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2d27a9f956
This mode behaves the same as the openai mode, except that it allows setting custom models not supported by OpenAI. It can be used with any tool that serves models from an OpenAI compatible API. Implements #1424
104 lines
3.6 KiB
Text
104 lines
3.6 KiB
Text
## Running the Server
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PrivateGPT supports running with different LLMs & setups.
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### Local models
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Both the LLM and the Embeddings model will run locally.
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Make sure you have followed the *Local LLM requirements* section before moving on.
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This command will start PrivateGPT using the `settings.yaml` (default profile) together with the `settings-local.yaml`
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configuration files. By default, it will enable both the API and the Gradio UI. Run:
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```bash
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PGPT_PROFILES=local make run
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```
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or
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```bash
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PGPT_PROFILES=local poetry run python -m private_gpt
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```
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When the server is started it will print a log *Application startup complete*.
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Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API
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using Swagger UI.
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### Using OpenAI
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If you cannot run a local model (because you don't have a GPU, for example) or for testing purposes, you may
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decide to run PrivateGPT using OpenAI as the LLM and Embeddings model.
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In order to do so, create a profile `settings-openai.yaml` with the following contents:
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```yaml
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llm:
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mode: openai
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openai:
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api_base: <openai-api-base-url> # Defaults to https://api.openai.com/v1
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api_key: <your_openai_api_key> # You could skip this configuration and use the OPENAI_API_KEY env var instead
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model: <openai_model_to_use> # Optional model to use. Default is "gpt-3.5-turbo"
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# Note: Open AI Models are listed here: https://platform.openai.com/docs/models
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```
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And run PrivateGPT loading that profile you just created:
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`PGPT_PROFILES=openai make run`
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or
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`PGPT_PROFILES=openai poetry run python -m private_gpt`
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When the server is started it will print a log *Application startup complete*.
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Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API.
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You'll notice the speed and quality of response is higher, given you are using OpenAI's servers for the heavy
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computations.
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### Using OpenAI compatible API
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Many tools, including [LocalAI](https://localai.io/) and [vLLM](https://docs.vllm.ai/en/latest/),
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support serving local models with an OpenAI compatible API. Even when overriding the `api_base`,
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using the `openai` mode doesn't allow you to use custom models. Instead, you should use the `openailike` mode:
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```yaml
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llm:
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mode: openailike
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```
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This mode uses the same settings as the `openai` mode.
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As an example, you can follow the [vLLM quickstart guide](https://docs.vllm.ai/en/latest/getting_started/quickstart.html#openai-compatible-server)
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to run an OpenAI compatible server. Then, you can run PrivateGPT using the `settings-vllm.yaml` profile:
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`PGPT_PROFILES=vllm make run`
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### Using AWS Sagemaker
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For a fully private & performant setup, you can choose to have both your LLM and Embeddings model deployed using Sagemaker.
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Note: how to deploy models on Sagemaker is out of the scope of this documentation.
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In order to do so, create a profile `settings-sagemaker.yaml` with the following contents (remember to
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update the values of the llm_endpoint_name and embedding_endpoint_name to yours):
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```yaml
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llm:
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mode: sagemaker
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sagemaker:
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llm_endpoint_name: huggingface-pytorch-tgi-inference-2023-09-25-19-53-32-140
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embedding_endpoint_name: huggingface-pytorch-inference-2023-11-03-07-41-36-479
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```
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And run PrivateGPT loading that profile you just created:
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`PGPT_PROFILES=sagemaker make run`
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or
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`PGPT_PROFILES=sagemaker poetry run python -m private_gpt`
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When the server is started it will print a log *Application startup complete*.
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Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API.
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