Integrate LangChain Code Tool in your LLM apps and 422+ apps and services

Introduction: Streamline your fundamental stock analysis process with AI-powered automation. By harnessing the power of SEC 10K reports - comprehensive documents required by the SEC containing vital company information - this template automates the analysis workflow. From planning by a Senior Research Analyst to execution by five Research Analysts and final review by a Senior Editor, this template takes an AI persona approach to compose the report that includes an overview of the business, strategy, SWOT (Strengths, Weaknesses, Opportunities, and Threads) analysis, near term catalysts, and top risks. Additionally, this template allows you to control the length and detail of the report generated. How it works There are three personas in the workflow: Senior Research Analyst** is the first part of the workflow. They are responsible for planning the work for the rest of the team. Squad of Research Analysts** is the second part of the workflow. They execute the plan created. Senior Editor** is the third part of the workflow. They polish the draft report and send it to publish This template uses a custom tool that is able to answer the SEC 10K questions from the Research team. Setup steps Setup the Stock Q&A Workflow for the company you want to analyze using this template Customize the setup node by specifying the company to analyze Customize the publish step by specifying the file name in the Google docs node Credit Inspired by Guilio's template

Video Guide I prepared a detailed guide that showed the whole process of building a resume analyzer. Who is this for? This workflow is ideal for developers, data analysts, and business owners who want to enable conversational interactions with their database. It’s particularly useful for cases where users need to extract, analyze, or aggregate data without writing SQL queries manually. What problem does this workflow solve? Accessing and analyzing database data often requires SQL expertise or dedicated reports, which can be time-consuming. This workflow empowers users to interact with a database conversationally through an AI-powered agent. It dynamically generates SQL queries based on user requests, streamlining data retrieval and analysis. What this workflow does This workflow integrates OpenAI with a Supabase database, enabling users to interact with their data via an AI agent. The agent can: Retrieve records from the database. Extract and analyze JSON data stored in tables. Provide summaries, aggregations, or specific data points based on user queries. Dynamic SQL Querying: The agent uses user prompts to create and execute SQL queries on the database. Understand JSON Structure: The workflow identifies JSON schema from sample records, enabling the agent to parse and analyze JSON fields effectively. Database Schema Exploration: It provides the agent with tools to retrieve table structures, column details, and relationships for precise query generation. Setup Preparation Create Accounts: N8N: For workflow automation. Supabase: For database hosting and management. OpenAI: For building the conversational AI agent. Configure Database Connection: Set up a PostgreSQL database in Supabase. Use appropriate credentials (username, password, host, and database name) in your workflow. N8N Workflow AI agent with tools: Code Tool: Execute SQL queries based on user input. Database Schema Tool: Retrieve a list of all tables in the database. Use a predefined SQL query to fetch table definitions, including column names, types, and references. Table Definition: Retrieve a list of columns with types for one table.

This n8n workflow is designed to work on the local network and assists with reconciling downloaded bank statements with internal tenant records to quickly highlight any issues with payments such as missed or late payments or those of incorrect amounts. This assistant can then generate a report to quick flag attention to ensure remedial action is taken. How it works The workflow monitors a local network drive to watch for new bank statements that are added. This bank statement is then imported into the n8n workflow, its contents extracted and sent to the AI Agent. The AI Agent analyses the line items to identify the dates and any incoming payments from tenants. The AI agent then uses an locally-hosted Excel ("XLSX") spreadsheet to get both tenant records and property records. From this data, it can determine for each active tenant when payment is due, the amount and the tenancy duration. Comparing to the bank statement, the AI Agent can now report on where tenants have missed their payments, made late payments or are paying the incorrect amounts. The final report is generated and logged in the same XLSX for a human to check and action. Requirements A self-hosted version of n8n is required. OpenAI account for the AI model Customising this workflow If you organisation has a Slack or Teams account, consider sending reports to a channel for increased productivity. Email may be a good choice too. Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/1YRKjfakpInm23F_g8AHupKPBN-fphWgK/view?usp=sharing

This n8n workflow is a fun way to query and search over your credentials on your n8n instance. Good to know Your credentials should remain safe as this workflow does not decrypt or use any decrypted data. Example Usage "Which workflows are using Slack and Google Calendar?" "Which workflows have AI in their name but are not using openAI?" How it works Using the n8n API, it fetches all workflow data on the instance. Workflow data contains references to credentials used so this will be extracted. With some necessary reformatting, the workflows and their credentials metadata are stored to a SQLite database. Next, an AI agent is used with a custom SQL tool that reads the SQLite database created in the previous step. The AI agent is instructed to perform SQL queries against our workflow credential table when asked about credentials by the user. Requirements You'll need an n8n API key. Please note that only workflows will be scoped to your API key. Customising the workflow Add extra table fields to the SQLite database to answer even more complex queries such as: workflow status to differentiate between active and inactive workflows.

This workflow implements a custom tool via JavaScript code which returns a random color to users and excludes the given colors. Note that to use this template, you need to be on n8n version 1.19.4 or later.

Time Logging on Clockify Using Slack How it works This workflow simplifies time tracking for teams and agencies by integrating Slack with Clockify. It enables users to log, update, or delete time entries directly within Slack, leveraging an AI-powered assistant for seamless and conversational interactions. Key features include: Effortless Time Logging**: Create and manage time entries in Clockify without leaving Slack. AI-Powered Assistant**: Get step-by-step guidance to ensure accurate and efficient time logging. Project and Client Management**: Retrieve project and client information from Clockify effortlessly. Overlap Prevention**: Avoid overlapping entries with built-in time validation. Automated Descriptions**: Generate ethical, grammatically correct descriptions for time logs. Set up steps 1. Prepare your integrations Ensure you have active accounts for both Slack and Clockify. Generate your Clockify API credentials for integration. 2. Import the workflow Download and import the workflow template into your n8n instance. Configure the workflow to connect with your Slack and Clockify accounts. 3. Configure the workflow Add your Clockify API credentials in the workflow settings. Set up the Slack Trigger to listen for app mentions or specific commands. 4. Test the workflow Use Slack to create a time entry and verify it in Clockify. Test updating and deleting existing entries to ensure smooth functionality. Check for any overlapping time logs or incorrect data entries. Why use this workflow? Efficiency**: Eliminate the need to switch between tools for time tracking. Accuracy**: AI-driven validation ensures error-free entries. Automation**: Simplify repetitive tasks like updating or deleting time logs. Proactive Guidance**: Conversational assistant ensures smooth operations.