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Adding docker files
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‎CHANGELOG.md‎

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# Change Log
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### 0.0.6
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### Added
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* Added dockerfiles and database export and import functionality.
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### 0.0.5
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### Fixed
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* Moved context window to only be handled on an LLM-level.

‎Dockerfile‎

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FROM python
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WORKDIR /app
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# nlp_pipeline requirements
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# install poppler, tesseract, antiword
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RUN apt-get update
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RUN apt-get install poppler-utils -y
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RUN apt-get install tesseract-ocr -y
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RUN apt-get install antiword
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# postgres
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RUN apt-get install -y postgresql-common
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RUN /usr/share/postgresql-common/pgdg/apt.postgresql.org.sh -y
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RUN apt-get update
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ARG DEBIAN_FRONTEND=noninteractive
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RUN apt-get purge postgresql-
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RUN apt-get install -y postgresql-16
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RUN apt-get install -y postgresql-client
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# nlp_pipeline libraries
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RUN pip install -r https://raw.githubusercontent.com/dhopp1/nlp_pipeline/main/requirements.txt
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RUN pip install --ignore-installed six
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RUN pip install nlp-pipeline
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# local_rag_llm requirements
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RUN pip install -r https://raw.githubusercontent.com/dhopp1/local_rag_llm/main/requirements.txt
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RUN pip install local-rag-llm
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# clone streamlit app
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RUN git clone https://github.com/dhopp1/streamlit_rag.git
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RUN pip install gnews
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# exclude gnews because of requests dependency
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RUN curl -s https://raw.githubusercontent.com/dhopp1/streamlit_rag/main/requirements.txt | grep -v gnews | xargs pip install

‎Dockerfile-gpu‎

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FROM nvidia/cuda:12.4.1-devel-ubuntu22.04
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WORKDIR /app
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# install python
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RUN apt-get update
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RUN apt-get install -y curl git python3-pip python3-dev python-is-python3
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RUN rm -rf /var/lib/apt/lists/*
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# nlp_pipeline requirements
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RUN apt-get update
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RUN apt-get install poppler-utils -y
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RUN apt-get install tesseract-ocr -y
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RUN apt-get install antiword
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# postgres
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RUN apt-get install -y postgresql-common
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RUN /usr/share/postgresql-common/pgdg/apt.postgresql.org.sh -y
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RUN apt-get update
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ARG DEBIAN_FRONTEND=noninteractive
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RUN apt-get purge postgresql-
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RUN apt-get install -y postgresql-16
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RUN apt-get install -y postgresql-client
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# nlp_pipeline libraries
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RUN pip install -r https://raw.githubusercontent.com/dhopp1/nlp_pipeline/main/requirements.txt
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RUN pip install --ignore-installed six
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RUN pip install nlp-pipeline
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# local_rag_llm requirements
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ENV CMAKE_ARGS="-DLLAMA_CUBLAS=ON"
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RUN pip install -r https://raw.githubusercontent.com/dhopp1/local_rag_llm/main/requirements.txt
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RUN pip install local-rag-llm
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# clone streamlit app
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RUN git clone https://github.com/dhopp1/streamlit_rag.git
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RUN pip install gnews
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# exclude gnews because of requests dependency
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RUN curl -s https://raw.githubusercontent.com/dhopp1/streamlit_rag/main/requirements.txt | grep -v gnews | xargs pip install

