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MongoDB Atlas VectorDB [clean] #2996
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First steps towards MongoDB as a VectorDB.
Co-authored-by: Jib <[email protected]>
Co-authored-by: Jib <[email protected]>
Co-authored-by: Jib <[email protected]>
Co-authored-by: Jib <[email protected]>
Co-authored-by: Jib <[email protected]>
Co-authored-by: Jib <[email protected]>
Co-authored-by: Jib <[email protected]>
update PREDEFINED_VECTOR_DB and change name to MongoDBAtlasVectorDB; upsert=True update logic; no more index/collection name check.
Co-authored-by: Jib <[email protected]>
Co-authored-by: Jib <[email protected]>
with MongoDB Atlas Vector Search indexes, things work a little differently than traditional MongoDB indexes. Atlas Search indexes are separate entities managed by the Atlas Search service. Deleting a collection doesn't automatically remove the associated Atlas Search index - leading to errors
Co-authored-by: Jib <[email protected]>
Co-authored-by: Li Jiang <[email protected]>
Update agentchat_mongodb_RetrieveChat.ipynb Update agentchat_mongodb_RetrieveChat.ipynb
Test is still skipped: Need to update contrib-tests.yml
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #2996 +/- ##
==========================================
- Coverage 32.49% 26.01% -6.49%
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Files 93 100 +7
Lines 10097 10299 +202
Branches 2167 2356 +189
==========================================
- Hits 3281 2679 -602
- Misses 6532 7318 +786
- Partials 284 302 +18
Flags with carried forward coverage won't be shown. Click here to find out more. ☔ View full report in Codecov by Sentry. |
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GitGuardian id | GitGuardian status | Secret | Commit | Filename | |
---|---|---|---|---|---|
- | MongoDB Credentials | 54655e8 | notebook/agentchat_mongodb_RetrieveChat.ipynb | View secret | |
- | MongoDB Credentials | 3122301 | notebook/agentchat_mongodb_RetrieveChat.ipynb | View secret |
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@thinkall - I think there is something going on with testing retrieval?
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I polluted this PR :( sorry -- lets try this one last time |
There is no need to worry about the commit history. Make a new PR will lost the track history. |
Why are these changes needed?
MongoDB has been ranked as the best vector database(https://www.mongodb.com/blog/post/atlas-vector-search-commands-highest-developer-nps-retool-state-ai-2023-survey) in the Retool AI report, so it is quite important to add MongoDB vector search as an option for Autogen RAG.
You can easily start the MongoDB vector search on a free tier M0 MongoDB Atlas cluster. Free tier cluster provides the full functionality of the MongoDB vector search. https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-overview/
But why is MongoDB such a standout? Well, there are a few key reasons.
As such, implementing MongoDB as a Retrieval Agent can unlock new potential in your AI applications, bringing the full power of vector storage to bear.
Related issue number: 711
Closes #711
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