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https://github.com/NCBM/plyngent.git
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NCBM
9b38a3b333
Add prek.toml so git commit runs ruff-pre-commit (fix then format) and pdm-based basedpyright. Document install/install-hook; clear type warnings that made basedpyright exit non-zero under recommended mode.
967 lines
34 KiB
Python
967 lines
34 KiB
Python
from __future__ import annotations
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from typing import TYPE_CHECKING, Literal, overload
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import pytest
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from msgspec import UNSET
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from plyngent.agent import (
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AssistantMessageEvent,
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ChatAgent,
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MaxRoundsEvent,
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ReasoningDeltaEvent,
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TextDeltaEvent,
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ToolCallEvent,
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ToolRegistry,
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ToolResultEvent,
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UsageEvent,
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run_chat_loop,
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tool,
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)
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from plyngent.config.models import DatabaseConfig
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from plyngent.lmproto.openai_compatible.model import (
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AnyChatMessage,
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AssistantChatMessage,
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AssistantFunctionTool,
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AssistantFunctionToolCall,
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ChatCompletionChoice,
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ChatCompletionChunk,
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ChatCompletionResponse,
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ChatCompletionsParam,
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ChunkChoice,
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DeltaMessage,
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FinishReason,
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StreamFunctionDelta,
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StreamToolCallDelta,
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ToolChatMessage,
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UserChatMessage,
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)
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from plyngent.memory import MemoryStore
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if TYPE_CHECKING:
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from collections.abc import AsyncIterator
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def _chunks_from_response(response: ChatCompletionResponse) -> list[ChatCompletionChunk]:
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"""Turn a full response into stream chunks (library-style stream=True path)."""
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message = response.choices[0].message
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chunks: list[ChatCompletionChunk] = []
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if isinstance(message.content, str) and message.content:
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chunks.append(
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ChatCompletionChunk(
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id=response.id,
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object="chat.completion.chunk",
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created=response.created,
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model=response.model,
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choices=[
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ChunkChoice(
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index=0,
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delta=DeltaMessage(content=message.content),
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finish_reason=None,
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)
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],
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)
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)
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# Emit terminal finish_reason when content was streamed without one.
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fr = response.choices[0].finish_reason
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if (
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fr
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and (isinstance(message.content, str) and message.content)
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and (message.tool_calls is UNSET or not message.tool_calls)
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):
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chunks.append(
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ChatCompletionChunk(
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id=response.id,
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object="chat.completion.chunk",
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created=response.created,
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model=response.model,
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choices=[
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ChunkChoice(
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index=0,
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delta=DeltaMessage(),
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finish_reason=fr,
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)
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],
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)
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)
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tool_calls = message.tool_calls
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if tool_calls is not UNSET and tool_calls:
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deltas: list[StreamToolCallDelta] = []
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for i, call in enumerate(tool_calls):
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if isinstance(call, AssistantFunctionToolCall):
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deltas.append(
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StreamToolCallDelta(
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index=i,
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id=call.id,
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type="function",
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function=StreamFunctionDelta(
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name=call.function.name,
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arguments=call.function.arguments,
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),
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)
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)
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if deltas:
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chunks.append(
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ChatCompletionChunk(
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id=response.id,
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object="chat.completion.chunk",
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created=response.created,
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model=response.model,
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choices=[
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ChunkChoice(
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index=0,
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delta=DeltaMessage(tool_calls=deltas),
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finish_reason="tool_calls",
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)
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],
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)
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)
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if not chunks:
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chunks.append(
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ChatCompletionChunk(
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id=response.id,
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object="chat.completion.chunk",
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created=response.created,
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model=response.model,
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choices=[
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ChunkChoice(
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index=0,
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delta=DeltaMessage(),
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finish_reason=response.choices[0].finish_reason or "stop",
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)
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],
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)
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)
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return chunks
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class ScriptedClient:
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"""Scripted chat completions; supports stream=True via chunked responses."""
