prompt chaining added to codeboltjs

Author: rawatSingh2022

examples/agent-workflow-example.ts

@@ -197,8 +197,153 @@ async function runRobustAgentWorkflow(userMessage: any, codebolt: CodeboltAPI) {
     }
 }
 
+/**
+ * Example using the new addLLMResponse method in PromptBuilder
+ * This demonstrates the simplified workflow with conversation management
+ */
+async function runWorkflowWithPromptBuilder(userMessage: any, codebolt: CodeboltAPI) {
+    try {
+        // Step 1: Build the initial prompt
+        const promptBuilder = new PromptBuilder(userMessage, codebolt);
+        let currentPrompt = await promptBuilder
+            .addMCPTools()
+            .addAgentTools()
+            .addEnvironmentDetails()
+            .addSystemPrompt('agent.yaml', 'test', 'example.md')
+            .addTaskInstruction('task.yaml', 'main_task')
+            .buildInferenceParams();
+
+        let maxTurns = 20;
+        let turn = 0;
+
+        // Step 2: Main conversation loop using PromptBuilder for conversation management
+        while (!promptBuilder.isTaskCompleted() && turn < maxTurns) {
+            console.log(`\n--- Conversation Turn ${turn + 1} ---`);
+            
+            // Get LLM response
+            const llmResponse = llm.inference(currentPrompt);
+            
+            // Add LLM response to conversation history
+            await promptBuilder.addLLMResponse(llmResponse);
+            
+            // Process the response using LLMOutputHandler
+            const outputHandler = new LLMOutputHandler(llmResponse, codebolt);
+            await outputHandler.sendMessageToUser();
+            
+            // Check if task is completed (using both methods for reliability)
+            if (outputHandler.isCompleted() || promptBuilder.isTaskCompleted()) {
+                console.log("Task completed successfully!");
+                break;
+            }
+            
+            // Execute tools and get results
+            const toolResults = await outputHandler.runTools();
+            
+            // Add tool results to conversation
+            if (toolResults.length > 0) {
+                promptBuilder.addToolResults(toolResults);
+            } else {
+                // Add default continuation message when no tools executed
+                promptBuilder.addDefaultContinuationMessage();
+            }
+            
+            // Check if conversation should be summarized
+            if (promptBuilder.shouldSummarizeConversation(30)) {
+                console.log("Conversation getting long, consider summarization...");
+                // Note: Actual summarization would require additional implementation
+            }
+            
+            // Build next prompt for the loop
+            currentPrompt = await promptBuilder.buildInferenceParams();
+            turn++;
+        }
+        
+        if (turn >= maxTurns) {
+            console.log("Maximum conversation turns reached. Stopping.");
+        }
+        
+        console.log(`Workflow completed in ${turn} turns`);
+        console.log(`Final conversation length: ${promptBuilder.getConversationLength()} messages`);
+        
+    } catch (error) {
+        console.error("Error in PromptBuilder workflow:", error);
+        throw error;
+    }
+}
+
+/**
+ * Example matching the user's agent code structure with the new addLLMResponse method
+ * This shows how to update the existing agent to use PromptBuilder for conversation management
+ */
+async function runUpdatedAgentWorkflow(userMessage: any, codebolt: CodeboltAPI) {
+    try {
+        // Step 1: Build the initial prompt
+        const promptBuilderObject = new PromptBuilder(userMessage, codebolt);
+        let userPrompt = await promptBuilderObject
+            .addMCPTools()
+            .addAgentTools()
+            .addEnvironmentDetails()
+            .addSystemPrompt('agent.yaml', 'test', 'example.md')
+            .addTaskInstruction('task.yaml', 'main_task')
+            .buildInferenceParams();
+
+        // Step 2: Get initial LLM response
+        let llmOutput = llm.inference(userPrompt);
+        
+        // Add the initial LLM response to conversation history
+        await promptBuilderObject.addLLMResponse(llmOutput);
+        
+        let llmOutputObject = new LLMOutputHandler(llmOutput, codebolt);
+
+        // Step 3: Main conversation loop with improved conversation management
+        while (!llmOutputObject.isCompleted() && !promptBuilderObject.isTaskCompleted()) {
+            // Send the assistant's message to the user
+            await llmOutputObject.sendMessageToUser();
+            
+            // Execute any tool calls in the response
+            const toolCallResult = await llmOutputObject.runTools();
+            
+            // Add tool results to conversation history
+            if (toolCallResult.length > 0) {
+                promptBuilderObject.addToolResults(toolCallResult);
+            } else {
+                // Add default continuation message when no tools executed
+                promptBuilderObject.addDefaultContinuationMessage();
+            }
+            
+            // Check if conversation should be summarized
+            if (promptBuilderObject.shouldSummarizeConversation(30)) {
+                console.log("Conversation getting long, consider summarization...");
+            }
+            
+            // Step 4: Build next prompt using PromptBuilder's conversation history
+            const nextUserPrompt = await promptBuilderObject.buildInferenceParams();
+
+            // Step 5: Get next LLM response
+            llmOutput = llm.inference(nextUserPrompt);
+            
+            // Add the new LLM response to conversation history
+            await promptBuilderObject.addLLMResponse(llmOutput);
+            
+            llmOutputObject = new LLMOutputHandler(llmOutput, codebolt);
+            
+            // Update userPrompt for next iteration
+            userPrompt = nextUserPrompt;
+        }
+
+        console.log("Agent workflow completed successfully!");
+        console.log(`Final conversation length: ${promptBuilderObject.getConversationLength()} messages`);
+        
+    } catch (error) {
+        console.error("Error in agent workflow:", error);
+        throw error;
+    }
+}
+
 export { 
     runAgentWorkflow, 
     runDetailedAgentWorkflow, 
-    runRobustAgentWorkflow 
+    runRobustAgentWorkflow,
+    runWorkflowWithPromptBuilder,
+    runUpdatedAgentWorkflow 
 }; 

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@codebolt/codeboltjs",
-  "version": "2.0.12",
+  "version": "2.0.13",
   "description": "",
   "keywords": [],
   "author": "",