agent tool error

Author: diberry

agent-message-2.json

@@ -0,0 +1,44 @@
+{
+    "data": {
+        "id": "run_h1AAJ25FuI0sXKEpqfKwJC6K",
+        "object": "thread.run",
+        "created_at": 1749046155,
+        "assistant_id": "asst_VHRy7r1EEu11x4jbkNlD9BZ6",
+        "thread_id": "thread_oLHxCoMn8WG6JwYWC6NkEkWt",
+        "status": "queued",
+        "started_at": null,
+        "expires_at": 1749046755,
+        "cancelled_at": null,
+        "failed_at": null,
+        "completed_at": null,
+        "required_action": null,
+        "last_error": null,
+        "model": "gpt-4o",
+        "instructions": "You are a helpful agent",
+        "tools": [
+            {
+                "type": "code_interpreter"
+            }
+        ],
+        "tool_resources": {
+            "code_interpreter": {
+                "file_ids": []
+            }
+        },
+        "metadata": {},
+        "temperature": 1,
+        "top_p": 1,
+        "max_completion_tokens": null,
+        "max_prompt_tokens": null,
+        "truncation_strategy": {
+            "type": "auto",
+            "last_messages": null
+        },
+        "incomplete_details": null,
+        "usage": null,
+        "response_format": "auto",
+        "tool_choice": "auto",
+        "parallel_tool_calls": true
+    },
+    "event": "thread.run.queued"
+}

agent-message-rate-limit-error.json

@@ -0,0 +1,35 @@
+{
+    "data": {
+        "id": "step_3jvJW2ljvo9BiGrjI7dWLnTD",
+        "object": "thread.run.step",
+        "created_at": 1749049871,
+        "run_id": "run_2JDnauXAoaz9zUO3po6dDQVo",
+        "assistant_id": "asst_T7EVn6EY9SffNjBSWfPquRCl",
+        "thread_id": "thread_m9EbMt50BauuWS1U73onUcEa",
+        "type": "message_creation",
+        "status": "failed",
+        "cancelled_at": null,
+        "completed_at": null,
+        "expires_at": 1749050464,
+        "failed_at": 1749049876,
+        "last_error": {
+            "code": "rate_limit_exceeded",
+            "message": "Rate limit is exceeded. Try again in 50 seconds."
+        },
+        "step_details": {
+            "type": "message_creation",
+            "message_creation": {
+                "message_id": "msg_GbuHVL7n2sK2ynWy6pcovMP8"
+            }
+        },
+        "usage": {
+            "prompt_tokens": 1490,
+            "completion_tokens": 37,
+            "total_tokens": 1527,
+            "prompt_token_details": {
+                "cached_tokens": 0
+            }
+        }
+    },
+    "event": "thread.run.step.failed"
+}

agent-message.json

@@ -0,0 +1,27 @@
+{
+    "data": {
+        "id": "msg_h52NoePFcWOOjIm4iKqdlh1O",
+        "object": "thread.message",
+        "created_at": 1749046163,
+        "assistant_id": "asst_VHRy7r1EEu11x4jbkNlD9BZ6",
+        "thread_id": "thread_oLHxCoMn8WG6JwYWC6NkEkWt",
+        "run_id": "run_h1AAJ25FuI0sXKEpqfKwJC6K",
+        "status": "completed",
+        "incomplete_details": null,
+        "incomplete_at": null,
+        "completed_at": 1749046164,
+        "role": "assistant",
+        "content": [
+            {
+                "type": "text",
+                "text": {
+                    "value": "The data has been filtered for companies in the transportation industry. Four companies were found:\n\n1. Consolidated Messenger: Operating profit = 290.7\n2. Northwind Traders: Operating profit = 9166.0\n3. Tailwind Traders: Operating profit = 164.9\n4. Wide World Importers: Operating profit = 473.6\n\nNow, I'll proceed to generate the bar chart illustrating this data.",
+                    "annotations": []
+                }
+            }
+        ],
+        "attachments": [],
+        "metadata": {}
+    },
+    "event": "thread.message.completed"
+}

