9.6 KiB
Quick Diagnostic Workflows
Workflow: "Runtime Not Connecting"
The client shows a connection error, banner error, or the chat never loads.
Step 1: Verify the runtime is running
curl -v http://localhost:3001/api/copilotkit/info
- No response / connection refused -> The server is not running. Start it.
- 404 -> The basePath is wrong. Check
createCopilotEndpoint({ basePath })vs the URL you are hitting. - 500 -> The agent loading failed. Check server logs for the error.
- 200 with JSON -> Runtime is up. Proceed to step 2.
Step 2: Check the client configuration
<CopilotKit runtimeUrl="/api/copilotkit">
- Does
runtimeUrlmatch the runtime's basePath exactly? - If cross-origin (e.g., runtime on port 3001, app on port 3000), is CORS configured?
- If using a proxy (Next.js rewrites, nginx), does the proxy preserve the full path?
Step 3: Check browser network tab
- Look for the GET request to
/info - If it is blocked by CORS, you will see a preflight OPTIONS failure
- If it returns an error, the error body contains the
CopilotKitErrorCode
Step 4: Check package versions
npm ls @copilotkit/runtime @copilotkit/react @copilotkit/core @ag-ui/client
All @copilotkit/* packages should be the same version. Mismatches cause VERSION_MISMATCH errors.
Step 5: Check CORS (if cross-origin)
Default CORS allows all origins without credentials. If you need credentials:
createCopilotEndpoint({
runtime,
basePath: "/api/copilotkit",
cors: {
origin: "https://your-frontend.com",
credentials: true,
},
});
And on the client:
<CopilotKit
runtimeUrl="https://your-api.com/api/copilotkit"
credentials="include"
/>
Workflow: "Agent Not Responding"
The chat connects but messages are never answered, or the agent returns an error.
Step 1: Verify agent is registered
curl http://localhost:3001/api/copilotkit/info | jq '.agents'
Check that the agent name matches the agentId prop in CopilotChat or useAgent.
Step 2: Check the SSE stream
- Open browser DevTools > Network tab
- Send a message in the chat
- Find the POST to
/agent/:agentId/run - Check the response:
- 404 -> Agent not found in runtime
- 500 -> Server error during agent execution
- 200 with empty body -> Agent started but produced no events
- 200 with events -> Check the events (step 3)
Step 3: Inspect the event stream
Look at the SSE events in the response:
-
Only
RunStartedEventthen nothing -> Agent is stalled. Check server logs. Common causes:- Missing LLM API key (agent cannot call the model)
- Agent waiting for a tool result that never comes
- Reasoning event stall (Anthropic models, issue #3323)
-
RunErrorEventpresent -> Read the error message. Common causes:- LLM API returned an error (rate limit, invalid key, model not found)
- Agent code threw an exception
-
RunFinishedEventwithout text messages -> Agent completed but produced no output. Check the agent's prompt and logic.
Step 4: Check LLM API key
For BuiltInAgent, verify the environment variable:
| Provider | Environment Variable |
|---|---|
| OpenAI | OPENAI_API_KEY |
| Anthropic | ANTHROPIC_API_KEY |
GOOGLE_API_KEY |
|
| Vertex | Application Default Credentials |
Step 5: Check the agent's model string
new BuiltInAgent({
model: "openai/gpt-4o", // Must be "provider/model-name"
});
Invalid model strings throw Error: Invalid model string "..." or Error: Unknown provider "...".
Step 6: Check server-side logs
The SSE response handler logs errors with full stack traces:
Error running agent: <error>
Error stack: <stack trace>
Error details: { name, message, cause }
Workflow: "Streaming Failures"
The agent starts responding but the stream cuts off, duplicates events, or corrupts messages.
Step 1: Check for premature stream termination
- Look at the SSE response in the Network tab
- Does it end with
RunFinishedEvent? If not:- Connection closed mid-stream -> Hosting platform timeout (Vercel: 30s default, Railway: 5min). Consider using Intelligence mode for long-running agents.
- Error in the stream -> Check for
RunErrorEventbefore the cutoff - Client navigated away -> Expected behavior, the
abortsignal cleaned up the stream
Step 2: Check for event ordering issues
Events must follow a logical sequence:
TextMessageStartbeforeTextMessageChunkbeforeTextMessageEndToolCallStartbeforeToolCallArgsbeforeToolCallEndRunStartedat the beginning,RunFinishedat the end
If events are out of order, the issue is in the agent's Observable implementation.
