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feat: Upgrade to LlamaIndex to 0.10 (#1663)
* Extract optional dependencies * Separate local mode into llms-llama-cpp and embeddings-huggingface for clarity * Support Ollama embeddings * Upgrade to llamaindex 0.10.14. Remove legacy use of ServiceContext in ContextChatEngine * Fix vector retriever filters
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@ -25,6 +25,30 @@ 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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#### Customizing low level parameters
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Currently, not all the parameters of `llama.cpp` and `llama-cpp-python` are available at PrivateGPT's `settings.yaml` file.
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In case you need to customize parameters such as the number of layers loaded into the GPU, you might change
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these at the `llm_component.py` file under the `private_gpt/components/llm/llm_component.py`.
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##### Available LLM config options
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The `llm` section of the settings allows for the following configurations:
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- `mode`: how to run your llm
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- `max_new_tokens`: this lets you configure the number of new tokens the LLM will generate and add to the context window (by default Llama.cpp uses `256`)
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Example:
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```yaml
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llm:
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mode: local
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max_new_tokens: 256
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```
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If you are getting an out of memory error, you might also try a smaller model or stick to the proposed
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recommended models, instead of custom tuning the parameters.
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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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