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Check it out →Dealing with long form content can be difficult, as models have limited context length. Let's learn some strategies for effectively handling long form content.
Before passing the long form content to a language model, it is helpful to preprocess the text to reduce its length and complexity. Some strategies for preprocessing include:
These preprocessing steps can help to reduce the length of the content and improve the model's ability to understand and generate responses.
Instead of providing the entire long form content to the model at once, it can be divided into smaller chunks or sections. These chunks can be processed individually, allowing the model to focus on a specific section at a time.
An iterative approach can be adopted to handle long form content. The model can generate responses for each chunk of text, and the generated output can serve as part of the input with the next chunk. This way, the conversation with the language model can progress in a step-by-step manner, effectively managing the length of the conversation.
The initial responses generated by the model might be lengthy or contain unnecessary information. It is important to perform post-processing on these responses to refine and condense them.
Some post-processing techniques include:
By refining the responses, the generated content can be made more concise and easier to understand.
While some language models have limited context length, there are AI assistants, like OpenAI's GPT-4 and Anthropic's Claude, that support longer conversations. These assistants can handle longer form content more effectively and provide more accurate responses without the need for extensive workarounds.
Python libraries like Llama Index and Langchain can be used to deal with long form content. In particular, Llama Index can "index" the content into smaller parts then perform a vector search to find which part of the content is most relevent, and solely use that. Langchain can perform recursive summaries over chunks of text in which in summarizes one chunk and includes that in the prompt with the next chunk to be summarized.
Dealing with long form content can be challenging, but by employing these strategies, you can effectively manage and navigate through the content with the assistance of language models. Remember to experiment, iterate, and refine your approach to determine the most effective strategy for your specific needs.