Files
FastGPT/packages/service/core/ai/utils.ts
Archer 830eb19055 feature: V4.12.2 (#5525)
* feat: favorite apps & quick apps with their own configuration (#5515)

* chore: extract chat history and drawer; fix model selector

* feat: display favourite apps and make it configurable

* feat: favorite apps & quick apps with their own configuration

* fix: fix tab title and add loading state for searching

* fix: cascade delete favorite app and quick app while deleting relative app

* chore: make improvements

* fix: favourite apps ui

* fix: add permission for quick apps

* chore: fix permission & clear redundant code

* perf: chat home page code

* chatbox ui

* fix: 4.12.2-dev (#5520)

* fix: add empty placeholder; fix app quick status; fix tag and layout

* chore: add tab query for the setting tabs

* chore: use `useConfirm` hook instead of `MyModal`

* remove log

* fix: fix modal padding (#5521)

* perf: manage app

* feat: enhance model provider handling and update icon references (#5493)

* perf: model provider

* sdk package

* refactor: create llm response (#5499)

* feat: add LLM response processing functions, including the creation of stream-based and complete responses

* feat: add volta configuration for node and pnpm versions

* refactor: update LLM response handling and event structure in tool choice logic

* feat: update LLM response structure and integrate with tool choice logic

* refactor: clean up imports and remove unused streamResponse function in chat and toolChoice modules

* refactor: rename answer variable to answerBuffer for clarity in LLM response handling

* feat: enhance LLM response handling with tool options and integrate tools into chat and tool choice logic

* refactor: remove volta configuration from package.json

* refactor: reorganize LLM response types and ensure default values for token counts

* refactor: streamline LLM response handling by consolidating response structure and removing redundant checks

* refactor: enhance LLM response handling by consolidating tool options and streamlining event callbacks

* fix: build error

* refactor: update tool type definitions for consistency in tool handling

* feat: llm request function

* fix: ts

* fix: ts

* fix: ahook ts

* fix: variable name

* update lock

* ts version

* doc

* remove log

* fix: translation type

* perf: workflow status check

* fix: ts

* fix: prompt tool call

* fix: fix missing plugin interact window & make tag draggable (#5527)

* fix: incorrect select quick apps state; filter apps type (#5528)

* fix: usesafe translation

* perf: add quickapp modal

---------

Co-authored-by: 伍闲犬 <whoeverimf5@gmail.com>
Co-authored-by: Ctrlz <143257420+ctrlz526@users.noreply.github.com>
Co-authored-by: francis <zhichengfan18@gmail.com>
2025-08-25 19:19:43 +08:00

