Better logging with more verbose trace options and channels

yGuy · Jul 31, 2023 · af315f2 · af315f2
1 parent 8ef5c69
commit af315f2
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Showing 4 changed files with 86 additions and 46 deletions.
diff --git a/package.json b/package.json
@@ -1,6 +1,6 @@
 {
   "name": "chatgpt-mattermost-bot",
-  "version": "2.1.1",
+  "version": "2.1.2",
   "private": true,
   "scripts": {
     "start": "ts-node ./src/botservice.ts",

diff --git a/src/botservice.ts b/src/botservice.ts
@@ -1,5 +1,4 @@
 import {continueThread, registerChatPlugin} from "./openai-wrapper";
-import {Log} from "debug-level"
 import {mmClient, wsClient} from "./mm-client";
 import 'babel-polyfill'
 import 'isomorphic-fetch'
@@ -13,6 +12,8 @@ import {JSONMessageData, MessageData} from "./types";
 import {ExitPlugin} from "./plugins/ExitPlugin";
 import {MessageCollectPlugin} from "./plugins/MessageCollectPlugin";
 
+import {botLog, matterMostLog} from "./logging";
+
 if (!global.FormData) {
     global.FormData = require('form-data')
 }
@@ -33,9 +34,9 @@ const botInstructions = "Your name is " + name + " and you are a helpful assista
     "provide them with succinct answers formatted using Markdown. You know the user's name as it is provided within the " +
     "meta data of the messages."
 
-async function onClientMessage(msg: WebSocketMessage<JSONMessageData>, meId: string, log: Log) {
+async function onClientMessage(msg: WebSocketMessage<JSONMessageData>, meId: string) {
     if (msg.event !== 'posted' || !meId) {
-        log.debug({msg: msg})
+        matterMostLog.debug({msg: msg})
         return
     }
 
@@ -55,7 +56,7 @@ async function onClientMessage(msg: WebSocketMessage<JSONMessageData>, meId: str
 
     // create the context
     for (const threadPost of posts.slice(-contextMsgCount)) {
-        log.trace({msg: threadPost})
+        matterMostLog.trace({msg: threadPost})
         if (threadPost.user_id === meId) {
             chatmessages.push({
                 role: ChatCompletionRequestMessageRoleEnum.Assistant,
@@ -76,9 +77,8 @@ async function onClientMessage(msg: WebSocketMessage<JSONMessageData>, meId: str
     const typingInterval = setInterval(typing, 2000)
 
     try {
-        log.trace({chatmessages})
         const {message, fileId, props} = await continueThread(chatmessages, msgData)
-        log.trace({message})
+        botLog.trace({message})
 
         // create answer response
         const newPost = await mmClient.createPost({
@@ -88,9 +88,9 @@ async function onClientMessage(msg: WebSocketMessage<JSONMessageData>, meId: str
             root_id: msgData.post.root_id || msgData.post.id,
             file_ids: fileId ? [fileId] : undefined
         })
-        log.trace({msg: newPost})
+        botLog.trace({msg: newPost})
     } catch (e) {
-        log.error(e)
+        botLog.error(e)
         await mmClient.createPost({
             message: "Sorry, but I encountered an internal error when trying to process your message",
             channel_id: msgData.post.channel_id,
@@ -208,28 +208,24 @@ async function userIdToName(userId: string): Promise<string> {
     return username
 }
 
-Log.options({json: true, colors: true})
-Log.wrapConsole('bot-ws', {level4log: 'INFO'})
-const log = new Log('bot')
-
 /* Entry point */
 async function main(): Promise<void> {
     const meId = (await mmClient.getMe()).id
 
-    log.log("Connected to Mattermost.")
+    botLog.log("Connected to Mattermost.")
 
     for (const plugin of plugins) {
         if (plugin.setup()) {
             registerChatPlugin(plugin)
-            log.trace("Registered plugin " + plugin.key)
+            botLog.trace("Registered plugin " + plugin.key)
         }
     }
 
-    wsClient.addMessageListener((e) => onClientMessage(e, meId, log))
-    log.trace("Listening to MM messages...")
+    wsClient.addMessageListener((e) => onClientMessage(e, meId))
+    botLog.trace("Listening to MM messages...")
 }
 
 main().catch(reason => {
-    log.error(reason);
+    botLog.error(reason);
     process.exit(-1)
 })
diff --git a/src/logging.ts b/src/logging.ts
@@ -0,0 +1,7 @@
+import {Log} from "debug-level";
+
+Log.options({json: true, colors: true})
+Log.wrapConsole('bot-ws', {level4log: 'INFO'})
+export const  botLog = new Log('bot')
+export const openAILog = new Log('open-ai')
+export const matterMostLog = new Log('mattermost')
diff --git a/src/openai-wrapper.ts b/src/openai-wrapper.ts
@@ -2,30 +2,36 @@ import {
     ChatCompletionFunctions,
     ChatCompletionRequestMessage,
     ChatCompletionResponseMessage, ChatCompletionResponseMessageRoleEnum,
-    Configuration,
+    Configuration, CreateChatCompletionRequest, CreateImageRequest,
     OpenAIApi
 } from "openai";
+import {openAILog as log} from "./logging"
+
 import {PluginBase} from "./plugins/PluginBase";
 import {AiResponse, MessageData} from "./types";
 
-const configuration = new Configuration({
-    apiKey: process.env['OPENAI_API_KEY']
-})
+const apiKey = process.env['OPENAI_API_KEY'];
+log.trace({apiKey})
+
+const configuration = new Configuration({ apiKey })
+
 const openai = new OpenAIApi(configuration)
 
 const model = process.env['OPENAI_MODEL_NAME'] ?? 'gpt-3.5-turbo'
 const max_tokens = Number(process.env['OPENAI_MAX_TOKENS'] ?? 2000)
 const temperature = Number(process.env['OPENAI_TEMPERATURE'] ?? 1)
 
