feat(reply): cap interactive LLM replies to 3 mesh packets

Add terse-answer guidance to the interactive system prompt and a hard
ceiling of 3 packets (3 x connector.max_chars) on LLM replies, with an
"ask for more" indicator when truncated. Protects LoRa airtime from
runaway replies. Broadcast chunking unchanged.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

work/meshai/chunker.py

@@ -13,6 +13,35 @@ import re
 
 logger = logging.getLogger(__name__)
 
+# Hard ceiling on interactive LLM replies — protects LoRa airtime.
+# Broadcast/notification chunking is NOT subject to this cap.
+MAX_REPLY_PACKETS = 3
+
+_TRUNCATION_INDICATOR = " …(ask for more)"
+
+
+def cap_reply_chunks(chunks: list[str], max_packets: int, max_chars: int) -> list[str]:
+    """Cap LLM reply chunks to max_packets; append truncation indicator if cut.
+
+    Args:
+        chunks: List of message chunks produced by chunk_response.
+        max_packets: Maximum number of packets to deliver (e.g. MAX_REPLY_PACKETS).
+        max_chars: Per-packet character budget (connector.max_chars).
+
+    Returns:
+        Original list when len(chunks) <= max_packets; otherwise a capped
+        copy of length max_packets with the truncation indicator appended
+        (and the last chunk trimmed if necessary to stay within max_chars).
+    """
+    if len(chunks) <= max_packets:
+        return chunks
+    capped = list(chunks[:max_packets])
+    last = capped[-1]
+    if len(last) + len(_TRUNCATION_INDICATOR) > max_chars:
+        last = last[: max_chars - len(_TRUNCATION_INDICATOR)]
+    capped[-1] = last + _TRUNCATION_INDICATOR
+    return capped
+
 
 def strip_markdown(text: str) -> str:
     """Remove markdown formatting from LLM output.

work/meshai/router.py

@@ -13,7 +13,7 @@ from .config import Config
 from .connector import MeshConnector, MeshMessage
 from .context import MeshContext
 from .history import ConversationHistory
-from .chunker import chunk_response, ContinuationState
+from .chunker import chunk_response, cap_reply_chunks, MAX_REPLY_PACKETS, ContinuationState
 
 logger = logging.getLogger(__name__)
 
@@ -889,6 +889,13 @@ class MessageRouter:
                 if env_summary:
                     system_prompt += "\n\n" + env_summary
 
+        # Terse-reply guidance for slow LoRa links (always appended last for
+        # interactive replies so it isn't buried by mesh-data blocks).
+        system_prompt += (
+            "\n\nYou're replying over a slow LoRa mesh. "
+            "Answer in 1-2 short messages. Be terse and direct; omit preamble and filler."
+        )
+
         # DEBUG: Log system prompt status
         logger.debug(f"System prompt length: {len(system_prompt)} chars")
 
@@ -929,6 +936,12 @@ class MessageRouter:
             max_messages=self.config.response.max_messages,
         )
 
+        # Hard cap: LLM interactive replies must not exceed MAX_REPLY_PACKETS.
+        # This is a safety ceiling on top of config.response.max_messages so
+        # LoRa airtime is protected even if config grows the message budget.
+        # Broadcast/notification chunking is NOT affected by this cap.
+        messages = cap_reply_chunks(messages, MAX_REPLY_PACKETS, self.connector.max_chars)
+
         # Store remaining content for continuation
         if remaining:
             logger.debug(f"Storing continuation for {message.sender_id}: {len(remaining)} chars remaining")

