chore: bump version to 1.2.2

fix: universal tool_call/tool_result orphan detection for OpenAI-comp… (#346 )
* fix: universal tool_call/tool_result orphan detection for OpenAI-compat providers The Anthropic provider had orphan detection for mismatched tool_call ↔ tool_result pairs, but OpenAI-compatible providers (Chat Completions, Google, Responses API) had none. When an Anthropic model runs behind an OpenAI-compat API (e.g. Azure) or cancellation creates orphans, the API rejects the malformed request. - Rewrite sanitize_messages() with orphan detection: synthesize error tool results for unmatched tool_calls, drop tool results with no matching tool_call, fill empty tool_call IDs with positional remap - Call sanitize_messages() from Responses API _convert_messages() * fix: address review feedback on orphan detection - Track answered IDs per-turn (local_answered) instead of scanning all of out, preventing false matches from reused IDs across turns - Drop empty-ID tool results that have no remap entry instead of passing them through with invalid empty tool_call_id - Increment empty_result_idx for every empty result, not just remapped - Remove dead result_ids peek-ahead code - Add test for repeated tool_call IDs across turns
2026-08-13 07:22:24 -06:00 · 2026-04-12 20:41:42 -07:00 · 2026-04-12 20:41:28 -07:00 · 2026-04-12 20:41:28 -07:00 · 2026-04-08 18:06:12 -07:00 · 2026-04-08 18:05:41 -07:00
12 changed files with 654 additions and 162 deletions
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "turnstone"
-version = "1.2.0"
+version = "1.2.2"
 description = "Multi-node AI orchestration platform with tool use, agent routing, and cluster simulation."
 readme = "README.md"
 license = "BUSL-1.1"
@@ -51,7 +51,7 @@ anthropic = ["anthropic>=0.39"]
 postgres = ["psycopg[binary]>=3.2"]
 ddg = ["ddgs>=9.0"]
 discord = ["discord.py>=2.4"]
-tls = ["lacme>=1.0.4"]
+tls = ["lacme>=1.0.5"]
 sandbox = ["sympy>=1.13", "numpy>=2.0", "scipy>=1.14", "pytest>=9.0"]
 all = ["turnstone[console,anthropic,postgres,discord,ddg,tls,sandbox]"]

@@ -128,6 +128,8 @@ def _anthropic_event(
        if "usage_input_tokens" in kwargs:
            msg_usage = MagicMock()
            msg_usage.input_tokens = kwargs.get("usage_input_tokens", 0)
+            msg_usage.cache_creation_input_tokens = 0
+            msg_usage.cache_read_input_tokens = 0
            msg.usage = msg_usage
        else:
            msg.usage = None
@@ -176,6 +178,217 @@ class TestOpenAIProvider:
        sanitize_messages([original])
        assert original["content"] is None

+    # -- sanitize_messages: orphan detection -----------------------------------
+
+    def test_sanitize_orphaned_tool_call_synthesized(self) -> None:
+        """Tool_call with no matching tool result gets a synthetic error result."""
+        msgs = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "bash", "arguments": "{}"},
+                    },
+                ],
+            },
+            {"role": "user", "content": "next"},
+        ]
+        result = sanitize_messages(msgs)
+        assert len(result) == 3
+        assert result[1]["role"] == "tool"
+        assert result[1]["tool_call_id"] == "call_1"
+        assert "cancelled" in result[1]["content"]
+        assert result[2]["role"] == "user"
+
+    def test_sanitize_partial_results(self) -> None:
+        """Only the missing tool_call gets a synthetic result."""
+        msgs = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "a", "arguments": "{}"},
+                    },
+                    {
+                        "id": "call_2",
+                        "type": "function",
+                        "function": {"name": "b", "arguments": "{}"},
+                    },
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "ok"},
+        ]
+        result = sanitize_messages(msgs)
+        assert len(result) == 3
+        assert result[1]["tool_call_id"] == "call_1"
+        assert result[1]["content"] == "ok"
+        assert result[2]["role"] == "tool"
+        assert result[2]["tool_call_id"] == "call_2"
+        assert "cancelled" in result[2]["content"]
+
+    def test_sanitize_complete_results_unchanged(self) -> None:
+        """All tool_calls paired → no changes."""
+        msgs = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "a", "arguments": "{}"},
+                    },
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "ok"},
+            {"role": "user", "content": "thanks"},
+        ]
+        result = sanitize_messages(msgs)
+        assert len(result) == 3
+        assert result[0]["tool_calls"][0]["id"] == "call_1"
+        assert result[1]["content"] == "ok"
+        assert result[2]["role"] == "user"
+
+    def test_sanitize_trailing_orphan(self) -> None:
+        """Orphaned tool_call at end of conversation (no following messages)."""
+        msgs = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "a", "arguments": "{}"},
+                    },
+                ],
+            },
+        ]
+        result = sanitize_messages(msgs)
+        assert len(result) == 2
+        assert result[1]["role"] == "tool"
+        assert result[1]["tool_call_id"] == "call_1"
+
+    def test_sanitize_orphaned_tool_result_dropped(self) -> None:
+        """Tool result with no matching tool_call in preceding assistant → dropped."""
+        msgs = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "a", "arguments": "{}"},
+                    },
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "ok"},
+            {"role": "tool", "tool_call_id": "call_ORPHAN", "content": "stale"},
+        ]
+        result = sanitize_messages(msgs)
+        assert len(result) == 2
+        assert result[1]["tool_call_id"] == "call_1"
+
+    def test_sanitize_empty_tool_call_id_filled(self) -> None:
+        """Empty tool_call IDs get synthetic values; tool results are remapped to match."""
+        msgs = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {"id": "", "type": "function", "function": {"name": "a", "arguments": "{}"}},
+                ],
+            },
+            {"role": "tool", "tool_call_id": "", "content": "ok"},
+        ]
+        result = sanitize_messages(msgs)
+        new_id = result[0]["tool_calls"][0]["id"]
+        assert new_id.startswith("call_")
+        assert len(new_id) > 10
+        # Tool result must have been remapped to match
+        assert result[1]["tool_call_id"] == new_id
+        # No synthetic result needed — the pairing is complete
+        assert len(result) == 2
+
+    def test_sanitize_stale_result_with_orphan(self) -> None:
+        """Stale tool results are dropped even when orphaned calls are present."""
+        msgs = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "a", "arguments": "{}"},
+                    },
+                    {
+                        "id": "call_2",
+                        "type": "function",
+                        "function": {"name": "b", "arguments": "{}"},
+                    },
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "ok"},
+            {"role": "tool", "tool_call_id": "call_STALE", "content": "stale"},
+        ]
+        result = sanitize_messages(msgs)
+        result_tc_ids = [m["tool_call_id"] for m in result if m.get("role") == "tool"]
+        assert "call_STALE" not in result_tc_ids
+        assert "call_1" in result_tc_ids
+        assert "call_2" in result_tc_ids  # synthesized
+
+    def test_sanitize_orphan_no_mutation(self) -> None:
+        """Original messages and dicts are not mutated by orphan detection."""
+        tc = {"id": "", "type": "function", "function": {"name": "a", "arguments": "{}"}}
+        msg = {"role": "assistant", "content": None, "tool_calls": [tc]}
+        sanitize_messages([msg])
+        assert tc["id"] == ""  # original dict untouched
+        assert msg["tool_calls"][0]["id"] == ""
+
+    def test_sanitize_repeated_ids_across_turns(self) -> None:
+        """Reused tool_call IDs across turns are handled per-turn, not globally."""
+        msgs = [
+            # Turn 1: call_1 fully paired
+            {"role": "user", "content": "do A"},
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "a", "arguments": "{}"},
+                    },
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "ok"},
+            # Turn 2: reuses call_1 but has no result → must be synthesized
+            {"role": "user", "content": "do B"},
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "b", "arguments": "{}"},
+                    },
+                ],
+            },
+        ]
+        result = sanitize_messages(msgs)
+        # Turn 2's orphaned call_1 should get a synthetic result
+        tool_msgs = [m for m in result if m.get("role") == "tool"]
+        assert len(tool_msgs) == 2  # one real from turn 1, one synthetic from turn 2
+
    # -- convert_tools --------------------------------------------------------

