LLM/DocsGPT
1
0
Fork 0
mirror of https://github.com/arc53/DocsGPT.git synced 2025-11-29 16:43:16 +00:00
Code Issues Packages Projects Releases Wiki Activity

refactor: update docs LLM_NAME and MODEL_NAME to LLM_PROVIDER and LLM_NAME

Browse Source
This commit is contained in:
Alex
2025-06-11 12:30:34 +01:00
parent 3351f71813
commit aaecf52c99
10 changed files with 59 additions and 57 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
docs/pages/Models/cloud-providers.mdx
View File

@@ -13,15 +13,15 @@ The primary method for configuring your LLM provider in DocsGPT is through the `
To connect to a cloud LLM provider, you will typically need to configure the following basic settings in your `.env` file:
* **`LLM_NAME`**: This setting is essential and identifies the specific cloud provider you wish to use (e.g., `openai`, `google`, `anthropic`).
* **`MODEL_NAME`**: Specifies the exact model you want to utilize from your chosen provider (e.g., `gpt-4o`, `gemini-2.0-flash`, `claude-3-5-sonnet-latest`). Refer to your provider's documentation for a list of available models.
* **`LLM_PROVIDER`**: This setting is essential and identifies the specific cloud provider you wish to use (e.g., `openai`, `google`, `anthropic`).
* **`LLM_NAME`**: Specifies the exact model you want to utilize from your chosen provider (e.g., `gpt-4o`, `gemini-2.0-flash`, `claude-3-5-sonnet-latest`). Refer to your provider's documentation for a list of available models.
* **`API_KEY`**: Almost all cloud LLM providers require an API key for authentication. Obtain your API key from your chosen provider's platform and securely store it in your `.env` file.
## Explicitly Supported Cloud Providers
DocsGPT offers direct, streamlined support for the following cloud LLM providers, making configuration straightforward. The table below outlines the `LLM_NAME` and example `MODEL_NAME` values to use for each provider in your `.env` file.
DocsGPT offers direct, streamlined support for the following cloud LLM providers, making configuration straightforward. The table below outlines the `LLM_PROVIDER` and example `LLM_NAME` values to use for each provider in your `.env` file.
| Provider | `LLM_NAME` | Example `MODEL_NAME` |
| Provider | `LLM_PROVIDER` | Example `LLM_NAME` |
| :--------------------------- | :------------- | :-------------------------- |
| DocsGPT Public API | `docsgpt` | `None` |
| OpenAI | `openai` | `gpt-4o` |
@@ -35,16 +35,16 @@ DocsGPT offers direct, streamlined support for the following cloud LLM providers
DocsGPT's flexible architecture allows you to connect to any cloud provider that offers an API compatible with the OpenAI API standard. This opens up a vast ecosystem of LLM services.
To connect to an OpenAI-compatible cloud provider, you will still use `LLM_NAME=openai` in your `.env` file. However, you will also need to specify the API endpoint of your chosen provider using the `OPENAI_BASE_URL` setting. You will also likely need to provide an `API_KEY` and `MODEL_NAME` as required by that provider.
To connect to an OpenAI-compatible cloud provider, you will still use `LLM_PROVIDER=openai` in your `.env` file. However, you will also need to specify the API endpoint of your chosen provider using the `OPENAI_BASE_URL` setting. You will also likely need to provide an `API_KEY` and `LLM_NAME` as required by that provider.
**Example for DeepSeek (OpenAI-Compatible API):**
To connect to DeepSeek, which offers an OpenAI-compatible API, your `.env` file could be configured as follows:
```
LLM_NAME=openai
LLM_PROVIDER=openai
API_KEY=YOUR_API_KEY # Your DeepSeek API key
MODEL_NAME=deepseek-chat # Or your desired DeepSeek model name
LLM_NAME=deepseek-chat # Or your desired DeepSeek model name
OPENAI_BASE_URL=https://api.deepseek.com/v1 # DeepSeek's OpenAI API URL
```

2
docs/pages/Models/embeddings.md
View File

@@ -60,7 +60,7 @@ To use OpenAI's `text-embedding-ada-002` embedding model, you need to set `EMBED
**Example `.env` configuration for OpenAI Embeddings:**
```
LLM_NAME=openai
LLM_PROVIDER=openai
API_KEY=YOUR_OPENAI_API_KEY # Your OpenAI API Key
EMBEDDINGS_NAME=openai_text-embedding-ada-002
```

24
docs/pages/Models/local-inference.mdx
View File

@@ -15,8 +15,8 @@ Setting up a local inference engine with DocsGPT is configured through environme
To connect to a local inference engine, you will generally need to configure these settings in your `.env` file:
* **`LLM_NAME`**: Crucially set this to `openai`. This tells DocsGPT to use the OpenAI-compatible API format for communication, even though the LLM is local.
* **`MODEL_NAME`**: Specify the model name as recognized by your local inference engine. This might be a model identifier or left as `None` if the engine doesn't require explicit model naming in the API request.
* **`LLM_PROVIDER`**: Crucially set this to `openai`. This tells DocsGPT to use the OpenAI-compatible API format for communication, even though the LLM is local.
* **`LLM_NAME`**: Specify the model name as recognized by your local inference engine. This might be a model identifier or left as `None` if the engine doesn't require explicit model naming in the API request.
* **`OPENAI_BASE_URL`**: This is essential. Set this to the base URL of your local inference engine's API endpoint. This tells DocsGPT where to find your local LLM server.
* **`API_KEY`**: Generally, for local inference engines, you can set `API_KEY=None` as authentication is usually not required in local setups.
@@ -24,16 +24,16 @@ To connect to a local inference engine, you will generally need to configure the
DocsGPT is readily configurable to work with the following local inference engines, all communicating via the OpenAI API format. Here are example `OPENAI_BASE_URL` values for each, based on default setups:
| Inference Engine | `LLM_NAME` | `OPENAI_BASE_URL` |
| :---------------------------- | :--------- | :------------------------- |
| LLaMa.cpp | `openai` | `http://localhost:8000/v1` |
| Ollama | `openai` | `http://localhost:11434/v1` |
| Text Generation Inference (TGI)| `openai` | `http://localhost:8080/v1` |
| SGLang | `openai` | `http://localhost:30000/v1` |
| vLLM | `openai` | `http://localhost:8000/v1` |
| Aphrodite | `openai` | `http://localhost:2242/v1` |
| FriendliAI | `openai` | `http://localhost:8997/v1` |
| LMDeploy | `openai` | `http://localhost:23333/v1` |
| Inference Engine | `LLM_PROVIDER` | `OPENAI_BASE_URL` |
| :---------------------------- | :------------- | :------------------------- |
| LLaMa.cpp | `openai` | `http://localhost:8000/v1` |
| Ollama | `openai` | `http://localhost:11434/v1` |
| Text Generation Inference (TGI)| `openai` | `http://localhost:8080/v1` |
| SGLang | `openai` | `http://localhost:30000/v1` |
| vLLM | `openai` | `http://localhost:8000/v1` |
| Aphrodite | `openai` | `http://localhost:2242/v1` |
| FriendliAI | `openai` | `http://localhost:8997/v1` |
| LMDeploy | `openai` | `http://localhost:23333/v1` |
**Important Note on `localhost` vs `host.docker.internal`:**