work/tests/test_llm_reply_cap.py

@@ -0,0 +1,117 @@
+"""Tests for the interactive LLM reply cap (MAX_REPLY_PACKETS).
+
+All tests are hermetic — no real LLM, no real socket.
+"""
+
+import pytest
+
+from meshai.chunker import cap_reply_chunks, chunk_response, MAX_REPLY_PACKETS, _TRUNCATION_INDICATOR
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+def _make_chunks(n: int, chars_each: int = 50) -> list[str]:
+    """Build n chunks of exactly chars_each ASCII characters."""
+    return [f"chunk{i}" + "x" * (chars_each - len(f"chunk{i}")) for i in range(n)]
+
+
+# ---------------------------------------------------------------------------
+# Test 1 — long reply produces exactly 3 chunks with truncation indicator
+# ---------------------------------------------------------------------------
+
+def test_long_reply_capped_to_three_chunks():
+    """A reply long enough to produce >3 chunks results in exactly 3 delivered
+    chunks, and the truncation indicator is present in the last chunk."""
+    max_chars = 140
+
+    # Build a response that will produce >3 chunks at 140 chars each.
+    # Each sentence is ~130 chars so 5 sentences → 5 chunks.
+    sentence = "A" * 130 + "."
+    text = " ".join([sentence] * 5)
+
+    # chunk_response with a high max_messages so it happily returns 5 chunks
+    raw_chunks, _ = chunk_response(text, max_chars=max_chars, max_messages=10)
+    assert len(raw_chunks) > MAX_REPLY_PACKETS, (
+        f"Precondition: expected >3 raw chunks, got {len(raw_chunks)}"
+    )
+
+    capped = cap_reply_chunks(raw_chunks, MAX_REPLY_PACKETS, max_chars)
+
+    assert len(capped) == MAX_REPLY_PACKETS
+    assert _TRUNCATION_INDICATOR in capped[-1], (
+        f"Expected truncation indicator in last chunk, got: {capped[-1]!r}"
+    )
+
+
+# ---------------------------------------------------------------------------
+# Test 2 — short reply is delivered unchanged, no indicator
+# ---------------------------------------------------------------------------
+
+def test_short_reply_unchanged():
+    """A short reply (<=3 chunks) is delivered unchanged with no indicator."""
+    max_chars = 140
+
+    # One chunk well under the limit
+    chunks_1 = ["Hello, this is a short reply."]
+    result_1 = cap_reply_chunks(chunks_1, MAX_REPLY_PACKETS, max_chars)
+    assert result_1 == chunks_1
+    assert _TRUNCATION_INDICATOR not in result_1[-1]
+
+    # Exactly 3 chunks — boundary condition
+    chunks_3 = _make_chunks(3, chars_each=50)
+    result_3 = cap_reply_chunks(chunks_3, MAX_REPLY_PACKETS, max_chars)
+    assert result_3 == chunks_3
+    assert _TRUNCATION_INDICATOR not in result_3[-1]
+
+
+# ---------------------------------------------------------------------------
+# Test 3 — cap respects connector.max_chars=140
+# ---------------------------------------------------------------------------
+
+def test_cap_respects_max_chars_140():
+    """cap_reply_chunks uses the max_chars budget (140) from connector.max_chars."""
+    max_chars = 140
+
+    # 5 chunks of 80 chars each (well under max_chars individually)
+    chunks = _make_chunks(5, chars_each=80)
+
+    capped = cap_reply_chunks(chunks, MAX_REPLY_PACKETS, max_chars)
+
+    assert len(capped) == 3
+    # Last chunk must not exceed max_chars in total length
+    assert len(capped[-1]) <= max_chars
+    assert _TRUNCATION_INDICATOR in capped[-1]
+
+
+# ---------------------------------------------------------------------------
+# Test 4 — 3rd chunk trimmed correctly when at max_chars limit
+# ---------------------------------------------------------------------------
+
+def test_third_chunk_trimmed_to_fit_indicator():
+    """When the 3rd chunk fills max_chars exactly, it is trimmed so that
+    trimmed_chunk + indicator == max_chars exactly."""
+    max_chars = 140
+    indicator = _TRUNCATION_INDICATOR  # len 16 Python chars (" …(ask for more)")
+
+    # 3rd chunk that is exactly max_chars long
+    full_chunk = "B" * max_chars
+    chunks = [
+        "First chunk.",
+        "Second chunk.",
+        full_chunk,
+        "Fourth chunk (should be dropped).",
+    ]
+
+    capped = cap_reply_chunks(chunks, MAX_REPLY_PACKETS, max_chars)
+
+    assert len(capped) == MAX_REPLY_PACKETS
+    last = capped[-1]
+    assert last.endswith(indicator), f"Expected indicator at end, got: {last!r}"
+    assert len(last) == max_chars, (
+        f"Expected trimmed chunk + indicator == {max_chars}, got len={len(last)}"
+    )
+    # The trimmed body is max_chars - len(indicator) Bs
+    expected_body = "B" * (max_chars - len(indicator))
+    assert last == expected_body + indicator