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Update environment variables and installation instructions

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Alex
2024-01-09 12:35:18 +00:00
parent 060c59e97d
commit c0f7b344d9
1 changed files with 14 additions and 6 deletions
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@@ -91,13 +91,13 @@ It will install all the dependencies and allow you to download the local model,
Otherwise, refer to this Guide:
1. Download and open this repository with `git clone https://github.com/arc53/DocsGPT.git`
2. Create a `.env` file in your root directory and set the env variable `API_KEY` with your [OpenAI API key](https://platform.openai.com/account/api-keys) and `VITE_API_STREAMING` to true or false, depending on whether you want streaming answers or not.
2. Create a `.env` file in your root directory and set the env variables and `VITE_API_STREAMING` to true or false, depending on whether you want streaming answers or not.
It should look like this inside:
```
LLM_NAME=[docsgpt or openai or others]
API_KEY=Yourkey
VITE_API_STREAMING=true
API_KEY=[if LLM_NAME is openai]
```
See optional environment variables in the [/.env-template](https://github.com/arc53/DocsGPT/blob/main/.env-template) and [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) files.
@@ -148,14 +148,22 @@ python -m venv venv
venv/Scripts/activate
```
3. Change to the `application/` subdir by the command `cd application/` and install dependencies for the backend:
3. Download embedding model and save it in the `model/` folder:
You can use the script below, or download it manually from [here](https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip), unzip it and save it in the `model/` folder.
```commandline
pip install -r application/requirements.txt
wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
unzip mpnet-base-v2.zip -d model
rm mpnet-base-v2.zip
4. Change to the `application/` subdir by the command `cd application/` and install dependencies for the backend:
```commandline
pip install -r requirements.txt
```
4. Run the app using `flask --app application/app.py run --host=0.0.0.0 --port=7091`.
5. Start worker with `celery -A application.app.celery worker -l INFO`.
5. Run the app using `flask --app application/app.py run --host=0.0.0.0 --port=7091`.
6. Start worker with `celery -A application.app.celery worker -l INFO`.
### Start Frontend