* Add default mode option to settings
* Revise default_mode to Literal (enum) and add to settings.yaml
* Revise to pass make check/test
* Default mode: RAG
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Co-authored-by: Jason <jason@sowinsight.solutions>
* Support for Google Gemini LLMs and Embeddings
Initial support for Gemini, enables usage of Google LLMs and embedding models (see settings-gemini.yaml)
Install via
poetry install --extras "llms-gemini embeddings-gemini"
Notes:
* had to bump llama-index-core to later version that supports Gemini
* poetry --no-update did not work: Gemini/llama_index seem to require more (transient) updates to make it work...
* fix: crash when gemini is not selected
* docs: add gemini llm
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Co-authored-by: Javier Martinez <javiermartinezalvarez98@gmail.com>
* Updated prompt_style to be moved to the main LLM setting since all LLMs from llama_index can utilize this. I also included temperature, context window size, max_tokens, max_new_tokens into the openailike to help ensure the settings are consistent from the other implementations.
* Removed prompt_style from llamacpp entirely
* Fixed settings-local.yaml to include prompt_style in the LLM settings instead of llamacpp.
* Added RAG settings to settings.py, vector_store and chat_service to add similarity_top_k and similarity_score
* Updated settings in vector and chat service per Ivans request
* Updated code for mypy
* Adding Postgres for the doc and index store
* Adding documentation. Rename postgres database local->simple. Postgres storage dependencies
* Update documentation for postgres storage
* Renaming feature to nodestore
* update docstore -> nodestore in doc
* missed some docstore changes in doc
* Updated poetry.lock
* Formatting updates to pass ruff/black checks
* Correction to unreachable code!
* Format adjustment to pass black test
* Adjust extra inclusion name for vector pg
* extra dep change for pg vector
* storage-postgres -> storage-nodestore-postgres
* Hash change on poetry lock
* 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
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
As discussed on Discord, the decision has been made to remove the system prompts by default, to better segregate the API and the UI usages.
A concurrent PR (#1353) is enabling the dynamic setting of a system prompt in the UI.
Therefore, if UI users want to use a custom system prompt, they can specify one directly in the UI.
If the API users want to use a custom prompt, they can pass it directly into their messages that they are passing to the API.
In the highlight of the two use case above, it becomes clear that default system_prompt does not need to exist.
* Fix the parallel ingestion mode, and make it available through conf
Also updated the documentation to show how to configure the ingest mode.
* PR feedback: redirect to documentation
* added max_new_tokens as a configuration option to the llm block in settings
* Update fern/docs/pages/manual/settings.mdx
Co-authored-by: lopagela <lpglm@orange.fr>
* Update private_gpt/settings/settings.py
Add default value for max_new_tokens = 256
Co-authored-by: lopagela <lpglm@orange.fr>
* Addressed location of docs comment
* reformatting from running 'make check'
* remove default config value from settings.yaml
---------
Co-authored-by: lopagela <lpglm@orange.fr>
* Add simple Basic auth
To enable the basic authentication, one must set `server.auth.enabled`
to true.
The static string defined in `server.auth.secret` must be set in the
header `Authorization`.
The health check endpoint will always be accessible, no matter the API
auth configuration.
* Fix linting and type check
* Fighting with mypy being too restrictive
Had to disable mypy in the `auth` as we are not using the same signature
for the authenticated method.
mypy was complaining that the signatures of `authenticated` must be
identical, no matter in which logical branch we are.
Given that fastapi is accomodating itself of method signatures (it will
inject the dependencies in the method call), this warning of mypy is
actually preventing us to do something legit.
mypy doc: https://mypy.readthedocs.io/en/stable/common_issues.html
* Write tests to verify that the simple auth is working
* Configure simple builtin logging
Changed the 2 existing `print` in the `private_gpt` code base into actual python logging, stop using loguru (dependency will be dropped in a later commit).
Try to use the `key=value` logging convention in logs (to indicate what dynamic values represents, and what is dynamic vs not).
Using `%s` log style, so that the string formatting is pushed inside the logger, giving the ability to the logger to determine if the string need to be formatted or not (i.e. strings from debug logs might not be formatted if the log level is not debug)
The (basic) builtin log configuration have been placed in `private_gpt/__init__.py` in order to initialize the logging system even before we start to launch any python code in `private_gpt` package (ensuring we get any initialization log formatted as we want to)
Disabled `uvicorn` custom logging format, resulting in having uvicorn logs being outputted in our formatted.
Some more concise format could be used if we want to, especially:
```
COMPACT_LOG_FORMAT = '%(asctime)s.%(msecs)03d [%(levelname)s] %(name)s - %(message)s'
```
Python documentation and cookbook on logging for reference:
* https://docs.python.org/3/library/logging.html
* https://docs.python.org/3/howto/logging.html
* Removing loguru from the dependencies
Result of `poetry remove loguru`
* PR feedback: using `logger` variable name instead of `log`
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Co-authored-by: Louis Melchior <louis@jaris.io>
