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Refactor LLM class initialization and add note about default value of num_ctx parameter

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lasseedfast 2024-10-07 17:24:40 +02:00
parent 54eece5d39
commit 8d5da7a5cd
2 changed files with 7 additions and 8 deletions
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2
README.md
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@ -172,6 +172,8 @@ A Streamlit example is provided in `example_streamlit_app.py` to demonstrate how
- `use_ollama(self, model)`: Configures the class to use Ollama for generating responses.
- `async generate(self, prompt)`: Asynchronously generates a response based on the provided prompt.
**Note:** The `num_ctx` parameter is set to 20000 by default, which may not be sufficient for all use cases. Adjust this value based on your specific requirements.
## Contributing
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

11
highlight_pdf.py
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@ -46,8 +46,8 @@ class LLM:
Attributes:
model (str): The model to be used for generating responses.
num_ctx (int): The number of context tokens to be used. Defaults to 20000.
temperature (float): The temperature setting for the model's response generation.
num_ctx (int): The number of context tokens to be used.
keep_alive (int): The keep-alive duration for the connection.
options (dict): Options for the model's response generation.
memory (bool): Whether to retain conversation history.
@ -70,11 +70,11 @@ class LLM:
def __init__(
self,
num_ctx=20000,
openai_key=False,
model=None,
temperature=0,
system_prompt=None,
num_ctx=None,
memory=True,
keep_alive=3600,
):
@ -86,7 +86,7 @@ class LLM:
model (str, optional): The model to be used. Defaults to None.
temperature (float, optional): Sampling temperature for the model. Defaults to 0.
system_prompt (str, optional): Initial system prompt for the model. Defaults to None.
num_ctx (int, optional): Number of context tokens. Defaults to None.
context_window (int, optional): Number of context tokens. Defaults to None.
memory (bool, optional): Whether to use memory. Defaults to True.
keep_alive (int, optional): Keep-alive duration in seconds. Defaults to 3600.
"""
@ -96,12 +96,9 @@ class LLM:
else:
self.model = os.getenv("LLM_MODEL")
self.temperature = temperature
self.num_ctx = num_ctx
self.keep_alive = keep_alive
self.options = {"temperature": self.temperature}
self.options = {"temperature": self.temperature, num_ctx: num_ctx}
self.memory = memory
if self.num_ctx:
self.options["num_ctx"] = self.num_ctx
if system_prompt:
self.messages = [{"role": "system", "content": system_prompt}]
else: