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feat(chat): add configurable streaming output

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This commit is contained in:
Nelson
2026-07-17 13:34:27 +08:00
parent f7076569a7
commit 13fed0467a
11 changed files with 172 additions and 24 deletions
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18
ai_knowledge_base_v2/apps/admin-web/src/components/AgentManagementView.vue
View File

@@ -50,6 +50,7 @@ const runtimeForm = reactive({
presencePenalty: null as number | null,
frequencyPenalty: null as number | null,
maxToken: 8192 as number | null,
streamEnabled: 1,
});
const promptDirty = computed(() => promptContent.value !== savedPromptContent.value);
@@ -104,6 +105,7 @@ function applyRuntimeConfig(value: AgentRuntimeConfig) {
presencePenalty: value.presencePenalty,
frequencyPenalty: value.frequencyPenalty,
maxToken: value.maxToken,
streamEnabled: value.streamEnabled,
});
}
@@ -132,6 +134,7 @@ async function saveRuntimeConfig() {
presencePenalty: runtimeForm.presencePenalty,
frequencyPenalty: runtimeForm.frequencyPenalty,
maxToken: runtimeForm.maxToken,
streamEnabled: runtimeForm.streamEnabled,
});
applyRuntimeConfig(saved);
const model = models.value.find((item) => item.id === saved.modelId);
@@ -368,6 +371,21 @@ function errorMessage(error: unknown, fallback: string) {
v-model:max-token="runtimeForm.maxToken"
:disabled="!runtimeConfig?.modelId"
/>
<el-form-item class="agent-stream-setting">
<div class="agent-stream-setting-copy">
<strong>用户端流式输出</strong>
<span>开启后回答正文会边生成边展示；关闭后等待模型完成，再一次性显示完整回答。</span>
</div>
<el-switch
v-model="runtimeForm.streamEnabled"
:active-value="1"
:inactive-value="0"
active-text="开启"
inactive-text="关闭"
inline-prompt
:disabled="!runtimeConfig?.modelId"
/>
</el-form-item>
</section>
</el-form>
</el-tab-pane>

40
ai_knowledge_base_v2/apps/admin-web/src/styles.css
View File

@@ -1017,6 +1017,46 @@ textarea {
font-size: 12px;
}
.agent-stream-setting {
margin: 16px 0 0;
padding: 14px 16px;
border: 1px solid #dce7e3;
border-radius: 8px;
background: #ffffff;
}
.agent-stream-setting > .el-form-item__content {
display: flex;
align-items: center;
justify-content: space-between;
gap: 20px;
}
.agent-stream-setting-copy {
display: grid;
gap: 4px;
min-width: 0;
}
.agent-stream-setting-copy strong {
color: #263832;
font-size: 14px;
}
.agent-stream-setting-copy span {
color: #667a73;
font-size: 12px;
line-height: 1.6;
}
@media (max-width: 680px) {
.agent-stream-setting > .el-form-item__content {
align-items: flex-start;
flex-direction: column;
gap: 12px;
}
}
.agent-parameter-label {
display: inline-flex;
align-items: center;

1
ai_knowledge_base_v2/apps/admin-web/src/types/api.ts
View File

@@ -137,6 +137,7 @@ export interface AgentGenerationConfig {
presencePenalty: number | null;
frequencyPenalty: number | null;
maxToken: number;
streamEnabled: number;
}
export interface AgentRuntimeConfig extends AgentGenerationConfig {

2
ai_knowledge_base_v2/apps/backend/app/api/admin_settings.py
View File

@@ -212,6 +212,7 @@ def save_agent_runtime_config(
model.presence_penalty = payload.presencePenalty
model.frequency_penalty = payload.frequencyPenalty
model.max_token = payload.maxToken
model.stream_enabled = payload.streamEnabled
db.add(model)
OperationLogService.write(
db,
@@ -436,6 +437,7 @@ def _agent_runtime_config_dict(model: ModelConfig | None) -> dict:
"presencePenalty": float(model.presence_penalty) if model is not None and model.presence_penalty is not None else None,
"frequencyPenalty": float(model.frequency_penalty) if model is not None and model.frequency_penalty is not None else None,
"maxToken": model.max_token if model is not None and model.max_token is not None else 8192,
"streamEnabled": model.stream_enabled if model is not None else 1,
}

