https://github.com/balaji1233/my_llm_projects-q-a-cbot
This is a Q & A chatbot .Use your Own openai-api key & huggingface-access-tokens
https://github.com/balaji1233/my_llm_projects-q-a-cbot
docker flask huggingface-access-tokens huggingface-api huggingface-spaces langchain openai-api python3 streamlit
Last synced: 2 months ago
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This is a Q & A chatbot .Use your Own openai-api key & huggingface-access-tokens
- Host: GitHub
- URL: https://github.com/balaji1233/my_llm_projects-q-a-cbot
- Owner: balaji1233
- Created: 2023-11-29T16:07:47.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-12-02T07:58:38.000Z (over 1 year ago)
- Last Synced: 2023-12-03T08:36:15.001Z (over 1 year ago)
- Topics: docker, flask, huggingface-access-tokens, huggingface-api, huggingface-spaces, langchain, openai-api, python3, streamlit
- Language: Jupyter Notebook
- Homepage: https://myllmprojects-rcgrgpsxzwjvafhuhb7lva.streamlit.app/
- Size: 26.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# MY_LLM_Projects
# How to run?
### STEPS:
Clone the repository
```bash
https://github.com/balaji1233/MY_LLM_Projects-Q-A-Cbot.git
```
### STEP 01- Create a conda environment after opening the repository
```bash
conda create -n cnncls python=3.8 -y
```
```bash
conda activate cnncls
```
### STEP 02- install the requirements
```bash
pip install -r requirements.txt
```
```bash
# Finally run the following command
python app.py
```
Now,
```bash
open up you local host and port
```
# AWS-CICD-Deployment-with-Github-Actions
## 1. Login to AWS console.
## 2. Create IAM user for deployment
#with specific access
1. EC2 access : It is virtual machine
2. ECR: Elastic Container registry to save your docker image in aws
#Description: About the deployment
1. Build docker image of the source code
2. Push your docker image to ECR
3. Launch Your EC2
4. Pull Your image from ECR in EC2
5. Lauch your docker image in EC2
#Policy:
1. AmazonEC2ContainerRegistryFullAccess
2. AmazonEC2FullAccess
## 3. Create ECR repo to store/save docker image
- Save the URI: 566373416292.dkr.ecr.us-east-1.amazonaws.com/chicken
## 4. Create EC2 machine (Ubuntu)
## 5. Open EC2 and Install docker in EC2 Machine:
#optinal
sudo apt-get update -y
sudo apt-get upgrade
#required
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker ubuntu
newgrp docker
# 6. Configure EC2 as self-hosted runner:
setting>actions>runner>new self hosted runner> choose os> then run command one by one
# 7. Setup github secrets:
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_REGION = us-east-1
AWS_ECR_LOGIN_URI = demo>> 566373416292.dkr.ecr.ap-south-1.amazonaws.com
ECR_REPOSITORY_NAME = simple-app
## Deployment Steps:
1. Build the Docker image of the Source Code
2. Push the Docker image to Container Registry
3. Launch the Web App Server in Azure
4. Pull the Docker image from the container registry to Web App server and run