v 2.5.0

dist/modules/chatgpt/chatgpt.service.js

@@ -35,10 +35,8 @@ const fanyi_service_1 = require("../fanyi/fanyi.service");
 const app_entity_1 = require("../app/app.entity");
 const chatGroup_service_1 = require("../chatGroup/chatGroup.service");
 const models_service_1 = require("../models/models.service");
-const baidu_1 = require("./baidu");
 const helper_1 = require("./helper");
 const store_1 = require("./store");
-const zhipu_1 = require("./zhipu");
 const openai_1 = require("./openai");
 const chatBoxType_entity_1 = require("./chatBoxType.entity");
 const chatBox_entity_1 = require("./chatBox.entity");
@@ -134,7 +132,7 @@ let ChatgptService = class ChatgptService {
         const { options = {}, appId, cusromPrompt, systemMessage = '' } = body;
         let setSystemMessage = systemMessage;
         const { parentMessageId } = options;
-        const { prompt } = body;
+        const { prompt, fileInfo } = body;
         const { groupId, usingNetwork } = options;
         const groupInfo = await this.chatGroupService.getGroupInfoFromId(groupId);
         const groupConfig = (groupInfo === null || groupInfo === void 0 ? void 0 : groupInfo.config) ? JSON.parse(groupInfo.config) : await this.modelsService.getBaseConfig();
@@ -149,7 +147,7 @@ let ChatgptService = class ChatgptService {
         if (!currentRequestModelKey) {
             throw new common_1.HttpException('当前流程所需要的模型已被管理员下架、请联系管理员上架专属模型！', common_1.HttpStatus.BAD_REQUEST);
         }
-        const { deduct, isTokenBased, deductType, key: modelKey, secret, modelName, id: keyId, accessToken } = currentRequestModelKey;
+        const { deduct, isTokenBased, tokenFeeRatio, deductType, key: modelKey, secret, modelName, id: keyId, accessToken } = currentRequestModelKey;
         await this.userService.checkUserStatus(req.user);
         await this.userBalanceService.validateBalance(req, deductType === 1 ? 'model3' : 'model4', deduct);
         res && res.setHeader('Content-type', 'application/octet-stream; charset=utf-8');
@@ -208,6 +206,7 @@ let ChatgptService = class ChatgptService {
                         userId: req.user.id,
                         type: balance_constant_1.DeductionKey.CHAT_TYPE,
                         prompt,
+                        fileInfo: fileInfo,
                         answer: '',
                         promptTokens: prompt_tokens,
                         completionTokens: 0,
@@ -249,79 +248,45 @@ let ChatgptService = class ChatgptService {
                     });
                     let charge = deduct;
                     if (isTokenBased === true) {
-                        charge = deduct * total_tokens;
+                        charge = Math.ceil((deduct * total_tokens) / tokenFeeRatio);
                     }
                     await this.userBalanceService.deductFromBalance(req.user.id, `model${deductType === 1 ? 3 : 4}`, charge, total_tokens);
                 });
-                if (Number(keyType) === 1) {
-                    const { key, maxToken, maxTokenRes, proxyResUrl } = await this.formatModelToken(currentRequestModelKey);
-                    const { parentMessageId, completionParams, systemMessage } = mergedOptions;
-                    const { model, temperature } = completionParams;
-                    const { context: messagesHistory } = await this.nineStore.buildMessageFromParentMessageId(usingNetwork ? netWorkPrompt : prompt, {
-                        parentMessageId,
-                        systemMessage,
-                        maxModelToken: maxToken,
-                        maxResponseTokens: maxTokenRes,
-                        maxRounds: (0, helper_1.addOneIfOdd)(rounds),
-                    });
-                    let firstChunk = true;
-                    response = await (0, openai_1.sendMessageFromOpenAi)(messagesHistory, {
-                        maxToken,
-                        maxTokenRes,
-                        apiKey: modelKey,
-                        model,
-                        temperature,
-                        proxyUrl: proxyResUrl,
-                        onProgress: (chat) => {
-                            res.write(firstChunk ? JSON.stringify(chat) : `\n${JSON.stringify(chat)}`);
-                            lastChat = chat;
-                            firstChunk = false;
-                        },
-                    });
-                    isSuccess = true;
-                }
-                if (Number(keyType) === 2) {
-                    let firstChunk = true;
-                    const { context: messagesHistory } = await this.nineStore.buildMessageFromParentMessageId(usingNetwork ? netWorkPrompt : prompt, {
-                        parentMessageId,
-                        maxRounds: (0, helper_1.addOneIfOdd)(rounds),
-                    });
-                    response = await (0, baidu_1.sendMessageFromBaidu)(usingNetwork ? netWorkPrompt : messagesHistory, {
-                        temperature,
-                        accessToken,
-                        model,
-                        onProgress: (data) => {
-                            res.write(firstChunk ? JSON.stringify(data) : `\n${JSON.stringify(data)}`);