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_responses: list[ChatCompletionResponse]
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calls: list[ChatCompletionsParam]
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def __init__(self, responses: list[ChatCompletionResponse]) -> None:
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self._responses = list(responses)
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self.calls = []
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@overload
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: Literal[False] = False
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) -> ChatCompletionResponse: ...
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@overload
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: Literal[True]
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) -> AsyncIterator[ChatCompletionChunk]: ...
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: bool = False
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) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
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self.calls.append(param)
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if not self._responses:
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msg = "no more scripted responses"
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raise RuntimeError(msg)
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response = self._responses.pop(0)
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if stream:
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return self._as_stream(response)
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return response
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async def _as_stream(self, response: ChatCompletionResponse) -> AsyncIterator[ChatCompletionChunk]:
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for chunk in _chunks_from_response(response):
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yield chunk
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def _response(
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message: AssistantChatMessage,
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*,
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usage: dict[str, object] | None = None,
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finish_reason: FinishReason | None = "stop",
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) -> ChatCompletionResponse:
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return ChatCompletionResponse(
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id="1",
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object="chat.completion",
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created=0,
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model="test",
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choices=[
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ChatCompletionChoice(
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index=0,
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message=message,
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logprobs={},
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finish_reason=finish_reason,
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)
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],
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system_fingerprint="",
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usage=usage if usage is not None else {},
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)
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async def test_run_chat_loop_text_only() -> None:
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client = ScriptedClient(
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[
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_response(AssistantChatMessage(content="hello")),
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]
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)
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messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
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events = [e async for e in run_chat_loop(client, messages, model="m", stream=False)]
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assert isinstance(events[0], TextDeltaEvent)
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assert events[0].content == "hello"
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assert isinstance(events[1], AssistantMessageEvent)
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assert len(messages) == 2
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assert len(client.calls) == 1
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async def test_non_stream_emits_usage() -> None:
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client = ScriptedClient(
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[
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_response(
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AssistantChatMessage(content="hi"),
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usage={"prompt_tokens": 9, "completion_tokens": 2, "total_tokens": 11},
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),
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]
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)
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messages: list[AnyChatMessage] = [UserChatMessage(content="x")]
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events = [e async for e in run_chat_loop(client, messages, model="m", stream=False)]
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usages = [e for e in events if isinstance(e, UsageEvent)]
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assert len(usages) == 1
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assert usages[0].usage.prompt_tokens == 9
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assert usages[0].usage.completion_tokens == 2
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assert usages[0].usage.total_tokens == 11
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assert usages[0].usage.source == "api"
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async def test_non_stream_estimates_usage_when_missing() -> None:
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client = ScriptedClient([_response(AssistantChatMessage(content="hello"))])
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messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
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events = [e async for e in run_chat_loop(client, messages, model="m", stream=False)]
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usages = [e for e in events if isinstance(e, UsageEvent)]
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assert len(usages) == 1
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assert usages[0].usage.source == "estimate"
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assert usages[0].usage.total_tokens > 0
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async def test_chat_agent_accumulates_session_usage() -> None:
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client = ScriptedClient(
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[
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_response(
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AssistantChatMessage(content="a"),
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usage={"prompt_tokens": 5, "completion_tokens": 1, "total_tokens": 6},
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),
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_response(
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AssistantChatMessage(content="b"),
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usage={"prompt_tokens": 7, "completion_tokens": 3, "total_tokens": 10},
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),
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]
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)
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agent = ChatAgent(client, model="m", stream=False)
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_ = [e async for e in agent.run("one")]
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assert agent.last_turn_usage.total_tokens == 6
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assert agent.last_request_usage.total_tokens == 6
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assert agent.last_turn_rounds == 1
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assert agent.session_usage.total_tokens == 6
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_ = [e async for e in agent.run("two")]
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assert agent.last_turn_usage.total_tokens == 10
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assert agent.last_request_usage.total_tokens == 10
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assert agent.session_usage.total_tokens == 16
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async def test_chat_agent_turn_usage_sums_tool_rounds() -> None:
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"""Multi-round tool loop: turn usage is billing sum; last_request is final call."""
