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Merge pull request #8 from goudete/adding-settings-doc
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⚙️ adding settings doc
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shroominic authored Oct 26, 2023
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# Settings

## Settings Class Overview

The configuration settings for Funcchain are encapsulated within the `FuncchainSettings` class. This class inherits from Pydantic's `BaseSettings`.

`funcchain/config.py`
```python
class FuncchainSettings(BaseSettings):
...
```

## Setting Descriptions

### General Settings

- `LLM: BaseChatModel | RunnableWithFallbacks | None = None`
Defines the language learning model to be used. It can be a type of `BaseChatModel`, `RunnableWithFallbacks`, or `None`.

- `VERBOSE: bool = True`
Enables or disables verbose logging.

### Prompt Settings

- `MAX_TOKENS: int = 4096`
Specifies the maximum number of tokens for chat models.

- `DEFAULT_SYSTEM_PROMPT: str = "You are a professional assistant solving tasks."`
Default prompt used for initializing the system.

### API Keys

- `OPENAI_API_KEY: Optional[str] = None`
API key for the OpenAI service.

- `AZURE_API_KEY: Optional[str] = None`
API key for the Azure service.

- `ANTHROPIC_API_KEY: Optional[str] = None`
API key for the Anthropic service.

- `GOOGLE_API_KEY: Optional[str] = None`
API key for the Google service.

- `JINACHAT_API_KEY: Optional[str] = None`
API key for the JinaChat service.

### Azure Settings

- `AZURE_API_BASE: Optional[str] = None`
Base URL for the Azure API.

- `AZURE_DEPLOYMENT_NAME: str = "gpt-4"`
Deployment name for the Azure service.

- `AZURE_DEPLOYMENT_NAME_LONG: Optional[str] = None`
Extended deployment name for the Azure service, if applicable.

- `AZURE_API_VERSION: str = "2023-07-01-preview"`
API version for the Azure service.

### Model Keyword Arguments

- `MODEL_NAME: str = "openai::gpt-3.5-turbo"`
Name of the language model.

- `MODEL_TEMPERATURE: float = 0.1`
Controls the randomness in the model's output.

- `MODEL_REQUEST_TIMEOUT: float = 210`
Timeout for the model API request, in seconds.

- `MODEL_VERBOSE: bool = False`
Enables or disables verbose logging for the model.

### Additional Methods

- `model_kwargs(self) -> dict[str, Any]`
Method that returns a dictionary of keyword arguments for the model initialization based on the settings.

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