-                            firstChunk = false;
-                            lastChat = data;
-                        },
-                    });
-                    isSuccess = true;
-                }
-                if (Number(keyType) === 3) {
-                    let firstChunk = true;
-                    const { context: messagesHistory } = await this.nineStore.buildMessageFromParentMessageId(usingNetwork ? netWorkPrompt : prompt, {
-                        parentMessageId,
-                        maxRounds: (0, helper_1.addOneIfOdd)(rounds),
-                    });
-                    response = await (0, zhipu_1.sendMessageFromZhipu)(usingNetwork ? netWorkPrompt : messagesHistory, {
-                        temperature,
-                        key,
-                        model,
-                        onProgress: (data) => {
-                            res.write(firstChunk ? JSON.stringify(data) : `\n${JSON.stringify(data)}`);
-                            firstChunk = false;
-                            lastChat = data;
-                        },
-                    });
-                    isSuccess = true;
-                }
+                const { key, maxToken, maxTokenRes, proxyResUrl } = await this.formatModelToken(currentRequestModelKey);
+                const { parentMessageId, completionParams, systemMessage } = mergedOptions;
+                const { model, temperature } = completionParams;
+                const { context: messagesHistory } = await this.nineStore.buildMessageFromParentMessageId(usingNetwork ? netWorkPrompt : prompt, {
+                    parentMessageId,
+                    systemMessage,
+                    maxModelToken: maxToken,
+                    maxResponseTokens: maxTokenRes,
+                    maxRounds: (0, helper_1.addOneIfOdd)(rounds),
+                    fileInfo: fileInfo,
+                    model: model
+                });
+                let firstChunk = true;
+                response = await (0, openai_1.sendMessageFromOpenAi)(messagesHistory, {
+                    maxToken,
+                    maxTokenRes,
+                    apiKey: modelKey,
+                    model,
+                    fileInfo,
+                    temperature,
+                    proxyUrl: proxyResUrl,
+                    onProgress: (chat) => {
+                        res.write(firstChunk ? JSON.stringify(chat) : `\n${JSON.stringify(chat)}`);
+                        lastChat = chat;
+                        firstChunk = false;
+                    },
+                });
+                isSuccess = true;
                 const userMessageData = {
                     id: this.nineStore.getUuid(),
                     text: prompt,
                     role: 'user',
                     name: undefined,
                     usage: null,
+                    fileInfo: fileInfo,
                     parentMessageId: parentMessageId,
                     conversationId: response === null || response === void 0 ? void 0 : response.conversationId,
                 };
@@ -356,11 +321,12 @@ let ChatgptService = class ChatgptService {
                     onProgress: null,
                 });
             }
-            const formatResponse = await (0, helper_1.unifiedFormattingResponse)(keyType, response, othersInfo);
-            const { prompt_tokens = 0, completion_tokens = 0, total_tokens = 0 } = formatResponse.usage;
+            let prompt_tokens = response.prompt_tokens || 0;
+            let completion_tokens = response.completion_tokens || 0;
+            let total_tokens = response.total_tokens || 0;
             let charge = deduct;
             if (isTokenBased === true) {
-                charge = deduct * total_tokens;
+                charge = Math.ceil((deduct * total_tokens) / tokenFeeRatio);
             }
             await this.userBalanceService.deductFromBalance(req.user.id, `model${deductType === 1 ? 3 : 4}`, charge, total_tokens);
             await this.modelsService.saveUseLog(keyId, total_tokens);
@@ -371,11 +337,12 @@ let ChatgptService = class ChatgptService {
                 userId: req.user.id,
                 type: balance_constant_1.DeductionKey.CHAT_TYPE,
                 prompt,
+                fileInfo: fileInfo,
                 answer: '',
                 promptTokens: prompt_tokens,
                 completionTokens: 0,
                 totalTokens: total_tokens,
-                model: formatResponse.model,
+                model: model,
                 role: 'user',
                 groupId,
                 requestOptions: JSON.stringify({
@@ -389,7 +356,7 @@ let ChatgptService = class ChatgptService {
                 userId: req.user.id,
                 type: balance_constant_1.DeductionKey.CHAT_TYPE,
                 prompt: prompt,
-                answer: formatResponse === null || formatResponse === void 0 ? void 0 : formatResponse.text,
+                answer: response.text,
                 promptTokens: prompt_tokens,
                 completionTokens: completion_tokens,
                 totalTokens: total_tokens,