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@tool
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def ping() -> str:
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return "pong"
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registry = ToolRegistry([ping])
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client = ScriptedClient(
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[
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_response(
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AssistantChatMessage(
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content="",
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tool_calls=[
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AssistantFunctionToolCall(
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id="1",
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function=AssistantFunctionTool(name="ping", arguments="{}"),
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)
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],
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),
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usage={"prompt_tokens": 100, "completion_tokens": 5, "total_tokens": 105},
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),
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_response(
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AssistantChatMessage(content="done"),
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usage={"prompt_tokens": 200, "completion_tokens": 3, "total_tokens": 203},
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),
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]
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)
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agent = ChatAgent(client, model="m", tools=registry, stream=False)
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_ = [e async for e in agent.run("go")]
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assert agent.last_turn_rounds == 2
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assert agent.last_request_usage.prompt_tokens == 200
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assert agent.last_turn_usage.prompt_tokens == 300
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assert agent.last_turn_usage.total_tokens == 308
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# Context size is last request prompt, not billed sum
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assert agent.context_tokens == 200
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assert agent.context_tokens_source == "api"
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async def test_context_tokens_falls_back_to_message_estimate() -> None:
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agent = ChatAgent(
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ScriptedClient([]),
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model="m",
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stream=False,
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messages=[UserChatMessage(content="12345678")],
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)
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assert agent.last_request_usage.is_zero()
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assert agent.context_tokens_source == "estimate"
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assert agent.context_tokens >= 1
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async def test_stream_yields_deltas_incrementally() -> None:
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"""Text deltas are yielded as chunks arrive, not only after the full stream."""
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class ChunkClient:
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@overload
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: Literal[False] = False
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) -> ChatCompletionResponse: ...
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@overload
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: Literal[True]
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) -> AsyncIterator[ChatCompletionChunk]: ...
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: bool = False
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) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
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del param
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if not stream:
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return _response(AssistantChatMessage(content="ab"))
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async def chunks() -> AsyncIterator[ChatCompletionChunk]:
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for part in ("a", "b"):
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yield ChatCompletionChunk(
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id="1",
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object="chat.completion.chunk",
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created=0,
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model="t",
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choices=[
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ChunkChoice(
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index=0,
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delta=DeltaMessage(content=part),
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finish_reason=None,
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)
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],
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)
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return chunks()
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messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
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events = [e async for e in run_chat_loop(ChunkClient(), messages, model="m", stream=True)]
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deltas = [e for e in events if isinstance(e, TextDeltaEvent)]
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assert [d.content for d in deltas] == ["a", "b"]
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assert any(isinstance(e, AssistantMessageEvent) for e in events)
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assert isinstance(messages[-1], AssistantChatMessage)
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assert messages[-1].content == "ab"
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async def test_stream_yields_reasoning_deltas() -> None:
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class ReasoningClient:
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@overload
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: Literal[False] = False
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) -> ChatCompletionResponse: ...
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@overload
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: Literal[True]
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) -> AsyncIterator[ChatCompletionChunk]: ...
