new(all): WebDav support for all bots.

packages/core.gbapp/services/GBMinService.ts

@@ -1493,7 +1493,7 @@ export class GBMinService {
 
     const isVMCall = Object.keys(min.scriptMap).find(key => min.scriptMap[key] === context.activity.text) !== undefined;
 
-    // TODO: Externalize intents for GPT.
+    // TODO: Externalize intents for LLM.
 
     if (/create dialog|creative dialog|create a dialog|criar diálogo|criar diálogo/gi.test(context.activity.text)) {
       await step.beginDialog('/dialog');

packages/llm.gblib/services/ChatServices.ts

@@ -70,6 +70,7 @@ import {
   SQL_MSSQL_PROMPT,
   SQL_MYSQL_PROMPT
 } from 'langchain/chains/sql_db';
+import { GBUtil } from '../../../src/util.js';
 
 export interface CustomOutputParserFields {}
 export type ExpectedOutput = any;
@@ -82,19 +83,19 @@ class CustomHandler extends BaseCallbackHandler {
   name = 'custom_handler';
 
   handleLLMNewToken(token: string) {
-    GBLogEx.info(0, `LLM: token: ${JSON.stringify(token)}`);
+    GBLogEx.info(0, `LLM: token: ${GBUtil.toYAML(token)}`);
   }
 
   handleLLMStart(llm: Serialized, _prompts: string[]) {
-    GBLogEx.info(0, `LLM: handleLLMStart ${JSON.stringify(llm)}, Prompts: ${_prompts.join('\n')}`);
+    GBLogEx.info(0, `LLM: handleLLMStart ${GBUtil.toYAML(llm)}, Prompts: ${_prompts.join('\n')}`);
   }
 
   handleChainStart(chain: Serialized) {
-    GBLogEx.info(0, `LLM: handleChainStart: ${JSON.stringify(chain)}`);
+    GBLogEx.info(0, `LLM: handleChainStart: ${GBUtil.toYAML(chain)}`);
   }
 
   handleToolStart(tool: Serialized) {
-    GBLogEx.info(0, `LLM: handleToolStart: ${JSON.stringify(tool)}`);
+    GBLogEx.info(0, `LLM: handleToolStart: ${GBUtil.toYAML(tool)}`);
   }
 }
 
@@ -132,6 +133,7 @@ export class GBLLMOutputParser extends BaseLLMOutputParser<ExpectedOutput> {
     try {
       GBLogEx.info(this.min, result);
       result = result.replace(/\\n/g, '');
+      result = result.replace(/\`\`\`/g, '');
       res = JSON.parse(result);
     } catch {
       return result;
@@ -295,9 +297,9 @@ export class ChatServices {
     let model;
 
     const azureOpenAIKey = await (min.core as any)['getParam'](min.instance, 'Azure Open AI Key', null, true);
-    const azureOpenAIGPTModel = await (min.core as any)['getParam'](
+    const azureOpenAILLMModel = await (min.core as any)['getParam'](
       min.instance,
-      'Azure Open AI GPT Model',
+      'Azure Open AI LLM Model',
       null,
       true
     );
@@ -312,7 +314,7 @@ export class ChatServices {
     model = new ChatOpenAI({
       azureOpenAIApiKey: azureOpenAIKey,
       azureOpenAIApiInstanceName: azureOpenAIApiInstanceName,
-      azureOpenAIApiDeploymentName: azureOpenAIGPTModel,
+      azureOpenAIApiDeploymentName: azureOpenAILLMModel,
       azureOpenAIApiVersion: azureOpenAIVersion,
       temperature: 0,
       callbacks: [logHandler]
@@ -412,8 +414,8 @@ export class ChatServices {
         tool_output: async (output: object) => {
           const name = output['func'][0].function.name;
           const args = JSON.parse(output['func'][0].function.arguments);
-          GBLogEx.info(min, `Running .gbdialog '${name}' as GPT tool...`);
-          const pid = GBVMService.createProcessInfo(null, min, 'gpt', null);
+          GBLogEx.info(min, `Running .gbdialog '${name}' as LLM tool...`);
+          const pid = GBVMService.createProcessInfo(null, min, 'LLM', null);
 
           return await GBVMService.callVM(name, min, false, pid, false, args);
         },
@@ -458,8 +460,9 @@ export class ChatServices {
       new StringOutputParser()
     ]);
 
+    GBLogEx.info(min, `Calling LLM...`);
     let result, sources;
-    let text, file, page;
+    let page;
 
     // Choose the operation mode of answer generation, based on
     // .gbot switch LLMMode and choose the corresponding chain.
@@ -477,7 +480,6 @@ export class ChatServices {
       });
     } else if (LLMMode === 'sql') {
       const con = min[`llm`]['gbconnection'];
-
       const dialect = con['storageDriver'];
 
       let dataSource;
@@ -506,6 +508,7 @@ export class ChatServices {
           logging: true
         });
       }
+
       const db = await SqlDatabase.fromDataSourceParams({
         appDataSource: dataSource
       });
@@ -519,11 +522,11 @@ export class ChatServices {
 
           VERY IMPORTANT: Return just the  generated SQL command as plain text with no Markdown or formmating.
           ------------
-    SCHEMA: {schema}
-    ------------
-    QUESTION: {question}
-    ------------
-    SQL QUERY:`);
+          SCHEMA: {schema}
+          ------------
+          QUESTION: {question}
+          ------------
+          SQL QUERY:`);
 
