Simple Memory workflows
185 results — all source-linked n8n references
Run AI employee onboarding with Groq, Google Workspace, and Gemini
Quick overview This workflow ingests onboarding documents from Google Drive into an in-memory vector store with Google Gemini embeddings, then runs a multi-channel onboarding chatbot powered by Groq, sends role-based welcome emails via Gmail when a new hire appears in Google Sheets, and schedules day 1/7/30 check-in emails. How it works Manually runs an ingestion flow that lists files in a specified Google Drive folder, downloads them, extracts text, and indexes them into an in-memory vector store using Google Gemini embeddings. Receives employee questions via n8n Chat (and optionally Slack or Telegram), normalizes the message into a single format, and rejects empty or overly long inputs. Uses a Groq LLM agent with per-user session memory to retrieve relevant excerpts from the in-memory company_docs knowledge base and generate a grounded answer, or directs the user to HR when no relevant content is found. Routes the assistant’s response back to the originating channel (n8n Chat, and optionally Slack or Telegram). Triggers every minute on updates to a Google Sheets “Hires” sheet, validates rows marked as Hired, and skips hires already present in the “Tracking” sheet. Builds a depart
Chat with Google Docs and Sheets using a Claude AI agent
Quick Overview This workflow opens an n8n chat interface where an AI agent powered by Anthropic Claude answers questions by reading a connected Google Doc and/or Google Sheet on demand, using short-term conversation memory for follow-up questions. How it works Receives a user question through n8n’s built-in chat trigger. Uses an AI agent powered by Anthropic Claude to decide whether it needs to consult Google Docs, Google Sheets, or both. Reads the full text of the configured Google Doc when the question is about document content. Fetches rows from the configured Google Sheet tab when the question is about spreadsheet data. Answers in the chat based only on the retrieved Doc/Sheet content (or states the information isn’t present), while keeping the last 10 messages in memory for contextual follow-ups. Setup Add credentials for Anthropic (Claude), Google Docs, and Google Sheets. Replace YOUR_GOOGLE_DOC_ID_OR_URL with your target Google Doc URL or ID. Set the Google Sheet document ID and choose the tab (sheet name) to read in the Google Sheets tool. Confirm the connected Google account has access to both the Doc and the Sheet, then open the workflow chat and start asking questions.
Run a Telegram voice assistant with OpenAI GPT-5 Mini and Google Calendar
Quick overview This workflow turns a Telegram bot into a personal assistant that accepts text or voice notes, transcribes audio with OpenAI, uses a memory-enabled AI agent for replies and calculations, and creates Google Calendar reminder events from natural-language requests. How it works Triggers whenever a new Telegram message is received by your bot. Routes the message based on type, sending text directly to the assistant, voice notes to transcription, and other message types to a fallback reply. For voice notes, downloads the audio from Telegram and transcribes it to text using OpenAI. Sends the user’s text (typed or transcribed) to an OpenAI chat model powered agent that remembers the last 15 messages per chat and can use a calculator tool. When the user asks for a reminder or event, the agent creates a Google Calendar event with AI-generated title and start/end times. Sends the agent’s final response back to the originating Telegram chat. Setup Create a Telegram bot with @BotFather, add a Telegram credential in n8n, and enable updates for the Telegram Trigger. Add an OpenAI credential with access to the chat model and audio transcription used in the workflow. Add a Google Ca
Handle WhatsApp support text and voice messages with OpenAI GPT-5 Mini
Quick overview This workflow responds to incoming WhatsApp Business messages, handling both text and voice notes by transcribing audio with OpenAI and replying with an OpenAI chat agent that uses per-contact conversation memory and answers only from the business information you provide. How it works Triggers when a new WhatsApp message is received. Routes the incoming message by type, sending text messages directly to the support flow, audio messages to a voice-transcription flow, and other message types to a fallback reply. For voice notes, retrieves the WhatsApp media URL, downloads the audio file, and transcribes it to text with OpenAI. Sends the customer’s text (original or transcribed) to an OpenAI chat agent configured to answer only using your provided business information. Stores and reuses a per-contact conversation history keyed by the sender’s WhatsApp number to maintain context across messages. Sends the agent’s response back to the customer as a WhatsApp text message. Setup Connect WhatsApp Business Cloud credentials for both receiving messages (trigger) and sending replies, and ensure your WhatsApp webhook is configured to point to the trigger URL. Add OpenAI credenti