output.txt

@@ -1,8 +1,8 @@
-name,revenue,operating_expenses,operating_profit,operating_profit_margin,depreciation,interest,profit_before_tax,tax,net_profit,EPS,profit_TTM,EPS_TTM,industry,sector
+name,revenue,operating_expenses,operating_profit,operating_profit_margin,depreciation,interest,profit_before_tax,tax,net_profit,EPS,profit_TTM,EPS_TTM,sector,industry
 "Adatum Corporation","1,057","847.4","192.1","18.48%","12.9","0.7","195.9","49.8","146.1","129.7","535.9","475.7","Technology","Information Technology"
 "Adventure Works Cycles","4,644.8","3,885.4","549.3","12.39%","212.8","28.9","517.7","131.5","387.9","20.7","1,202.7","64","Retail","Consumer Discretionary"
 "Alpine Ski House","1,357.1","912.7","382.1","29.51%","24.5","7.4","412.5","88.4","323.1","34.3","1,216.1","128.9","Hospitality/Leisure","Consumer Discretionary"
-"Bellows College","4,65","4,305.4","325","7.02%","41.3","26.6","276.7","73.8","202.9","7.3","767.5","27.7","Education","Consumer Discretionary"
+"Bellows College","4,650","4,305.4","325","7.02%","41.3","26.6","276.7","73.8","202.9","7.3","767.5","27.7","Education","Consumer Discretionary"
 "Best For You Organics Company","2,956.5","1,026.7","647.7","25.59%","0","1,282.1","533.4","131.5","401.8","6","1,606.2","24","Food & Beverage","Consumer Staples"
 "Boulder Innovations","6,951.9","2,982.4","3,664","55.13%","974.5","520.1","2,474.9","759","1,747.8","8.1","6,337","29.3","Technology","Information Technology"
 "Contoso","3,766.5","2,169.3","1,504.6","40.95%","432.1","640.8","369.9","84.9","275.9","2.5","1,315.1","11.8","Technology","Information Technology"
@@ -12,7 +12,7 @@ name,revenue,operating_expenses,operating_profit,operating_profit_margin,depreci
 "Fabrikam","1,605.1","1,386.7","208.2","13.06%","67.6","15.7","135.1","-1.9","136.6","7","531.7","27","Technology","Information Technology"
 "Fabrikam Residences","3,503.4","2,693.4","746.7","21.71%","73.9","30.3","648","33.1","620.5","51.9","1,432.9","119.9","Real Estate","Real Estate"
 "First Up Consultants","2,988.6","2,556.9","402.5","13.60%","115.7","6.2","309.8","83.5","226.3","13.2","779.8","45.7","Professional services","Industrials"
-"Fourth Coffee","7,9","6,122.1","1,301.8","17.54%","380.9","61.2","1,335.7","352.5","793","4","2,777.9","14","Food & Beverage","Consumer Staples"
+"Fourth Coffee","7,900","6,122.1","1,301.8","17.54%","380.9","61.2","1,335.7","352.5","983.2","4","2,777.9","14","Food & Beverage","Consumer Staples"
 "Graphic Design Institute","4,869.1","4,219.4","627.5","12.95%","163.4","111.3","376.9","130.2","232.9","16.2","697.5","48.5","Education","Consumer Discretionary"
 "Humongous Insurance","6,304.9","5,119.8","1,159.8","18.47%","360.3","132.8","679.9","205.8","474.3","7.5","1,590.7","25","Financial services","Financials"
 "Lakeshore Retail","11,463","9,558.6","1,870.4","16.37%","226.6","715.1","924.4","358","526","1.8","2,141.5","7.3","Retail","Consumer Discretionary"
@@ -23,10 +23,10 @@ name,revenue,operating_expenses,operating_profit,operating_profit_margin,depreci
 "Munson's Pickles and Preserves Farm","1,312","1,184.5","94","7.35%","14.3","0.2","113","30.5","74.2","5.5","336.4","24.7","Food & Beverage","Consumer Staples"
 "Nod Publishers","12,661.3","11,619.4","1,005","7.96%","174.4","15.6","851.9","228.6","623.6","9.6","2,332.1","35.8","Publishing","Communication Services"
 "Northwind Traders","33,122.2","9,207.3","9,166","33.43%","0","14,749","8,313.8","2,096.1","6,204.1","20.1","13,121","42.6","Transportation","Industrials"
-"Proseware","11,206.8","8,708.1","2,130.1","19.65%","91.8","6.5","2,400.4","564","2,02","71.4","6,841.6","241.8","Technology","Information Technology"
+"Proseware","11,206.8","8,708.1","2,130.1","19.65%","91.8","6.5","2,400.4","564","1,836.4","71.4","6,841.6","241.8","Technology","Information Technology"
 "Relecloud","13,381.8","2,851.5","9,449.7","70.63%","158.5","4,537.1","4,757.6","1,207","3,550.8","58.7","13,118.5","216.7","Technology","Information Technology"
-"School of Fine Art","26,022.7","14,992.2","9,949.9","38.24%","208.8","4,449.1","5,292","1,536.5","1,929","12.1","7,422.6","46.6","Education","Consumer Discretionary"
-"Southridge Video","240.1","33.5","191.2","85.08%","8.4","0.2","197.9","73.9","1,491.2","134","5,545.1","498.3","Entertainment","Communication Services"
+"School of Fine Art","26,022.7","14,992.2","9,949.9","38.24%","208.8","4,449.1","5,292","1,536.5","3,755.5","12.1","7,422.6","46.6","Education","Consumer Discretionary"
+"Southridge Video","240.1","33.5","191.2","85.08%","8.4","0.2","197.9","73.9","124.0","134","5,545.1","498.3","Entertainment","Communication Services"
 "Tailspin Toys","2,360.3","1,720.5","532.7","23.64%","160.4","23.9","455.5","108.1","347.4","18","1,047.5","54.2","Retail","Consumer Discretionary"
 "Tailwind Traders","1,649","1,374.6","164.9","10.71%","41.2","17.2","215.9","56.6","166.3","8.2","540.5","26.8","Transportation","Industrials"
 "Trey Research","35,766","8,430.4","9,807.9","33.52%","0","17,527.7","6,022.8","1,679.7","4,458.4","8.5","18,602.9","35.9","R&D","Information Technology"