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async def chat_completions(
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self, param: ChatCompletionsParam, *, stream: bool = False
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) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
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del param
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if not stream:
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return _response(AssistantChatMessage(content="ans", reasoning_content="think"))
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async def chunks() -> AsyncIterator[ChatCompletionChunk]:
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for part in ("th", "ink"):
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yield ChatCompletionChunk(
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id="1",
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object="chat.completion.chunk",
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created=0,
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model="t",
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choices=[
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ChunkChoice(
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index=0,
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delta=DeltaMessage(reasoning_content=part),
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finish_reason=None,
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)
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],
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)
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yield ChatCompletionChunk(
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id="1",
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object="chat.completion.chunk",
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created=0,
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model="t",
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choices=[
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ChunkChoice(
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index=0,
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delta=DeltaMessage(content="ans"),
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finish_reason="stop",
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)
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],
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)
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return chunks()
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messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
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events = [e async for e in run_chat_loop(ReasoningClient(), messages, model="m", stream=True)]
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reasoning = [e for e in events if isinstance(e, ReasoningDeltaEvent)]
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assert [r.content for r in reasoning] == ["th", "ink"]
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deltas = [e for e in events if isinstance(e, TextDeltaEvent)]
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assert [d.content for d in deltas] == ["ans"]
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assert isinstance(messages[-1], AssistantChatMessage)
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assert messages[-1].content == "ans"
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assert messages[-1].reasoning_content == "think"
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async def test_non_stream_yields_reasoning() -> None:
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client = ScriptedClient([_response(AssistantChatMessage(content="ok", reasoning_content="plan"))])
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messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
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events = [e async for e in run_chat_loop(client, messages, model="m", stream=False)]
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reasoning = [e for e in events if isinstance(e, ReasoningDeltaEvent)]
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assert len(reasoning) == 1
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assert reasoning[0].content == "plan"
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assert isinstance(messages[-1], AssistantChatMessage)
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assert messages[-1].reasoning_content == "plan"
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async def test_run_chat_loop_with_tools() -> None:
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@tool
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def add(a: int, b: int) -> int:
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return a + b
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registry = ToolRegistry([add])
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client = ScriptedClient(
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[
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_response(
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AssistantChatMessage(
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content="",
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tool_calls=[
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AssistantFunctionToolCall(
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id="c1",
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function=AssistantFunctionTool(name="add", arguments='{"a": 1, "b": 2}'),
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)
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],
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)
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),
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_response(AssistantChatMessage(content="3")),
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]
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)
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messages: list[AnyChatMessage] = [UserChatMessage(content="1+2")]
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events = [e async for e in run_chat_loop(client, messages, model="m", tools=registry)]
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types = [type(e) for e in events]
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assert ToolCallEvent in types
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assert ToolResultEvent in types
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assert any(isinstance(e, TextDeltaEvent) and e.content == "3" for e in events)
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assert len(client.calls) == 2
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# second call includes tool result message
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assert any(getattr(m, "tool_call_id", None) == "c1" for m in client.calls[1].messages)
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|
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async def test_max_rounds() -> None:
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@tool
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def ping() -> str:
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return "pong"
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registry = ToolRegistry([ping])
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forever = _response(
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AssistantChatMessage(
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content="",
