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OAuth2 settings finder with OpenRouter chat model and Llama 3.3

HendriekusHendriekus
523 views
2/3/2026
Daily DigestSlackSales ReportingShopifyE-commerce
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Find OAuth URIs with AI Llama

Overview: The AI agent identifies:

  • Authorization URI
  • Token URI
  • Audience

Methodology: Confidence scoring is utilized to assess the trustworthiness of extracted data:

  • Score Range: 0 < x ≤ 1
  • Score Granularity: 0.01 increments

Model Details: Leveraging the Wayfarer Large 70b Llama 3.3 model.

How it works:

This template is designed to assist users in obtaining OAuth2 settings using AI-powered insights. It is ideal for developers, IT professionals, or anyone working with APIs that require OAuth2 authentication. By leveraging the AI agent, users can simplify the process of extracting and validating key details such as the authorization_url, token_url, and audience.

Set up instructions:

1. Configuration Nodes

  • Structured Output Node: Parses the AI model's output using a predefined JSON schema. This ensures the data is structured for downstream processing.
  • Code Node: If the AI model’s output does not match the required format, use the Code node to re-arrange and transform the data. Example code snippets are provided below for common scenarios.

2. AI Model Prompt

The prompt for the AI model includes:

  • A detailed structure and objectives of the query.
  • Flexibility for the model to improvise when accurate results cannot be determined.

3. Confidence Scoring

The AI model assigns a confidence score (0 < x ≤ 1) to indicate the reliability of the extracted data. Scores are provided in increments of 0.01 for granularity.

Adaptability

Customize this template:

  • Update the AI model prompt with details specific to your API or OAuth2 setup.
  • Adjust the JSON schema in the Structured Output node to match the data format.
  • Modify the Code logic to suit the application's requirements.

n8n Workflow: OpenRouter OAuth2 Settings Finder with Llama 3

This n8n workflow leverages the power of Large Language Models (LLMs) via OpenRouter to dynamically identify and extract OAuth2 settings from provided text. It's designed to assist developers and integrators in quickly pinpointing the necessary OAuth2 configuration details within documentation or API responses.

What it does

This workflow automates the process of finding OAuth2 settings by:

  1. Receiving Input: It's triggered by an external workflow, expecting a text input that potentially contains OAuth2 configuration details.
  2. Preparing the Prompt: A "Code" node dynamically constructs a prompt for the LLM, instructing it to act as an expert in OAuth2 and extract specific settings (like authorization_url, token_url, scope, client_id, client_secret, redirect_uri, grant_type, and resource). It also specifies that the output should be in JSON format.
  3. LLM Processing (OpenRouter): The prepared prompt is sent to an OpenRouter Chat Model. The workflow is configured to use the llama-3-8b-chat model, which processes the input text and attempts to identify the requested OAuth2 settings.
  4. Structured Output Parsing: A "Structured Output Parser" node is used to ensure the LLM's response is correctly formatted as JSON, making it easy to consume in subsequent steps.
  5. Returning Results: The extracted OAuth2 settings, formatted as JSON, are returned as the output of the workflow.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • OpenRouter Account and API Key: An account with OpenRouter (https://openrouter.ai/) and a corresponding API key configured as an n8n credential.
  • Langchain Nodes: Ensure the @n8n/n8n-nodes-langchain package is installed in your n8n instance.

Setup/Usage

  1. Import the Workflow:
    • Copy the provided JSON code.
    • In your n8n instance, go to "Workflows".
    • Click "New" -> "Import from JSON".
    • Paste the JSON code and click "Import".
  2. Configure OpenRouter Credentials:
    • Locate the "OpenRouter Chat Model" node (ID: 1281).
    • Click on the "Credentials" field and select "Create New".
    • Choose "OpenRouter API" as the credential type.
    • Enter your OpenRouter API Key.
    • Save the credentials.
  3. Test the Workflow:
    • This workflow is designed to be executed by another workflow. To test it manually, you can simulate input for the "When Executed by Another Workflow" trigger.
    • For example, you could create a simple "Start" node in a new workflow, followed by an "Execute Workflow" node that calls this workflow. Pass a sample text containing OAuth2 details (e.g., from an API documentation page) into the "Execute Workflow" node's input.
    • Execute the workflow to see the extracted OAuth2 settings.

This workflow provides a powerful tool for automating the extraction of critical configuration details, saving time and reducing manual errors in integration projects.

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