Quality score 85Athreadplane.ai#coding #design #no-code #productivity #video #writing

Threadplane

Threadplane is an open-source tool for Angular developers to build chat interfaces for AI agents, with streaming, tool calls, and agent-built UI.

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About this tool

Threadplane helps Angular developers integrate AI agents into Angular applications. It provides packages like @threadplane/chat and @threadplane/langgraph, supporting streaming responses, tool call rendering, and agent-built UI (A2UI). Developers can configure agents via provideAgent({ url: 'http://localhost:8000/agent' }) and embed chat interfaces using components such as <chat [agent]="agent" [views]="analyticsViews" />. Threadplane supports deploying LangGraph agents via CLI (langgraph deploy --project my-agent) or the LangSmith UI. It targets enterprise scenarios including compliance, analytics, and customer support.

Use cases

- providers: [provideAgent({ url: 'http://localhost:8000/agent' })], + import { provideAgent } from '@threadplane/langgraph'
--> <chat [agent]="agent" [views]="analyticsViews" /> Field report The last-mile gap in Angular AI
--push # Deploy via CLI (alternative to the LangSmith UI) pip install langgraph-cli langgraph deploy --project my-agent The CLI watches your repository and builds a container image on LangGraph Cloud
', }, { label: 'How agents pick tools', value: 'Show me how an agent decides which tool to use
', description: 'Agent emits a render spec
', description: 'Explains tool-selection reasoning
', description: 'Watch tokens arrive incrementally — the simplest @threadplane/chat integration
" ) async def generate(state: MessagesState) -> dict: reply = await llm

Features & use cases

- providers: [provideAgent({ url: 'http://localhost:8000/agent' })], + import { provideAgent } from '@threadplane/langgraph'--> <chat [agent]="agent" [views]="analyticsViews" /> Field report The last-mile gap in Angular AI--push # Deploy via CLI (alternative to the LangSmith UI) pip install langgraph-cli langgraph deploy --project my-agent The CLI watches your repository and builds a container image on LangGraph Cloud', }, { label: 'How agents pick tools', value: 'Show me how an agent decides which tool to use', description: 'Agent emits a render spec', description: 'Explains tool-selection reasoning', description: 'Watch tokens arrive incrementally — the simplest @threadplane/chat integration" ) async def generate(state: MessagesState) -> dict: reply = await llm" A2UI A2UI is a wire protocol for agent-built interfaces" return {"refund_id": refund_id, "messages": [AIMessage(content=msg)]} def route_after_approval(state: RefundState) -> str: return "issue" if state""" llm = ChatOpenAI(model="gpt-5-mini", streaming=True) async def generate(state: MessagesState) -> dict: """Generate a response using the full message history""" llm = ChatOpenAI(model="gpt-5-mini", streaming=True) async def generate(state: MessagesState) -> dict: """Generate a response with conversation history preserved

Quick facts

Public API available

Self-hosting supported

At a glance

Monetization

Freemium

Maturity signals

Open source
Public API

Learning curve

Medium

Pricing

Free

Pricing verified Oct 17, 2026Official pricing page

Sources

Every profile keeps its sources and latest verification date.

01https://threadplane.ai/solutions/analyticsProduct page

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