HuggingFaceReader¶

Overview¶

The HuggingFaceReader class is designed to interface with Hugging Face's models to generate text based on a given prompt. It extends the BaseLLMReader class and uses the transformers library to communicate with the models.

Installation¶

Install the transformers library:
```
pip install transformers
```

Example Usage¶

Here's an example demonstrating how to use the HuggingFaceReader class:

from euler.llm_readers import HuggingFaceReader

# Initialize the HuggingFaceReader
huggingface_reader = HuggingFaceReader(
    api_key='your_hugging_face_api_key_here',
    model_id='gpt2'
)

# Generate text based on the input prompt
text = "Once upon a time in a faraway land,"
response = huggingface_reader.read(text)
print(response.text if response else "No response received.")

Using LLMReaderFactory¶

The LLMReaderFactory class can be used to easily initialize different LLM readers, including HuggingFaceReader.

from euler.llm_readers import LLMReaderFactory

# Initialize the HuggingFaceReader using LLMReaderFactory
huggingface_reader = LLMReaderFactory.get_llm_reader(
    reader_type='huggingface',
    api_key='your_hugging_face_api_key_here',
    model_id='gpt2'
)

# Generate text based on the input prompt
text = "Once upon a time in a faraway land,"
response = huggingface_reader.read(text)
print(response.text if response else "No response received.")

Classes and Methods¶

`HuggingFaceConfig`¶

The HuggingFaceConfig class is a configuration model that holds the API key, model ID, and an optional default prompt.

Attributes: - api_key (str): The API key for accessing the Hugging Face API. - model_id (str): The model ID to use for generating responses. - default_prompt (Optional[str]): A default prompt to use if no custom prompt is provided.

`HuggingFaceResponse`¶

The HuggingFaceResponse class represents the response from the Hugging Face API.

Attributes: - text (str): The response text generated by the Hugging Face model.