Update GPT Index --> Llama Index (#1087)

docs/intermediate/long_form_content.md

@@ -40,8 +40,8 @@ While some language models have limited context length, there are AI assistants,
 
 ## 6. Code libraries
 
-Python libraries like [Llama Index](https://github.com/jerryjliu/llama_index) and [Langchain](https://github.com/langchain-ai/langchain) can be used to deal with long form content. In particular, GPT 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.
+Python libraries like [Llama Index](https://github.com/jerryjliu/llama_index) and [Langchain](https://github.com/langchain-ai/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.
 
 ## Conclusion
 
-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.
+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.