core/agent: streaming loop with text deltas and tool-call reconstruction

src/plyngent/agent/loop.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, cast
 
 from msgspec import UNSET
 
@@ -11,10 +11,12 @@ from plyngent.lmproto.openai_compatible.model import (
     ChatCompletionsParam,
     ToolChatMessage,
 )
+from plyngent.typedef import Unset  # noqa: TC001
 
 from .events import (
     AgentEvent,
     AssistantMessageEvent,
+    ErrorEvent,
     MaxRoundsEvent,
     TextDeltaEvent,
     ToolCallEvent,
@@ -43,7 +45,11 @@ async def _execute_tool_calls(
     for call in tool_calls:
         yield ToolCallEvent(tool_call=call)
         if isinstance(call, AssistantFunctionToolCall):
+            try:
                 result_text = await tools.execute(call.function.name, call.function.arguments)
+            except Exception as exc:  # noqa: BLE001
+                result_text = f"error: tool {call.function.name!r} failed: {exc}"
+                yield ErrorEvent(message=result_text)
             tool_msg = ToolChatMessage(content=result_text, tool_call_id=call.id)
         else:
             tool_msg = ToolChatMessage(
@@ -54,7 +60,61 @@ async def _execute_tool_calls(
         yield ToolResultEvent(message=tool_msg)
 
 
-async def run_chat_loop(  # noqa: PLR0913
+async def _stream_and_build_assistant(  # noqa: C901
+    client: ChatClient,
+    param: ChatCompletionsParam,
+) -> tuple[AssistantChatMessage, list[TextDeltaEvent]]:
+    """Stream a round, return the assistant message and any text deltas."""
+    raw_lines_attr = getattr(client, "chat_completions_raw_lines", None)
+    if raw_lines_attr is None:
+        response = await client.chat_completions(param, stream=False)
+        if not response.choices:
+            msg = "chat completion response contained no choices"
+            raise RuntimeError(msg)
+        assistant = response.choices[0].message
+        text_events = []
+        if isinstance(assistant.content, str) and assistant.content:
+            text_events.append(TextDeltaEvent(content=assistant.content))
+        return assistant, text_events
+
+    stream_iter = await raw_lines_attr(param)  # type: ignore[misc]
+    raw_lines: list[bytes] = []
+    content_parts: list[str] = []
+    finish_reason: str | None = None
+    text_events = []
+    stream_decoder = getattr(client, "stream_decoder", None)
+
+    async for raw in stream_iter:
+        raw_lines.append(raw)
+        if stream_decoder is not None:
+            try:
+                chunk = stream_decoder.decode(raw)
+            except Exception:  # noqa: BLE001
+                continue
+            if chunk.choices:
+                delta_text = chunk.choices[0].delta.content
+                if isinstance(delta_text, str) and delta_text:
+                    content_parts.append(delta_text)
+                    text_events.append(TextDeltaEvent(content=delta_text))
+                fr = chunk.choices[0].finish_reason
+                if isinstance(fr, str):
+                    finish_reason = fr
+
+    full_content = "".join(content_parts) or ""
+    tool_calls: list[AnyAssistantToolCall] | Unset = UNSET
+
+    if finish_reason in ("tool_calls", "function_call"):
+        from plyngent.lmproto.openai_compatible.client import merge_stream_tool_calls
+
+        calls = merge_stream_tool_calls(raw_lines)
+        if calls:
+            tool_calls = cast("list[AnyAssistantToolCall]", calls)
+
+    assistant = AssistantChatMessage(content=full_content or None, tool_calls=tool_calls)
+    return assistant, text_events
+
+
+async def run_chat_loop(  # noqa: PLR0913, C901
     client: ChatClient,
     messages: list[AnyChatMessage],
     *,
@@ -63,12 +123,14 @@ async def run_chat_loop(  # noqa: PLR0913
     max_rounds: int = DEFAULT_MAX_ROUNDS,
     temperature: float | None = None,
     on_limit: LimitContinueHook | None = None,
+    stream: bool = True,
 ) -> AsyncIterator[AgentEvent]:
     """Multi-round chat/tool loop; mutates ``messages`` in place and yields events.
 
+    When ``stream=True``, text tokens yield as they arrive; for tool-calling
+    rounds, the full response is reconstructed from stream deltas.
+
     Continues until the model returns no tool calls, or ``max_rounds`` is hit.
-    If ``on_limit`` is set and returns True when the cap is reached, another
-    batch of ``max_rounds`` is granted and the loop continues.
     """
     tool_items: Sequence[AnyToolItem] | None = None
     if tools is not None and len(tools) > 0:
@@ -86,17 +148,23 @@ async def run_chat_loop(  # noqa: PLR0913
                 temperature=temperature if temperature is not None else UNSET,
                 tools=list(tool_items) if tool_items is not None else UNSET,
             )
+
+            if stream:
+                assistant, text_events = await _stream_and_build_assistant(client, param)
+                for event in text_events:
+                    yield event
+            else:
                 response = await client.chat_completions(param, stream=False)
                 if not response.choices:
                     msg = "chat completion response contained no choices"
                     raise RuntimeError(msg)
                 assistant = response.choices[0].message
-            messages.append(assistant)
-            yield AssistantMessageEvent(message=assistant)
-
                 if isinstance(assistant.content, str) and assistant.content:
                     yield TextDeltaEvent(content=assistant.content)
 
+            messages.append(assistant)
+            yield AssistantMessageEvent(message=assistant)
+
             tool_calls = assistant.tool_calls
             if tool_calls is UNSET or not tool_calls:
                 return
@@ -112,7 +180,3 @@ async def run_chat_loop(  # noqa: PLR0913
             continue
         yield MaxRoundsEvent(rounds=allowance, continued=False)
         return
-
-
-def collect_assistant_messages(events: Sequence[AgentEvent]) -> list[AssistantChatMessage]:
-    return [e.message for e in events if isinstance(e, AssistantMessageEvent)]