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#rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

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Mitigating Hallucinations in Theology AI: Implementing Groundedness Evaluation Pipelines
mactrixxr profile

Mitigating Hallucinations in Theology AI: Implementing Groundedness Evaluation Pipelines

#ai #llm #rag #softwareengineering
Comments 1
7 min read
I Built a Local RAG Assistant with Ollama, ChromaDB and LangChain. Here's What I Learned

Strict offline constraints drive practical lessons
josaphatstar profile

I Built a Local RAG Assistant with Ollama, ChromaDB and LangChain. Here's What I Learned

#rag #langchain #python #ollama
6
Comments 9
7 min read
How to Build a RAG Knowledge Base from Any Documentation Site in 5 Minutes
codefather profile

How to Build a RAG Knowledge Base from Any Documentation Site in 5 Minutes

#rag #llm #python #ai
Comments
2 min read
How to move from an LLM demo to a production-ready healthcare AI agent
kajol_shah profile

How to move from an LLM demo to a production-ready healthcare AI agent

#ai #architecture #healthcare #rag
Comments
6 min read
Where Does RAG Actually Cost You Money? (Episode 4)
surajrkhonde profile

Where Does RAG Actually Cost You Money? (Episode 4)

#ai #rag #productivity #computerscience
4
Comments 2
9 min read
KoutenDB v0.6.0: Locality Validation, Topology Remapping, and Safer Query Boundaries
puffball1567 profile

KoutenDB v0.6.0: Locality Validation, Topology Remapping, and Safer Query Boundaries

#database #ai #rag #nim
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4 min read
Embedding Model Selection for Production: The Decision Nobody Documents
aloknecessary profile

Embedding Model Selection for Production: The Decision Nobody Documents

#ai #rag #embeddings #architecture
Comments
3 min read
RAG vs Fine-Tuning: Which One Does Your Business Actually Need?
sraurora profile

RAG vs Fine-Tuning: Which One Does Your Business Actually Need?

#ai #rag #llm #genai
1
Comments 2
4 min read
Bedrock Managed Knowledge Base: Anatomy of a Managed RAG Pipeline
fernando_azevedo_6844e930 profile

Bedrock Managed Knowledge Base: Anatomy of a Managed RAG Pipeline

#aiagents #bedrock #rag #knowledgebase
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10 min read
I spent 10 years building enterprise search for clients. Then I open-sourced all of it.
alegauss profile

I spent 10 years building enterprise search for clients. Then I open-sourced all of it.

#opensource #ai #rag #selfhosted
2
Comments
3 min read
Contract Intelligence on AWS: Field-Notes Architecture
fernando_azevedo_6844e930 profile

Contract Intelligence on AWS: Field-Notes Architecture

#aiagents #bedrock #rag #contracts
Comments
10 min read
Why I Kept Search Scope Inside a Single Supabase RPC
romiteld profile

Why I Kept Search Scope Inside a Single Supabase RPC

#supabase #postgres #pgvector #rag
Comments 2
8 min read
Building a RAG System from Scratch with pgvector and Gemini — Implementation
hiroki-kameyama profile

Building a RAG System from Scratch with pgvector and Gemini — Implementation

#rag #llm #python #pgvector
Comments 2
5 min read
Fix Your Search, Fix Your RAG Output
jon_handler_9bb3e6b4a2fd0 profile

Fix Your Search, Fix Your RAG Output

#opensearch #search #ai #rag
1
Comments
6 min read
Building a Free AI PDF Assistant: How I Solved Parsing Issues and Minimized LLM Costs
yue7090 profile

Building a Free AI PDF Assistant: How I Solved Parsing Issues and Minimized LLM Costs

#showdev #ai #llm #rag
Comments
3 min read
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