quickstarts/ai-agents/ts/az-cli-roles-dina.sh

@@ -34,10 +34,16 @@ const modelDeploymentName = process.env["MODEL_DEPLOYMENT_NAME"] || "gpt-4o";
 
 export async function main(): Promise<void> {
   // Create an Azure AI Client
-  const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());
+  const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential(), {
+    retryOptions: {
+      maxRetries: 3,
+      retryDelayInMs: 2000
+    }
+  });
 
   // Upload file and wait for it to be processed
   const filePath = "./data/niftyList.csv";
+  console.log(`Uploading file from path: ${filePath}`);
   const localFileStream = fs.createReadStream(filePath);
   const localFile = await client.files.upload(localFileStream, "assistants", {
     fileName: "myLocalFile",
@@ -65,7 +71,7 @@ export async function main(): Promise<void> {
   const message = await client.messages.create(
     thread.id,
     "user",
-    "Could you please create a bar chart in the USA transportation industry for the operating profit from the uploaded CSV file and provide the file to me? If you can't create an image file, please provide the data in a text format and say what is wrong with the data to stop you from generating the image.",
+    "Could you please create a bar chart to explain the operating profit for companies related to the transportation area from the uploaded CSV file and provide the file to me?",
   );
 
   console.log(`Created message, message ID: ${message.id}`);
@@ -101,7 +107,34 @@ export async function main(): Promise<void> {
         console.log("Stream completed.");
         break;
       default:
-        console.log(`Unknown event type: ${eventMessage.event}`);
+
+        console.log(`Unhandled event type: ${JSON.stringify(eventMessage)}`);
+
+        let waitSeconds = 1000;
+
+        if (eventMessage.event.includes("thread.message")) {
+          const messageType = eventMessage.event;
+          const message = eventMessage?.data?.content?.forEach((contentPart) => {
+            if (contentPart.type === "text") {
+
+              const message: string = contentPart.text?.value || "No text";
+
+              if( message.includes("Rate limit is exceeded. Try again in ")) {
+                const regex = /Rate limit is exceeded. Try again in (\d+) seconds/;
+                const match = message.match(regex);
+                if (match && match[1]) {
+                  waitSeconds = parseInt(match[1], 10) * 1000; // Convert seconds to milliseconds
+                  console.log(`Rate limit exceeded, waiting for ${waitSeconds} milliseconds`);
+                  return new Promise((resolve) => setTimeout(resolve, waitSeconds));
+                }
+              } else {
+
+              return contentPart?.text?.value + ", " || "no text, ";
+              }
+            }
+          });
+          console.log(`${messageType} received:: ${eventMessage?.event}`);
+        }
         break;
     }
   }
@@ -122,9 +155,9 @@ export async function main(): Promise<void> {
   const assistantMessage = messagesArray.find((msg) => msg.role === "assistant");
   if (assistantMessage) {
     // Look for an image file in the assistant's message
-    const imageFileOutput = assistantMessage.content.find(content => 
+    const imageFileOutput = assistantMessage.content.find(content =>
       content.type === "image_file" && content.imageFile?.fileId);
-    
+
     if (imageFileOutput) {
       try {
         // Save the newly created file

quickstarts/ai-agents/ts/data/niftyList.csv

@@ -230,6 +230,14 @@ async function downloadGeneratedFiles(
   }
 
   const imageFileName = path.resolve(
+    "./data/" + (await client.files.get(imageFileId)).filename + "ImageFile.png",
+  );
+  console.log(`Image file name : ${imageFileName}`);
+
+  const fileContent = await (await client.files.getContent(imageFileId).asNodeStream()).body;
+  if (!fileContent) {
+    console.log("No file content available");
+    return;
   }
 
   const chunks = [];
@@ -275,7 +283,12 @@ async function cleanupResources(
 async function main() {
   try {
     // Create an Azure AI Client
-    const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential());
+    const client = new AgentsClient(projectEndpoint, new DefaultAzureCredential(), {
+      retryOptions: {
+        maxRetries: 3,            // number of retry attempts
+        retryDelayInMs: 2000      // delay between retries in milliseconds
+      }
+    });
 
     // Step 1: Setup agent and resources
     const { agent, thread, localFile } = await setupAgentAndResources(client);