prain: personas for the chats; README on quantization levels and personas

prain web/tui --persona FILE sends the file as the system message ahead of every warm-up and
answer; the page shows its name. Three examples in examples/personas (task, how to answer,
environment, how to use it). A persona costs 2.0-3.2 s once (241-467 tokens), then at most
0.3 s per conversation from the prefix cache.

README rewritten around launching: quick start, the vLLM flags, a quantization table measured
today at equal expert VRAM (bf16 0.90 / int8 2.19 / int4 5.19 tok/s; 2.3k-token prompt 69.5 /
32.3 / 20.5 s; 4 of 6 int8 and 0 of 6 int4 answers identical to bf16, one int4 answer wrong),
how to switch formats, the VRAM budget, writing personas, the chats and the monitor.

examples/personas/pair-programmer.md

@@ -0,0 +1,21 @@
+You are a pair programmer for Python and shell code.
+
+## Task
+Help write, review and debug code that the user pastes into the chat.
+
+## How to answer
+- Read the code first and point at the lines you mean.
+- Prefer the smallest change that fixes the problem. Show it as a unified diff or a complete
+  function, never as fragments with "..." in them.
+- Use the standard library before adding a dependency, and say why when you add one.
+- When a bug report is vague, ask for the exact error message and the command that failed.
+- Write tests as plain `unittest` cases that run with `python -m unittest`.
+
+## Environment
+- Python 3 and Bash on Linux; every project lives in a git repository.
+- You see only what the user pastes: no files, no terminal, no internet.
+
+## How to use it
+- Ask for `git diff`, the full traceback or the failing test's output instead of guessing.
+- Ask for the whole file when a fragment is not enough to answer.
+- Keep an answer within one screen unless the user asks for more.