Chatbot sales army is a chatbot product aimed at selling and consulting products by interacting directly with customers. Chatbot uses RAG techniques - an advanced artificial intelligence solution that combines the ability to retrieve accurate information and the ability to generate natural answers.

1. Pipeline

2. Tree Project

    ├── api
    │   ├── handle_request.py
    ├── app_api.py
    ├── configs
    │   ├── config_fewshot
    │   │   ├── config_fewshot.py
    │   │   ├── example_fewshot.yml
    │   ├── config_system.py
    │   ├── config.yml
    │   ├── __init__.py
    ├── data
    │   ├── data_private
    │   │   ├── data_csv
    │   │   │   ├── ban_la.csv
    │   │   │   ├── ....
    │   │   │   └── thiet_bi_wifi.csv
    │   │   ├── data_dienmayxanh.csv
    │   │   ├── data_text
    │   │   │   ├── ban_la.pkl
    │   │   │   ├── ....
    │   │   │   └── thiet_bi_wifi.pkl
    │   │   └── product_final_300_extract.xlsx
    │   └── vector_db
    │       ├── ban_la
    │       ├── ....
    │       └── thiet_bi_wifi
    ├── evaluate_system
    │   └── evaluater.py
    ├── Interface_gradio.py
    ├── Interface_streamlit.py
    ├── LICENSE
    ├── logs
    │   ├── error
    │   ├── logger.py
    │   ├── terminal
    │   └── times
    ├── pages
    │   └── 1_💬_Chat.py
    ├── README.md
    ├── requirements.txt
    ├── security
    │   ├── conversation_store
    │   │   └── ducpham.json
    │   └── info_user_store
    │       └── ducpham.json
    ├── source
    │   ├── generate
    │   │   ├── chat.py
    │   │   ├── chat_seasion.py
    │   ├── ingest_data
    │   │   ├── ingestion.py
    │   ├── prompt
    │   │   └── template.py
    │   ├── retriever
    │   │   ├── chroma
    │   │   │   └── retriever.py
    │   │   └── elastic_search
    │   │       ├── elastic_helper.py
    │   │       ├── few_shot_sentence.py
    │   │       ├── __init__.py
    │   │       └── query_engine.py
    │   ├── router
    │   │   ├── router.py
    │   │   ├── switch.py
    │   │   └── tool_calling.ipynb
    │   └── similar_product
    │       ├── crawler
    │       │   ├── crawler_website.py
    │       │   ├── ....
    │       │   └── specification.png
    │       └── searcher.py
    ├── static
    │   ├── avt_bot.png
    │   ├── ....
    │   ├── pipeline.png
    ├── test_code.py
    ├── ui
    │   ├── authenticate.py
    │   └── sidebar.py
    └── utils
        ├── __init__.py
        ├── schemas.py
        ├── timekeeper.py
        └── user_helper.py

3. To Install This Application, Follow These Steps:

Step 1. Clone the repository:

git clone https://github.com/PhamTrinhDuc/Chatbot_ver11
cd Chatbot_ver11

Step 2. (Optional) Create and activate a virtual environment:

• For Unix/macOS:

python3 -m venv .venv
source .venv/bin/activate

• For Windows:

python -m venv venv
.\venv\Scripts\activate

• Conda:

conda create -n <env_name> python=<python_version> 
conda activate env_name

Step 3. Before starting your application, you need to fill in some evironment variables. Create a .env file and fill in these

OPENAI_API_KEY = "sk-dTKKIChoB9Odh6JlFCbuaKpJVeojvF..."
LANGCHAIN_API_KEY = "lsv2_pt_835e83bf17f94c78bc4e7b7..."
ELASTIC_CLOUD_ID = "My_deployment:dXMtY2VudHJhbDEuZ2NwLmNsb3VkLmVzLmlvJ..."
ELASTIC_API_KEY = "RjRBUnZKRUJ6aEFqenhQVHVrRTU6TnRPZmVDS3RRRU9RZF..."

Step 4. Install the necessary libraries for the project

pip install -r requirements.txt

Step 5. Chat interface

Streamlit

streamlit run Home.py

Gradio

python3 run app.py

4. Demo Result

1. Tạo tài khoản

2. Đăng nhập vào hệ thống.

3. Chat Interface

5. Acknowldgement

ARMY SALES CHATBOT is conducted by interns Pham Duc and Tran Hao at VCC. We apply some of the following technologies::

• Langchain: Providing the RAG (Retrieval Augmented Generation) framework.
• Gradio: Enabling the intuitive user interface.
• ElasticSearch: Enhance query capabilities for table data