fix: avoid gluing reasoning sentences across deltas

src/fast_agent/llm/provider/openai/llm_openai.py

@@ -52,6 +52,7 @@
 from fast_agent.llm.usage_tracking import TurnUsage
 from fast_agent.mcp.helpers.content_helpers import get_text
 from fast_agent.types import LlmStopReason, PromptMessageExtended
+from fast_agent.utils.reasoning_chunk_join import normalize_reasoning_delta
 
 _logger = get_logger(__name__)
 
@@ -235,17 +236,22 @@ def _handle_reasoning_delta(
         if not reasoning_text:
             return reasoning_active
 
+        last_char = reasoning_segments[-1][-1] if reasoning_segments and reasoning_segments[-1] else None
+        normalized_text = normalize_reasoning_delta(last_char, reasoning_text)
+        if not normalized_text:
+            return reasoning_active
+
         if reasoning_mode == "tags":
             if not reasoning_active:
                 reasoning_active = True
-            self._notify_stream_listeners(StreamChunk(text=reasoning_text, is_reasoning=True))
-            reasoning_segments.append(reasoning_text)
+            self._notify_stream_listeners(StreamChunk(text=normalized_text, is_reasoning=True))
+            reasoning_segments.append(normalized_text)
             return reasoning_active
 
         if reasoning_mode in {"stream", "reasoning_content", "gpt_oss"}:
             # Emit reasoning as-is
-            self._notify_stream_listeners(StreamChunk(text=reasoning_text, is_reasoning=True))
-            reasoning_segments.append(reasoning_text)
+            self._notify_stream_listeners(StreamChunk(text=normalized_text, is_reasoning=True))
+            reasoning_segments.append(normalized_text)
             return reasoning_active
 
         return reasoning_active

src/fast_agent/llm/provider/openai/openresponses_streaming.py

@@ -11,6 +11,7 @@
 from fast_agent.llm.provider.openai.streaming_utils import finalize_stream_response
 from fast_agent.llm.provider.openai.tool_notifications import OpenAIToolNotificationMixin
 from fast_agent.llm.stream_types import StreamChunk
+from fast_agent.utils.reasoning_chunk_join import normalize_reasoning_delta
 
 if TYPE_CHECKING:
     from openai.types.responses import (
@@ -201,11 +202,19 @@ async def _process_stream(
                     part_type = getattr(part, "type", None)
                     part_text = getattr(part, "text", None)
                     if part_type in {"reasoning", "reasoning_text"} and part_text:
-                        reasoning_segments.append(part_text)
+                        last_char = (
+                            reasoning_segments[-1][-1]
+                            if reasoning_segments and reasoning_segments[-1]
+                            else None
+                        )
+                        normalized_delta = normalize_reasoning_delta(last_char, part_text)
+                        if not normalized_delta:
+                            continue
+                        reasoning_segments.append(normalized_delta)
                         self._notify_stream_listeners(
-                            StreamChunk(text=part_text, is_reasoning=True)
+                            StreamChunk(text=normalized_delta, is_reasoning=True)
                         )
-                        reasoning_chars += len(part_text)
+                        reasoning_chars += len(normalized_delta)
                         await self._emit_streaming_progress(
                             model=f"{model} (reasoning)",
                             new_total=reasoning_chars,
@@ -218,11 +227,19 @@ async def _process_stream(
                     "response.reasoning_summary.delta",
                 }:
                     if delta:
-                        reasoning_segments.append(delta)
+                        last_char = (
+                            reasoning_segments[-1][-1]
+                            if reasoning_segments and reasoning_segments[-1]
+                            else None
+                        )
+                        normalized_delta = normalize_reasoning_delta(last_char, delta)
+                        if not normalized_delta:
+                            continue
+                        reasoning_segments.append(normalized_delta)
                         self._notify_stream_listeners(
-                            StreamChunk(text=delta, is_reasoning=True)
+                            StreamChunk(text=normalized_delta, is_reasoning=True)
                         )
-                        reasoning_chars += len(delta)
+                        reasoning_chars += len(normalized_delta)
                         await self._emit_streaming_progress(
                             model=f"{model} (summary)",
                             new_total=reasoning_chars,
@@ -235,11 +252,19 @@ async def _process_stream(
                     "response.reasoning_text.delta",
                 }:
                     if delta:
-                        reasoning_segments.append(delta)
+                        last_char = (
+                            reasoning_segments[-1][-1]
+                            if reasoning_segments and reasoning_segments[-1]
+                            else None
+                        )
+                        normalized_delta = normalize_reasoning_delta(last_char, delta)
+                        if not normalized_delta:
+                            continue
+                        reasoning_segments.append(normalized_delta)
                         self._notify_stream_listeners(
-                            StreamChunk(text=delta, is_reasoning=True)
+                            StreamChunk(text=normalized_delta, is_reasoning=True)
                         )
-                        reasoning_chars += len(delta)
+                        reasoning_chars += len(normalized_delta)
                         await self._emit_streaming_progress(
                             model=f"{model} (reasoning)",
                             new_total=reasoning_chars,