    def test_convert_tools_passthrough(self) -> None:
@@ -637,6 +850,8 @@ class TestAnthropicProvider:
        response.usage = MagicMock()
        response.usage.input_tokens = 10
        response.usage.output_tokens = 5
+        response.usage.cache_creation_input_tokens = 0
+        response.usage.cache_read_input_tokens = 0

        client = MagicMock()
        stream_ctx = MagicMock()
@@ -673,6 +888,8 @@ class TestAnthropicProvider:
        response.usage = MagicMock()
        response.usage.input_tokens = 15
        response.usage.output_tokens = 20
+        response.usage.cache_creation_input_tokens = 0
+        response.usage.cache_read_input_tokens = 0

        client = MagicMock()
        stream_ctx = MagicMock()
@@ -708,6 +925,8 @@ class TestAnthropicProvider:
        response.usage = MagicMock()
        response.usage.input_tokens = 100
        response.usage.output_tokens = 50
+        response.usage.cache_creation_input_tokens = 0
+        response.usage.cache_read_input_tokens = 0

        client = MagicMock()
        stream_ctx = MagicMock()
@@ -1910,6 +2129,8 @@ class TestAnthropicWebSearch:
        response.stop_reason = "end_turn"
        response.usage.input_tokens = 100
        response.usage.output_tokens = 50
+        response.usage.cache_creation_input_tokens = 0
+        response.usage.cache_read_input_tokens = 0

        client = MagicMock()
        stream_ctx = MagicMock()
@@ -2876,7 +3097,8 @@ class TestAnthropicPromptCaching:
                messages=[{"role": "user", "content": "hi"}],
            )
        )
-        start_chunks = [r for r in results if r.usage is not None and r.usage.prompt_tokens == 100]
+        # prompt_tokens = input_tokens (100) + cache_creation (80) + cache_read (0) = 180
+        start_chunks = [r for r in results if r.usage is not None and r.usage.prompt_tokens == 180]
        assert len(start_chunks) == 1
        assert start_chunks[0].usage is not None
        assert start_chunks[0].usage.cache_creation_tokens == 80
@@ -3224,11 +3446,14 @@ class TestResponsesMessageConversion:
            },
        ]
        _, items = self.provider._convert_messages(messages)
-        assert len(items) == 1
+        # sanitize_messages synthesizes a missing tool result for the orphaned call
+        assert len(items) == 2
        assert items[0]["type"] == "function_call"
        assert items[0]["call_id"] == "call_1"
        assert items[0]["name"] == "read_file"
        assert items[0]["arguments"] == '{"path": "/tmp"}'
+        assert items[1]["type"] == "function_call_output"
+        assert items[1]["call_id"] == "call_1"

