Langchain: Fix For No Retry On Schema Validation Error
Introduction
In this article, we'll dive deep into a peculiar issue encountered while using Langchain for structured output: the absence of retries when schema validation errors occur. Specifically, we will address the problem where, despite the documentation suggesting otherwise, Langchain fails to retry when it encounters a schema validation error during structured output parsing. This can lead to unexpected failures and a less robust application. We'll explore the code snippet that triggers this issue, the error messages, and possible reasons why the retry mechanism isn't working as expected. By the end of this article, you'll have a clearer understanding of the problem and potential workarounds to ensure your Langchain applications handle schema validation errors more gracefully.
Problem Description
The core issue at hand is that Langchain's structured output functionality, which is designed to automatically retry when it encounters schema validation errors, does not do so in practice. This behavior contradicts the official documentation, leading to confusion and potential instability in applications that rely on this retry mechanism. When a schema validation error occurs—for example, if the output doesn't conform to the expected data types or constraints defined in the schema—the process should ideally retry, giving the language model another chance to produce valid output. However, the system throws an error instead of retrying, interrupting the workflow.
Example
Consider a scenario where you're using Langchain to extract structured data from a text. You define a schema that specifies the format and data types of the expected output. When the language model generates output that violates this schema (e.g., providing a rating outside the acceptable range), Langchain should ideally recognize this and prompt the model to try again. But instead, it halts with a StructuredOutputParsingError.
Code and Error
To illustrate this issue, let's consider a simple example using Langchain. The code sets up an agent to parse a product review and extract the rating and comment. The rating is defined as a number between 1 and 5, according to a Zod schema. However, when the agent encounters a rating outside this range, it fails without retrying.
import * as z from "zod";
import { createAgent, toolStrategy } from "langchain";
const ProductRating = z.object({
rating: z.number().min(1).max(5).describe("Rating from 1-5"),
comment: z.string().describe("Review comment"),
});
const agent = createAgent({
model: "gpt-4o-mini",
tools: [],
responseFormat: toolStrategy(ProductRating),
});
const result = await agent.invoke({
messages: [
{
role: "user",
content: "Parse this: Amazing product, 10/10!",
},
],
});
console.log(result);
Error Message
When running this code, you might encounter the following error:
StructuredOutputParsingError: Failed to parse structured output for tool 'extract-1':
- Property "rating" does not match schema.
- 10 is greater than 5..
at ToolStrategy.parse (/path/to/node_modules/.pnpm/langchain@1.0.4_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-trace-base@_gtabb5tinvnwav4xuadixtxyjq/node_modules/langchain/src/agents/responses.ts:135:13)
at #handleSingleStructuredOutput (/path/to/node_modules/.pnpm/langchain@1.0.4_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-trace-base@_gtabb5tinvnwav4xuadixtxyjq/node_modules/langchain/src/agents/nodes/AgentNode.ts:567:39)
at baseHandler (/path/to/node_modules/.pnpm/langchain@1.0.4_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-trace-base@_gtabb5tinvnwav4xuadixtxyjq/node_modules/langchain/src/agents/nodes/AgentNode.ts:341:19)
at process.processTicksAndRejections (node:internal/process/task_queues:105:5)
at async AgentNode.#run (/path/to/node_modules/.pnpm/langchain@1.0.4_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-trace-base@_gtabb5tinvnwav4xuadixtxyjq/node_modules/langchain/src/agents/nodes/AgentNode.ts:204:22)
at async AgentNode.invoke (/path/to/node_modules/.pnpm/langchain@1.0.4_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-trace-base@_gtabb5tinvnwav4xuadixtxyjq/node_modules/langchain/src/agents/RunnableCallable.ts:71:25)
at async RunnableSequence.invoke (/path/to/node_modules/.pnpm/@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-trace-base@2.0.1_@opentelem_k6l6kiomtc3ix24ihmqpmryu6y/node_modules/@langchain/core/src/runnables/base.ts:1904:25)
at async _runWithRetry (/path/to/node_modules/.pnpm/@langchain+langgraph@1.0.2_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-_5ofik5i35uy3f3toh2xfqvt7yq/node_modules/@langchain/langgraph/src/pregel/retry.ts:103:16)
at async PregelRunner._executeTasksWithRetry (/path/to/node_modules/.pnpm/@langchain+langgraph@1.0.2_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-_5ofik5i35uy3f3toh2xfqvt7yq/node_modules/@langchain/langgraph/src/pregel/runner.ts:330:27)
at async PregelRunner.tick (/path/to/node_modules/.pnpm/@langchain+langgraph@1.0.2_@langchain+core@1.0.5_@opentelemetry+api@1.9.0_@opentelemetry+sdk-_5ofik5i35uy3f3toh2xfqvt7yq/node_modules/@langchain/langgraph/src/pregel/runner.ts:138:37) {
toolName: 'extract-1',
errors: [
'Property "rating" does not match schema.',
'10 is greater than 5.'