dist/modules/chatgpt/dto/chatProcess.dto.js

@@ -27,6 +27,10 @@ __decorate([
     (0, class_validator_1.IsNotEmpty)({ message: '提问信息不能为空！' }),
     __metadata("design:type", String)
 ], ChatProcessDto.prototype, "prompt", void 0);
+__decorate([
+    (0, swagger_1.ApiProperty)({ example: 'https://123.png', description: '对话附带的链接', required: false }),
+    __metadata("design:type", String)
+], ChatProcessDto.prototype, "url", void 0);
 __decorate([
     (0, swagger_1.ApiProperty)({ example: '{ parentMessageId: 0 }', description: '上次对话信息', required: false }),
     (0, class_transformer_1.Type)(() => Options),

dist/modules/chatgpt/helper.js

@@ -4,7 +4,6 @@ exports.addOneIfOdd = exports.unifiedFormattingResponse = void 0;
 function unifiedFormattingResponse(keyType, response, others) {
     let formatRes = {
         keyType,
-        model: '',
         parentMessageId: '',
         text: '',
         usage: {
@@ -13,45 +12,26 @@ function unifiedFormattingResponse(keyType, response, others) {
             total_tokens: 0,
         }
     };
-    if ([1].includes(Number(keyType))) {
-        const { model, parentMessageId } = response === null || response === void 0 ? void 0 : response.detail;
-        let { usage } = response === null || response === void 0 ? void 0 : response.detail;
-        if (!usage) {
-            usage = {
-                prompt_tokens: 0,
-                completion_tokens: 0,
-                total_tokens: 0
-            };
+    const { parentMessageId } = response === null || response === void 0 ? void 0 : response.detail;
+    let { usage } = response === null || response === void 0 ? void 0 : response.detail;
+    if (!usage) {
+        usage = {
+            prompt_tokens: 0,
+            completion_tokens: 0,
+            total_tokens: 0
+        };
+    }
+    const { prompt_tokens, completion_tokens, total_tokens } = usage;
+    formatRes = {
+        keyType,
+        parentMessageId,
+        text: response.text,
+        usage: {
+            prompt_tokens,
+            completion_tokens,
+            total_tokens
         }
-        const { prompt_tokens, completion_tokens, total_tokens } = usage;
-        formatRes = {
-            keyType,
-            model,
-            parentMessageId,
-            text: response.text,
-            usage: {
-                prompt_tokens,
-                completion_tokens,
-                total_tokens
-            }
-        };
-    }
-    if ([2, 3].includes(Number(keyType))) {
-        const { usage, text } = response;
-        const { prompt_tokens, completion_tokens, total_tokens } = usage;
-        const { model, parentMessageId } = others;
-        formatRes = {
-            keyType,
-            model,
-            parentMessageId,
-            text,
-            usage: {
-                prompt_tokens,
-                completion_tokens,
-                total_tokens
-            }
-        };
-    }
+    };
     return formatRes;
 }
 exports.unifiedFormattingResponse = unifiedFormattingResponse;