-const plugins: Record<string, PluginBase<any>> = {}
+log.debug({model, max_tokens, temperature})
+
+const plugins: Map<string, PluginBase<any>> = new Map()
 const functions: ChatCompletionFunctions[] = []
 
 /**
  * Registers a plugin as a GPT function. These functions are sent to openAI when the user interacts with chatGPT.
  * @param plugin
  */
 export function registerChatPlugin(plugin: PluginBase<any>) {
-    plugins[plugin.key] = plugin
+    plugins.set(plugin.key, plugin)
     functions.push({
         name: plugin.key,
         description: plugin.description,
@@ -48,27 +54,52 @@ export async function continueThread(messages: ChatCompletionRequestMessage[], m
         message: 'Sorry, but it seems I found no valid response.'
     }
 
+    // the number of rounds we're going to run at maximum
+    let maxChainLength = 7;
+
+    // check whether ChatGPT hallucinates a plugin name.
+    const missingPlugins = new Set<string>()
+
     let isIntermediateResponse = true
-    while(isIntermediateResponse) {
+    while(isIntermediateResponse && maxChainLength-- > 0) {
         const responseMessage = await createChatCompletion(messages, functions)
+        log.trace(responseMessage)
         if(responseMessage) {
             // if the function_call is set, we have a plugin call
             if(responseMessage.function_call && responseMessage.function_call.name) {
+                const pluginName = responseMessage.function_call.name;
+                log.trace({pluginName})
                 try {
-                    const pluginResponse = await plugins[responseMessage.function_call!.name!].runPlugin((JSON.parse(responseMessage.function_call!.arguments!)), msgData)
-
-                    if(pluginResponse.intermediate) {
-                        messages.push({
-                            role: ChatCompletionResponseMessageRoleEnum.Function,
-                            name: responseMessage.function_call!.name!,
-                            content: pluginResponse.message
-                        })
-                        continue
-                    }
+                    const plugin = plugins.get(pluginName);
+                    if (plugin){
+                        const pluginArguments = JSON.parse(responseMessage.function_call.arguments ?? '[]');
+                        log.trace({plugin, pluginArguments})
+                        const pluginResponse = await plugin.runPlugin(pluginArguments, msgData)
+                        log.trace({pluginResponse})
 
-                    aiResponse = pluginResponse
+                        if(pluginResponse.intermediate) {
+                            messages.push({
+                                role: ChatCompletionResponseMessageRoleEnum.Function,
+                                name: pluginName,
+                                content: pluginResponse.message
+                            })
+                            continue
+                        }
+                        aiResponse = pluginResponse
+                    } else {
+                        if (!missingPlugins.has(pluginName)){
+                            missingPlugins.add(pluginName)
+                            log.debug({ error: 'Missing plugin ' + pluginName, pluginArguments: responseMessage.function_call.arguments})
+                            messages.push({ role: 'system', content: `There is no plugin named '${pluginName}' available. Try without using that plugin.`})
+                            continue
+                        } else {
+                            log.debug({ messages })
+                            aiResponse.message = `Sorry, but it seems there was an error when using the plugin \`\`\`${pluginName}\`\`\`.`
+                        }
+                    }
                 } catch (e) {
-                    aiResponse.message = `Sorry, but it seems there was an error when using the plugin \`\`\`${responseMessage.function_call!.name!}\`\`\`.`
+                    log.debug({ messages, error: e })
+                    aiResponse.message = `Sorry, but it seems there was an error when using the plugin \`\`\`${pluginName}\`\`\`.`
                 }
             } else if(responseMessage.content) {
                 aiResponse.message = responseMessage.content
@@ -87,18 +118,22 @@ export async function continueThread(messages: ChatCompletionRequestMessage[], m
  * @param functions Function calls which can be called by the openAI model
  */
 export async function createChatCompletion(messages: ChatCompletionRequestMessage[], functions: ChatCompletionFunctions[] | undefined = undefined): Promise<ChatCompletionResponseMessage | undefined> {
-    const options: any = {
+    const chatCompletionOptions: CreateChatCompletionRequest = {
         model: model,
         messages: messages,
         max_tokens: max_tokens,
         temperature: temperature,
     }
     if(functions) {
-        options.functions = functions
-        options.function_call = 'auto'
+        chatCompletionOptions.functions = functions
+        chatCompletionOptions.function_call = 'auto'
     }
 
-    const chatCompletion = await openai.createChatCompletion(options)
+    log.trace({chatCompletionOptions})
+
+    const chatCompletion = await openai.createChatCompletion(chatCompletionOptions)
+
+    log.trace({chatCompletion})
 
     return chatCompletion.data?.choices?.[0]?.message
 }
@@ -108,12 +143,14 @@ export async function createChatCompletion(messages: ChatCompletionRequestMessag
  * @param prompt The image description provided to DALL-E.
  */
 export async function createImage(prompt: string): Promise<string | undefined> {
-    const image = await openai.createImage({
-        prompt: prompt,
+    const createImageOptions: CreateImageRequest = {
+        prompt,
         n: 1,
         size: '512x512',
-        response_format: "b64_json"
-    })
-
+        response_format: 'b64_json'
+    };
+    log.trace({createImageOptions})
+    const image = await openai.createImage(createImageOptions)
+    log.trace({image})
     return image.data?.data[0]?.b64_json
 }