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tool_calls=[
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AssistantFunctionToolCall(
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id="c",
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function=AssistantFunctionTool(name="ping", arguments="{}"),
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)
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],
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)
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)
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client = ScriptedClient([forever, forever, forever])
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messages: list[AnyChatMessage] = [UserChatMessage(content="x")]
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events = [e async for e in run_chat_loop(client, messages, model="m", tools=registry, max_rounds=2)]
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assert any(isinstance(e, MaxRoundsEvent) and e.rounds == 2 and not e.continued for e in events)
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assert len(client.calls) == 2
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|
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async def test_max_rounds_continue_hook() -> None:
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@tool
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def ping() -> str:
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return "pong"
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registry = ToolRegistry([ping])
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forever = _response(
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AssistantChatMessage(
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content="",
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tool_calls=[
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AssistantFunctionToolCall(
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id="c",
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function=AssistantFunctionTool(name="ping", arguments="{}"),
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)
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],
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)
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)
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final = _response(AssistantChatMessage(content="done"))
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client = ScriptedClient([forever, forever, final])
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messages: list[AnyChatMessage] = [UserChatMessage(content="x")]
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asks: list[str] = []
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def on_limit(reason: str) -> bool:
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asks.append(reason)
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return len(asks) == 1
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events = [
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e
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async for e in run_chat_loop(
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client,
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messages,
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model="m",
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tools=registry,
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max_rounds=2,
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on_limit=on_limit,
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)
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]
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assert len(asks) == 1
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assert any(isinstance(e, MaxRoundsEvent) and e.continued for e in events)
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assert any(isinstance(e, TextDeltaEvent) and e.content == "done" for e in events)
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assert len(client.calls) == 3
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|
async def test_max_rounds_async_continue_hook() -> None:
|
|
@tool
|
|
def ping() -> str:
|
|
return "pong"
|
|
|
|
registry = ToolRegistry([ping])
|
|
forever = _response(
|
|
AssistantChatMessage(
|
|
content="",
|
|
tool_calls=[
|
|
AssistantFunctionToolCall(
|
|
id="c",
|
|
function=AssistantFunctionTool(name="ping", arguments="{}"),
|
|
)
|
|
],
|
|
)
|
|
)
|
|
final = _response(AssistantChatMessage(content="done"))
|
|
client = ScriptedClient([forever, forever, final])
|
|
messages: list[AnyChatMessage] = [UserChatMessage(content="x")]
|
|
asks: list[str] = []
|
|
|
|
async def on_limit(reason: str) -> bool:
|
|
asks.append(reason)
|
|
return True
|
|
|
|
events = [
|
|
e
|
|
async for e in run_chat_loop(
|
|
client,
|
|
messages,
|
|
model="m",
|
|
tools=registry,
|
|
max_rounds=2,
|
|
on_limit=on_limit,
|
|
)
|
|
]
|
|
assert len(asks) == 1
|
|
assert any(isinstance(e, MaxRoundsEvent) and e.continued for e in events)
|
|
assert any(isinstance(e, TextDeltaEvent) and e.content == "done" for e in events)
|
|
|
|
|
|
async def test_default_max_rounds_is_generous() -> None:
|
|
from plyngent.agent.loop import DEFAULT_MAX_ROUNDS
|
|
|
|
assert DEFAULT_MAX_ROUNDS >= 16
|
|
|
|
|
|
async def test_chat_agent_memory_roundtrip() -> None:
|
|
store = await MemoryStore.open(DatabaseConfig())
|
|
session = await store.create_session(name="t")
|
|
client = ScriptedClient([_response(AssistantChatMessage(content="yo"))])
|
|
agent = ChatAgent(client, model="m", memory=store, session_id=session.sid)
|
|
events = [e async for e in agent.run("hi")]
|
|
assert any(isinstance(e, TextDeltaEvent) and e.content == "yo" for e in events)
|
|
|
|
loaded = await store.list_messages(session.sid)
|
|
assert len(loaded) == 2
|
|
assert isinstance(loaded[0], UserChatMessage)
|
|
assert loaded[0].content == "hi"
|
|
|
|
agent2 = ChatAgent(client, model="m", memory=store, session_id=session.sid)
|
|
await agent2.load_history()
|
|
assert len(agent2.messages) == 2
|
|
await store.close()
|
|
|
|
|
|
async def test_chat_agent_failed_turn_keeps_user_in_db() -> None:
|
|
store = await MemoryStore.open(DatabaseConfig())
|
|
session = await store.create_session(name="t")
|
|
|
|
class BoomClient:
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[False] = False
|
|
) -> ChatCompletionResponse: ...
|
|
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[True]
|
|
) -> AsyncIterator[ChatCompletionChunk]: ...
|
|
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: bool = False
|
|
) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
|
|
del param, stream
|
|
msg = "network down"
|
|
raise RuntimeError(msg)
|
|
|
|
agent = ChatAgent(BoomClient(), model="m", memory=store, session_id=session.sid)
|
|
with pytest.raises(RuntimeError, match="network down"):
|
|
_ = [e async for e in agent.run("hello")]
|
|
|
|
assert len(agent.messages) == 1
|
|
assert isinstance(agent.messages[0], UserChatMessage)
|
|
assert agent.pending_retry_text == "hello"
|
|
loaded = await store.list_messages(session.sid)
|
|
assert len(loaded) == 1
|
|
assert isinstance(loaded[0], UserChatMessage)
|
|
assert loaded[0].content == "hello"
|
|
await store.close()
|
|
|
|
|
|
async def test_chat_agent_retry_after_failure() -> None:
|
|
store = await MemoryStore.open(DatabaseConfig())
|
|
session = await store.create_session(name="t")
|
|
|
|
class FlakyClient:
|
|
calls: int
|
|
|
|
def __init__(self) -> None:
|
|
self.calls = 0
|
|
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[False] = False
|
|
) -> ChatCompletionResponse: ...