Step 3: Check for duplicate events
If the same message appears multiple times:
- Message ID collision -> Check issue #3410 (OpenAI-compatible providers reusing IDs)
- Agent re-running -> The
runIdchanged mid-conversation. Check for HITL issues (issue #3456).
Step 4: Check for message corruption
If message content is garbled or mixed:
- Model-specific issue -> DeepSeek and some models produce malformed streaming chunks (issue #3351)
- Encoding issue -> Verify the SSE response has
Content-Type: text/event-streamand is UTF-8
Step 5: Check hosting platform limits
| Platform | Default SSE Timeout | Notes |
|---|---|---|
| Vercel (Serverless) | 30s (Hobby), 60s (Pro) | Use Edge Runtime or Intelligence mode |
| Vercel (Edge) | 30s | Better but still limited |
| Railway | 5 min | Usually sufficient |
| Render | 5 min | Usually sufficient |
| Self-hosted | No limit | Depends on reverse proxy config |
For long agent runs, consider:
- Intelligence mode (persisted threads, WebSocket updates)
- Increasing the platform timeout if possible
- Breaking the agent work into smaller runs
Workflow: "Frontend Tool Not Working"
A frontend tool registered with useFrontendTool is not being called or not returning results.
Step 1: Verify tool registration
Check that the tool is registered before the agent runs:
useFrontendTool({
name: "get_weather", // Must match exactly what the agent calls
description: "Get weather",
parameters: z.object({ city: z.string() }),
execute: async ({ city }) => {
/* ... */
},
});
Step 2: Check the SSE stream for tool events
Look for ToolCallStartEvent in the SSE stream:
- Not present -> The agent decided not to call the tool. Check the tool description.
- Present but no
ToolCallResultEvent-> The frontend did not respond. Check:- Is the component with
useFrontendToolmounted? - Did the
executehandler throw? (Checktool_handler_failederror) - Is the tool name an exact match (case-sensitive)?
- Is the component with
Step 3: Check tool argument parsing
If tool_argument_parse_failed error appears:
- The LLM generated arguments that do not match the Zod/JSON schema
- Check
ToolCallArgsEventfor the raw arguments - Consider relaxing the schema or improving parameter descriptions
Step 4: Check HITL tool flow
For renderAndWaitForResponse tools:
- The tool renders UI and waits for user input
- If the tool does not execute after user confirmation, check issue #3442
- The
runIdmay change after HITL resolve (issue #3456)
Workflow: "Transcription Not Working"
Voice input fails or produces errors.
Step 1: Check transcription service configuration
const runtime = new CopilotRuntime({
agents: {
/* ... */
},
transcriptionService: myTranscriptionService, // Must be provided
});
If not configured, the error code is service_not_configured (HTTP 503).
Step 2: Check the /info response
curl http://localhost:3001/api/copilotkit/info | jq '.audioFileTranscriptionEnabled'
Should be true. If false, the transcription service is not configured.
Step 3: Check browser microphone permissions
- The browser must grant microphone access
AudioRecorderError: "Microphone permission denied"-> User denied permissionAudioRecorderError: "No microphone found"-> No microphone hardware detected
Step 4: Check transcription provider credentials
auth_failed-> API key is invalid or expiredrate_limited-> Too many requests, wait and retryprovider_error-> Provider-side issue, check provider status page
Step 5: Check audio format
invalid_audio_format-> Browser sends unsupported formataudio_too_long/audio_too_short-> Recording duration out of bounds
Escalation Path
If the issue is unresolved after following these workflows:
-
Check the CopilotKit GitHub Issues: Search https://github.com/CopilotKit/CopilotKit/issues for your error message or symptom.
-
Enable the Web Inspector: Add
<CopilotKitWebInspector />to capture detailed event traces. -
Collect a diagnostic bundle:
- Package versions (
npm ls @copilotkit/*) - Runtime
/inforesponse - SSE stream capture (copy from Network tab)
- Server-side error logs
- Browser console errors
- Package versions (
-
File a GitHub issue: https://github.com/CopilotKit/CopilotKit/issues/new with the diagnostic bundle.
-
Reach out to the CopilotKit team: Book time with the CopilotKit team via their Discord (https://discord.gg/copilotkit) or contact support for urgent production issues.