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⚙️ adding settings doc
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# Settings | ||
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## Settings Class Overview | ||
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The configuration settings for Funcchain are encapsulated within the `FuncchainSettings` class. This class inherits from Pydantic's `BaseSettings`. | ||
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`funcchain/config.py` | ||
```python | ||
class FuncchainSettings(BaseSettings): | ||
... | ||
``` | ||
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## Setting Descriptions | ||
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### General Settings | ||
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- `LLM: BaseChatModel | RunnableWithFallbacks | None = None` | ||
Defines the language learning model to be used. It can be a type of `BaseChatModel`, `RunnableWithFallbacks`, or `None`. | ||
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- `VERBOSE: bool = True` | ||
Enables or disables verbose logging. | ||
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### Prompt Settings | ||
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- `MAX_TOKENS: int = 4096` | ||
Specifies the maximum number of tokens for chat models. | ||
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- `DEFAULT_SYSTEM_PROMPT: str = "You are a professional assistant solving tasks."` | ||
Default prompt used for initializing the system. | ||
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### API Keys | ||
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- `OPENAI_API_KEY: Optional[str] = None` | ||
API key for the OpenAI service. | ||
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- `AZURE_API_KEY: Optional[str] = None` | ||
API key for the Azure service. | ||
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- `ANTHROPIC_API_KEY: Optional[str] = None` | ||
API key for the Anthropic service. | ||
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- `GOOGLE_API_KEY: Optional[str] = None` | ||
API key for the Google service. | ||
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- `JINACHAT_API_KEY: Optional[str] = None` | ||
API key for the JinaChat service. | ||
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### Azure Settings | ||
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- `AZURE_API_BASE: Optional[str] = None` | ||
Base URL for the Azure API. | ||
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- `AZURE_DEPLOYMENT_NAME: str = "gpt-4"` | ||
Deployment name for the Azure service. | ||
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- `AZURE_DEPLOYMENT_NAME_LONG: Optional[str] = None` | ||
Extended deployment name for the Azure service, if applicable. | ||
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- `AZURE_API_VERSION: str = "2023-07-01-preview"` | ||
API version for the Azure service. | ||
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### Model Keyword Arguments | ||
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- `MODEL_NAME: str = "openai::gpt-3.5-turbo"` | ||
Name of the language model. | ||
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- `MODEL_TEMPERATURE: float = 0.1` | ||
Controls the randomness in the model's output. | ||
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- `MODEL_REQUEST_TIMEOUT: float = 210` | ||
Timeout for the model API request, in seconds. | ||
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- `MODEL_VERBOSE: bool = False` | ||
Enables or disables verbose logging for the model. | ||
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### Additional Methods | ||
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- `model_kwargs(self) -> dict[str, Any]` | ||
Method that returns a dictionary of keyword arguments for the model initialization based on the settings. |