|
|
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[True]
|
|
) -> AsyncIterator[ChatCompletionChunk]: ...
|
|
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: bool = False
|
|
) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
|
|
del param
|
|
self.calls += 1
|
|
if self.calls == 1:
|
|
msg = "temporary"
|
|
raise RuntimeError(msg)
|
|
response = _response(AssistantChatMessage(content="recovered"))
|
|
if stream:
|
|
|
|
async def as_stream() -> AsyncIterator[ChatCompletionChunk]:
|
|
for chunk in _chunks_from_response(response):
|
|
yield chunk
|
|
|
|
return as_stream()
|
|
return response
|
|
|
|
client = FlakyClient()
|
|
agent = ChatAgent(client, model="m", memory=store, session_id=session.sid)
|
|
with pytest.raises(RuntimeError, match="temporary"):
|
|
_ = [e async for e in agent.run("ping")]
|
|
assert agent.pending_retry_text == "ping"
|
|
# User already in DB after first attempt
|
|
assert len(await store.list_messages(session.sid)) == 1
|
|
|
|
events = [e async for e in agent.retry()]
|
|
assert any(isinstance(e, TextDeltaEvent) and e.content == "recovered" for e in events)
|
|
assert agent.pending_retry_text is None
|
|
loaded = await store.list_messages(session.sid)
|
|
assert len(loaded) == 2
|
|
assert isinstance(loaded[0], UserChatMessage)
|
|
assert loaded[0].content == "ping"
|
|
# Single user message (no duplicate on retry)
|
|
assert sum(1 for m in loaded if isinstance(m, UserChatMessage)) == 1
|
|
await store.close()
|
|
|
|
|
|
async def test_retry_after_resume_orphan_user() -> None:
|
|
store = await MemoryStore.open(DatabaseConfig())
|
|
session = await store.create_session(name="t")
|
|
_ = await store.append_message(session.sid, UserChatMessage(content="left hanging"))
|
|
|
|
client = ScriptedClient([_response(AssistantChatMessage(content="ok now"))])
|
|
agent = ChatAgent(client, model="m", memory=store, session_id=session.sid)
|
|
await agent.load_history()
|
|
assert agent.pending_retry_text == "left hanging"
|
|
|
|
events = [e async for e in agent.retry()]
|
|
assert any(isinstance(e, TextDeltaEvent) and e.content == "ok now" for e in events)
|
|
loaded = await store.list_messages(session.sid)
|
|
assert len(loaded) == 2
|
|
assert sum(1 for m in loaded if isinstance(m, UserChatMessage)) == 1
|
|
await store.close()
|
|
|
|
|
|
async def test_retry_keeps_committed_tools_after_second_round_fails() -> None:
|
|
"""Tools that already ran stay in history; retry continues without re-calling them."""
|
|
store = await MemoryStore.open(DatabaseConfig())
|
|
session = await store.create_session(name="t")
|
|
calls: list[str] = []
|
|
|
|
@tool
|
|
def side_effect() -> str:
|
|
calls.append("ran")
|
|
return "done-once"
|
|
|
|
registry = ToolRegistry([side_effect])
|
|
|
|
class ToolThenBoom:
|
|
n: int
|
|
|
|
def __init__(self) -> None:
|
|
self.n = 0
|
|
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[False] = False
|
|
) -> ChatCompletionResponse: ...
|
|
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[True]
|
|
) -> AsyncIterator[ChatCompletionChunk]: ...
