From 8cda5798487a8c908aac17c059a0ab32c6060c86 Mon Sep 17 00:00:00 2001 From: Daniel Glogowski Date: Sun, 29 Dec 2024 22:21:49 -0800 Subject: [PATCH] readme updates --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 017534f..0beaf54 100644 --- a/README.md +++ b/README.md @@ -16,7 +16,7 @@ You can view a mermaid diagram of our system [here](docs/README.md). echo "MAX_CONCURRENT_REQUESTS=1" >> .env ``` - Note that in production we use the NVIDIA Eleven Labs API key which can handle concurrent requests. For local development, you may want to set `MAX_CONCURRENT_REQUESTS=1` to avoid rate limiting issues. You can generate your own testing API key for free [here](https://elevenlabs.io/). + Note that in production we use the NVIDIA Eleven Labs API key, which can handle concurrent requests. For local development, you may want to set `MAX_CONCURRENT_REQUESTS=1` to avoid rate-limiting issues. You can generate your own testing API key for free [here](https://elevenlabs.io/). 2. **Install Dependencies**: We use UV to manage python dependencies. @@ -65,7 +65,7 @@ echo "MODEL_API_URL=> .env ### Using `nv-ingest` -We also support using a fork of NVIDIA's [NV-Ingest](https://github.com/NVIDIA/NV-Ingest) as our PDF service. This requires 2 A100-SXM machines. See the [repo](https://github.com/jdye64/nv-ingest/tree/brev-dev-convert-endpoint) for more information. If you would like to use this, you can add the following to your `.env` file: +We also support using a fork of NVIDIA's [NV-Ingest](https://github.com/NVIDIA/NV-Ingest) as our PDF service. This requires two A100-SXM machines. See the [repo](https://github.com/jdye64/nv-ingest/tree/brev-dev-convert-endpoint) for more information. If you would like to use this, you can add the following to your `.env` file: ```bash echo "MODEL_API_URL=/v1" >> .env ``` @@ -73,7 +73,7 @@ echo "MODEL_API_URL=/v1" >> .env ## Selecting LLMs -We currently use an ensemble of 3 LLMS to generate these podcasts. Out of the box, we recommend using the LLama 3.1-70B NIM. If you would like to use a different model, you can update the `models.json` file with the desired model. The default `models.json` calls a NIM that I have currently hosted. Feel free to use it as you develop locally. When you deploy, please use our NIM API Catalog endpoints. +We currently use an ensemble of 3 LLMS to generate these podcasts. Out of the box, we recommend using the LLama 3.1-70B NIM. If you would like to use a different model, you can update the `models.json` file with the desired model. The default `models.json` calls a NIM that we have currently hosted. Feel free to use it as you develop locally. When you deploy, please use our NIM API Catalog endpoints. ## Optimizing for GPU usage @@ -93,7 +93,7 @@ make ruff # Runs both lint and format ## CI/CD We use GitHub Actions for CI/CD. We run the following actions: - `ruff`: Runs linting and formatting -- `pr-test`: Runs an e2e podcast test on the PR +- `pr-test`: Runs an end-to-end podcast test on the PR - `build-and-push`: Builds and pushes a new container image to the remote repo. This is used to update production deployments ## Contributing