    def test_tool_result(self) -> None:
        messages = [
@@ -3279,11 +3504,14 @@ class TestResponsesMessageConversion:
            },
        ]
        _, items = self.provider._convert_messages(messages)
-        assert len(items) == 2
+        # sanitize_messages synthesizes a missing tool result for the orphaned call
+        assert len(items) == 3
        assert items[0]["type"] == "message"
        assert items[0]["content"] == "I'll read that file"
        assert items[1]["type"] == "function_call"
        assert items[1]["name"] == "read_file"
+        assert items[2]["type"] == "function_call_output"
+        assert items[2]["call_id"] == "call_1"


 class TestResponsesToolConversion:
@@ -105,7 +105,8 @@ class TestChatSessionConstruction:
    def test_msg_char_count_content_only(self, tmp_db):
        session = _make_session()
        msg = {"role": "assistant", "content": "hello world"}
-        assert session._msg_char_count(msg) == 11
+        # "hello world" (11) + "assistant" (9) = 20
+        assert session._msg_char_count(msg) == 20

    def test_msg_char_count_with_tool_calls(self, tmp_db):
        session = _make_session()
@@ -122,13 +123,14 @@ class TestChatSessionConstruction:
                }
            ],
        }
-        # "hi" (2) + "bash" (4) + '{"command": "ls"}' (17) = 23
-        assert session._msg_char_count(msg) == 23
+        # "hi" (2) + "tc_1" (4) + "bash" (4) + '{"command": "ls"}' (17) + "assistant" (9) = 36
+        assert session._msg_char_count(msg) == 36

    def test_msg_char_count_none_content(self, tmp_db):
        session = _make_session()
        msg = {"role": "assistant", "content": None}
-        assert session._msg_char_count(msg) == 0
+        # len("assistant") = 9
+        assert session._msg_char_count(msg) == 9

    def test_reasoning_effort_stored(self, tmp_db):
        session = _make_session(reasoning_effort="high")
@@ -1,3 +1,3 @@
 """turnstone - Multi-node AI orchestration platform with tool use, agent routing, and cluster simulation."""

-__version__ = "1.2.0"
+__version__ = "1.2.2"
@@ -714,14 +714,19 @@ class AnthropicProvider:
            elif event_type == "message_delta":
                if hasattr(event, "usage") and event.usage:
                    u = event.usage
+                    inp = getattr(u, "input_tokens", 0) or 0
+                    out = getattr(u, "output_tokens", 0) or 0
+                    cc = getattr(u, "cache_creation_input_tokens", 0) or 0
+                    cr = getattr(u, "cache_read_input_tokens", 0) or 0
+                    # prompt_tokens = total input (non-cached + cached) so
+                    # context-window tracking matches OpenAI semantics.
+                    total_input = inp + cc + cr
                    sc.usage = UsageInfo(
-                        prompt_tokens=getattr(u, "input_tokens", 0),
-                        completion_tokens=getattr(u, "output_tokens", 0),
-                        total_tokens=(
-                            getattr(u, "input_tokens", 0) + getattr(u, "output_tokens", 0)
-                        ),
-                        cache_creation_tokens=getattr(u, "cache_creation_input_tokens", 0) or 0,
-                        cache_read_tokens=getattr(u, "cache_read_input_tokens", 0) or 0,
+                        prompt_tokens=total_input,
+                        completion_tokens=out,
+                        total_tokens=total_input + out,
+                        cache_creation_tokens=cc,
+                        cache_read_tokens=cr,
                    )
                if hasattr(event.delta, "stop_reason") and event.delta.stop_reason:
                    sc.finish_reason = _normalize_finish_reason(event.delta.stop_reason)
@@ -732,12 +737,16 @@ class AnthropicProvider:
            elif event_type == "message_start":
                if hasattr(event.message, "usage") and event.message.usage:
                    u = event.message.usage
+                    inp = getattr(u, "input_tokens", 0) or 0
+                    cc = getattr(u, "cache_creation_input_tokens", 0) or 0
+                    cr = getattr(u, "cache_read_input_tokens", 0) or 0
+                    total_input = inp + cc + cr
                    sc.usage = UsageInfo(
-                        prompt_tokens=getattr(u, "input_tokens", 0),
+                        prompt_tokens=total_input,
                        completion_tokens=0,
-                        total_tokens=getattr(u, "input_tokens", 0),
-                        cache_creation_tokens=getattr(u, "cache_creation_input_tokens", 0) or 0,
-                        cache_read_tokens=getattr(u, "cache_read_input_tokens", 0) or 0,
+                        total_tokens=total_input,
+                        cache_creation_tokens=cc,
+                        cache_read_tokens=cr,
                    )

            has_content = sc.content_delta or sc.reasoning_delta or sc.tool_call_deltas
@@ -826,12 +835,17 @@ class AnthropicProvider:
        usage = None
        if hasattr(response, "usage") and response.usage:
            u = response.usage
+            inp = getattr(u, "input_tokens", 0) or 0
+            out = getattr(u, "output_tokens", 0) or 0
+            cc = getattr(u, "cache_creation_input_tokens", 0) or 0
+            cr = getattr(u, "cache_read_input_tokens", 0) or 0
+            total_input = inp + cc + cr
            usage = UsageInfo(
-                prompt_tokens=u.input_tokens,
-                completion_tokens=u.output_tokens,
-                total_tokens=u.input_tokens + u.output_tokens,
-                cache_creation_tokens=getattr(u, "cache_creation_input_tokens", 0) or 0,
-                cache_read_tokens=getattr(u, "cache_read_input_tokens", 0) or 0,
+                prompt_tokens=total_input,
+                completion_tokens=out,
+                total_tokens=total_input + out,
+                cache_creation_tokens=cc,
+                cache_read_tokens=cr,
            )

        return CompletionResult(
@@ -7,14 +7,19 @@ formatting, and message sanitisation live here so both

 from __future__ import annotations

+import uuid
 from typing import Any

+import structlog
+
 from turnstone.core.providers._protocol import (
    ModelCapabilities,
    UsageInfo,
    _lookup_capabilities,
 )

+log = structlog.get_logger(__name__)
+
 # ---------------------------------------------------------------------------
 # Model capability table
 # ---------------------------------------------------------------------------
@@ -304,21 +309,132 @@ def format_citations(content: str, annotations: list[Any]) -> str:
 def sanitize_messages(
    messages: list[dict[str, Any]],
 ) -> list[dict[str, Any]]:
-    """Ensure assistant messages always have ``content`` or ``tool_calls``.
+    """Sanitize messages for OpenAI-compatible APIs.

