VS Code Redis Copilot Extension
Budget: ₹999 – ₹1,000 INR
I’m building a VS Code extension that plugs directly into a Redis vector database populated with sentence-transformers embeddings. Inside the editor a user will type a natural-language question; the extension must immediately embed that question, run a semantic search against Redis, and forward the top-ranked metadata to GitHub Copilot Chat so Copilot can return a fully formed SQL query.
Key behaviour I need implemented:
• Auto-embed user questions on the fly (English only).
• Fetch the most relevant vectors from Redis with minimal latency.
• Highlight—in code comments only—the data Copilot used, then let Copilot generate and return the SQL query; no separate panel or pop-up UI is required.
Technical notes
– VS Code Extension API, TypeScript preferred.
– Redis with vector search (RediSearch module) and sentence-transformers for both the stored documents and live queries.
– Clean interface for supplying the Redis connection string and model name.
– Copilot Chat interaction through the existing VS Code API surface; the extension should hand off the retrieved context and display Copilot’s SQL response inline.
Acceptance criteria
1. Installing the VS Code package enables a new command “Semantic SQL from Redis”.
2. Typing a question and running the command produces an SQL query within Copilot Chat in ≤3 seconds on a sample 100k-row dataset.
3. Only English queries are accepted; other languages yield a polite warning.
4. Source is lint-clean, documented, and ready for Marketplace submission.
Key behaviour I need implemented:
• Auto-embed user questions on the fly (English only).
• Fetch the most relevant vectors from Redis with minimal latency.
• Highlight—in code comments only—the data Copilot used, then let Copilot generate and return the SQL query; no separate panel or pop-up UI is required.
Technical notes
– VS Code Extension API, TypeScript preferred.
– Redis with vector search (RediSearch module) and sentence-transformers for both the stored documents and live queries.
– Clean interface for supplying the Redis connection string and model name.
– Copilot Chat interaction through the existing VS Code API surface; the extension should hand off the retrieved context and display Copilot’s SQL response inline.
Acceptance criteria
1. Installing the VS Code package enables a new command “Semantic SQL from Redis”.
2. Typing a question and running the command produces an SQL query within Copilot Chat in ≤3 seconds on a sample 100k-row dataset.
3. Only English queries are accepted; other languages yield a polite warning.
4. Source is lint-clean, documented, and ready for Marketplace submission.