How to Fix 'timeout error during development' in AutoGen (TypeScript)
If you’re seeing timeout error during development in AutoGen TypeScript, it usually means one of your agent calls, model requests, or tool executions is taking longer than the default timeout window. In practice, this shows up during local development when you’re iterating on long-running prompts, slow tools, or a misconfigured runtime.
The important part: this is rarely an AutoGen bug. It’s usually a timeout mismatch between your code, your model provider, and any tool or server sitting behind the agent.
The Most Common Cause
The #1 cause is a short request timeout combined with a long-running AssistantAgent or tool call.
A lot of developers wire up AssistantAgent and OpenAIChatCompletionClient correctly, but leave the default timeout too low for the actual work being done. If your prompt triggers multiple turns, function calls, or a slow backend API, the request gets killed before AutoGen finishes.
Broken vs fixed pattern
| Broken | Fixed |
|---|---|
| Timeout is too short for dev workloads | Timeout is increased to cover agent/tool latency |
| Tool call blocks the whole run | Tool call has explicit timeout handling |
| No visibility into where time is spent | Logs and per-step timing are enabled |
// ❌ Broken
import { AssistantAgent } from "@autogen/core";
import { OpenAIChatCompletionClient } from "@autogen/openai";
const modelClient = new OpenAIChatCompletionClient({
model: "gpt-4o-mini",
apiKey: process.env.OPENAI_API_KEY!,
// Too aggressive for local dev + tools
timeout: 5000,
});
const agent = new AssistantAgent({
name: "support_agent",
modelClient,
});
const result = await agent.run("Summarize this PDF and extract key risks.");
// ✅ Fixed
import { AssistantAgent } from "@autogen/core";
import { OpenAIChatCompletionClient } from "@autogen/openai";
const modelClient = new OpenAIChatCompletionClient({
model: "gpt-4o-mini",
apiKey: process.env.OPENAI_API_KEY!,
// Give room for retries + tool calls
timeout: 30000,
});
const agent = new AssistantAgent({
name: "support_agent",
modelClient,
});
// If your workflow is long-running, also set an app-level timeout
const result = await Promise.race([
agent.run("Summarize this PDF and extract key risks."),
new Promise((_, reject) =>
setTimeout(() => reject(new Error("App-level timeout exceeded")), 35000)
),
]);
If you’re calling external tools from the agent, the same rule applies. A slow database query or HTTP request can trigger errors like:
- •
Error: Request timed out - •
TimeoutError: The operation was aborted - •
OpenAI API request timed out - •
Tool execution exceeded timeout
Other Possible Causes
1) Your tool function is blocking too long
If you registered a tool with registerFunction, make sure it returns quickly or has its own timeout.
// ❌ Blocks indefinitely if upstream service hangs
async function getPolicyDetails(policyId: string) {
return fetch(`https://internal-api/policies/${policyId}`).then(r => r.json());
}
// ✅ Add explicit fetch timeout
async function getPolicyDetails(policyId: string) {
const controller = new AbortController();
const timer = setTimeout(() => controller.abort(), 8000);
try {
const res = await fetch(`https://internal-api/policies/${policyId}`, {
signal: controller.signal,
});
return await res.json();
} finally {
clearTimeout(timer);
}
}
2) Streaming is enabled but your consumer is slow
If you use streaming responses and don’t drain the stream fast enough, the request can appear to hang and eventually time out.
// Example symptom:
// Error: stream closed unexpectedly
// Error: Request timed out while waiting for tokens
const stream = await agent.runStream("Draft a claim summary");
// Make sure you consume chunks promptly
for await (const event of stream) {
console.log(event);
}
3) Network/proxy issues in local development
Corporate proxies, VPNs, and flaky DNS often look like AutoGen timeouts.
# Check whether your environment variables are interfering
echo $HTTP_PROXY
echo $HTTPS_PROXY
echo $NO_PROXY
If you’re behind a proxy, make sure Node can reach the provider endpoint consistently. A request that works once and times out on retries is often network-related, not model-related.
4) Model selection is too slow for the task
Using a larger model for every step can push simple workflows over the edge.
// Slower than necessary for short classification tasks
const modelClient = new OpenAIChatCompletionClient({
model: "gpt-4.1",
});
// Better for fast routing / extraction steps
const fastModelClient = new OpenAIChatCompletionClient({
model: "gpt-4o-mini",
});
Use smaller models for routing, extraction, and validation. Reserve larger models for synthesis or complex reasoning.
How to Debug It
- •
Isolate the failing step
- •Run just the model call without tools.
- •Then run just the tool.
- •Then run both together.
- •This tells you whether the timeout comes from AutoGen orchestration or an external dependency.
- •
Increase timeouts temporarily
- •Set client timeout to something obvious like
30000or60000. - •If the error disappears, you’ve confirmed it’s latency-related.
- •If it still fails immediately, it’s likely config or network.
- •Set client timeout to something obvious like
- •
Log timestamps around each stage
console.time("agent-run"); const result = await agent.run("..."); console.timeEnd("agent-run");Add logs inside each tool too. If one function takes most of the time, that’s your bottleneck.
- •
Check for hidden retries
- •Some SDKs retry requests automatically.
- •Three failed attempts with a short per-attempt timeout can look like one mysterious timeout.
- •Inspect provider logs and count actual HTTP requests.
Prevention
- •
Set explicit timeouts at three levels:
- •HTTP/tool level
- •model client level
- •application workflow level
- •
Treat every external dependency as untrusted latency:
- •databases
- •internal APIs
- •file conversion services
- •OCR jobs
- •
Use fast models for fast jobs:
- •classification
- •extraction
- •routing
If you keep seeing timeout error during development in AutoGen TypeScript after fixing these points, look at your specific stack order next: most failures are caused by one slow tool wrapped inside an otherwise healthy agent chain.
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