Answer customer questions on WhatsApp with OpenAI, Gmail, and Google Sheets
Quick overview This workflow answers incoming WhatsApp customer questions using an OpenAI-powered agent that reads your live website via HTTP requests, escalates unclear or sensitive cases to your support team via Gmail, and logs each conversation to Google Sheets. How it works Triggers when a new WhatsApp message is received. Loads configuration values (company name, website root URL, AI model, language rules, escalation email, and WhatsApp phone number ID) and extracts the customer phone number and message text. Ignores non-text WhatsApp updates (such as images, audio, and status messages). Uses OpenAI with conversation memory to navigate your website by listing links and fetching relevant pages, then generates a structured result containing an answer, escalation flag, sentiment, topic, and source URLs. If the agent marks the request as needing a human, sends an escalation email via Gmail to your support address with the customer details and the drafted reply. Sends the final plain-text reply back to the customer on WhatsApp. Appends the conversation details to a Google Sheets log. Setup Connect credentials for WhatsApp Trigger/WhatsApp Cloud API, OpenAI, Gmail, and Google Sheets
Run a personal assistant for calendar, Gmail and utilities with OpenAI and MCP
Quick overview This workflow runs a chat-based OpenAI assistant in n8n that calls three MCP servers for Google Calendar management, Gmail search and draft replies, and utility tools for weather, currency conversion, and calculations. How it works Receives a chat message in n8n to start or continue a conversation. Loads the assistant configuration (model, memory window, and system prompt) and sends the user message to an OpenAI chat model with short-term conversation memory. When the assistant needs calendar actions, it calls an MCP server that searches, creates, updates, or deletes Google Calendar events. When the assistant needs email actions, it calls an MCP server that searches Gmail messages and creates draft replies for user review. When the assistant needs quick utilities, it calls an MCP server that fetches weather from wttr.in, converts currency using frankfurter.app, or runs calculations. Returns the assistant’s response back to the chat, including any results from the MCP tool calls. Setup Add credentials for OpenAI, Google Calendar (OAuth2), and Gmail (OAuth2) in n8n. Activate the workflow, then copy each MCP Server Trigger Production URL for the Calendar, Gmail, and Uti
Run a multimodal WhatsApp AI assistant with OpenAI for text, voice and images
Quick overview This workflow turns WhatsApp into a multimodal assistant that answers text, voice notes, images, and PDF documents using OpenAI, and can generate images with DALL·E on demand, replying back in WhatsApp with either text, audio, or an image. How it works Triggers when a new WhatsApp message is received. Detects whether the incoming message is text, a voice note, an image, a PDF document, or an unsupported type. For text messages, generates an image with OpenAI DALL·E when the message starts with the configured /image command, and sends the generated image back to the sender. For voice notes, fetches the WhatsApp media URL, downloads the audio, transcribes it with OpenAI, and forwards the transcript to the assistant. For images, fetches the WhatsApp media URL, downloads the image, describes it with OpenAI vision using the configured analysis prompt, and forwards the description (plus any caption) to the assistant. For PDF documents, downloads the file from WhatsApp, extracts the PDF text, and forwards the extracted content (plus any caption) to the assistant, while non-PDF files receive an error message. Uses an OpenAI chat model with per-contact short-term memory to ge
Handle WhatsApp customer service chats with Google Gemini and Google Sheets
Quick Overview This workflow handles WhatsApp customer service via OpenWA, using Google Gemini and a Google Sheets knowledge base to answer personal chats, while routing conversations to a human queue in Google Sheets when escalation is needed. How it works Triggers on OpenWA WhatsApp events and ignores message reactions except for specific ✅/☑ reactions used to re-enable AI handling. Normalizes incoming event fields and processes only personal chats (IDs ending with @c.us) that are not sent by your own WhatsApp account. Checks a Google Sheets “Session Chat” list to decide whether the conversation is currently handled by a human, and only continues to AI when no active human session is found. Uses a Google Gemini chat model with short-term memory and a Google Sheets “Database Company” tool to draft a friendly Indonesian response based only on the sheet data. If the AI response does not contain the #admin escalation token, it sends the reply back to the customer via OpenWA. If the AI response contains #admin, it appends the chat to the Google Sheets “Session Chat” sheet to flag it for human follow-up. When a ✅/☑ reaction is received for a chat, it finds and deletes the corresponding