src/fast_agent/llm/provider/openai/responses_streaming.py

@@ -15,6 +15,7 @@
 from fast_agent.llm.provider.openai.streaming_utils import finalize_stream_response
 from fast_agent.llm.provider.openai.tool_notifications import OpenAIToolNotificationMixin
 from fast_agent.llm.stream_types import StreamChunk
+from fast_agent.utils.reasoning_chunk_join import normalize_reasoning_delta
 
 _logger = get_logger(__name__)
 
@@ -156,11 +157,19 @@ def _close_tool(index: int, tool_use_id: str | None) -> None:
             }:
                 delta = getattr(event, "delta", None)
                 if delta:
-                    reasoning_segments.append(delta)
+                    last_char = (
+                        reasoning_segments[-1][-1]
+                        if reasoning_segments and reasoning_segments[-1]
+                        else None
+                    )
+                    normalized_delta = normalize_reasoning_delta(last_char, delta)
+                    if not normalized_delta:
+                        continue
+                    reasoning_segments.append(normalized_delta)
                     self._notify_stream_listeners(
-                        StreamChunk(text=delta, is_reasoning=True)
+                        StreamChunk(text=normalized_delta, is_reasoning=True)
                     )
-                    reasoning_chars += len(delta)
+                    reasoning_chars += len(normalized_delta)
                     await self._emit_streaming_progress(
                         model=f"{model} (summary)",
                         new_total=reasoning_chars,

src/fast_agent/utils/reasoning_chunk_join.py

@@ -0,0 +1,31 @@
+from __future__ import annotations
+
+_SENTENCE_PUNCTUATION = ".!?;:"
+_MARKDOWN_PREFIXES = "\"`*["
+
+
+def _looks_like_sentence_chunk(incoming: str) -> bool:
+    if not incoming:
+        return False
+    if " " not in incoming:
+        return False
+    first = incoming[0]
+    return first.isupper() or first in _MARKDOWN_PREFIXES
+
+
+def normalize_reasoning_delta(last_char: str | None, incoming: str) -> str:
+    """Normalize one reasoning delta without rebuilding the full accumulated text.
+
+    Keep the Codex-style append-only flow, but patch the specific broken case where
+    providers split natural-language reasoning into sentence chunks without a
+    separating space, e.g. "approach." + "Specifying session retrieval format".
+    """
+    if not incoming:
+        return ""
+    if not last_char or last_char.isspace() or incoming[0].isspace():
+        return incoming
+    if last_char in _SENTENCE_PUNCTUATION and _looks_like_sentence_chunk(incoming):
+        return f" {incoming}"
+    if last_char.islower() and _looks_like_sentence_chunk(incoming):
+        return f" {incoming}"
+    return incoming

tests/unit/fast_agent/test_reasoning_chunk_join.py

@@ -0,0 +1,40 @@
+from fast_agent.utils.reasoning_chunk_join import normalize_reasoning_delta
+
+
+def test_normalize_reasoning_delta_inserts_space_after_sentence_break() -> None:
+    last_char = None
+    emitted = ""
+    parts = [
+        "approach.",
+        "Specifying session retrieval format",
+        "Selecting session retrieval method",
+    ]
+
+    for part in parts:
+        delta = normalize_reasoning_delta(last_char, part)
+        emitted += delta
+        last_char = emitted[-1] if emitted else None
+
+    assert emitted == "approach. Specifying session retrieval format Selecting session retrieval method"
+
+
+def test_normalize_reasoning_delta_preserves_contractions() -> None:
+    last_char = None
+    emitted = ""
+    for part in ["don", "'t do that"]:
+        delta = normalize_reasoning_delta(last_char, part)
+        emitted += delta
+        last_char = emitted[-1] if emitted else None
+
+    assert emitted == "don't do that"
+
+
+def test_normalize_reasoning_delta_preserves_identifier_fragments() -> None:
+    last_char = None
+    emitted = ""
+    for part in ["session", "_id is required"]:
+        delta = normalize_reasoning_delta(last_char, part)
+        emitted += delta
+        last_char = emitted[-1] if emitted else None
+
+    assert emitted == "session_id is required"