Topic
LangChain Debugging & Observability
14 posts on langchain debugging & observability — part of developer tools on the n4n AI blog.
Why your LangChain retriever returns irrelevant chunks
Why your LangChain retriever returns irrelevant chunks: a practical analysis of chunking, embedding mismatch, and missing observability, with fixes.
Tracing token usage across a LangChain pipeline
End-to-end guide to trace token usage langchain pipeline with custom callbacks, runnable code, and verification across chained LLM calls.
Setting up LangSmith tracing for LangChain apps
Step-by-step guide to langsmith tracing langchain setup: configure env vars, instrument chains, inspect runs, and debug LLM apps in production.
LangChain vs LlamaIndex for observability tooling
A practitioner's head-to-head comparison of LangChain and LlamaIndex for LLM observability: capabilities, cost, latency, ergonomics, and verdict.
Instrumenting LangChain with OpenTelemetry
Step-by-step langchain opentelemetry instrumentation tutorial: add OTLP tracing to LangChain apps, capture token metrics, and debug pipelines.
Debugging tool-calling loops that never terminate
Practical steps to diagnose and fix a LangChain agent that infinitely calls tools, with code to enforce stop conditions and verify termination.
Debugging slow LangChain chains step by step
A practical step-by-step guide to profiling and fixing latency in LangChain apps: trace calls, find bottlenecks, cache, batch, and verify gains.
Debugging silent failures in LangChain agent loops
Diagnose silent failures langchain agent loop with tracing, error boundaries, iteration caps, and output validation. Step-by-step fixes for LangChain agents.
Debugging LangChain memory objects losing state
Step-by-step debugging guide to fix LangChain memory objects losing state across conversations, with runnable code to inspect, persist, and verify chat history.
Debugging LangChain chains with verbose mode
Learn how to use LangChain verbose mode debugging to trace chain execution, inspect prompts, and fix failures with step-by-step code examples.
Debugging LangChain callback handler errors
Step-by-step guide to diagnosing and fixing LangChain callback handler error exceptions in production pipelines, with runnable code and verification.
Common LangChain error messages and what they mean
Decode the most common LangChain error messages, from authentication failures to output parsing issues, and learn actionable fixes for production.
Building a custom LangChain callback for cost tracking
Learn how to build a LangChain custom callback for cost tracking to attribute token spend per chain or user, with runnable Python code and pricing tables.
Adding structured logging to LangChain agents
Practical how-to for adding structured logging langchain agents: use LangChain callbacks, JSON lines, correlation IDs, and gateway metering to observe.
More topics in developer tools
- CI/CD Pipelines for LLM Apps15
- LLM Evaluation Frameworks15
- Cost Optimization & Model Routing14
- Debugging Hallucinations & Output Quality14
- LLM Observability Platforms14
- Migrating Between LLM Providers14
- Model Deprecation & Version Migration14
- RAG Pipeline Observability14
- Regression Testing for Prompts14
- Compliance & Audit Logging for Regulated Industries13
- CrewAI & AutoGen Multi-Agent Debugging13
- Guardrails & Content Moderation Testing13