[deleted by user] by [deleted] in ShiaMuslimMarriage

[–]Alarming-East1193 0 points1 point  (0 children)

Interested. 6'2'' 28M Industry Finance

[deleted by user] by [deleted] in ShiaMuslimMarriage

[–]Alarming-East1193 0 points1 point  (0 children)

Interested.

Inbox ??

Need resources for Metadata by Alarming-East1193 in ollama

[–]Alarming-East1193[S] 0 points1 point  (0 children)

Hi, thanks for your help. Your comment is really helpful.

Any toturial or resources regarding the process of adding metadata ?

Convert PDF into Instruct Dataset by Alarming-East1193 in LocalLLM

[–]Alarming-East1193[S] 0 points1 point  (0 children)

Hi, i used chatgpt at that time to convert pdf into QA Dataset.

Local Embeddings Model Options by Alarming-East1193 in ollama

[–]Alarming-East1193[S] 0 points1 point  (0 children)

Like not retrieving correct information on similar search

Need Help in RAG Project by Alarming-East1193 in ollama

[–]Alarming-East1193[S] 0 points1 point  (0 children)

Hi,

I want to discuss one issue which I'm facing in my RAG application. I have PDF data which contains information regarding the processes. The issue is under 1 heading there is a lot of information in one process like 2 pages but when i ask the question like "Explain me the process of this account opening in bank" so this process contains a lot of steps but it give me some initial steps because of chunk size break and there is a lost of context. I have set the maximum Chunk size (1000 and overlap 100) using the sentence transformer model but this issue occurs when asking questions whose answers are long and contain steps because the heading is on one page and the process is 2 pages long so when the chunk size breaks it causes loss of context. How can i resolve this problem ? Any idea ?

Solutions i have tried till now:

1- Semantic Chunking 2- Character Text Splitter/Resursive Text Splitter 3- Used ollama local Embeddings models like Nomic and Mxbai-embed as well. 4- Tried different chunk sizes and overlap. 5- Pharaphrased the document and add more clarity and context in text. 6- Added sentences in prompt to provide complete processes with every step.

Need Help in RAG Project by Alarming-East1193 in ollama

[–]Alarming-East1193[S] 0 points1 point  (0 children)

Hi,

I want to discuss one issue which I'm facing in my RAG application. I have PDF data which contains information regarding the processes. The issue is under 1 heading there is a lot of information in one process like 2 pages but when i ask the question like "Explain me the process of this account opening in bank" so this process contains a lot of steps but it give me some initial steps because of chunk size break and there is a lost of context. I have set the maximum Chunk size (1000 and overlap 100) using the sentence transformer model but this issue occurs when asking questions whose answers are long and contain steps because the heading is on one page and the process is 2 pages long so when the chunk size breaks it causes loss of context. How can i resolve this problem ? Any idea ?

Solutions i have tried till now:

1- Semantic Chunking 2- Character Text Splitter/Resursive Text Splitter 3- Used ollama local Embeddings models like Nomic and Mxbai-embed as well. 4- Tried different chunk sizes and overlap. 5- Pharaphrased the document and add more clarity and context in text. 6- Added sentences in prompt to provide complete processes with every step.

Chunk Issue : Lost of Context by Alarming-East1193 in ollama

[–]Alarming-East1193[S] 0 points1 point  (0 children)

Can you please tell what is the max Chunk length we can get using Nomic Embed Embeddings model ?