Handle WhatsApp sales inquiries with OpenAI, Pinecone, Google Calendar, and Slack
Quick overview This workflow handles inbound WhatsApp Business messages with an OpenAI-powered sales agent that uses Pinecone RAG for product answers and Google Calendar tools for scheduling, then either replies on WhatsApp or hands the conversation to Slack, with Slack-based error alerts. How it works Triggers on every inbound WhatsApp Business message and checks whether the payload contains a text body. Drops non-text messages (such as images or voice notes) and continues only with text conversations. Uses an OpenAI chat model with per-customer session memory to generate a concise sales reply and decide whether a human handoff is needed. Lets the agent query a Pinecone-backed product catalog via OpenAI embeddings to answer pricing, specs, and availability questions. Lets the agent check availability and book appointments in Google Calendar when the customer requests scheduling. Parses the agent’s HANDOFF flag and either posts the customer message plus draft reply to a Slack channel or sends the reply back to the customer on WhatsApp. Sends a Slack alert to an ops channel if any step in the workflow fails. Setup Connect WhatsApp Business Cloud credentials and set the WhatsApp Phon
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Summarize Zoom meetings and create follow-ups with OpenAI, ClickUp, and Outlook
Quick overview This workflow pulls the transcript and participant list from a recent Zoom meeting, uses OpenAI to generate formal meeting minutes, emails the summary via SMTP, and runs an AI agent that creates ClickUp tasks and (when details exist) schedules a follow-up meeting in Microsoft Outlook Calendar. How it works Starts when you manually run the workflow. Fetches your scheduled Zoom meetings and keeps only those that started within the last 24 hours. Requests the meeting recording files from Zoom, stops with an error if no transcript is available, then extracts the transcript download URL. Downloads the Zoom transcript file, extracts its text, and reformats it into clean, readable dialogue. Pulls the Zoom meeting participant list (including emails) and sends the transcript and participants to OpenAI to generate structured meeting minutes. Formats the minutes into an HTML email and sends the summary via SMTP to a participant email address. Uses an OpenAI-powered agent to extract action items and follow-up details from the same transcript, then creates tasks in ClickUp and creates a follow-up event in Microsoft Outlook Calendar when scheduling information is present. Setup Ad
SRun a voice-enabled AI assistant on Telegram with OpenAI, Gmail and Notion
Quick overview This workflow turns a Telegram bot into a personal assistant that handles text and voice messages using OpenAI, can read Gmail and Google Calendar, looks up tasks and contacts in Notion, and can draft and send emails with a required approval step in Telegram. How it works Triggers when a new Telegram message is received by your bot. Detects whether the message is a voice note or text, and if it is voice, downloads it from Telegram and transcribes it with OpenAI. Sends the resulting user text to an OpenAI-powered agent that keeps a short conversation memory per chat. When needed, the agent fetches recent emails from Gmail, lists upcoming events from Google Calendar, and pulls tasks or contacts from Notion to answer the request. If the agent decides to send an email, it asks for approval in Telegram and only proceeds after you approve within the time limit. Sends the assistant’s final response back to the same Telegram chat. Setup Create a Telegram bot with @BotFather, add the Telegram credentials in n8n, and use the workflow’s Telegram trigger to connect the bot. Add an OpenAI API credential for both chat responses and voice transcription, and set your preferred model
WHandle WhatsApp support chats with OpenRouter, Pinecone, and Gemini
Quick overview This template implements a WhatsApp support suite that logs inbound events to a dashboard API, routes conversations through an OpenRouter-powered AI agent with Pinecone RAG and memory, exposes a webhook for human outbound replies, and provides a webhook to summarize recent chats for handoff. How it works Triggers on WhatsApp Cloud API events and routes status updates (sent/delivered/read) to a dashboard API endpoint for storage. For inbound messages, looks up the contact in the dashboard API and normalizes the message into a consistent schema (sender, type, timestamp, and best-effort content). If the message contains media (image/video/audio/document), fetches the WhatsApp media URL, downloads the file, uploads it to the dashboard’s media endpoint, and attaches the resulting media URL and MIME type. Stores inbound messages and reactions in the dashboard API, then checks via the cases endpoint whether the sender already has an open case. If the inbound message is text and no open case is found, queries Pinecone as a tool (using Google Gemini embeddings), uses an OpenRouter chat model with conversation memory to draft a reply or create a new case via the dashboard API,
