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RagCheck is a proactive corpus quality assessment tool that analyses RAG application document collections before deployment, identifying content gaps and providing specific recommendations to improve query performance. The platform transforms reactive corpus fixes into proactive quality assurance, helping organisations achieve as high as 85% score.
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192
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Merge pull request #14 from neomatrix369/dockerise-application-update-docs
64eff36View on GitHubDocs: add comments to more docker-compose files in the project
bafc1faView on GitHubMerge pull request #13 from neomatrix369/dockerise-application-update-docs
b936ef3View on GitHubDocs: added comments per line or per 3 kines of the config file and summary of comments (at the top of the file) to help easily understand the docker compose config file
64bd437View on GitHubMerge pull request #12 from neomatrix369/dockerise-application-update-docs
a522673View on GitHubImprove service management UX with clearer stop options and safety confirmations
be15412View on GitHubMerge pull request #11 from neomatrix369/dockerise-application-update-docs
474a77dView on GitHubMove supporting badges to bottom of documentation files
fe388caView on GitHubUpdated the documents with issues reported and observed when using Document management
0027096View on GitHubAmended the slogan/message over retrieval and generation
fd8578aView on GitHubMerge pull request #10 from neomatrix369/dockerise-application-update-docs
f1601f7View on GitHubFix corpus statistics to read current chunk selection state
9004722View on GitHubMerge pull request #9 from neomatrix369/dockerise-application-update-docs
e15f8f9View on GitHubBug: fixed the issue reported by users, [Error] ❌ WebSocket connection timeout (anonymous function) (experiment-9bddcbe2348ae8a6.js:1:5319)
13b37e1View on GitHub