-    OpenAI-compatible APIs reject assistant messages that have neither.
-    This is a defensive catch-all; the upstream layers should already
-    guarantee well-formed messages.
+    Performs three repairs:
+
+    1. Ensures assistant messages always have ``content`` or ``tool_calls``
+       (APIs reject messages with neither).
+    2. Fills empty tool_call IDs with synthetic ``call_{uuid}`` values
+       (local servers sometimes omit them).
+    3. Detects and repairs orphaned tool_call / tool_result pairs:
+
+       - Synthesizes error tool messages for tool_calls with no matching
+         tool result.
+       - Drops tool messages whose ``tool_call_id`` has no matching
+         tool_call in the preceding assistant message.
+
+    Returns a new list; the original messages are not mutated.
    """
    out: list[dict[str, Any]] = []
-    for msg in messages:
-        if (
-            msg.get("role") == "assistant"
-            and msg.get("content") is None
-            and not msg.get("tool_calls")
-        ):
+    i = 0
+    while i < len(messages):
+        msg = messages[i]
+        role = msg.get("role", "")
+
+        # (1) Fix empty-content assistant messages
+        if role == "assistant" and msg.get("content") is None and not msg.get("tool_calls"):
            msg = {**msg, "content": ""}
+            out.append(msg)
+            i += 1
+            continue
+
+        # (2+3) Assistant with tool_calls: fix IDs and detect orphans
+        if role == "assistant" and msg.get("tool_calls"):
+            tool_calls = msg["tool_calls"]
+
+            # Back-fill empty IDs and build positional remap for tool results.
+            # Local servers (vLLM, llama.cpp) sometimes omit IDs entirely;
+            # positional pairing is the best heuristic in that case.
+            needs_id_fix = any(not tc.get("id") for tc in tool_calls)
+            id_remap: dict[int, str] = {}  # positional index → new ID
+            if needs_id_fix:
+                new_tcs = []
+                empty_idx = 0
+                for tc in tool_calls:
+                    if not tc.get("id"):
+                        new_id = f"call_{uuid.uuid4().hex}"
+                        id_remap[empty_idx] = new_id
+                        empty_idx += 1
+                        new_tcs.append({**tc, "id": new_id})
+                    else:
+                        new_tcs.append(tc)
+                msg = {**msg, "tool_calls": new_tcs}
+                tool_calls = msg["tool_calls"]
+
+            # Collect IDs from this assistant message
+            tc_ids = [tc["id"] for tc in tool_calls if tc.get("id")]
+            tc_id_set = set(tc_ids)
+
+            out.append(msg)
+            i += 1
+
+            # Copy through existing tool messages, applying ID remap and
+            # filtering out stale results that don't match any tool_call.
+            local_answered: set[str] = set()
+            empty_result_idx = 0
+            while i < len(messages) and messages[i].get("role") == "tool":
+                tool_msg = messages[i]
+                result_tc_id = tool_msg.get("tool_call_id", "")
+                if not result_tc_id and empty_result_idx in id_remap:
+                    # Positional remap: empty result → matching new ID
+                    new_id = id_remap[empty_result_idx]
+                    tool_msg = {**tool_msg, "tool_call_id": new_id}
+                    local_answered.add(new_id)
+                    empty_result_idx += 1
+                    out.append(tool_msg)
+                elif not result_tc_id:
+                    # Empty ID with no remap available — drop it
+                    log.debug("sanitize_messages: dropping tool result with empty ID")
+                    empty_result_idx += 1
+                elif result_tc_id in tc_id_set:
+                    local_answered.add(result_tc_id)
+                    out.append(tool_msg)
+                else:
+                    log.debug(
+                        "sanitize_messages: dropping stale tool result: %s",
+                        result_tc_id,
+                    )
+                i += 1
+
+            # Synthesize error results for tool_calls not answered in
+            # THIS turn (not all of `out`, to avoid false matches from
+            # reused IDs across turns).
+            still_orphaned = [uid for uid in tc_ids if uid not in local_answered]
+            if still_orphaned:
+                log.debug(
+                    "sanitize_messages: synthesizing %d tool result(s) for orphaned tool_calls",
+                    len(still_orphaned),
+                )
+                for uid in still_orphaned:
+                    out.append(
+                        {
+                            "role": "tool",
+                            "tool_call_id": uid,
+                            "content": "Tool execution was cancelled.",
+                        }
+                    )
+            continue
+
+        # (3d) Drop orphaned tool results
+        if role == "tool":
+            tc_id = msg.get("tool_call_id", "")
+            # Find the preceding assistant message's tool_call IDs
+            prev_tc_ids: set[str] = set()
+            for k in range(len(out) - 1, -1, -1):
+                if out[k].get("role") == "assistant" and out[k].get("tool_calls"):
+                    prev_tc_ids = {tc.get("id", "") for tc in out[k]["tool_calls"] if tc.get("id")}
+                    break
+            if prev_tc_ids and tc_id and tc_id not in prev_tc_ids:
+                log.debug(
+                    "sanitize_messages: dropping orphaned tool result (no matching tool_call): %s",
+                    tc_id,
+                )
+                i += 1
+                continue
+
        out.append(msg)
+        i += 1
    return out


