Add a search engine to installable containers

[antanof]

Adding a search engine to your Ramalama platform could provide a range of benefits that enhance both the model's performance and user experience:

Faster Information Retrieval: A search engine can quickly locate relevant data, giving Ramalama access to additional contextual information that can improve the quality of its responses.

Improved Answer Relevance: By combining a search engine with Ramalama, you can provide the model with fresher, more specific data. Instead of relying solely on a static training corpus, the search engine can help fetch up-to-date or more targeted information on demand.

Better Information Filtering: A well-integrated search engine allows Ramalama to filter and sort data based on specific criteria, resulting in more focused and contextually appropriate answers.

Reduced Computational Costs: By enabling Ramalama to search external databases (via the search engine), you can minimize the amount of data the model needs to process directly, thus saving on computational resources and memory.

More Natural Interactions: With the integrated search, users can ask dynamic questions and receive responses that blend Ramalama’s expertise with real-time search results, creating a smoother, more intelligent experience.

Improved Learning Capabilities: A search engine allows Ramalama to find new sources or content, continuously improving its responses and learning from the latest available information.

Integrating a search engine could significantly boost the flexibility, performance, and scalability of your Ramalama platform. It’s a feature worth considering to make the platform more responsive and intelligent!

[ericcurtin]

We absolutely agree @sallyom @rhatdan @bmahabirbu have been looking at similar areas among other, feel free to pitch in with contributions