Hi guys I have been working on finetuning small task specific models and would love to connect to people working closely with LLM .

Sharing a quick breakdown of something I recently built that dramatically improved long-session performance in LLM-based agents. The challenge => Most chatbots forget everything between sessions — or worse, overload memory with raw logs that aren’t meaningful. My solution => a structured memory system that’s adaptive, contextual, and forgets what it should. Here’s the architecture: 1. Memory Points - Each user message is turned into a memory point with: - A content summary - A dynamic importance score - A category (like “personal info” or “casual”) - A timestamp - Linked to a user ID 2. Memory Decay - Memories fade over time — but not equally. - Critical info (like names or settings) decays slowly - Small talk fades fast I use exponential decay with category-based rates. 3. Long-Term Summarization - When a memory fades below a threshold, the LLM generates a long-term summary (e.g., "User likes dark mode"). These are stored as part of the user’s evolving profile. 4. Contextual Retrieval & Conflict Handling - At inference time, the bot pulls in recent memory points + long-term memory. If there are conflicts, it resolves them based on score, recency, and category. Why it matters:It creates conversations that feel personalized and consistent, without storing everything. It’s lean, adaptive, and avoids token overload. If anyone else here is building AI agents or tools around personalization/memory — happy to trade notes or dive deeper!

Hey everyone! I’ve been diving into the concept of GraphRAG lately and it seems like a super powerful way to improve RAG systems by integrating knowledge graphs for more structured and context-rich retrieval. I was wondering if anyone here in the PapaFam community is interested in exploring this idea together? Could be fun to experiment and maybe even build something cool for production-level use. Would love to connect with others curious about this too! Ps . It's a very important usecase .. as current rag does not maps the relationship between chunks Like true ER. This leads to a lot of loss in context Hit me up in dms if interested 🤞

Hey everyone! I’ve recently started diving deep into the world of AI, and I’m super pumped about the journey ahead! 🤖✨ AI is such a fascinating field, and I’d love to share what I’m learning with you all. If anyone has questions or is working on AI implementations and needs some help or insights, feel free to reach out! I'm here to collaborate, brainstorm, and dive into any challenges you’re facing. Let’s explore this amazing space together! 🌟💡 #AI #MachineLearning #SoftwareDev #AICommunity #Collaboration

Recently I built a project , but when indexing it it redirects the googlebot . I am using a production environment still and made homepage public still the bot is being redirected . Help plz anyone!!