319 lines
9.9 KiB
TypeScript
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import { type LLMModelItemType } from '@fastgpt/global/core/ai/model.d';
import type { CompletionFinishReason, CompletionUsage } from '@fastgpt/global/core/ai/type';
import { getLLMDefaultUsage } from '@fastgpt/global/core/ai/constants';
import { removeDatasetCiteText } from '@fastgpt/global/core/ai/llm/utils';
/*
Count response max token
*/
export const computedMaxToken = ({
maxToken,
model,
min
}: {
maxToken?: number;
model: LLMModelItemType;
min?: number;
}) => {
if (maxToken === undefined) return;
maxToken = Math.min(maxToken, model.maxResponse);
return Math.max(maxToken, min || 0);
};
// FastGPT temperature range: [0,10], ai temperature:[0,2],{0,1]……
export const computedTemperature = ({
model,
temperature
}: {
model: LLMModelItemType;
temperature: number;
}) => {
if (typeof model.maxTemperature !== 'number') return undefined;
temperature = +(model.maxTemperature * (temperature / 10)).toFixed(2);
temperature = Math.max(temperature, 0.01);
return temperature;
};
// LLM utils
// Parse <think></think> tags to think and answer - unstream response
export const parseReasoningContent = (text: string): [string, string] => {
const regex = /<think>([\s\S]*?)<\/think>/;
const match = text.match(regex);
if (!match) {
return ['', text];
}
const thinkContent = match[1].trim();
// Add answer (remaining text after think tag)
const answerContent = text.slice(match.index! + match[0].length);
return [thinkContent, answerContent];
};
// Parse llm stream part
export const parseLLMStreamResponse = () => {
let isInThinkTag: boolean | undefined = undefined;
let startTagBuffer = '';
let endTagBuffer = '';
const thinkStartChars = '<think>';
const thinkEndChars = '</think>';
let citeBuffer = '';
const maxCiteBufferLength = 32; // [Object](CITE)总长度为32
// Buffer
let buffer_finishReason: CompletionFinishReason = null;
let buffer_usage: CompletionUsage = getLLMDefaultUsage();
let buffer_reasoningContent = '';
let buffer_content = '';
/*
parseThinkTag - 只控制是否主动解析 <think></think>,如果接口已经解析了,则不再解析。
retainDatasetCite -
*/
const parsePart = ({
part,
parseThinkTag = true,
retainDatasetCite = true
}: {
part: {
choices: {
delta: {
content?: string | null;
reasoning_content?: string;
};
finish_reason?: CompletionFinishReason;
}[];
usage?: CompletionUsage;
};
parseThinkTag?: boolean;
retainDatasetCite?: boolean;
}): {
reasoningContent: string;
content: string; // 原始内容,不去掉 cite
responseContent: string; // 响应的内容,会去掉 cite
finishReason: CompletionFinishReason;
} => {
const data = (() => {
buffer_usage = part.usage || buffer_usage;
const finishReason = part.choices?.[0]?.finish_reason || null;
buffer_finishReason = finishReason || buffer_finishReason;
const content = part.choices?.[0]?.delta?.content || '';
// @ts-ignore
const reasoningContent = part.choices?.[0]?.delta?.reasoning_content || '';
const isStreamEnd = !!buffer_finishReason;
// Parse think
const { reasoningContent: parsedThinkReasoningContent, content: parsedThinkContent } =
(() => {
if (reasoningContent || !parseThinkTag) {
isInThinkTag = false;
return { reasoningContent, content };
}
// 如果不在 think 标签中,或者有 reasoningContent(接口已解析),则返回 reasoningContent 和 content
if (isInThinkTag === false) {
return {
reasoningContent: '',
content
};
}
// 检测是否为 think 标签开头的数据
if (isInThinkTag === undefined) {
// Parse content think and answer
startTagBuffer += content;
// 太少内容时候,暂时不解析
if (startTagBuffer.length < thinkStartChars.length) {
if (isStreamEnd) {
const tmpContent = startTagBuffer;
startTagBuffer = '';
return {
reasoningContent: '',
content: tmpContent
};
}
return {
reasoningContent: '',
content: ''
};
}
if (startTagBuffer.startsWith(thinkStartChars)) {
isInThinkTag = true;
return {
reasoningContent: startTagBuffer.slice(thinkStartChars.length),
content: ''
};
}
// 如果未命中 think 标签,则认为不在 think 标签中,返回 buffer 内容作为 content
isInThinkTag = false;
return {
reasoningContent: '',
content: startTagBuffer
};
}
// 确认是 think 标签内容,开始返回 think 内容,并实时检测 </think>
/*
检测 </think> 方案。
存储所有疑似 </think> 的内容,直到检测到完整的 </think> 标签或超出 </think> 长度。
content 返回值包含以下几种情况:
abc - 完全未命中尾标签
abc<th - 命中一部分尾标签
abc</think> - 完全命中尾标签
abc</think>abc - 完全命中尾标签
</think>abc - 完全命中尾标签
k>abc - 命中一部分尾标签
*/
// endTagBuffer 专门用来记录疑似尾标签的内容
if (endTagBuffer) {
endTagBuffer += content;
if (endTagBuffer.includes(thinkEndChars)) {
isInThinkTag = false;
const answer = endTagBuffer.slice(thinkEndChars.length);
return {
reasoningContent: '',
content: answer
};
} else if (endTagBuffer.length >= thinkEndChars.length) {
// 缓存内容超出尾标签长度,且仍未命中 </think>,则认为本次猜测 </think> 失败,仍处于 think 阶段。
const tmp = endTagBuffer;
endTagBuffer = '';
return {
reasoningContent: tmp,
content: ''
};
}
return {
reasoningContent: '',
content: ''
};
} else if (content.includes(thinkEndChars)) {
// 返回内容,完整命中</think>,直接结束
isInThinkTag = false;
const [think, answer] = content.split(thinkEndChars);
return {
reasoningContent: think,
content: answer
};
} else {
// 无 buffer且未命中 </think>,开始疑似 </think> 检测。
for (let i = 1; i < thinkEndChars.length; i++) {
const partialEndTag = thinkEndChars.slice(0, i);
// 命中一部分尾标签
if (content.endsWith(partialEndTag)) {
const think = content.slice(0, -partialEndTag.length);
endTagBuffer += partialEndTag;
return {
reasoningContent: think,
content: ''
};
}
}
}
// 完全未命中尾标签,还是 think 阶段。
return {
reasoningContent: content,
content: ''
};
})();
// Parse datset cite
if (retainDatasetCite) {
return {
reasoningContent: parsedThinkReasoningContent,
content: parsedThinkContent,
responseContent: parsedThinkContent,
finishReason: buffer_finishReason
};
}
// 缓存包含 [ 的字符串,直到超出 maxCiteBufferLength 再一次性返回
const parseCite = (text: string) => {
// 结束时,返回所有剩余内容
if (isStreamEnd) {
const content = citeBuffer + text;
return {
content: removeDatasetCiteText(content, false)
};
}
// 新内容包含 [,初始化缓冲数据
if (text.includes('[') || text.includes('【')) {
const index = text.indexOf('[') !== -1 ? text.indexOf('[') : text.indexOf('【');
const beforeContent = citeBuffer + text.slice(0, index);
citeBuffer = text.slice(index);
// beforeContent 可能是:普通字符串,带 [ 的字符串
return {
content: removeDatasetCiteText(beforeContent, false)
};
}
// 处于 Cite 缓冲区,判断是否满足条件
else if (citeBuffer) {
citeBuffer += text;
// 检查缓冲区长度是否达到完整Quote长度或已经流结束
if (citeBuffer.length >= maxCiteBufferLength) {
const content = removeDatasetCiteText(citeBuffer, false);
citeBuffer = '';
return {
content
};
} else {
// 暂时不返回内容
return { content: '' };
}
}
return {
content: text
};
};
const { content: pasedCiteContent } = parseCite(parsedThinkContent);
return {
reasoningContent: parsedThinkReasoningContent,
content: parsedThinkContent,
responseContent: pasedCiteContent,
finishReason: buffer_finishReason
};
})();
buffer_reasoningContent += data.reasoningContent;
buffer_content += data.content;
return data;
};
const getResponseData = () => {
return {
finish_reason: buffer_finishReason,
usage: buffer_usage,
reasoningContent: buffer_reasoningContent,
content: buffer_content
};
};
const updateFinishReason = (finishReason: CompletionFinishReason) => {
buffer_finishReason = finishReason;
};
return {
parsePart,
getResponseData,
updateFinishReason
};
};