feat: dataset quote role support system; fix: adapt o1 model (#2733)

* feat: dataset quote support system role

* perf: adapt dataset quote role

* fix: adapt o1 model

packages/service/core/ai/functions/createQuestionGuide.ts

@@ -2,6 +2,7 @@ import type { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type.d'
 import { getAIApi } from '../config';
 import { countGptMessagesTokens } from '../../../common/string/tiktoken/index';
 import { loadRequestMessages } from '../../chat/utils';
+import { llmCompletionsBodyFormat } from '../utils';
 
 export const Prompt_QuestionGuide = `你是一个AI智能助手，可以回答和解决我的问题。请结合前面的对话记录，帮我生成 3 个问题，引导我继续提问，生成问题的语言要与原问题相同。问题的长度应小于20个字符，按 JSON 格式返回: ["问题1", "问题2", "问题3"]`;
 
@@ -23,16 +24,21 @@ export async function createQuestionGuide({
   const ai = getAIApi({
     timeout: 480000
   });
-  const data = await ai.chat.completions.create({
-    model: model,
-    temperature: 0.1,
-    max_tokens: 200,
-    messages: await loadRequestMessages({
-      messages: concatMessages,
-      useVision: false
-    }),
-    stream: false
-  });
+  const data = await ai.chat.completions.create(
+    llmCompletionsBodyFormat(
+      {
+        model,
+        temperature: 0.1,
+        max_tokens: 200,
+        messages: await loadRequestMessages({
+          messages: concatMessages,
+          useVision: false
+        }),
+        stream: false
+      },
+      model
+    )
+  );
 
   const answer = data.choices?.[0]?.message?.content || '';
 

packages/service/core/ai/functions/queryExtension.ts

@@ -2,9 +2,10 @@ import { replaceVariable } from '@fastgpt/global/common/string/tools';
 import { getAIApi } from '../config';
 import { ChatItemType } from '@fastgpt/global/core/chat/type';
 import { countGptMessagesTokens } from '../../../common/string/tiktoken/index';
-import { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type';
+import { ChatCompletion, ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type';
 import { chatValue2RuntimePrompt } from '@fastgpt/global/core/chat/adapt';
 import { getLLMModel } from '../model';
+import { llmCompletionsBodyFormat } from '../utils';
 
 /* 
     query extension - 问题扩展
@@ -150,14 +151,19 @@ A: ${chatBg}
       })
     }
   ] as ChatCompletionMessageParam[];
-  const result = await ai.chat.completions.create({
-    model: modelData.model,
-    temperature: 0.01,
-    // @ts-ignore
-    messages,
-    stream: false,
-    ...modelData.defaultConfig
-  });
+
+  const result = (await ai.chat.completions.create(
+    llmCompletionsBodyFormat(
+      {
+        stream: false,
+        model: modelData.model,
+        temperature: 0.01,
+        // @ts-ignore
+        messages
+      },
+      modelData
+    )
+  )) as ChatCompletion;
 
   let answer = result.choices?.[0]?.message?.content || '';
   if (!answer) {

packages/service/core/ai/utils.ts

@@ -1,6 +1,11 @@
 import { LLMModelItemType } from '@fastgpt/global/core/ai/model.d';
-import { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type';
+import {
+  ChatCompletionCreateParamsNonStreaming,
+  ChatCompletionCreateParamsStreaming,
+  ChatCompletionMessageParam
+} from '@fastgpt/global/core/ai/type';
 import { countGptMessagesTokens } from '../../common/string/tiktoken';
+import { getLLMModel } from './model';
 
 export const computedMaxToken = async ({
   maxToken,
@@ -32,8 +37,49 @@ export const computedTemperature = ({
   model: LLMModelItemType;
   temperature: number;
 }) => {
+  if (temperature < 1) return temperature;
+
   temperature = +(model.maxTemperature * (temperature / 10)).toFixed(2);
   temperature = Math.max(temperature, 0.01);
 
   return temperature;
 };
+
+type CompletionsBodyType =
+  | ChatCompletionCreateParamsNonStreaming
+  | ChatCompletionCreateParamsStreaming;
+
+export const llmCompletionsBodyFormat = <T extends CompletionsBodyType>(
+  body: T,
+  model: string | LLMModelItemType
+) => {
+  const modelData = typeof model === 'string' ? getLLMModel(model) : model;
+  if (!modelData) {
+    return body;
+  }
+
+  const requestBody: T = {
+    ...body,
+    temperature: body.temperature
+      ? computedTemperature({
+          model: modelData,
+          temperature: body.temperature
+        })
+      : undefined,
+    ...modelData?.defaultConfig
+  };
+
+  // field map
+  if (modelData.fieldMap) {
+    Object.entries(modelData.fieldMap).forEach(([sourceKey, targetKey]) => {
+      // @ts-ignore
+      requestBody[targetKey] = body[sourceKey];
+      // @ts-ignore
+      delete requestBody[sourceKey];
+    });
+  }
+
+  // console.log(requestBody);
+
+  return requestBody;
+};