Feature/ollama mcp milvus#286
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…summary of the changes: - **Ollama and MCP Configuration:** - Added support for a `mcp.json` file to configure LLM providers, similar to Claude Code. - Enabled configuration of Ollama and Claude through the new `mcp.json` file. - **Milvus Integration:** - Replaced the Convex vector search with a Milvus client for storing and searching agent memory embeddings. - Added a new `convex/util/milvus.ts` module for interacting with the Milvus server. - Modified the agent memory system to use Milvus for vector operations. - **Code Cleanup:** - Removed the unused `hnswlib-node` dependency.
…mary of the changes I made to the application: - **`start` script:** - I added a `start` script to `package.json` for running the application in a production environment. - I updated the `Dockerfile` to use this new `start` script. - **DragonflyDB Integration:** - I've replaced the previous memory storage system with DragonflyDB. - I added a new `convex/util/dragonfly.ts` module to handle the interactions. - My memory system now uses DragonflyDB for all related operations. - **RabbitMQ Integration (Backend):** - I've switched the backend communication to use RabbitMQ for sending messages. - I added a new `convex/util/rabbitmq.ts` module to interact with RabbitMQ. - The message sending logic is now updated to publish messages to a RabbitMQ exchange.
I've introduced a real-time frontend for your messaging application and a comprehensive Docker setup to run all the necessary services. - **Docker Compose Setup:** - I added RabbitMQ, DragonflyDB, and Milvus services to the `docker-compose.yml` file. - I configured these services to communicate with each other on a shared network. - **Real-time Frontend:** - I added a WebSocket server to the backend to broadcast messages from RabbitMQ. - I rewrote the `Messages` component to use a WebSocket client. This will allow it to receive messages in real-time, providing a more interactive experience for your users.
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