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refactor(agent/config): Modularize Config and revive Azure support (#6497)

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* feat: Refactor config loading and initialization to be modular and decentralized

   - Refactored the `ConfigBuilder` class to support modular loading and initialization of the configuration from environment variables.
   - Implemented recursive loading and initialization of nested config objects.
   - Introduced the `SystemConfiguration` base class to provide common functionality for all system settings.
   - Added the `from_env` attribute to the `UserConfigurable` decorator to provide environment variable mappings.
   - Updated the `Config` class and its related classes to inherit from `SystemConfiguration` and use the `UserConfigurable` decorator.
   - Updated `LoggingConfig` and `TTSConfig` to use the `UserConfigurable` decorator for their fields.
   - Modified the implementation of the `build_config_from_env` method in `ConfigBuilder` to utilize the new modular and recursive loading and initialization logic.
   - Updated applicable test cases to reflect the changes in the config loading and initialization logic.

   This refactor improves the flexibility and maintainability of the configuration loading process by introducing modular and recursive behavior, allowing for easier extension and customization through environment variables.

* refactor: Move OpenAI credentials into `OpenAICredentials` sub-config

   - Move OpenAI API key and other OpenAI credentials from the global config to a new sub-config called OpenAICredentials.
   - Update the necessary code to use the new OpenAICredentials sub-config instead of the global config when accessing OpenAI credentials.
   - (Hopefully) unbreak Azure support.
      - Update azure.yaml.template.
   - Enable validation of assignment operations on SystemConfiguration and SystemSettings objects.

* feat: Update AutoGPT configuration options and setup instructions

   - Added new configuration options for logging and OpenAI usage to .env.template
   - Removed deprecated configuration options in config/config.py
   - Updated setup instructions in Docker and general setup documentation to include information on using Azure's OpenAI services

* fix: Fix image generation with Dall-E

   - Fix issue with image generation with Dall-E API

Additional user context: This commit fixes an issue with image generation using the Dall-E API. The code now correctly retrieves the API key from the agent's legacy configuration.

* refactor(agent/core): Refactor `autogpt.core.configuration.schema` and update docstrings

   - Refactor the `schema.py` file in the `autogpt.core.configuration` module.
   - Added docstring to `SystemConfiguration.from_env()`
   - Updated docstrings for functions `_get_user_config_values`, `_get_non_default_user_config_values`, `_recursive_init_model`, `_recurse_user_config_fields`, and `_recurse_user_config_values`.
This commit is contained in:
Reinier van der Leer
2023-12-05 16:28:23 +01:00
committed by GitHub
parent 03eb921ca6
commit 7b05245286
17 changed files with 666 additions and 401 deletions
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2
docs/content/AutoGPT/setup/docker.md
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@@ -144,7 +144,7 @@ found in the [repository].
**Note:** Azure support has been dropped in `master`, so these instructions will only work with v0.4.7 (or earlier).
[repository]: https://github.com/Significant-Gravitas/AutoGPT/autogpts/autogpt
[repository]: https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpts/autogpt
[show hidden files/Windows]: https://support.microsoft.com/en-us/windows/view-hidden-files-and-folders-in-windows-97fbc472-c603-9d90-91d0-1166d1d9f4b5
[show hidden files/macOS]: https://www.pcmag.com/how-to/how-to-access-your-macs-hidden-files
[openai-python docs]: https://github.com/openai/openai-python#microsoft-azure-endpoints

22
docs/content/AutoGPT/setup/index.md
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@@ -88,6 +88,28 @@ Once you have cloned or downloaded the project, you can find the AutoGPT Agent i
```yaml
OPENAI_API_KEY=sk-qwertykeys123456
```
!!! info "Using a GPT Azure-instance"
If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and
make an Azure configuration file.
Rename `azure.yaml.template` to `azure.yaml` and provide the relevant
`azure_api_base`, `azure_api_version` and deployment IDs for the models that you
want to use.
E.g. if you want to use `gpt-3.5-turbo-16k` and `gpt-4-0314`:
```yaml
# Please specify all of these values as double-quoted strings
# Replace string in angled brackets (<>) to your own deployment Name
azure_model_map:
gpt-3.5-turbo-16k: "<auto-gpt-deployment>"
...
```
Details can be found in the [openai-python docs], and in the [Azure OpenAI docs] for the embedding model.
If you're on Windows you may need to install an [MSVC library](https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170).
6. Enter any other API keys or tokens for services you would like to use.
!!! note