feat: add opt-in Pinecone retrieval practice - #40
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✨ Finishing Touches🧪 Generate unit tests (beta)
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| # Vector DB | ||
| # Vector DB (Qdrant remains the default local backend) | ||
| VECTOR_SEARCH_BACKEND=qdrant |
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Setting VECTOR_SEARCH_BACKEND=pinecone has no runtime effect because the setting is never read anywhere; ai/graph/langgraph_flow.py still imports and unconditionally constructs QdrantSearch at lines 2 and 12. Consequently, every user following the new opt-in instructions continues querying Qdrant instead of the configured Pinecone index, so the advertised backend cannot be activated.
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| @@ -0,0 +1,2 @@ | |||
| # Optional hosted semantic-search backend. | |||
| pinecone>=6.0.0 | |||
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In a clean environment following the documented install command, importing PineconeSearch fails with ModuleNotFoundError: cohere: this file installs only pinecone, while pinecone_search.py imports CohereEmbedder, whose module imports cohere at module load time. The base requirements.txt also does not declare cohere, so installing both declared requirement files still leaves the new adapter unusable.
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Summary
Implements the Pinecone and portfolio engineering practices from SentinelAI issue #13 for TrojanChat.
Validation
The repository's existing CI, tests, security scans, and benchmark workflows should validate the change. Pinecone network calls are not required for default CI.
Refs CoreyLeath-code/SentinelAI#13