|
|
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: bool = False
|
|
) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
|
|
del stream
|
|
self.n += 1
|
|
if self.n == 1:
|
|
return _response(
|
|
AssistantChatMessage(
|
|
content="",
|
|
tool_calls=[
|
|
AssistantFunctionToolCall(
|
|
id="c1",
|
|
function=AssistantFunctionTool(
|
|
name="side_effect",
|
|
arguments="{}",
|
|
),
|
|
)
|
|
],
|
|
)
|
|
)
|
|
if self.n == 2:
|
|
msg = "api down after tools"
|
|
raise RuntimeError(msg)
|
|
# Retry continues: third call is next model round with tools in history.
|
|
assert any(getattr(m, "tool_call_id", None) == "c1" for m in param.messages)
|
|
return _response(AssistantChatMessage(content="finished"))
|
|
|
|
client = ToolThenBoom()
|
|
agent = ChatAgent(
|
|
client,
|
|
model="m",
|
|
tools=registry,
|
|
memory=store,
|
|
session_id=session.sid,
|
|
stream=False,
|
|
)
|
|
with pytest.raises(RuntimeError, match="api down after tools"):
|
|
_ = [e async for e in agent.run("do it")]
|
|
|
|
assert calls == ["ran"]
|
|
assert agent.pending_retry_text == "do it"
|
|
# User + assistant(tool_calls) + tool result kept; incomplete second assistant dropped.
|
|
assert isinstance(agent.messages[-1], ToolChatMessage)
|
|
loaded = await store.list_messages(session.sid)
|
|
assert len(loaded) == 3 # user, assistant, tool — committed before boom
|
|
|
|
events = [e async for e in agent.retry()]
|
|
assert any(isinstance(e, TextDeltaEvent) and e.content == "finished" for e in events)
|
|
assert calls == ["ran"] # tool not re-executed
|
|
assert agent.pending_retry_text is None
|
|
await store.close()
|
|
|
|
|
|
async def test_chat_agent_system_prompt_prepended() -> None:
|
|
from plyngent.lmproto.openai_compatible.model import SystemChatMessage
|
|
|
|
client = ScriptedClient([_response(AssistantChatMessage(content="ok"))])
|
|
agent = ChatAgent(client, model="m", system_prompt="Be brief.", stream=False)
|
|
_ = [e async for e in agent.run("hi")]
|
|
assert isinstance(agent.messages[0], SystemChatMessage)
|
|
assert agent.messages[0].content == "Be brief."
|
|
assert isinstance(client.calls[0].messages[0], SystemChatMessage)
|
|
|
|
|
|
async def test_tool_result_char_budget() -> None:
|
|
@tool
|
|
def big() -> str:
|
|
return "x" * 100
|
|
|
|
registry = ToolRegistry([big])
|
|
client = ScriptedClient(
|
|
[
|
|
_response(
|
|
AssistantChatMessage(
|
|
content="",
|
|
tool_calls=[
|
|
AssistantFunctionToolCall(
|
|
id="1",
|
|
function=AssistantFunctionTool(name="big", arguments="{}"),
|
|
)
|
|
],
|
|
)
|
|
),
|
|
_response(AssistantChatMessage(content="done")),
|
|
]
|
|
)
|
|
messages: list[AnyChatMessage] = [UserChatMessage(content="go")]
|
|
_ = [
|
|
e
|
|
async for e in run_chat_loop(
|
|
client,
|
|
messages,
|
|
model="m",
|
|
tools=registry,
|
|
stream=False,
|
|
max_tool_result_chars=20,
|
|
parallel_tools=False,
|
|
)
|
|
]
|
|
from plyngent.lmproto.openai_compatible.model import ToolChatMessage
|
|
|
|
tool_msgs = [m for m in messages if isinstance(m, ToolChatMessage)]
|
|
assert len(tool_msgs) == 1
|
|
assert tool_msgs[0].content.startswith("x" * 20)
|
|
assert "truncated" in tool_msgs[0].content
|
|
|
|
|
|
async def test_empty_completion_raises() -> None:
|
|
client = ScriptedClient([_response(AssistantChatMessage(content=None))])
|
|
messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
|
|