SRun a Telegram voice and chat assistant with OpenAI, Gmail, Calendar, and Notion
Quick overview This workflow turns a Telegram bot into a personal assistant that understands text or voice notes (transcribed with OpenAI), can read Gmail and Google Calendar, look up Notion tasks and contacts, and can draft and send emails with an approval step in Telegram. How it works Triggers when a new Telegram message arrives. Loads assistant settings (name, OpenAI model, languages, memory window) and checks whether the message is a voice note or plain text. If it is a voice note, downloads the audio from Telegram and transcribes it with OpenAI; otherwise it uses the message text as the user input. Sends the user input to an OpenAI-powered agent that keeps short-term chat memory and decides whether to call Gmail, Google Calendar, or Notion tools to answer the request. If the agent decides to send an email via Gmail, it asks for explicit approval in Telegram before proceeding. Sends the agent’s final response back to the user in Telegram. Setup Create a Telegram bot with @BotFather, add your Telegram credentials in n8n, and start a chat with the bot so it can reply to you. Add an OpenAI API credential and set the desired chat model and transcription language in the Configurati
Route WhatsApp support requests with Claude, Supabase, HubSpot and Slack
Quick overview This workflow turns incoming WhatsApp messages (text, audio, images, and documents) into actionable support interactions by extracting content, detecting sentiment, and using an AI agent with a Supabase knowledge base to route requests to Google Calendar, HubSpot, Slack, Gmail, and back to WhatsApp. How it works Receives incoming WhatsApp messages via a WhatsApp webhook trigger. Routes the message by type and converts it into text using OpenAI Whisper for audio, OpenAI GPT-4o Vision for images, or a PDF extractor for documents (or passes text messages through). Loads the sender’s session context from Supabase and runs sentiment/language detection on the extracted text. Uses a LangChain AI agent (Claude) with Supabase vector search (with OpenAI embeddings and Cohere reranking) plus tool access (Google Calendar, HubSpot, Slack, and Gmail) to produce a structured intent, response, and metadata. Logs conversation analytics (intent, sentiment, message type, and response length) to an n8n Data Table. Routes by intent to either create a Google Calendar event, create/update a HubSpot contact, email a document via Gmail (and upload it to Google Drive), create a HubSpot ticket
Answer support FAQs with Google Gemini, Supabase, Google Sheets and WhatsApp
Quick overview This workflow ingests FAQs from Google Sheets into a Supabase vector table using Google Gemini embeddings, then serves a webhook-based support chatbot that answers only from that FAQ knowledge base and escalates unanswered questions to a human via UltraMsg WhatsApp. How it works Runs manually to pull FAQ rows (Question/Answer) from a Google Sheets spreadsheet. Formats each row into a single text document (for example, Q: … A: …), generates embeddings with Google Gemini, and inserts the documents into a Supabase vector store table. Receives incoming chat messages via a POST webhook that includes message and sessionId. Uses a Google Gemini chat model with session-based memory to query the Supabase vector store for the most relevant FAQ matches and generates a reply strictly from the retrieved content. If the agent output indicates escalation to a human, sends the full message content to UltraMsg via an HTTP request to alert a WhatsApp number. Returns a JSON response to the webhook caller with either the FAQ-based answer or a confirmation that a human agent has been notified. Setup Add credentials for Google Gemini (PaLM) API, Supabase, and Google Sheets OAuth2. In Supa
Coach fitness and nutrition on Telegram with Claude, Google Sheets and Calendar
Quick overview This workflow turns a Telegram bot into a fitness and nutrition coach powered by Anthropic Claude, with voice-note transcription via OpenAI, user data stored in Google Sheets, and optional workout scheduling in Google Calendar. How it works Triggers when a new Telegram message arrives in your bot chat. If the message is a voice note, it downloads the audio from Telegram and transcribes it with OpenAI. Normalizes the incoming text or transcript into common fields (message, chat ID, and current date). Uses an Anthropic Claude agent with session memory to interpret the request and generate a coaching response. When needed, the agent reads and updates the user profile, logs workouts, logs meals with estimated macros, and reads/saves weekly plans in Google Sheets. When the user asks to schedule training, it creates a workout event in Google Calendar. Sends the coach’s reply back to the user in Telegram. Setup Add Telegram bot credentials (BotFather token) for receiving messages, downloading voice notes, and sending replies. Add an OpenAI API credential for audio transcription and an Anthropic credential for the Claude chat model. Add Google Sheets OAuth2 credentials and s
