Incremental Knowledge Graph updates

[dhirenmathur]

Implement Incremental Knowledge Graph Updates

Problem

Currently, the knowledge graph system performs a complete rebuild of both code mapping and inference generation on any update, regardless of the change magnitude. This approach is computationally expensive and time-consuming, impacting system performance and resource utilization.

Proposed Solution

Develop an incremental update system for the knowledge graph that processes only the changed components rather than rebuilding the entire graph.

Requirements

Core Functionality

• Implement differential analysis to detect and isolate changes between versions
• Create an incremental update mechanism that preserves existing graph structure
• Develop a system to track and maintain relationship integrity during updates

Key Features

1. Change Detection

   • Identify modified, added, and deleted components
   • Determine affected relationships and dependencies
   • Map impact scope of changes

2. Relationship Management

   • Maintain accurate relationship tracking across updates
   • Handle cascading relationship updates
   • Preserve existing relationship metadata

3. Inference Handling

   • Generate inferences only for new/modified components
   • Preserve existing valid inferences
   • Update affected inference chains without full regeneration

4. Performance Optimization

   • Eliminate full graph reconstruction
   • Minimize parsing operations to affected components only
   • Optimize resource usage during updates

Technical Considerations

• Must maintain data consistency throughout incremental updates
• Need to implement versioning/tracking for incremental changes
• Requires robust error handling for partial updates
• Should include rollback capability for failed updates

[dhirenmathur]

/bounty 20

[algora-pbc]

💎 $20 bounty • potpie.ai

Steps to solve:

1. Start working: Comment /attempt #221 with your implementation plan
2. Submit work: Create a pull request including /claim #221 in the PR body to claim the bounty
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Thank you for contributing to potpie-ai/potpie!

Attempt	Started (UTC)	Solution	Actions
🟢 @Harihara04sudhan	Jan 09, 2025, 01:28:06 PM	WIP
🟢 @onyedikachi-david	Jan 26, 2025, 04:15:44 AM	#232	Reward
🟢 @chawansrujeeth	Dec 31, 2025, 09:57:39 AM	WIP

[Harihara04sudhan]

/attempt #221

Options

• Cancel my attempt

[dhirenmathur]

Hey @Harihara04sudhan do you have a plan on how to go about this?

[onyedikachi-david]

/attempt #221

Algora profile	Completed bounties	Tech	Active attempts	Options
@onyedikachi-david	14 bounties from 7 projects	TypeScript, Python, JavaScript & more		Cancel attempt

[algora-pbc]

💡 @onyedikachi-david submitted a pull request that claims the bounty. You can visit your bounty board to reward.

[PriyanshGodhani22]

@dhirenmathur is this issue solved otherwise I can submit a plan to it just wanted confirm so that it doesn't replicate the efforts thanks.

[chawansrujeeth]

/attempt #221
Hi
@dhirenmathur
@yashkrishan

I am working on this issue and have a simple, incremental approach in mind to avoid rebuilding the Knowledge Graph on every run.

The idea is to persist the extracted graph artifacts (e.g., nx_nodes.jsonl / nx_edges.jsonl), diff the previous snapshot against the newly extracted one using stable identifiers, and apply only the resulting add/delete deltas to Neo4j instead of wiping and rebuilding the graph.

This keeps unchanged parts of the codebase untouched while making ingestion incremental and safer. I’ll open a PR with this approach .

Thanks.