‎README.md‎

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## Example image
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![Example image](metadata/example_screen.png)
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## Docker usage
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### CPU only and CUDA
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If only using the CPU or an Nvidia GPU, you can run the application exclusively with Docker.
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- Download the `docker-compose.yml` and `Dockerfile` (for CPU-only) or `Dockerfile-gpu` (for GPU) files
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- In `docker-compose.yml`, edit the HF_TOKEN to your API token
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- There are four elements which need to exist outside of the container for persistence, portability, and personalization:
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- **`corpora/` directory**: this is where processed corpora (text files and vector database dumps) are saved. Change the `<local corpora directory>` line in `docker-compose.yml` to your local path for these files.
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- **`metadata/` directory**: this is where various information like database credentials, user list, llm list, etc. are stored. Change the `<local metadata directory>` line in `docker-compose.yml` to your local path for these files. The elements to be manually checked and changed are `db_creds.csv`, the `app_title`, `author_name`, and `author_email` columns, `llm_list.csv`, and `user_list.csv`.
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- **`models/` directory**: this is where the actual LLMs are stored. Change the `<local models directory>` line in `docker-compose.yml` to your local path for these files.
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- **`secrets.toml` file**: this is where you can change the application's password. Change the `<local secrets.toml file path>` line in `docker-compose.yml` to your local path for this file.
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- If you are using the CPU, delete or comment out the `deploy:` section in `docker-compose.yml`, and change the `dockerfile: Dockerfile-gpu` line to `dockerfile: Dockerfile`.
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- Navigate to the directory where you saved the `docker-compose.yml` file and Dockerfile and run `docker compose up`
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- The application will now be available on port 8502 by default.
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### Apple silicon
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If you are using Apple silicon, you won't be able to run everything in Docker because of the lack of MPS drivers. You can still use the pgvector image however.
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- follow the instructions to install [local\_rag\_llm](https://github.com/dhopp1/local_rag_llm/) and [nlp\_pipeline](https://github.com/dhopp1/nlp_pipeline) individually
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- Download the `docker-compose.yml` file
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- From the `docker-compose.yml` file, delete the `streamlit:` line and everything below it
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- Start the postgres container with `docker compose up`
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- Edit your `metadata/db_creds.csv` file and change the `host` column from `localhost` to `postgres` and `username` to `postgres`
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- Run the application as normal.

‎docker-compose.yml‎

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services:
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postgres:
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image: pgvector/pgvector:pg16
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environment:
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POSTGRES_PASSWORD: secret
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POSTGRES_USER: postgres
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POSTGRES_DB: postgres
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expose:
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- 5432
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ports:
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- 5432:5432
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streamlit:
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build:
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dockerfile: Dockerfile-gpu
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environment:
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HF_TOKEN: <HF API token>
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depends_on:
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- postgres
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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capabilities: [gpu]
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count: 'all'
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working_dir: /app/streamlit_rag
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ports:
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- 8502:8502
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volumes:
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- <local corpora directory>:/app/streamlit_rag/corpora
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- <local metadata directory>:/app/streamlit_rag/metadata
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- <local models directory>:/app/streamlit_rag/models
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- <local secret.toml file path>:/app/streamlit_rag/.streamlit/secrets.toml
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command: ["streamlit", "run", "app.py", "--server.port=8502", "--server.address=0.0.0.0"]

‎helper/clear_corpus.py‎

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from psycopg2 import sql
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from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT
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from own_corpus import check_db_exists
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# standalone script to clear out corpora. Run standalone directly from the helper/ directory
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# ex: python clear_corpus --keep corpus1,corpus1 | python clear_corpus --remove corpus1,corpus2
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def check_db_exists(host, port, user, password, db_name):
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"check if a database exists"
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conn = psycopg2.connect(
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f"host={host} port={port} dbname=postgres user={user} password={password}"
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)
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conn.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)
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cur = conn.cursor()
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cur.execute(sql.SQL("SELECT datname FROM pg_database WHERE datistemplate = false;"))
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dbs = cur.fetchall()
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result = db_name in [x[0] for x in dbs]
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cur.close()
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conn.close()
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return result
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def parse_list(arg):
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return arg.split(",")
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):
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# establish connection
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conn = psycopg2.connect(
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f"dbname=vector_db user={db_info.loc[0, 'user']} password={db_info.loc[0, 'password']}"
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f"""host={db_info.loc[lambda x: x.field == "host", "value"].values[0]} port={db_info.loc[lambda x: x.field == "port", "value"].values[0]} dbname={db_info.loc[lambda x: x.field == "master_db_name", "value"].values[0]} user={db_info.loc[lambda x: x.field == "user", "value"].values[0]} password={db_info.loc[lambda x: x.field == "password", "value"].values[0]}"""
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)
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conn.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT)
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cur = conn.cursor()
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