new(gpt.gblib): GPT Tools and .gbdialog.

.vscode/launch.json

@@ -6,6 +6,7 @@
       "request": "launch",
       "sourceMaps": true,
       "name": "Debug Program",
+      "runtimeExecutable": "/root/.nvm/versions/node/v19.9.0/bin/node",
       "program": "${workspaceRoot}/boot.mjs",
       "cwd": "${workspaceRoot}",
       "env": {

boot.mjs

@@ -1,24 +1,23 @@
 #!/usr/bin/env node
 
-import chalkAnimation from 'chalk-animation';
 import Fs from 'fs';
+import os from 'node:os';
 import Path from 'path';
 import { exec } from 'child_process';
 import pjson from './package.json' assert { type: 'json' };
-import { GBUtil } from './dist/src/util.js';
 
 // Displays version of Node JS being used at runtime and others attributes.
 
-console.log(`General Bots is loading source code files...`);
+process.stdout.write(`General Bots. BotServer@${pjson.version}, botlib@${pjson.dependencies.botlib}, botbuilder@${pjson.dependencies.botbuilder}, node@${process.version.replace('v', '')}, ${process.platform} ${process.arch} `);
+os.setPriority(process.pid, os.constants.priority.PRIORITY_HIGHEST);
+
+console.log(`\nLoading virtual machine source code files...`);
 
 var __dirname = process.env.PWD || process.cwd();
 try {
   var run = () => {
 
     import('./dist/src/app.js').then((gb)=> {
-      console.log(`\n`);
-      process.stdout.write(`${pjson.version}, botlib@${pjson.dependencies.botlib}, botbuilder@${pjson.dependencies.botbuilder}, node@${process.version.replace('v', '')}, ${process.platform} ${process.arch} `);
-      console.log(`\n`);
       gb.GBServer.run()
     });
   };

packages/core.gbapp/services/GBDeployer.ts

@@ -56,8 +56,8 @@ import MicrosoftGraph from '@microsoft/microsoft-graph-client';
 import { GBLogEx } from './GBLogEx.js';
 import { DialogKeywords } from '../../basic.gblib/services/DialogKeywords.js';
 import { GBUtil } from '../../../src/util.js';
-import { HNSWLib } from 'langchain/vectorstores/hnswlib';
+import { HNSWLib } from '@langchain/community/vectorstores/hnswlib';
-import { OpenAIEmbeddings } from 'langchain/embeddings/openai';
+import { OpenAIEmbeddings } from '@langchain/openai';
 
 /**
  * Deployer service for bots, themes, ai and more.

packages/gpt.gblib/services/ChatServices.ts

@@ -48,16 +48,6 @@ import { GBConfigService } from '../../core.gbapp/services/GBConfigService.js';
 import { GuaribasSubject } from '../../kb.gbapp/models/index.js';
 import { z } from "zod";
 import { DynamicStructuredTool } from "@langchain/core/tools";
-import { JsonOutputToolsParser } from "langchain/output_parsers";
-import {
-  RunnableLambda,
-  RunnablePassthrough,
-} from "@langchain/core/runnables";
-import {
-  CombiningOutputParser,
-} from "langchain/output_parsers";
-
-
 import {
   BaseLLMOutputParser,
   OutputParserException,
@@ -65,8 +55,6 @@ import {
 import { ChatGeneration, Generation } from "@langchain/core/outputs";
 
 export interface CustomOutputParserFields { }
-
-// This can be more generic, like Record<string, string>
 export type ExpectedOutput = string;
 
 function isChatGeneration(
@@ -78,8 +66,13 @@ function isChatGeneration(
 export class CustomLLMOutputParser extends BaseLLMOutputParser<ExpectedOutput> {
   lc_namespace = ["langchain", "output_parsers"];
 
-  constructor(fields?: CustomOutputParserFields) {
+  private toolChain: RunnableSequence
-    super(fields);
+  private documentChain: RunnableSequence;
+
+  constructor( toolChain: RunnableSequence,  documentChain: RunnableSequence) {
+    super();
+    this.toolChain = toolChain;
+    this.documentChain = documentChain;
   }
 
   async parseResult(
@@ -92,15 +85,19 @@ export class CustomLLMOutputParser extends BaseLLMOutputParser<ExpectedOutput> {
     }
     let parsedOutput;
 