],
pregelTaskId: '1610d4bc-303e-508c-b648-ce09979c4003'
}
Analysis of the Error
The error message StructuredOutputParsingError clearly indicates that the output from the language model does not conform to the defined schema. Specifically, the rating property failed validation because the provided value (10) exceeds the maximum allowed value of 5. According to the documentation, Langchain should automatically retry in such cases, prompting the language model to correct its output. However, the error halts the process, suggesting that the retry mechanism is not functioning as expected.
Possible Causes and Solutions
There are several reasons why Langchain might not be retrying on schema validation errors, and addressing them involves understanding the underlying mechanisms and configurations.
1. Configuration Issues
One potential cause is incorrect or incomplete configuration of the agent or chain. Ensure that the retry parameters are properly set up. Langchain's retry mechanism often relies on specific configurations that dictate how many times to retry, under what conditions, and with what backoff strategy. Verify that these settings are correctly defined in your agent or chain setup.
2. Bug in Langchain Version
It's also possible that there is a bug in the specific version of Langchain you are using. Software libraries can have unforeseen issues, and a bug in the retry logic could prevent it from functioning correctly. Check the Langchain's issue tracker on GitHub to see if others have reported similar problems. If so, consider updating to a newer version or applying a patch if available.
3. Error Handling Overrides
Custom error handling might be interfering with the default retry behavior. If you've implemented custom error handlers or middleware, they might be catching the StructuredOutputParsingError and preventing it from propagating to the retry mechanism. Review your error handling code to ensure it doesn't inadvertently block the retry process.
4. Model Limitations
In some cases, the language model itself might be the issue. Certain models may not respond well to retry requests, or they might consistently produce output that violates the schema. Experiment with different language models to see if the problem persists. Simpler models or those specifically fine-tuned for structured output might yield better results.
5. Schema Complexity
A highly complex schema can sometimes confuse the language model, leading to frequent validation errors. Simplify your schema if possible, breaking it down into smaller, more manageable parts. This can reduce the likelihood of errors and improve the overall reliability of the structured output parsing.
Workarounds
If the automatic retry mechanism is not working, you can implement manual retry logic in your code. This involves catching the StructuredOutputParsingError and re-invoking the agent with the same input. Here’s an example of how you might implement this:
async function invokeAgentWithRetry(agent: any, input: any, maxRetries: number = 3) {
let retries = 0;
while (retries < maxRetries) {
try {
const result = await agent.invoke(input);
return result;
} catch (error) {
if (error instanceof StructuredOutputParsingError) {
console.log(`Retry attempt ${retries + 1} failed with schema validation error:`, error.message);
retries++;
} else {
throw error; // Re-throw if it's not a StructuredOutputParsingError
}
}
}
throw new Error(`Failed to get valid output after ${maxRetries} retries.`);
}
// Usage
invokeAgentWithRetry(agent, { messages: [{ role: "user", content: "Parse this: Amazing product, 10/10!" }] })
.then(result => console.log(result))
.catch(error => console.error("Failed to get valid output:", error));
This code defines an invokeAgentWithRetry function that takes the agent, input, and a maximum number of retries as parameters. It repeatedly invokes the agent, catching StructuredOutputParsingError exceptions. If a schema validation error occurs, it logs the error and retries until the maximum number of retries is reached. If the agent fails to produce valid output after all retries, it throws an error.
Conclusion
The issue of Langchain not retrying on schema validation errors can be a significant obstacle in building robust applications. By understanding the potential causes—such as configuration issues, bugs in Langchain, error handling overrides, model limitations, and schema complexity—you can take steps to mitigate the problem. Implementing manual retry logic is a practical workaround that ensures your application can gracefully handle schema validation errors and continue processing. Always keep your Langchain version up to date and monitor the community for any reported issues and solutions. For more information on Langchain and its capabilities, visit the Langchain Official Documentation.