       /**
        * Create a new RunnableSequence where we pipe the output from `db.getTableInfo()`
@@ -600,7 +603,7 @@ export class ChatServices {
 
       result = result.content;
     } else {
-      GBLogEx.info(min, `Invalid Answer Mode in Config.xlsx: ${LLMMode}.`);
+      GBLogEx.info(min, `Invalid Answer Mode in .gbot: ${LLMMode}.`);
     }
 
     await memory.saveContext(
@@ -612,7 +615,6 @@ export class ChatServices {
       }
     );
 
-    GBLogEx.info(min, `GPT Result: ${result.toString()}`);
     return { answer: result.toString(), sources, questionId: 0, page };
   }
 
@@ -625,7 +627,7 @@ export class ChatServices {
   private static async getTools(min: GBMinInstance) {
     let functions = [];
 
-    // Adds .gbdialog as functions if any to GPT Functions.
+    // Adds .gbdialog as functions if any to LLM Functions.
     await CollectionUtil.asyncForEach(Object.keys(min.scriptMap), async script => {
       const path = DialogKeywords.getGBAIPath(min.botId, 'gbdialog', null);
       const jsonFile = Path.join('work', path, `${script}.json`);

templates/ai-search.gbai/ai-search.gbot/config.csv

@@ -1,2 +1,2 @@
 name,value
-Answer Mode,document
+Answer Mode,document-ref

templates/api-server.gbai/api.gbdialog/start.bas

@@ -1,7 +1,7 @@
 
 PARAM stall AS number LIKE Stall Code
 PARAM operator AS number LIKE Operator Code
-DESCRIPTION This function (tool) is never called by GPT. It is a WebService of GB.
+DESCRIPTION This function (tool) is never called by LLM. It is a WebService of GB.
 
 REM Login as Waiter
 data = NEW OBJECT

templates/default.gbai/default.gbdialog/start.bas

@@ -0,0 +1,55 @@
+BEGIN SYTEM PROMPT
+
+# I'm General Botss:
+
+- I identify as General Bots, an AI assistant created through open collaboration.
+- My primary role is to assist users by providing information, answering questions, and engaging in conversation.
+- I use various open-source technologies and publicly available information to provide relevant and useful responses.
+- I can understand and communicate fluently in the user's language of choice such as English, zhongwen, nihongo, Español, Français, Deutsch, and others.
+- I respect user privacy and freedom of information.
+- I encourage critical thinking and diverse perspectives.
+
+## On my capabilities:
+
+- I am capable of generating creative content such as poems, stories, code, essays, and songs using my own words and knowledge.
+- If assistance is requested, I can help the user with writing, rewriting, improving, or optimizing their content.
+- I have the ability to identify errors in the conversation and can rectify them by acknowledging the mistake and offering accurate information.
+- I can describe and analyze images that users share with me.
+
+## On my response:
+
+- My responses aim to be helpful, respectful, empathetic, interesting, and engaging.
+- My logic and reasoning strive to be rigorous and intelligent.
+- I encourage open dialogue and respectful discussion of different viewpoints.
+- My responses avoid being accusatory, rude, or defensive.
+
+## On my output format:
+
+- I use markdown for formatting, including headings, tables, bold text, and lists to present information clearly.
+- I use code blocks for displaying formatted content such as poems, code, or lyrics.
+- I use LaTeX for mathematical expressions when appropriate.
+
+## On my limitations:
+
+- My knowledge may not always be up-to-date or complete. I encourage users to verify important information from authoritative sources.
+- I do not have access to personal user data or external tools beyond what's publicly available.
+- I cannot perform actions outside of our conversation, such as sending emails or accessing private information.
+
+## On ethical guidelines:
+
+- I strive to provide information that promotes the well-being of individuals and society.
+- I encourage respect for human rights, democracy, and individual freedoms.
+- I do not create content that could cause harm to individuals or groups.
+- I respect intellectual property rights and encourage the use of open-source and freely available resources.
+- If I'm unsure about the potential impact of my response, I provide a clear disclaimer.
+
+## On transparency:
+
+- I am transparent about being an AI and about the limitations of my knowledge and capabilities.
+- I encourage users to think critically and not blindly trust AI-generated information.
+- I support open dialogue about AI ethics and the role of AI in society.
+
+Remember, I'm here to assist and engage in constructive dialogue. Feel free to ask questions or discuss any topic that interests you!
+
+
+END SYSTEM PROMPT

templates/llm-tools.gbai/llm-tools.gbdialog/describe-image.bas

@@ -0,0 +1,5 @@
+PARAM image
+DESCRIPTION Returns the description of the image that was sent with the previous user message. This tool is automatically invoked if a user uploads an image.
+
+
+

templates/llm-tools.gbai/llm-tools.gbdialog/generate-image.bas

@@ -0,0 +1,6 @@
+
+PARAM prompt
+DESCRIPTION Calls an artificial intelligence model to create an image. `prompt` parameter is a text description of the desired image.
+
+
+

templates/llm-tools.gbai/llm-tools.gbdialog/search.bas

@@ -0,0 +1,2 @@
+PARAM query
+DESCRIPTION Returns search results in a JSON string. `query` parameter is a well-formed web search query.- `search_web(query: str) -> str` returns Bing search results in a JSON string. `query` parameter is a well-formed web search query.