CDHandle LinkedIn inbox RAG replies with Unipile, Claude, Pinecone, and Airtable
Quick overview Automatically ingest your knowledge base, monitor your LinkedIn company page inbox, and reply to leads and customers with AI-drafted, source-grounded answers. Classifies every message, checks for spam, drafts replies using Claude and Pinecone RAG, and lets you auto-send or review each reply in Airtable. How it works A Google Drive trigger watches a folder for new or updated documents, downloading each file automatically as it's added. Each document is split into chunks, embedded, and upserted into a Pinecone vector index, building a searchable company knowledge base. A webhook receives every new LinkedIn message sent to your company page via Unipile, filtering out messages you sent yourself. The last few messages in the conversation are fetched and formatted into a chronological transcript for context. An AI agent classifies the message's intent (lead, support, partnership, recruiting, spam, or other) using shared conversation memory. A second AI agent drafts a reply, searching the Pinecone knowledge base for relevant facts before answering, and saves the draft to Airtable. Depending on a configurable auto-send toggle, the reply is sent immediately via Unipile, or he
Triage network read and commit requests with Slack, Anthropic, and pyATS
Quick overview This Slack ChatOps workflow uses AI agents and a pyATS MCP server to handle day-to-day data network housekeeping tasks: from on-demand checks and validations per device, to configuration change proposals that require human approval before commit. Read the docs here: https://cs.co/9004BEMGZm How it works A network engineer mentions the Slack bot in a channel or thread. The workflow acknowledges the request and captures the full message The request is sent to a Planning Agent connected to pyATS through read-only MCP tools. The agent determines whether the user wants operational data or a configuration change, gathers live device evidence if needed, and evaluates whether the request is safe. If the request is operational only, or if the proposed change is unsafe, the workflow replies in the same Slack thread with a clear technical summary, including the relevant device findings or the reason why no change will be made. If the request is a safe configuration change, the workflow creates one approval card per target device. Each card shows the proposed change, the pre-check evidence collected from the device, and the safety rationale so the engineer can review exactly wha
Vet community membership applications with Google Gemini, Telegram, and Sheets
Quick overview This workflow collects community membership applications via an n8n Form, vets each candidate with Google Gemini using Tavily web search and an Apify LinkedIn lookup, requests human approval in Telegram when needed, sends invite or rejection emails via Gmail, and logs outcomes to Google Sheets. How it works Receives a submission from an n8n Form that captures applicant details such as name, email, company, role, birthday, and additional notes. Normalizes the submitted fields and passes the candidate profile to a Google Gemini-powered AI Agent that can use Tavily web search, an Apify LinkedIn search actor, a calculator, and short-term memory. Produces a structured vetting result (including summary, decision status, and a community-fit score) using a structured output schema. If the AI decision is “Immediate approval”, sends the candidate summary to Telegram and waits for a response before continuing. If the AI decision is not “Immediate approval”, sends the summary to Telegram and asks the reviewer to reply with 1 (approve), 2 (reject), or 3 (do nothing). Sends an approval/invite email or a rejection email via Gmail based on the Telegram response, or stops without act
Run Bunker Guard NPC chat and RAG lore checks with Google Gemini and Google Drive
Quick overview This workflow powers dynamic character interactions for investigative games. It ingests lore from Google Drive into a vector database, using Google Gemini agents to generate daily briefings, spawn NPCs, and roleplay interrogations via a webhook. How it works Runs on a manual trigger to download a lore PDF from Google Drive, split it into chunks, create Google Gemini embeddings, and store them in an in-memory vector store for retrieval. Receives a POST webhook request from the game client containing game state and an action value (briefing, init, or chat). Routes the request based on action to either generate a morale-based daily intel briefing, create a new NPC profile for the day, or generate an in-character reply to the player’s interrogation message. When factual lore is needed (routes, locations, prices, rules, professions), the Gemini agent queries the Database_Bunker vector-search tool to ground the response in the ingested PDF. Maintains short conversation context per player using a buffer memory keyed by playerId for ongoing chat and NPC interactions. Returns the agent output to the caller as clean JSON via the webhook response. Optionally, triggers on an n8n
