Sweep: Document Insertion with time-weighted postprocessor

Here's the PR! https://github.com/kevinlu1248/llama_index/pull/10.

💎 Sweep Pro: I used GPT-4 to create this ticket. You have 33 GPT-4 tickets left.

Install Sweep Configs: Pull Request

Step 1: 🔍 Code Search

I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.

Some code snippets I looked at (click to expand). If some file is missing from here, you can mention the path in the ticket description.

https://github.com/kevinlu1248/llama_index/blob/50e6bfe8a976287f2b9e434f81115b95adca88ab/llama_index/indices/base.py#L113-L246 https://github.com/kevinlu1248/llama_index/blob/50e6bfe8a976287f2b9e434f81115b95adca88ab/tests/indices/postprocessor/test_base.py#L20-L335 https://github.com/kevinlu1248/llama_index/blob/50e6bfe8a976287f2b9e434f81115b95adca88ab/llama_index/indices/vector_store/base.py#L140-L267 https://github.com/kevinlu1248/llama_index/blob/50e6bfe8a976287f2b9e434f81115b95adca88ab/llama_index/vector_stores/redis.py#L75-L204 https://github.com/kevinlu1248/llama_index/blob/50e6bfe8a976287f2b9e434f81115b95adca88ab/llama_index/indices/postprocessor/node_recency.py#L134-L244

Step 2: 🧐 Snippet Analysis

From looking through the relevant snippets, I decided to make the following modifications:

File Path	Proposed Changes
`llama_index/indices/base.py`	Modify the `insert` and `insert_nodes` methods to apply the Time-Weighted Rerank postprocessor during the document insertion process. You will need to create an instance of the `TimeWeightedPostprocessor` class and call its `postprocess_nodes` method with the nodes to be inserted.
`llama_index/indices/vector_store/base.py`	Ensure that the document's metadata (including its timestamp) is properly stored in the index when the document is inserted. You may need to modify the `_add_nodes_to_index` and `_async_add_nodes_to_index` methods to include the document's timestamp in the metadata that is stored in the index.

Step 3: 📝 Planning

I have created a plan for writing the pull request. I am now working my plan and coding the required changes to address this issue. Here is the planned pull request:

Add Time-Weighted Rerank postprocessor to document insertion process sweep/add-time-weighted-rerank-postprocessor

Description

This PR adds support for the Time-Weighted Rerank postprocessor during the document insertion process in the LlamaIndex repository. The Time-Weighted Rerank postprocessor allows for better ranking of documents based on their recency.

Changes Made

Modified the insert and insert_nodes methods in llama_index/indices/base.py to apply the Time-Weighted Rerank postprocessor during the document insertion process.

Updated the _add_nodes_to_index and _async_add_nodes_to_index methods in llama_index/indices/vector_store/base.py to properly store the document's metadata (including its timestamp) in the index.

How to Test

Clone the repository and switch to the add-time-weighted-rerank-postprocessor branch.

Install the required dependencies.

Run the test suite to ensure that all existing tests pass.

Create a new document and insert it into the index using the modified insert or insert_nodes methods.

Verify that the Time-Weighted Rerank postprocessor is applied and the document is properly ranked based on its recency.

Related Issues

Resolves #[issue_number]

Checklist

[ ] I have tested the changes locally and verified that they work as expected.

[ ] I have added appropriate test cases to cover the changes.

[ ] I have updated the documentation, if necessary.

[ ] I have added a changelog entry, if applicable.

[ ] I have assigned the PR to myself.

[ ] I have requested reviews from the relevant team members.

Step 4: ⌨️ Coding

I have finished coding the issue. I am now reviewing it for completeness.

Step 5: 🔁 Code Review

Success! 🚀

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kevinlu1248 / llama_index