@@ -24,6 +24,7 @@ from turnstone.core.providers._openai_common import (
    format_citations,
    lookup_openai_capabilities,
    resolve_reasoning_effort,
+    sanitize_messages,
 )
 from turnstone.core.providers._protocol import (
    CompletionResult,
@@ -83,6 +84,7 @@ class OpenAIResponsesProvider:
        concatenated system/developer messages (or ``None``) and *input_items*
        is the Responses API ``input`` array.
        """
+        messages = sanitize_messages(messages)
        instructions_parts: list[str] = []
        items: list[dict[str, Any]] = []

@@ -372,6 +372,7 @@ class ChatSession:
        self._applied_skill_version: int = 0
        self._applied_skill_content: str = ""  # inline prompt from applied skill
        self._assistant_pending_tokens = 0
+        self._calibrated_msg_count = 0  # len(messages) at last _update_token_table
        self.creative_mode = False
        self._notify_count = 0
        # Watch support: server-level runner injected via set_watch_runner()
@@ -918,11 +919,25 @@ class ChatSession:
    def _remaining_token_budget(self) -> int:
        """Estimate how many tokens are available for new content.

+        When provider-reported usage is available, uses the last API
+        call's ``prompt_tokens`` as ground truth and only estimates the
+        delta (messages added since that call).  Falls back to pure
+        local estimates otherwise.
+
        Reserves a response budget (capped at 25% of context window, since
        ``max_tokens`` is an upper bound, not guaranteed consumption) plus
        a 5% safety margin.  Returns at least 0.
        """
        used = self._system_tokens + sum(self._msg_tokens)
+        if self._last_usage:
+            # Provider-reported tokens from the last API call
+            base = self._last_usage["prompt_tokens"]
+            # Only estimate tokens for messages added AFTER calibration.
+            # Clamp index to prevent stale _calibrated_msg_count from
+            # over-slicing after compaction or message list mutations.
+            start = min(self._calibrated_msg_count, len(self._msg_tokens))
+            new_msg_tokens = sum(self._msg_tokens[start:])
+            used = base + new_msg_tokens
        response_reserve = min(self.max_tokens, self.context_window // 4)
        safety_margin = int(self.context_window * 0.05)
        return max(0, self.context_window - used - response_reserve - safety_margin)
@@ -1090,6 +1105,7 @@ class ChatSession:
        self._read_files.clear()
        self._recent_tool_sigs.clear()
        self._last_usage = None
+        self._calibrated_msg_count = 0
        self._title_generated = True  # don't re-title resumed workstreams
        self._msg_tokens = [
            max(1, int(self._msg_char_count(m) / self._chars_per_token)) for m in self.messages
@@ -1836,6 +1852,7 @@ class ChatSession:
                    return

                self._update_token_table(assistant_msg)
+                self._print_status_line()  # Report usage for EVERY API call
                self.messages.append(assistant_msg)
                self._msg_tokens.append(
                    self._assistant_pending_tokens
@@ -1875,7 +1892,6 @@ class ChatSession:

                tool_calls = assistant_msg.get("tool_calls")
                if not tool_calls:
-                    self._print_status_line()
                    # Auto-compact when prompt exceeds threshold
                    if (
                        self._last_usage
@@ -2093,6 +2109,18 @@ class ChatSession:
                if user_feedback:
                    self.messages.append({"role": "user", "content": user_feedback})
                    self._msg_tokens.append(max(1, int(len(user_feedback) / self._chars_per_token)))
+
+                # Mid-turn compaction: prevent context overflow during long
+                # tool chains.  Uses local estimates since _last_usage reflects
+                # the previous API call, not the tool results just appended.
+                estimated_prompt = self._system_tokens + sum(self._msg_tokens)
+                if estimated_prompt > self.context_window * self.auto_compact_pct:
+                    pct_display = int(self.auto_compact_pct * 100)
+                    self.ui.on_info(
+                        f"\n[Auto-compacting mid-turn: estimated prompt "
+                        f"exceeds {pct_display}% of context window]"
+                    )
+                    self._compact_messages(auto=True)
        except GenerationCancelled:
            # If a newer send() has started (force cancel), this thread is
            # orphaned — skip all message mutations and state changes.
@@ -2259,6 +2287,11 @@ class ChatSession:
        Returns the complete assistant message as a dict suitable for
        appending to self.messages.
        """
+        # Reset so this API call captures fresh usage — prevents stale
+        # completion_tokens from a prior tool-chain iteration leaking
+        # through the max() accumulator.
+        self._last_usage = None
+
        content_parts: list[str] = []
        reasoning_parts: list[str] = []
        tool_calls_acc: dict[int, dict[str, Any]] = {}
@@ -2598,17 +2631,44 @@ class ChatSession:

