I like the suggestion of using something like google translate -- as they will be doing all the work for you.
You might be able to build a rule-based system that gets you part of the way there. Build heuristic rules for languages and see if that is sufficient. Certain Tibetan characters do indicate Tibetan, and there are unique characters in many languages that will be a give away. But as the other answer pointed out, a limited sample of text may not be that accurate, as you may not have a clear indicator.
Languages will however differ in the frequencies that each character appears, so you could have a basic fingerprint of each language you need to classify and make guesses based on letter frequency. This probably goes a bit further than a rule-based system. Probably a good tool to build this would be a text classification algorithm, which will do all the analysis for you. You would train an algorithm on different languages, instead of having to articulate the actual rules yourself.
A much more sophisticated version of this is presumably what Google does.