This is a fork from https://github.com/sdw-online/ai-postgres-database-chatbot

This is an AI chatbot that is able to answer any question about the information stored in a relational database. The chatbot created is plugged into a Postgres database. Additionally this version runs on a Docker container. Also postgress and pgadmin running on Docker.

• Streamlit: For an interactive, user-friendly web-based interface.
• OpenAI: The power behind the chatbot's intelligent responses.
• Postgres: The database where all the magic data resides.

├── bin
    ├── app-setup-docker-program.sh
    ├── app-start-docker-program.sh
    ├── build-docker-images.sh
    ├── ollallm-setup-docker.sh
    ├── ollallm-start-docker-programs.sh
    ├── setup-conda.sh
    ├── start-docker-app.sh
    ├── start-docker-ollallm.sh
    ├── start-docker-postgres.sh
    └── start.sh
├── src
    ├── api_functions.py
    ├── app.py
    ├── chat_functions.py
    ├── config.json
    ├── config.py
    ├── database_functions.py
    ├── function_calling_spec.py
    ├── helper_functions.py
    ├── logger_config.py
├── conf
    ├── conda_config.yaml
    └── config
├── conversation_history
│   └── ....
├── data
│   └── employees.sql.gz
├── logs
│   └── app.log
├── docs
│   └── postgresql-setup.md
├── LICENSE
├── README.md

The active selection is a tree-like representation of the directory structure of a software project. Here's a brief explanation of what each file and directory might be used for:

• app.py: This is likely the main application file. When you run the application, this is the file that gets executed.

• conda_config.yaml: This file is used to configure a Conda environment. Conda is a package manager that helps you manage dependencies in your Python projects.

• conversation_history: This directory might contain logs or records of past conversations if this is a chatbot or similar application.

• data: This directory contains sample data used by the application. Clean_db.sql, realestatedb.sql and fill_db.sql are sql script to create and fillup RealEsateDB. The employees.sql.gz file is a compressed SQL file, likely containing data about employees. Realestatedata.txt and zillow-data.txt are text files containing data about real estate.

• logs: This directory contains log files. The app.log file is a log file for the main application.

• docs: This directory contains documentation for the project. The postgresql-setup.md file likely contains instructions for setting up a PostgreSQL database for this project.

• LICENSE: This file contains the license for the project, which dictates how others can use and contribute to the project.

• README.md: This file usually contains information about the project, such as what it does, how to install it, and how to use it.

• start.sh other script on bin folder are shell and batch scripts. They are used to start the application, or the docker containers and the commands they contain will be executed when they are run.

1. Clone this repository with 'git clone URL' git clone [email protected]:rafael1856/ai-chatsql.git

2. Install Docker (only first time) [Read documentation about Docker installation]](https://docs.docker.com/engine/install/)

3. Add your configuraton file conf/config::

   Set config values

    # system
    export DATA_FOLDER="data/"
    export LOG_FILE="logs/app.log"
    export SCHEMA="listing"
    export LOG_LEVEL="ERROR"
    export STREAMLIT_SERVER_ADDRESS=0.0.0.0
    export STREAMLIT_SERVER_PORT=8501
    export APPDIR="/home/nonroot/code"
    export MNTDIR="/code"
   
    # for postgres and pgadmin
    export POSTGRES_DB="realestate24"
    export POSTGRES_USER="myuser"
    export POSTGRES_PASSWORD="mypassword"
    export PGADMIN_DEFAULT_EMAIL="[email protected]"
    export PGADMIN_DEFAULT_PASSWORD="adminpassword"
    export POSTGRES_HOST="pgvectordb1"
    export POSTGRES_PORT="5432"
   
    # for ollama and litellm
    export OLLAMA_HOST="0.0.0.0:11434"
    export MODEL="llama3.1"
    export OLLAMA_KEEP_ALIVE=24h
        
    # TODO: explain the following
    export UID="$(id -u)"
    export GID="$(id -g)"
        
    export OPENAI_API_KEY="sk-p0ouHvojFbzx8nBhusfsdfdsf"
   

4. Build images run: build-docker-images.sh results: ``` - verifiy the images running: docker image ls

    ai-chatsql-ollallm (~ 10Gb)
    ankane/pgvector (~ 0.5Gb)
    dpage/pgadmin4  (~ 0.5Gb)
    condaforge/miniforge3:latest (~ 0.5Gb)
    
    - verify the containers created running: docker ps
   
    ollallm1
    pgvector1
    pgadmin1
    mamba1
   
    - And it should get these port mappings:
   
    ollallm1
    0.0.0.0:24000->4000/tcp, [::]:24000->4000/tcp, 0.0.0.0:21434->11434/tcp, [::]:21434->11434/tcp   
   
    pgvector1
    0.0.0.0:5432->5432/tcp, :::5432->5432/tcp                                                        
   
    pgadmin1
    443/tcp, 0.0.0.0:20080->80/tcp, [::]:20080->80/tcp                                               
   
    mamba1
    0.0.0.0:8501->8501/tcp, :::8501->8501/tcp                                                        
    ```
   
    Is status of the containers: is NOT up and running. Run:
    1) for start ollama + litellm: start-docker-ollallm.sh
    2) for start pgadmin and postgres: start-docker-postgres.sh
    3) for start ai-chatsql: start-docker-app.sh
   

browser: https://localhost:8501

browser: https://localhost:20080

• Ask questions related to data stored in the database the chatbot is connected to
• Get answers - Enjoy the structured and dynamic answers the chatbot provides
• Save conversations - Preserve conversations into a markdown file for your future use