    # -- Token tracking & status ----------------------------------------------

-    def _msg_char_count(self, msg: dict[str, Any]) -> int:
-        """Count characters in a message, including tool call arguments."""
+    # Fixed token count per image (provider-agnostic average).
+    _IMAGE_TOKENS = 1000
+
+    @staticmethod
+    def _msg_text_chars(msg: dict[str, Any]) -> tuple[int, int]:
+        """Return (text_chars, image_count) for a message.
+
+        Counts all textual content plus structural overhead (role,
+        tool_call IDs, tool call names/arguments).  Images are counted
+        separately so the calibration can subtract their fixed token
+        cost from prompt_tokens.
+        """
        content = msg.get("content")
+        n = 0
+        images = 0
        if isinstance(content, list):
-            n = sum(len(p.get("text", "")) for p in content if p.get("type") == "text")
+            n += sum(len(p.get("text", "")) for p in content if p.get("type") == "text")
+            images += sum(1 for p in content if p.get("type") == "image_url")
        else:
-            n = len(content or "")
+            n += len(content or "")
        for tc in msg.get("tool_calls", []):
+            n += len(tc.get("id", ""))
            n += len(tc.get("function", {}).get("name", ""))
            n += len(tc.get("function", {}).get("arguments", ""))
-        return n
+        # Structural overhead: role, tool_call_id
+        n += len(msg.get("role", ""))
+        n += len(msg.get("tool_call_id", ""))
+        return n, images
+
+    def _msg_char_count(self, msg: dict[str, Any]) -> int:
+        """Count characters in a message, including structural overhead.
+
+        Includes role markers, tool_call IDs, and image placeholders so
+        that the chars_per_token calibration matches what providers
+        actually bill.
+        """
+        text_chars, images = self._msg_text_chars(msg)
+        return text_chars + int(images * self._IMAGE_TOKENS * self._chars_per_token)

    def _update_token_table(self, assistant_msg: dict[str, Any]) -> None:
        """Update per-message token estimates using API usage data."""
@@ -2619,12 +2679,28 @@ class ChatSession:
        compl_tok = self._last_usage["completion_tokens"]

        # Calibrate chars_per_token ratio from actual usage.
+        # Images get a fixed token budget, so we subtract those from the
+        # provider-reported prompt_tokens and calibrate only the text portion.
        all_msgs = self._full_messages()  # system + self.messages (before append)
        active_tools = self._get_active_tools() or []
        tool_def_chars = sum(len(json.dumps(t)) for t in active_tools)
-        total_chars = sum(self._msg_char_count(m) for m in all_msgs) + tool_def_chars
-        if total_chars > 0 and prompt_tok > 0:
-            self._chars_per_token = total_chars / prompt_tok
+        text_chars = 0
+        image_count = 0
+        for m in all_msgs:
+            tc, ic = self._msg_text_chars(m)
+            text_chars += tc
+            image_count += ic
+        text_chars += tool_def_chars
+        image_tokens = image_count * self._IMAGE_TOKENS
+        text_prompt_tok = prompt_tok - image_tokens
+        if text_prompt_tok <= 0:
+            log.debug(
+                "Image token estimate (%d) >= prompt_tokens (%d), skipping calibration",
+                image_tokens,
+                prompt_tok,
+            )
+        elif text_chars > 0:
+            self._chars_per_token = text_chars / text_prompt_tok

        # Compute system_tokens (stable after first call)
        sys_chars = sum(self._msg_char_count(m) for m in self.system_messages)
@@ -2638,6 +2714,10 @@ class ChatSession:
        # Stash completion_tokens for the assistant message about to be appended
        self._assistant_pending_tokens = compl_tok

+        # Record how many messages were in context at calibration time so
+        # _remaining_token_budget() can estimate only the delta.
+        self._calibrated_msg_count = len(self.messages)
+
        # Token budget tracking
        if self._token_budget > 0:
            total = prompt_tok + compl_tok
@@ -2849,6 +2929,7 @@ class ChatSession:
        su_tok = max(1, int(self._msg_char_count(summary_user) / self._chars_per_token))
        sa_tok = max(1, int(self._msg_char_count(summary_asst) / self._chars_per_token))
        self._msg_tokens = [su_tok, sa_tok]
+        self._calibrated_msg_count = len(self.messages)  # anchored to compacted state
        after_tokens = self._system_tokens + sum(self._msg_tokens)

        # Update usage estimate so the status bar reflects post-compaction state
@@ -6713,6 +6794,7 @@ class ChatSession:
            self._read_files.clear()
            self._recent_tool_sigs.clear()
            self._last_usage = None
+            self._calibrated_msg_count = 0
            self._msg_tokens = []
            self.ui.on_info("Context cleared (messages preserved in database).")

