format instructions for gpt-5 only

Author: sutigit

src/config.ts

@@ -20,6 +20,14 @@ export const DEFAULT_RESET_CRON = process.env.DEFAULT_RESET_CRON || '0 0 1 */3 *
 
 export const EMBED_MODEL = process.env.EMBED_MODEL ?? 'text-embedding-small'
 
+export const formatInstructions = `
+        Always format responses in plain Markdown.
+        Use Markdown headings (#, ##, ###) for structure, even for normal text.
+        Use lists, tables, and blockquotes where useful.
+        Put math in $$ ... $$ for LaTeX rendering.
+        Wrap code in triple backticks with the correct language tag (js, ts, py, etc.) so syntax highlighting and rendering work.
+      `
+
 /**
  * name: the acual model name, which is shown to users, configures the model to be used and is also the azure deployment name.
  */
@@ -36,6 +44,7 @@ export const validModels = [
     name: 'gpt-5',
     context: 128_000,
     temperature: 1.0,
+    instructions: formatInstructions,
   },
   {
     name: 'mock',
@@ -55,11 +64,3 @@ export const DEFAULT_MODEL_ON_ENABLE = 'gpt-5'
 
 export const DEFAULT_ASSISTANT_INSTRUCTIONS = '' // 11th August 2025 we decided it should be empty
 export const DEFAULT_MODEL_TEMPERATURE = 0.5
-
-export const formatInstructions = `
-        Always format responses in plain Markdown.
-        Use Markdown headings (#, ##, ###) for structure, even for normal text.
-        Use lists, tables, and blockquotes where useful.
-        Put math in $$ ... $$ for LaTeX rendering.
-        Wrap code in triple backticks with the correct language tag (js, ts, py, etc.) so syntax highlighting and rendering work.
-      `

src/server/services/langchain/chat.ts

@@ -4,8 +4,8 @@ import type { AIMessageChunk, BaseMessageLike } from '@langchain/core/messages'
 import type { Runnable } from '@langchain/core/runnables'
 import type { StructuredTool } from '@langchain/core/tools'
 import { concat } from '@langchain/core/utils/stream'
-import { AzureChatOpenAI } from '@langchain/openai'
-import { formatInstructions, ValidModelName, validModels } from '../../../config'
+import { AzureChatOpenAI, ChatOpenAICallOptions } from '@langchain/openai'
+import { ValidModelName, validModels } from '../../../config'
 import type { ChatEvent } from '../../../shared/chat'
 import type { ChatMessage } from '../../../shared/chat'
 import type { ChatToolDef, ChatToolOutput } from '../../../shared/tools'
@@ -16,20 +16,15 @@ import { MockModel } from './MockModel'
 
 type ChatModel = Runnable<BaseLanguageModelInput, AIMessageChunk, BaseChatModelCallOptions>
 
-const getChatModel = (model: ValidModelName, tools: StructuredTool[], temperature: number): ChatModel => {
-  const modelConfig = validModels.find((m) => m.name === model)
-  if (!modelConfig) {
-    throw new Error(`Invalid model: ${model}`)
-  }
-
+const getChatModel = (modelConfig: (typeof validModels)[number], tools: StructuredTool[], temperature: number): ChatModel => {
   const chatModel =
     modelConfig.name === 'mock'
       ? new MockModel({ tools, temperature })
-      : new AzureChatOpenAI({
-          model,
+      : new AzureChatOpenAI<ChatOpenAICallOptions>({
+          model: modelConfig.name,
           azureOpenAIApiKey: AZURE_API_KEY,
           azureOpenAIApiVersion: '2023-05-15',
-          azureOpenAIApiDeploymentName: model, // In Azure, always use the acual model name as the deployment name
+          azureOpenAIApiDeploymentName: modelConfig.name, // In Azure, always use the acual model name as the deployment name
           azureOpenAIApiInstanceName: AZURE_RESOURCE,
           temperature: 'temperature' in modelConfig ? modelConfig.temperature : temperature, // If model config specifies a temperature, use it; otherwise, use the user supplied temperature.
           reasoning: {
@@ -65,20 +60,24 @@ export const streamChat = async ({
 }) => {
   const toolsByName = Object.fromEntries(tools.map((tool) => [tool.name, tool]))
 
-  const chatModel = getChatModel(model, tools, temperature)
+  const modelConfig = validModels.find((m) => m.name === model)
+  if (!modelConfig) {
+    throw new Error(`Invalid model: ${model}`)
+  }
+
+  const chatModel = getChatModel(modelConfig, tools, temperature)
 
   const messages: BaseMessageLike[] = [
-    {
-      role: 'system',
-      content: formatInstructions,
-    },
+    ...('instructions' in modelConfig ? [{ role: 'system', content: modelConfig.instructions }] : []),
     {
       role: 'system',
       content: systemMessage,
     },
     ...chatMessages,
   ]
 
+  console.log('📌 messages', messages)
+
   const result = await chatTurn(chatModel, messages, toolsByName, writeEvent, user)
 
   if (result.toolCalls.length > 0) {