dist/modules/chatgpt/openai.js

@@ -13,7 +13,6 @@ function getFullUrl(proxyUrl) {
 function sendMessageFromOpenAi(messagesHistory, inputs) {
     var _a;
     const { onProgress, maxToken, apiKey, model, temperature = 0.95, proxyUrl } = inputs;
-    console.log('current request options: ', apiKey, model, maxToken, proxyUrl);
     const max_tokens = compilerToken(model, maxToken);
     const options = {
         method: 'POST',
@@ -49,7 +48,7 @@ function sendMessageFromOpenAi(messagesHistory, inputs) {
                     catch (error) {
                         ISEND = false;
                     }
-                    if (data === '[DONE]' || ISEND) {
+                    if (ISEND) {
                         result.text = result.text.trim();
                         return result;
                     }
@@ -98,6 +97,9 @@ exports.sendMessageFromOpenAi = sendMessageFromOpenAi;
 function getTokenCount(text) {
     if (!text)
         return 0;
+    if (typeof text !== 'string') {
+        text = String(text);
+    }
     text = text.replace(/<\|endoftext\|>/g, '');
     return tokenizer.encode(text).length;
 }

dist/modules/chatgpt/store.js

@@ -3,6 +3,7 @@ Object.defineProperty(exports, "__esModule", { value: true });
 exports.NineStore = void 0;
 const uuid_1 = require("uuid");
 const tiktoken_1 = require("@dqbd/tiktoken");
+const common_1 = require("@nestjs/common");
 const tokenizer = (0, tiktoken_1.get_encoding)('cl100k_base');
 class NineStore {
     constructor(options) {
@@ -26,16 +27,46 @@ class NineStore {
         await this.store.set(message.id, message, expires);
     }
     async buildMessageFromParentMessageId(text, options) {
-        let { maxRounds, maxModelToken, maxResponseTokens, systemMessage = '', name } = options;
+        let { maxRounds, maxModelToken, maxResponseTokens, systemMessage = '', name, fileInfo, model } = options;
         let { parentMessageId } = options;
         let messages = [];
         let nextNumTokensEstimate = 0;
         if (systemMessage) {
-            messages.push({ role: 'system', content: systemMessage });
+            const specialModels = ['gemini-pro', 'ERNIE', 'qwen', 'SparkDesk', 'hunyuan'];
+            const isSpecialModel = specialModels.some(specialModel => model.includes(specialModel));
+            if (isSpecialModel) {
+                messages.push({ role: 'user', content: systemMessage });
+                messages.push({ role: 'assistant', content: "好的" });
+            }
+            else {
+                messages.push({ role: 'system', content: systemMessage, name });
+            }
         }
         const systemMessageOffset = messages.length;
         let round = 0;
-        let nextMessages = text ? messages.concat([{ role: 'user', content: text, name }]) : messages;
+        if (model === 'gpt-4-vision-preview' && fileInfo) {
+            const content = [
+                {
+                    "type": "text",
+                    "text": text
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": fileInfo
+                    }
+                }
+            ];
+            messages.push({ role: 'user', content: content, name });
+        }
+        else {
+            if (model === 'gpt-4-all' && fileInfo) {
+                text = fileInfo + "\n" + text;
+            }
+            messages.push({ role: 'user', content: text, name });
+        }
+        common_1.Logger.debug(`发送的参数：${messages}`);
+        let nextMessages = messages;
         do {
             if (!parentMessageId) {
                 break;
@@ -44,9 +75,21 @@ class NineStore {
             if (!parentMessage) {
                 break;
             }
-            const { text, name, role } = parentMessage;
+            const { text, name, role, fileInfo } = parentMessage;
+            let content = text;
+            if (role === 'user' && fileInfo) {
+                if (model === 'gpt-4-vision-preview') {
+                    content = [
+                        { "type": "text", "text": text },
+                        { "type": "image_url", "image_url": { "url": fileInfo } }
+                    ];
+                }
+                else if (model === 'gpt-4-all') {
+                    content = fileInfo + "\n" + text;
+                }
+            }
             nextMessages = nextMessages.slice(0, systemMessageOffset).concat([
-                { role, content: text, name },
+                { role, content, name },
                 ...nextMessages.slice(systemMessageOffset)
             ]);
             round++;
@@ -69,7 +112,16 @@ class NineStore {
     }
     _getTokenCount(messages) {
         let text = messages.reduce((pre, cur) => {
-            return pre += cur.content;
+            if (Array.isArray(cur.content)) {
+                const contentText = cur.content
+                    .filter((item) => item.type === 'text')
+                    .map((item) => item.text)
+                    .join(' ');
+                return pre + contentText;
+            }
+            else {
+                return pre + (cur.content || '');
+            }
         }, '');
         text = text.replace(/<\|endoftext\|>/g, '');
         return tokenizer.encode(text).length;