@@ -6723,6 +6805,7 @@ class ChatSession:
            self._read_files.clear()
            self._recent_tool_sigs.clear()
            self._last_usage = None
+            self._calibrated_msg_count = 0
            self._msg_tokens = []
            self._ws_id = uuid.uuid4().hex
            self._title_generated = False
@@ -3368,6 +3368,7 @@ function renderSavedWorkstreams(items) {
      chk.type = "checkbox";
      chk.className = "ws-card-check";
      chk.checked = !!_wsDeleteSelected[sess.ws_id];
+      chk.setAttribute("aria-label", "Select " + label + " for deletion");
      chk.onclick = function (e) {
        e.stopPropagation();
        if (chk.checked) _wsDeleteSelected[sess.ws_id] = true;
@@ -3376,11 +3377,19 @@ function renderSavedWorkstreams(items) {
        updateWsDeleteBar();
      };
      card.appendChild(chk);
+      card.setAttribute("tabindex", "0");
      card.onclick = function (e) {
        if (e.target === chk) return;
        chk.checked = !chk.checked;
        chk.onclick(e);
      };
+      card.onkeydown = function (e) {
+        if (e.key === "Enter" || e.key === " ") {
+          e.preventDefault();
+          chk.checked = !chk.checked;
+          chk.onclick(e);
+        }
+      };
    } else {
      card.setAttribute("role", "button");
      card.setAttribute("tabindex", "0");
@@ -3505,6 +3514,7 @@ function confirmWsDeleteSelection() {
  if (delBtn) {
    delBtn.textContent = "Delete";
    delBtn.disabled = false;
+    delBtn.classList.remove("ws-delete-close");
    delBtn.onclick = confirmWsDelete;
  }
  var cancelBtn = document.getElementById("ws-delete-cancel-btn");
@@ -3636,6 +3646,7 @@ function confirmWsDelete() {
    if (delBtn) {
      delBtn.disabled = false;
      delBtn.textContent = "Close";
+      delBtn.classList.add("ws-delete-close");
      delBtn.onclick = function () {
        cancelWsDelete();
        cancelWsDeleteMode();
@@ -60,7 +60,7 @@
      <div id="ws-delete-bar" class="ws-delete-bar">
        <span class="ws-delete-count-label" id="ws-delete-bar-count" role="status" aria-live="polite" aria-atomic="true">0 selected</span>
        <button class="ws-delete-cancel-btn" onclick="cancelWsDeleteMode()">Cancel</button>
-        <button class="ws-delete-cancel-btn" id="ws-delete-bar-select-all" onclick="toggleSelectAll()">Select All</button>
+        <button class="ws-delete-selectall-btn" id="ws-delete-bar-select-all" onclick="toggleSelectAll()">Select All</button>
        <button class="ws-delete-bar-btn" id="ws-delete-bar-delete" onclick="confirmWsDeleteSelection()" disabled>Delete Selected</button>
      </div>
    </section>
@@ -1504,8 +1504,12 @@ audio.media-player {
 .dashboard-card .card-meta { font-size: 11px; color: var(--fg-dim); }

 /* Delete mode */
-.dashboard-card.ws-delete-mode { cursor: default; }
-.dashboard-card.ws-delete-mode:hover { border-color: var(--border); background: var(--bg-surface); }
+.dashboard-card.ws-delete-mode { cursor: pointer; }
+.dashboard-card.ws-delete-mode:hover { border-color: var(--red); background: rgba(248, 113, 113, 0.04); }
+.dashboard-card.ws-delete-mode.ws-selected { cursor: default; }
+.dashboard-card.ws-delete-mode.ws-selected:hover { border-color: var(--red); background: rgba(248, 113, 113, 0.08); }
+[data-theme="light"] .dashboard-card.ws-delete-mode:hover { background: rgba(220, 38, 38, 0.04); }
+[data-theme="light"] .dashboard-card.ws-delete-mode.ws-selected:hover { background: rgba(220, 38, 38, 0.08); }
 .ws-card-check {
  position: absolute;
  top: 8px;
@@ -1515,7 +1519,10 @@ audio.media-player {
  accent-color: var(--red);
  cursor: pointer;
  z-index: 1;
+  opacity: 0;
+  animation: ws-check-fadein 0.2s ease-out forwards;
 }
+@keyframes ws-check-fadein { to { opacity: 1; } }
 .dashboard-card.ws-selected {
  border-color: var(--red);
  background: rgba(248, 113, 113, 0.08);
@@ -1533,7 +1540,12 @@ audio.media-player {
  border: 1px solid var(--border);
  border-radius: var(--radius);
 }
-.ws-delete-bar.visible { display: flex; }
+.ws-delete-bar.visible { display: flex; animation: ws-bar-slide 0.2s ease-out; }
+@keyframes ws-bar-slide { from { opacity: 0; transform: translateY(-8px); } to { opacity: 1; transform: translateY(0); } }
+@media (prefers-reduced-motion: reduce) {
+  .ws-card-check { animation: none; opacity: 1; }
+  .ws-delete-bar.visible { animation: none; }
+}
 .ws-delete-bar .ws-delete-count-label { font-size: 12px; color: var(--fg-dim); }
 .ws-delete-bar .ws-delete-bar-btn {
  margin-left: auto;
@@ -1563,6 +1575,20 @@ audio.media-player {
  border-color: var(--border-strong);
  background: var(--bg-highlight);
 }
+.ws-delete-bar .ws-delete-selectall-btn {
+  background: transparent;
+  color: var(--fg-bright);
+  border: 1px solid var(--border);
+  border-radius: var(--radius);
+  padding: 6px 12px;
+  font-size: 12px;
+  font-weight: 500;
+  cursor: pointer;
+}
+.ws-delete-bar .ws-delete-selectall-btn:hover {
+  border-color: var(--border-strong);
+  background: var(--bg-highlight);
+}

 /* Delete modal */
 #ws-delete-overlay {
@@ -1608,6 +1634,11 @@ audio.media-player {
  color: #fff;
  border-color: var(--red);
 }
+#ws-delete-buttons button.ws-delete-close {
+  background: transparent;
+  color: var(--fg-bright);
+  border-color: var(--border);
+}

 /* Server dashboard row — clickable */
 .dash-row { cursor: pointer; }
@@ -155,7 +155,7 @@ wheels = [