10
ai_knowledge_base_v2/apps/backend/app/api/chat.py
View File

@@ -83,7 +83,15 @@ def completions(
db: Session = Depends(get_db),
current_user: User = Depends(get_current_user),
) -> StreamingResponse:
return StreamingResponse(_chat_stream(payload, db, current_user), media_type="text/event-stream")
return StreamingResponse(
_chat_stream(payload, db, current_user),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache, no-transform",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
@router.post("/stop")

1
ai_knowledge_base_v2/apps/backend/app/schemas/admin.py
View File

@@ -98,6 +98,7 @@ class AgentRuntimeConfigSaveRequest(BaseModel):
presencePenalty: float | None = Field(default=None, ge=-2, le=2)
frequencyPenalty: float | None = Field(default=None, ge=-2, le=2)
maxToken: int = Field(default=8192, ge=256, le=100000)
streamEnabled: int = Field(default=1, ge=0, le=1)
class ModelSaveRequest(BaseModel):

31
ai_knowledge_base_v2/apps/backend/app/services/model_stream_service.py
View File

@@ -60,7 +60,7 @@ class ModelStreamService:
model_id=model.id if model is not None else None,
model_name=model_name,
input_token=_rough_token_count(rag_result.prompt),
chunks=_chunk_text(_mock_answer(rag_result)),
chunks=_display_chunks(model, _mock_answer(rag_result)),
)
if not rag_result.is_hit and not rag_result.allow_general_knowledge:
@@ -68,7 +68,7 @@ class ModelStreamService:
model_id=model.id if model is not None else None,
model_name=model.model_name if model is not None else "no-hit",
input_token=_rough_token_count(rag_result.prompt),
chunks=_chunk_text(NO_HIT_ANSWER),
chunks=_display_chunks(model, NO_HIT_ANSWER),
)
if model is None:
@@ -94,7 +94,7 @@ class ModelStreamService:
model_id=model.id if model is not None else None,
model_name=model_name,
input_token=_rough_token_count(rag_result.prompt),
chunks=_async_chunk_text(_mock_answer(rag_result)),
chunks=_async_display_chunks(model, _mock_answer(rag_result)),
)
if not rag_result.is_hit and not rag_result.allow_general_knowledge:
@@ -102,7 +102,7 @@ class ModelStreamService:
model_id=model.id if model is not None else None,
model_name=model.model_name if model is not None else "no-hit",
input_token=_rough_token_count(rag_result.prompt),
chunks=_async_chunk_text(NO_HIT_ANSWER),
chunks=_async_display_chunks(model, NO_HIT_ANSWER),
)
if model is None:
@@ -130,12 +130,12 @@ def _get_enabled_model(db: Session) -> ModelConfig | None:
def _stream_configured_model(model: ModelConfig, rag_result: RagResult) -> Iterator[str]:
api_type = model.api_type or "openai_compatible"
if model.stream_enabled != 1:
return _chunk_text(_call_configured_model(model, rag_result, allow_no_hit=rag_result.allow_general_knowledge))
return iter((_call_configured_model(model, rag_result, allow_no_hit=rag_result.allow_general_knowledge),))
if api_type == "anthropic_messages":
return _stream_anthropic_messages(model, rag_result)
if api_type == "openai_compatible":
return _stream_openai_compatible_model(model, rag_result)
return _chunk_text(_call_configured_model(model, rag_result, allow_no_hit=rag_result.allow_general_knowledge))
return iter((_call_configured_model(model, rag_result, allow_no_hit=rag_result.allow_general_knowledge),))
async def _stream_configured_model_async(model: ModelConfig, rag_result: RagResult) -> AsyncIterator[str]:
@@ -144,8 +144,7 @@ async def _stream_configured_model_async(model: ModelConfig, rag_result: RagResu
answer = await asyncio.to_thread(
_call_configured_model, model, rag_result, allow_no_hit=rag_result.allow_general_knowledge
)
async for chunk in _async_chunk_text(answer):
yield chunk
yield answer
return
if api_type == "anthropic_messages":
@@ -161,8 +160,7 @@ async def _stream_configured_model_async(model: ModelConfig, rag_result: RagResu
answer = await asyncio.to_thread(
_call_configured_model, model, rag_result, allow_no_hit=rag_result.allow_general_knowledge
)
async for chunk in _async_chunk_text(answer):
yield chunk
yield answer
def _stream_openai_compatible_model(model: ModelConfig, rag_result: RagResult) -> Iterator[str]:
@@ -479,6 +477,19 @@ def _chunk_text(text: str, *, chunk_size: int = 12) -> Iterator[str]:
async def _async_chunk_text(text: str, *, chunk_size: int = 12) -> AsyncIterator[str]:
for index in range(0, len(text), chunk_size):
yield text[index : index + chunk_size]
await asyncio.sleep(0)
def _display_chunks(model: ModelConfig | None, text: str) -> Iterator[str]:
return _chunk_text(text) if model is None or model.stream_enabled == 1 else iter((text,))
async def _async_display_chunks(model: ModelConfig | None, text: str) -> AsyncIterator[str]:
if model is not None and model.stream_enabled != 1:
yield text
return
async for chunk in _async_chunk_text(text):
yield chunk
def _string_or_empty(value: Any) -> str:

29
ai_knowledge_base_v2/apps/backend/tests/test_agent_runtime_config.py
View File

@@ -1,4 +1,6 @@
import asyncio
from decimal import Decimal
from unittest.mock import patch
from sqlalchemy import create_engine
from sqlalchemy.orm import Session
@@ -9,7 +11,7 @@ from app.models import Base
from app.models.admin import Admin
from app.models.ai_config import ModelConfig
from app.schemas.admin import AgentRuntimeConfigSaveRequest
from app.services.model_stream_service import _openai_stream_payload
from app.services.model_stream_service import _openai_stream_payload, _stream_configured_model_async
from app.services.model_service import ModelClientService, _max_output_tokens
from app.services.rag_service import RagResult
@@ -58,6 +60,7 @@ def test_runtime_config_defaults_to_long_answer_safe_max_tokens():
assert result["modelId"] == model.id
assert result["modelName"] == "正式模型"
assert result["maxToken"] == 8192
assert result["streamEnabled"] == 1
assert _max_output_tokens(model) == 8192
@@ -76,6 +79,7 @@ def test_saved_runtime_config_is_persisted_on_enabled_model():
presencePenalty=0.2,
frequencyPenalty=0.4,
maxToken=12000,
streamEnabled=0,
),
db=db,
current_admin=admin,
@@ -89,6 +93,8 @@ def test_saved_runtime_config_is_persisted_on_enabled_model():
assert model.top_k == 40
assert model.presence_penalty == Decimal("0.20")
assert model.frequency_penalty == Decimal("0.40")
assert model.stream_enabled == 0
assert result["streamEnabled"] == 0
payload = _openai_stream_payload(
model,
@@ -101,6 +107,27 @@ def test_saved_runtime_config_is_persisted_on_enabled_model():
assert payload["frequency_penalty"] == 0.4
def test_disabled_stream_returns_one_complete_chunk():
model = _model()
model.stream_enabled = 0
answer = "完整回答" * 20
rag_result = RagResult(
question="测试",
knowledge_scopes=[],
chunks=[],
prompt="测试",
allow_general_knowledge=True,
)
async def collect():
return [item async for item in _stream_configured_model_async(model, rag_result)]
with patch("app.services.model_stream_service._call_configured_model", return_value=answer):
chunks = asyncio.run(collect())
assert chunks == [answer]
def test_agent_debug_does_not_truncate_long_answer(monkeypatch):
monkeypatch.setattr(
"app.services.model_service._call_configured_model",