with pytest.raises(RuntimeError, match="empty model completion"):
|
|
_ = [e async for e in run_chat_loop(client, messages, model="m", stream=False)]
|
|
|
|
|
|
async def test_length_finish_raises() -> None:
|
|
client = ScriptedClient(
|
|
[
|
|
_response(
|
|
AssistantChatMessage(content="partial"),
|
|
finish_reason="length",
|
|
)
|
|
]
|
|
)
|
|
messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
|
|
with pytest.raises(RuntimeError, match="truncated"):
|
|
_ = [e async for e in run_chat_loop(client, messages, model="m", stream=False)]
|
|
|
|
|
|
async def test_content_filter_finish_raises() -> None:
|
|
client = ScriptedClient(
|
|
[
|
|
_response(
|
|
AssistantChatMessage(content=""),
|
|
finish_reason="content_filter",
|
|
)
|
|
]
|
|
)
|
|
messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
|
|
with pytest.raises(RuntimeError, match="content filter"):
|
|
_ = [e async for e in run_chat_loop(client, messages, model="m", stream=False)]
|
|
|
|
|
|
async def test_stream_missing_terminal_empty_raises() -> None:
|
|
class EmptyStreamClient:
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[False] = False
|
|
) -> ChatCompletionResponse: ...
|
|
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[True]
|
|
) -> AsyncIterator[ChatCompletionChunk]: ...
|
|
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: bool = False
|
|
) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
|
|
del param
|
|
if not stream:
|
|
return _response(AssistantChatMessage(content="x"))
|
|
|
|
async def chunks() -> AsyncIterator[ChatCompletionChunk]:
|
|
# Usage-only style chunk with no finish_reason and no content.
|
|
yield ChatCompletionChunk(
|
|
id="1",
|
|
object="chat.completion.chunk",
|
|
created=0,
|
|
model="t",
|
|
choices=[],
|
|
usage={"prompt_tokens": 1, "completion_tokens": 0, "total_tokens": 1},
|
|
)
|
|
|
|
return chunks()
|
|
|
|
messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
|
|
with pytest.raises(RuntimeError, match="stream ended without a terminal"):
|
|
_ = [e async for e in run_chat_loop(EmptyStreamClient(), messages, model="m", stream=True)]
|
|
|
|
|
|
async def test_stream_payload_without_finish_reason_ok() -> None:
|
|
"""Some providers omit finish_reason; non-empty text still counts as terminal."""
|
|
|
|
class PayloadNoFinishClient:
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[False] = False
|
|
) -> ChatCompletionResponse: ...
|
|
|
|
@overload
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: Literal[True]
|
|
) -> AsyncIterator[ChatCompletionChunk]: ...
|
|
|
|
async def chat_completions(
|
|
self, param: ChatCompletionsParam, *, stream: bool = False
|
|
) -> ChatCompletionResponse | AsyncIterator[ChatCompletionChunk]:
|
|
del param
|
|
if not stream:
|
|
return _response(AssistantChatMessage(content="ok"))
|
|
|
|
async def chunks() -> AsyncIterator[ChatCompletionChunk]:
|
|
yield ChatCompletionChunk(
|
|
id="1",
|
|
object="chat.completion.chunk",
|
|
created=0,
|
|
model="t",
|
|
choices=[
|
|
ChunkChoice(
|
|
index=0,
|
|
delta=DeltaMessage(content="ok"),
|
|
finish_reason=None,
|
|
)
|
|
],
|
|
)
|
|
|
|
return chunks()
|
|
|
|
messages: list[AnyChatMessage] = [UserChatMessage(content="hi")]
|
|
events = [e async for e in run_chat_loop(PayloadNoFinishClient(), messages, model="m", stream=True)]
|
|
assert any(isinstance(e, TextDeltaEvent) and e.content == "ok" for e in events)
|