- agents-towards-production VS tamingLLMs
- agents-towards-production VS amazon-bedrock-agentcore-samples
- agents-towards-production VS awesome-AI-toolkit
- agents-towards-production VS adk-java
- agents-towards-production VS syftr
- agents-towards-production VS Agentic-AI-Systems
- agents-towards-production VS GenAI_Agents
- agents-towards-production VS Roy
- agents-towards-production VS beyondllm
- agents-towards-production VS vertex-ai-samples
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agents-towards-production discussion
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Show HN: GibRAM an in-memory ephemeral GraphRAG runtime for retrieval
GraphRAG's approach certainly makes sense for regulation-heavy documents, where interconnected references can be critical for retrieval quality. The challenge you mentioned about separate systems for graph storage and vector indexing resonates with what we've seen in the field. In practice, this separation often adds unnecessary complexity for ephemeral analysis tasks. One thing we've explored is using a dual-memory architecture, which might be relevant here even in an in-memory context. It allows you to effectively manage recent context and longer-term semantic connections without the overhead of persistent storage. If you're interested in seeing how this approach could be integrated into production systems, I wrote up some patterns that might be useful: https://github.com/NirDiamant/agents-towards-production.
- Agents-Towards-Production Tutorials
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1 day ago
NirDiamant/agents-towards-production is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of agents-towards-production is Jupyter Notebook.
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AppSignal knows why the f*#k it crashed.
Stop vibe-debugging. Every exception, every backtrace, grouped so you see patterns, not noise.
www.appsignal.com