+    if (llmOutputs[0]['message'].lc_kwargs.additional_kwargs.tool_calls) {
+      this.toolChain.invoke({func: llmOutputs[0]['message'].lc_kwargs.additional_kwargs.tool_calls});
+    }
 
     if (isChatGeneration(llmOutputs[0])) {
       parsedOutput = llmOutputs[0].message.content;
     } else {
       parsedOutput = llmOutputs[0].text;
     }
-    let parsedText;
+
-    parsedText = parsedOutput;
+    this.documentChain.invoke(parsedOutput);
-    return parsedText;
+
+    return ``;
   }
 }
 
@@ -153,12 +150,8 @@ export class ChatServices {
       GBConfigService.get('DEFAULT_CONTENT_LANGUAGE')
     );
 
-    let tools = await ChatServices.getTools(min);
-    let toolsAsText = ChatServices.getToolsAsText(tools);
 
-    const toolMap: Record<string, any> = {
+    const context = min['vectorStore'];
-      multiply: tools[0]
-    };
 
     const memory = new BufferWindowMemory({
       returnMessages: true,
@@ -173,41 +166,17 @@ export class ChatServices {
       temperature: 0,
     });
 
-    const context = min['vectorStore'];
 
+    let tools = await ChatServices.getTools(min);
+    let toolsAsText = ChatServices.getToolsAsText(tools);
     const modelWithTools = model.bind({
       tools: tools.map(convertToOpenAITool)
     });
 
-    // Function for dynamically constructing the end of the chain based on the model-selected tool.
-    const callSelectedTool = RunnableLambda.from(
-      (toolInvocation: Record<string, any>) => {
-        const selectedTool = toolMap[toolInvocation.type];
-        if (!selectedTool) {
-          throw new Error(
-            `No matching tool available for requested type "${toolInvocation.type}".`
-          );
-        }
-        const toolCallChain = RunnableSequence.from([
-          (toolInvocation) => toolInvocation.args,
-          selectedTool,
-        ]);
-        // We use `RunnablePassthrough.assign` here to return the intermediate `toolInvocation` params
-        // as well, but you can omit if you only care about the answer.
-        return RunnablePassthrough.assign({
-          output: toolCallChain,
-        });
-      },
-
-    );
-
     const questionGeneratorTemplate = ChatPromptTemplate.fromMessages([
       AIMessagePromptTemplate.fromTemplate(
         `Answer the question without calling any tool, but if there is a need to call:
-
-
          You have access to the following set of tools. Here are the names and descriptions for each tool:
-
           ${toolsAsText}
         `
       ),
@@ -227,6 +196,26 @@ export class ChatServices {
       HumanMessagePromptTemplate.fromTemplate("Question: {question}"),
     ]);
 
+    const callToolChain = RunnableSequence.from([
+      {
+        func: async (output: object) =>{
+
+          const pid = 1;
+          const name = output['func'][0].function.name;
+          const args = JSON.parse(output['func'][0].function.arguments);
+          return await GBVMService.callVM(name, min, false, pid, false, args);
+
+        },
+        chat_history: async () => {
+          const { chat_history } = await memory.loadMemoryVariables({});
+          return chat_history;
+        },
+      },
+      new StringOutputParser()
+    ]);
+
+
+
     const combineDocumentsChain = RunnableSequence.from([
       {
         question: (output: string) => output,
@@ -254,7 +243,7 @@ export class ChatServices {
       },
       questionGeneratorTemplate,
       modelWithTools,
-      new  CustomLLMOutputParser()
+      new CustomLLMOutputParser(callToolChain, combineDocumentsChain)
     ]);
 
     const systemPrompt = user['systemPrompt'];
@@ -262,6 +251,13 @@ export class ChatServices {
     let result = await conversationalQaChain.invoke({
       question,
     });
+
+    if (result['name']) {
+      const func = result['func'];
+      await func.func(min, result['args']);
+
+    } else {
+
       // await memory.saveContext(
       //   {
       //     input: query,
@@ -270,11 +266,12 @@ export class ChatServices {
       //     output: result,
       //   }
       // ); 
+
       GBLog.info(`GPT Result: ${result.toString()}`);
       return { answer: result.toString(), questionId: 0 };
 
     }
-
+  }
 
   private static getToolsAsText(tools) {
     return Object.keys(tools)
@@ -293,14 +290,6 @@ export class ChatServices {
       if (Fs.existsSync(functionJSON)) {
         const func = JSON.parse(Fs.readFileSync(functionJSON, 'utf8'));
         func.schema = jsonSchemaToZod(func.properties, { module: "esm" });
-        func.func = async () => {
-          const name = '';
-          const pid = 1;
-          const text = ''; // TODO:
-          const result = await GBVMService.callVM(name, min, false, pid, false, [text]);
-
-        }
-
         functions.push(func);
       }