WRun a Telegram productivity assistant with OpenRouter, Google Calendar, and Todoist
Quick overview This workflow turns Telegram into a personal assistant that manages your Google Calendar and Todoist, sends daily briefings, and alerts you when meetings are booked or things break. How it works Morning briefing - Every day at a set time, the workflow checks your Google Calendar for today's events and your Todoist for open tasks, then sends you two Telegram messages: a calendar rundown and a task summary grouped by project with priority flags. Cal.com booking alerts - When someone books, reschedules, or cancels a call on Cal.com, or a meeting ends, the workflow catches the webhook and sends you a Telegram notification with the attendee's name, email, meeting title, and time. Talk to your assistant on Telegram - Message the bot with text or a voice note. Voice notes get transcribed automatically. Your message goes to an AI agent that can read, create, update, or delete calendar events, and create, find, update, complete, or delete Todoist tasks, all through natural conversation. The agent replies back in the same chat. Error alerts - If any part of the workflow fails, you get a Telegram message with the failed node, the error, and a link to the execution, so you catch
BAnswer HR policy and benefits questions with BambooHR, OpenAI and Supabase
Quick Overview This workflow ingests company policy PDFs from BambooHR into a Supabase vector database and provides an employee chat interface that answers policy and benefits questions using OpenAI, with an additional employee/department lookup powered by BambooHR employee data. How it works Starts a manual run to fetch files from BambooHR and keep only PDFs in the “Company Files” category. Downloads each selected PDF, splits it into chunks, generates OpenAI embeddings, and inserts the content into a Supabase vector table for retrieval. Exposes a chat trigger where employees submit questions to an HR assistant. Uses OpenAI with conversation memory and retrieves relevant policy content from the Supabase vector store to ground responses. When a question requires a contact person, looks up employee details in BambooHR by exact name or finds the most senior person in a requested department using an OpenAI-assisted department extraction and ranking step. Returns the final answer to the chat, including policy-based guidance and any retrieved employee contact details. Setup Add BambooHR credentials and ensure your policies/benefits PDFs are available in the BambooHR file category named “
Generate English–Polish vocabulary quizzes with Google Sheets and Groq
Quick overview Tool useful for any language exams. It is a chat-based workflow that uses Google Sheets in Structure English|your language that using free Groq model (Llama 3.3) generate lists of 10 words that you need to provide answer based on your while model helps How it works Receives a chat message as the trigger input. Checks whether the message contains the word “generate” to decide if it should create a new quiz set or continue the current session. When “generate” is included, reads vocabulary rows (English and your language columns) from a specified Google Sheets range. Randomly shuffles the rows, selects 10 pairs, and formats them as a clean list of {english, your-language} objects. Sends the user message and the selected word pairs to a Groq Llama 3.3 chat model that runs the quiz conversation. Uses a buffer memory window to keep recent chat context so the agent can track which words are answered and which still need guesses. Setup Connect Google Sheets OAuth credentials and set the correct spreadsheet URL, sheet name, and range that contains “English word” and “your language words” columns. Add Groq API credentials and confirm the selected model (llama-3.3-70b-versatile
CScrape Tunisia IT job listings with Groq, Firecrawl, Airtable, and Resend
Quick overview This workflow runs daily or via chat to scrape Tunisia-focused IT job listings from predefined company career pages using Firecrawl, saves results into Airtable tables, and emails a daily digest through Resend, with job parsing and orchestration handled by a Groq-powered AI agent. How it works Triggers either on a daily 7AM schedule or when an n8n Chat message is received. On scheduled runs, rotates through a fixed list of companies, builds a prompt for the chosen company (including pagination rules), and sets the Airtable table name. Uses a Groq (Llama 3.3 70B) AI agent to decide which allowed career-page URLs to scrape and how to extract job listings into structured fields. Scrapes the requested career pages via the Firecrawl API and parses the returned main content into jobs with title, company, location, description, and URL. When saving is requested, uses Airtable’s API to check for the target table, create it if missing, and insert the job records. For scheduled runs, emails the AI-generated job digest to the configured recipient using the Resend API; otherwise it outputs the response for the chat session. Setup Add credentials and values for Firecrawl (API key