Langflow Tools & Extensions

Perform basic prompting with an OpenAI model.

Write blog posts from web references using an Agent. URL fetches references, you provide the topic via Chat Input, and the Agent writes a grounded post. Core components only.

Aggregate recent content on a topic: Web Search (News) gathers articles, a Batch Run summarizes each one, and an Agent curates them into a clean digest that is shown and saved to a file.

Describe a Langflow component and an Agent generates its Python code. The Agent fetches Langflow reference code on demand with a URL tool and remembers the conversation with a Memory tool.

Ask a research question and get a thorough, synthesized answer. Three Agents collaborate: a planner, a web researcher (core Web Search), and a synthesizer.

Ask questions about your own document using a built-in Knowledge Base (RAG). File ingests into the KB; an Agent answers from retrieved context. No external vector database required.

Upload a financial report; an Agent extracts key metrics (Gross Profit, EBITDA, Net Income, ...) as structured output. Core components only - the Agent's built-in structured output replaces the Structured Output component; File replaces …

Self-contained hybrid RAG on one canvas: an ingestion branch (File -> Split Text -> Astra DB) to populate the collection, and a search branch (semantic vector + keyword lexical, reranked) where an Agent extracts the lexical keywords.

Upload an image; a vision Language Model classifies its sentiment (positive/negative/neutral) and briefly describes it. The Language Model receives the image natively, so the model actually sees it.

Generate an Instagram caption + image prompt from a topic. A two-Agent chain: a Caption Agent researches the topic with the core Web Search tool (DuckDuckGo, no key) and writes the caption, then an Image Agent appends a matching image pr…

An example of performing a vector search against data in a Knowledge Base to retrieve relevant documents.

Research a company and extract a structured profile (pricing, plans, market, features, target industries).

Transcribe a meeting (custom AssemblyAI Transcriber using the current API), summarize it with a Summary Agent, and chat about it with a Chat Agent grounded in the transcript and backed by Memory.

Create a chatbot that saves and references previous messages, enabling the model to maintain context throughout the conversation.

A three-step chain of specialist Agents (Innovator -> Analyst -> Product Manager) that turns a market trend into a product concept, an evaluation, and a development plan.

Upload a resume and an Agent generates a single-page portfolio website (HTML/CSS).

A Price Deal Finder Agent: searches the web (incl. coupon news), reads listings (URL), computes savings (Calculator) and remembers your watchlist (Memory), returning the best deals as a structured table.

This template iterates over search results using LoopComponent and translates each result into Portuguese automatically. 🚀

Generates targeted SEO keywords based on product information, pain points, and customer profiles for strategic marketing.

Calculate the optimal monthly SaaS subscription price from costs, margin, and subscriber estimate. The Agent uses its built-in calculator and can optionally query the user's own database via a SQL Database tool.

A generic three-step agent pipeline: a Research Agent (Web Search) gathers information, an Analysis Agent analyzes it, and a Writer Agent synthesizes both into a final report. Generalized from the finance-specific original;

A starter Agent with tools: core Web Search (find info) and URL (read a page), plus the Agent's built-in calculator and current-date tools.

A general social-media research Agent: it searches the web (core Web Search) and reads pages (core URL tool) to gather current information, then completes your task. Replaces the Apify google-search and TikTok scraper tools with core tools.

Upload a text file and analyze its sentiment two ways: a direct analysis and a summarize-then-analyze pass.

Three Agents plan a trip: research the destination (core Web Search), draft the itinerary (URL), and budget it (Calculator).

Generate an engaging tweet or Twitter thread from a project brief. An Agent (replacing the Language Model) follows the Prompt's style guidelines as its system prompt and writes from the Chat Input context. Core components only, bundle-free.

Load your data for chat context with Retrieval Augmented Generation.