieval-Augmented Generation (RAG) technique to enhance the accuracy and reliability of our generative AI models. RAG optimizes the output of a large language model by referencing an authoritative knowledge base outside of its training data sources before generating a response.

The main tool we employed for making the RAG is Langchain 🦜️⛓️ for performence and simplicity .

Phase 1: Data Collection and Embedding

  1. Data Collection:

    • Gathered detailed blogs on entrepreneurship,taxes,and everything related to starting a company from BHAdviser.

  2. Embedding:

    • Utilized a model from Hugging Face to transform data into vector representation.

  3. Vector Storage:

    • Stored embeddings in the vector database FAISS.

Phase 2: User Interaction

  1. User Interaction:

    • Users input prompts through the Streamlit interface.

  2. Prompt Embedding:

    • Embedded user prompts using the same model used for data embedding.

  3. Similarity Search:

    • Compared embedded user prompts with vector database data to find the best match.

Phase 3: Large Language Model (LLM)

  1. LLM Selection:

  2. Answers Generation:

    • Fed results of similarity search to the LLM to generate answers based on user-specific needs and available information the answer are also saved in chat memroy to make use of them later .

  3. User Interface (UI):

    • Presented answers in the Streamlit UI for user consumption.

Global Architechtures

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Instructions

To run the Mokawil .AI application, follow these steps:

  1. Open Google Colab:

    • Access Google Colab using your preferred web browser.

  2. Install Requirements:

    • Inside the Colab environment, install the necessary requirements. You can do this by running the following command in a code cell: 
      !pip install -r requirements.txt

  3. Run the Notebook:

    • Open the notebook named "Rag financial advisor GPU.ipynb" in the Colab environment.
    • Execute the cells in the notebook to run the application.

Alternatively, you can explore a demo of the application directly on Hugging Face : Geek Team - Hugging Face Note : it takes time for generation for low ressouce

Demo

Geek_Team_-a_Hugging_Face_Space_by_MahmoudRox-_Google_Chrome_2023-12-18_14-32-56 demo2

Future work

we plan on making Mokawil.AI more advanced and more helapful for the users by making it :

  • Personalized Responses:

    • Provied tailord responses based on user-specific information.

  • Multilingual Support:

    • to be Capable of understanding and responding in multiple languages.

  • Notification System:

    • Sends notifications for important deadlines to keep users informed.

  • Versatile Input Support:

    • Accepts text, audio, and document inputs for flexibility.

  • Financial Document Analysis:

    • Analyzes financial documents to provide insightful information.

  • And Much More...

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Geek Team