9
ai_knowledge_base_v2/apps/backend/tests/test_production_readiness.py
View File

@@ -113,6 +113,15 @@ def test_queued_chat_reports_position_and_completes(monkeypatch):
assert released is True
def test_chat_streaming_response_disables_proxy_buffering():
payload = type("Payload", (), {"sessionId": 1, "message": "问题"})()
response = chat.completions(payload, object(), object())
assert response.headers["cache-control"] == "no-cache, no-transform"
assert response.headers["x-accel-buffering"] == "no"
assert response.media_type == "text/event-stream"
def test_sensitive_system_config_never_returns_plaintext():
from app.api.admin_settings import _config_dict

47
ai_knowledge_base_v2/apps/user-client/src/components/ChatMessage.vue
View File

@@ -15,16 +15,47 @@ const markdown = new MarkdownIt({ breaks: true, html: false, linkify: true });
const answer = computed(() => {
if (props.role === "user") return props.content;
// 部分模型会产生嵌套 think 标签，使用贪婪匹配移除完整思考区，再清理流式残留标签。
let content = props.content.replace(/<think>[\s\S]*<\/think>/gi, "");
content = content.replace(/<think>[\s\S]*$/i, "");
content = content.replace(/<\/?think>/gi, "");
return content.trim();
return stripStreamingReasoning(props.content).replace(/^\s+/, "");
});
const renderedContent = computed(() =>
props.role === "assistant" ? markdown.render(answer.value) : answer.value,
);
const hasAnswer = computed(() => answer.value.trim().length > 0);
const renderedContent = computed(() => {
if (props.role !== "assistant") return answer.value;
return hasAnswer.value ? markdown.render(answer.value) : "";
});
function stripStreamingReasoning(content: string) {
const lower = content.toLowerCase();
let visible = "";
let cursor = 0;
let reasoningDepth = 0;
while (cursor < content.length) {
const tagStart = content.indexOf("<", cursor);
if (tagStart === -1) {
if (reasoningDepth === 0) visible += content.slice(cursor);
break;
}
if (reasoningDepth === 0) visible += content.slice(cursor, tagStart);
const tail = lower.slice(tagStart);
const openTag = tail.match(/^<think(?:\s[^>]*)?>/);
if (openTag) {
reasoningDepth += 1;
cursor = tagStart + openTag[0].length;
continue;
}
const closeTag = tail.match(/^<\/think\s*>/);
if (closeTag) {
reasoningDepth = Math.max(0, reasoningDepth - 1);
cursor = tagStart + closeTag[0].length;
continue;
}
if ("<think".startsWith(tail) || "</think>".startsWith(tail)) break;
if (reasoningDepth === 0) visible += "<";
cursor = tagStart + 1;
}
return visible;
}
const displayTime = computed(() => {
// 消息服务返回的是 UTC 无时区字符串，补齐时区后再按用户本地时间展示。

8
ai_knowledge_base_v2/apps/user-client/src/services/api.ts
View File

@@ -107,12 +107,12 @@ export async function streamChat(
const { done, value } = await reader.read();
if (done) break;
buffer += decoder.decode(value, { stream: true });
const parts = buffer.split("\n\n");
const parts = buffer.split(/\r?\n\r?\n/);
buffer = parts.pop() ?? "";
for (const part of parts) {
const line = part.trim();
if (!line.startsWith("data:")) continue;
const payload = line.slice(5).trim();
const dataLines = part.split(/\r?\n/).filter((line) => line.startsWith("data:"));
if (!dataLines.length) continue;
const payload = dataLines.map((line) => line.slice(5).trimStart()).join("\n").trim();
if (payload === "[DONE]") return;
const parsed = JSON.parse(payload) as { type?: string; content?: string; message?: string };
if (parsed.type === "queued" || parsed.type === "generating") {