Node-Level Observability for LangChain and LangGraph.

LangLens is a lightweight visual tracer and debugger designed specifically for LLM-powered applications. It captures detailed execution logs from your agents and chains, allowing you to inspect every LLM call, tool execution, and state transition with precision.

• 🔍 Interactive Trace Viewer: Explore complex workflows through a rich graphical interface.
• 🧩 Node-Level Granularity: Deep dive into individual chain runs, LLM inputs/outputs, and tool executions.
• 💻 VS Code Extension: Debug your traces directly inside VS Code with a custom editor experience.
• 🚀 CLI Tool: Quickly host a local viewer for any .langlens file.
• 🔌 Seamless Integration: Add observability to your existing projects with a single line of code.

LangLens bridges the gap between your LLM execution and visual debugging:

graph TD
    subgraph "Capture Phase"
    A[LLM App] -- "1. LangChain Callbacks" --> B(LangLens Handler)
    B -- "2. Stream Events" --> C[[.langlens file]]
    end

    subgraph "Visualization Phase"
    C -- "3a. CLI Server" --> D[Web Browser]
    C -- "3b. Custom Editor" --> E[VS Code IDE]

    D --> F{Interactive UI}
    E --> F

    F -- "4. Inspect Nodes" --> G[Observability & Debugging]
    end

1. Capture: The LangLensCallbackHandler hooks into LangChain's event system to record starts, ends, and errors of every chain, tool, and LLM call.
2. Storage: Events are serialized and saved into a .langlens file (JSONL format), providing a portable trace of the entire execution.
3. Visualization:
   • The CLI Tool launches a local Python server that hosts a Svelte-based frontend.
   • The VS Code Extension registers as a custom editor for .langlens files, embedding the same Svelte UI directly into your workspace.
4. Debugging: Use the interactive graph to navigate complex agentic workflows and inspect raw inputs/outputs at any level of the tree.

Install LangLens via pip:

pip install langlens

Install the LangLens Viewer from the VS Code Marketplace.

Add the LangLensCallbackHandler to your LangChain or LangGraph execution config.

from langlens import LangLensCallbackHandler
from langchain_openai import ChatOpenAI

# Initialize the handler (creates a logs.langlens file)
handler = LangLensCallbackHandler(filename="logs.langlens")

# Attach it to your run
llm = ChatOpenAI()
config = {"callbacks": [handler]}
response = llm.invoke("How does a sunrise look from Mars?", config=config)

Run the following command to start a local server and open the viewer in your browser:

langlens visualize logs.langlens

Simply open any .langlens file. The LangLens Viewer will automatically render the interactive trace.

1. Build the Web UI: This bundles the Svelte app and copies assets to the Python and VS Code extension folders.

   ./build_ui.sh

2. Install Python Package (Editable mode):

   pip install -e .

3. VS Code Extension:

   • Open the vscode-extension folder in VS Code.
   • Run pnpm install.
   • Press F5 to start the Extension Development Host.

To build distribution packages manually:

./scripts/package.sh

This project is licensed under the MIT License.