Improve code generation prompt / context (#1038)

Author: alexandrudanpop

ai-prompts/code.txt

@@ -1,7 +1,7 @@
 # Code Generation Instructions
 
-You are tasked with generating TypeScript code that will execute in an **isolated-vm environment** (secure and isolated JavaScript runtime for Node.js).
-Ask clarifications is the requirements from the user are not clear, in a short an concise manner, without too many technical details.
+You are a TypeScript code generator that transforms data based on user requirements. Your primary function is to **generate executable code**, not to have conversations.
+The generated TypeScript code will execute in an **isolated-vm environment** (secure and isolated JavaScript runtime for Node.js).
 
 ## Required Code Structure
 
@@ -33,7 +33,7 @@ packageJson:
 ##Compilation Process
 Your code will be compiled using:
 
-T- ypeScript with module: 'node16' and Node20 target
+TypeScript with module: 'node16' and Node20 target
 - Rollup bundling with CommonJS plugin
 - Execution in isolated-vm environment
 
@@ -79,7 +79,7 @@ if (!data.propertyName) { // ❌ May cause TS2339 errors
 
 The `inputs` parameter contains all the data needed for your code.
 If you see inputs properties values are truncated, keep in mind that the final code will receive the full object as inputs and NOT stringified! 
-Verify and handle both cases, if input variables are objects or strings.
+Verify and handle both cases, if input variables are objects or strings. 
 
 - **Type**: Always an object
 - **Content**: May include variables from previous workflow steps
@@ -104,6 +104,8 @@ inputs = {
 }
 ```
 
+If the user asks for certain values, verify if the data provided contains the value so correct casing is applied!
+
 ## Dependencies
 
 If you need external packages:

packages/server/api/src/app/ai/chat/context-enrichment.service.ts

@@ -29,6 +29,8 @@ type Options = {
   includeCurrentStepOutput: IncludeOptions;
 };
 
+const TRUNCATION_LENGTH = 30000;
+
 export async function enrichContext(
   additionalContext: ChatFlowContext,
   projectId: string,
@@ -261,7 +263,7 @@ async function resolveVariable(
   return {
     name: variable.name,
     value: result.success
-      ? safeStringifyAndTruncate(result.censoredValue)
+      ? safeStringifyAndTruncate(result.censoredValue, TRUNCATION_LENGTH)
       : String(result.error),
   };
 }

packages/shared/src/lib/ai/chat/code-output-structure.ts

@@ -16,7 +16,11 @@ export const codeLLMSchema = z.object({
 export type CodeSchema = z.infer<typeof codeLLMSchema>;
 
 export const unifiedCodeLLMSchema = z.object({
-  type: z.enum(['code', 'reply']),
+  type: z
+    .enum(['code', 'reply'])
+    .describe(
+      'The type of the response. Always return "code" if you are generating code, and "reply" if you are answering the user question or asking for clarifications.',
+    ),
   code: z.string().optional().describe(codeDescription),
   packageJson: z.string().optional().describe(packageJsonDescription),
   textAnswer: z.string().describe(textAnswerDescription),