⚡ Bolt: [performance improvement] Concurrent embedding generation in Weaver

[ishaanxgupta]

💡 What:

Refactored flush_add_batch in src/pipelines/weaver.py to concurrently generate embeddings for all valid ADD operations before inserting them into the vector store.

🎯 Why:

The embed_fn makes a synchronous network request to an embedding service. When processing a batch of operations (e.g., from an ingestion pipeline extraction), calling this function sequentially inside an async loop blocks the event loop and multiplies network latency by the number of operations in the batch.

📊 Impact:

Reduces the time complexity of embedding generation for a batch of N additions from O(N) round-trips to ~O(1) (dependent on thread pool size), significantly lowering the latency of the Weaver pipeline for large inputs.

🔬 Measurement:

By mocking embed_fn with a sleep, execution of N items drops from N seconds to 1 second. The event loop is no longer blocked.

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PR created automatically by Jules for task 4337648397894169834 started by @ishaanxgupta

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