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https://github.com/phamtrinhduc/chatbot_ver13
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.
https://github.com/phamtrinhduc/chatbot_ver13
chromadb elasticsearch langchain openai retrieval-augmented-generation
Last synced: 3 months ago
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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.
- Host: GitHub
- URL: https://github.com/phamtrinhduc/chatbot_ver13
- Owner: PhamTrinhDuc
- License: gpl-3.0
- Created: 2024-09-13T08:32:55.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-10-02T12:30:33.000Z (3 months ago)
- Last Synced: 2024-10-02T14:56:42.464Z (3 months ago)
- Topics: chromadb, elasticsearch, langchain, openai, retrieval-augmented-generation
- Language: Python
- Homepage:
- Size: 3.92 MB
- Stars: 3
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://github.com/PhamTrinhDuc/Chatbot_ver11/stargazers)[](https://github.com/PhamTrinhDuc/Chatbot_ver11/issues)
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**
├── app.py # demo on gradio app
├── configs
│ ├── config_fewshot # config cho elastic search và các ví dụ fewshot
│ │ ├── config_fewshot.py
│ │ ├── example_fewshot.yml
│ ├── config.yml
│ ├── __init__.py
│ ├── config_system.py
├── data
│ ├── Cau_hoi_thuong_gap.csv # file chứa các câu hỏi thường gặp của khách hàng
│ ├── dieu_hoa.csv # file sản phẩm điều hòa
│ ├── product_final_300_extract.xlsx # file tất cả các sản phẩm
│ └── vector_db # folder lưu embedding của sản phẩm và câu hỏi thường gặp
│ ├── Cau_hoi_thuong_gap
│ │ └── chroma.sqlite3
│ └── dieu_hoa
│ └── chroma.sqlite3
├── elastic_search # folder chưa code sử dụng elastic search để search thông tin sp
│ ├── few_shot_sentence.py
│ ├── elastic_helper.py
│ └── query_engine.py
├── images # ảnh giao diện app
│ ├── avt_bot.png
│ ├── avt_user.png
│ ├── logo.png
│ └── pipeline.png
├── logs # chứa 3 loại log: thông tin, lỗi, thời gian
│ ├── logger.py
├── README.md
├── requirements.txt # các thư viện yêu cầu của project
├── source
│ ├── generater.py # file chat chính
│ ├── load_db.py # load vector embedding
│ ├── retriever.py # file khởi tạo retrieval và lấy context
│ └── router.py # router điều hướng: elastic search, chroma db, tương tự, tồn kho
├── test_code.py
└── utils # các file code sử dụng cho cho các file khác
├── pydantic_model.py # base model
├── timekeeper.py # tính thời gian
├── data_processer.py # convert csv to text
├── __init__.py # import các thư viện từ module utils
└── prompt.py # chưa toàn bộ prompt cho LLM
## **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:
```bash
python3 -m venv .venv
source .venv/bin/activate
```
- For Windows:
```bash
python -m venv venv
.\venv\Scripts\activate
```
- Conda:
```bash
conda create -n python=
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
```bash
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
```bash
pip install -r requirements.txt
```
#### Step 5. Chat interface gradio
```bash
python3 run app.py
```
## **5. Demo Result**
## **6. Acknowldgement**
ARMY SALES CHATBOT is conducted by interns Pham Duc and Tran Hao at VCC. We apply some of the following technologies::
- [Langchain](https://www.langchain.com/): Providing the RAG (Retrieval Augmented Generation) framework.
- [Gradio](https://www.gradio.app/): Enabling the intuitive user interface.
- [ElasticSearch](https://www.elastic.co/docs): Enhance query capabilities for table data