Is this compatible with FastAPI?

Yes, the skill includes specific implementations for FastAPI WebSocket and StreamingResponse (SSE) endpoints.

Does it support external webhooks?

Definitely. It includes a WebhookCallbackHandler designed to POST event data to any external API endpoint automatically during the LLM lifecycle.

Can I use this for monitoring chain performance?

Yes, it includes a TraceAggregator handler that logs start times, end times, and intermediate events to help you analyze execution flow and latency.

How does this skill help with LLM streaming?

It provides specific callback handlers for WebSockets and SSE, allowing you to stream tokens from your LangChain model directly to your frontend as they are generated.

LangChain Webhooks & Events

Name: LangChain Webhooks & Events
Author: Brmbobo

byBrmbobo

0•

API Development

Implements custom callback handlers and real-time event streaming for LangChain applications using webhooks, WebSockets, and SSE.

This skill enables developers to integrate LangChain applications with external systems and real-time interfaces by implementing robust event-driven patterns. It provides pre-configured templates for custom webhook handlers, WebSocket streaming for interactive chat, and Server-Sent Events (SSE) for efficient data delivery. By using these callback handlers, you can monitor LLM starts, completions, errors, and tool usage while aggregating execution traces for enhanced observability and debugging within any LangChain-based workflow.

Key Features

01Chain event aggregation and tracing for debugging and logging

02Real-time WebSocket streaming for low-latency LLM responses

03Comprehensive token and tool usage monitoring

04Custom Webhook Callback Handlers for external system integration

05FastAPI-compatible Server-Sent Events (SSE) implementation

060 GitHub stars

Use Cases

01Triggering external workflows or notifications based on LLM lifecycle events

02Building real-time AI chat interfaces with token-by-token streaming

03Monitoring and auditing chain execution via event-driven tracing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add brmbobo/web2podcast langchain-webhooks-events

For use in Claude.ai and ChatGPT

Key Features

01Chain event aggregation and tracing for debugging and logging

02Real-time WebSocket streaming for low-latency LLM responses

03Comprehensive token and tool usage monitoring

04Custom Webhook Callback Handlers for external system integration

05FastAPI-compatible Server-Sent Events (SSE) implementation

060 GitHub stars

Use Cases

01Triggering external workflows or notifications based on LLM lifecycle events

02Building real-time AI chat interfaces with token-by-token streaming

03Monitoring and auditing chain execution via event-driven tracing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add brmbobo/web2podcast langchain-webhooks-events

For use in Claude.ai and ChatGPT