 [[package]]
 name = "anthropic"
-version = "0.89.0"
+version = "0.92.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "anyio" },
@@ -167,9 +167,9 @@ dependencies = [
    { name = "sniffio" },
    { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/60/af/862e216dd6c5e9bc02fb374eeaaa19017c51b90ddfa5692668a3811947bd/anthropic-0.89.0.tar.gz", hash = "sha256:f3d75b8ccef4b35f3702639519e461eba437d4bcdfabb69378c65a02ab7bda66", size = 596758, upload-time = "2026-04-03T18:57:01.348Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/01/2d/fc5c5a369db977efbaa646d77ba42b38a6de4e95789884032b0e2e3fc834/anthropic-0.92.0.tar.gz", hash = "sha256:d1e792ed0692379452a1af6b266df495e973c3695cd0aace2a108b838393cbc4", size = 652420, upload-time = "2026-04-08T16:55:35.37Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/22/ba/9f973f22abb512d5d17428a76e4ecbc8d49b9dd1b5a1152576d48c24dc1d/anthropic-0.89.0-py3-none-any.whl", hash = "sha256:c6d23854af798f2471ca3bc653cca394d392cc272fe803d3da9d63575b8445f0", size = 478847, upload-time = "2026-04-03T18:56:59.54Z" },
+    { url = "https://files.pythonhosted.org/packages/c3/21/bf5b5ab10b6932c5c43eaa66b6e3f256de569cf0323d89f9cc281a0d0f39/anthropic-0.92.0-py3-none-any.whl", hash = "sha256:f92a4bd065d5cab90a96b65bb44e473bf7c6fe731a743cd156e9ad1d245c381e", size = 621195, upload-time = "2026-04-08T16:55:33.639Z" },
 ]

 [[package]]
@@ -538,75 +538,75 @@ wheels = [

 [[package]]
 name = "cryptography"
-version = "46.0.6"
+version = "46.0.7"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "cffi", marker = "platform_python_implementation != 'PyPy'" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/47/93/ac8f3d5ff04d54bc814e961a43ae5b0b146154c89c61b47bb07557679b18/cryptography-46.0.7.tar.gz", hash = "sha256:e4cfd68c5f3e0bfdad0d38e023239b96a2fe84146481852dffbcca442c245aa5", size = 750652, upload-time = "2026-04-08T01:57:54.692Z" }
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Author	SHA1	Message	Date
Patrick Buckley	2ab60853f5	chore: bump version to 1.2.2	2026-04-12 20:41:42 -07:00
Patrick Buckley	fed5b96a6f	fix: universal tool_call/tool_result orphan detection for OpenAI-comp… (#346 ) * fix: universal tool_call/tool_result orphan detection for OpenAI-compat providers The Anthropic provider had orphan detection for mismatched tool_call ↔ tool_result pairs, but OpenAI-compatible providers (Chat Completions, Google, Responses API) had none. When an Anthropic model runs behind an OpenAI-compat API (e.g. Azure) or cancellation creates orphans, the API rejects the malformed request. - Rewrite sanitize_messages() with orphan detection: synthesize error tool results for unmatched tool_calls, drop tool results with no matching tool_call, fill empty tool_call IDs with positional remap - Call sanitize_messages() from Responses API _convert_messages() * fix: address review feedback on orphan detection - Track answered IDs per-turn (local_answered) instead of scanning all of out, preventing false matches from reused IDs across turns - Drop empty-ID tool results that have no remap entry instead of passing them through with invalid empty tool_call_id - Increment empty_result_idx for every empty result, not just remapped - Remove dead result_ids peek-ahead code - Add test for repeated tool_call IDs across turns	2026-04-12 20:41:28 -07:00
Patrick Buckley	4a65535e00	fix: accurate token usage tracking for compaction across all providers (#345 ) * fix: accurate token usage tracking for compaction across all providers Anthropic's input_tokens excluded cached tokens, causing massive under-reporting (e.g. 327 vs 9000 actual) when prompt caching was active. This prevented auto-compaction from triggering. - Normalize Anthropic prompt_tokens to total input (input_tokens + cache_creation + cache_read), matching OpenAI semantics - Reset _last_usage per API call so tool-chain iterations get fresh usage instead of max()-merging with stale values - Add mid-turn compaction check during tool chains to prevent context overflow before end-of-turn - Anchor _remaining_token_budget() on provider-reported prompt_tokens with local estimates only for the delta since last API call - Improve _msg_char_count() to include structural overhead (role, tool_call_id, tool call IDs) and handle image tokens in calibration - Emit status after every API call, not just end of turn * fix: defensive null coercion and index clamping from review feedback - Add `or 0` to all getattr calls for input_tokens/output_tokens in Anthropic provider (streaming + non-streaming) to handle SDK nulls - Use getattr for non-streaming input_tokens/output_tokens instead of direct attribute access for consistency - Clamp _calibrated_msg_count with min() in _remaining_token_budget() to prevent stale state from over-slicing after compaction	2026-04-12 20:41:28 -07:00
Patrick Buckley	519b86f56e	chore: bump version to 1.2.1	2026-04-08 18:06:12 -07:00
Patrick Buckley	024a2e98d2	fix(ui): remove broken hint animation and restore card toggle The ws-check-hint animation clobbered the fadein's forwards fill, making the checkbox invisible for 0.6s on card-body click — appearing as a deselect-then-reselect. Remove the hint, the unused role=checkbox on the card, and restore the original symmetric toggle behavior.	2026-04-08 18:05:41 -07:00
Patrick Buckley	e9c141aba5	fix(ui): improve delete workstream UX and accessibility (#339 ) * fix(ui): improve delete workstream UX and accessibility Card body click no longer deselects (prevents confusing red border loss); checkbox pulse hint guides users to deselect affordance. Adds keyboard navigation, aria-labels, hover feedback, animations, and neutral Close button styling after deletion. * fix(ui): remove duplicate a11y checkbox from delete-mode cards Hide the visual checkbox from the a11y tree and tab order so the card (role=checkbox) is the sole keyboard/screen-reader target. Addresses Copilot review feedback about nested interactive elements.	2026-04-08 17:20:45 -07:00
Patrick Buckley	b038dbdd5b	chore(deps): bump lacme to >=1.0.5 (cryptography security update)	2026-04-08 16:48:35 -07:00