Files
FastGPT/projects/app/src/service/moduleDispatch/tools/cfr.ts
Archer 51bbdf26a3 4.6.8-production (#822)
* Json completion (#16)

* json-completion

* fix duplicate

* fix

* fix: config json

* feat: query extension

* perf: i18n

* 468 doc

* json editor

* perf: doc

* perf: default extension model

* docker file

* doc

* perf: token count

* perf: search extension

* format

* perf: some constants data

---------

Co-authored-by: heheer <71265218+newfish-cmyk@users.noreply.github.com>
2024-02-05 00:51:46 +08:00

65 lines
1.9 KiB
TypeScript

import type { ChatItemType, moduleDispatchResType } from '@fastgpt/global/core/chat/type.d';
import type { ModuleDispatchProps } from '@fastgpt/global/core/module/type.d';
import { ModuleInputKeyEnum, ModuleOutputKeyEnum } from '@fastgpt/global/core/module/constants';
import { ModelTypeEnum, getLLMModel } from '@/service/core/ai/model';
import { formatModelPrice2Store } from '@/service/support/wallet/bill/utils';
import { queryCfr } from '@fastgpt/service/core/ai/functions/cfr';
import { getHistories } from '../utils';
type Props = ModuleDispatchProps<{
[ModuleInputKeyEnum.aiModel]: string;
[ModuleInputKeyEnum.aiSystemPrompt]?: string;
[ModuleInputKeyEnum.history]?: ChatItemType[] | number;
[ModuleInputKeyEnum.userChatInput]: string;
}>;
type Response = {
[ModuleOutputKeyEnum.text]: string;
[ModuleOutputKeyEnum.responseData]?: moduleDispatchResType;
};
export const dispatchCFR = async ({
histories,
params: { model, systemPrompt, history, userChatInput }
}: Props): Promise<Response> => {
if (!userChatInput) {
return Promise.reject('Question is empty');
}
// none
// first chat and no system prompt
if (systemPrompt === 'none' || (histories.length === 0 && !systemPrompt)) {
return {
[ModuleOutputKeyEnum.text]: userChatInput
};
}
const cfrModel = getLLMModel(model);
const chatHistories = getHistories(history, histories);
const { cfrQuery, inputTokens, outputTokens } = await queryCfr({
chatBg: systemPrompt,
query: userChatInput,
histories: chatHistories,
model: cfrModel.model
});
const { total, modelName } = formatModelPrice2Store({
model: cfrModel.model,
inputLen: inputTokens,
outputLen: outputTokens,
type: ModelTypeEnum.llm
});
return {
[ModuleOutputKeyEnum.responseData]: {
price: total,
model: modelName,
inputTokens,
outputTokens,
query: userChatInput,
textOutput: cfrQuery
},
[ModuleOutputKeyEnum.text]: cfrQuery
};
};