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Anthropic AI Agent: Claude Sonnet 4 and Opus 4 with Think and Web Search tool

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Created by: Davide || n3witalia

Davide

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Last update a month ago

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This workflow dynamically chooses between two new powerful Anthropic models — Claude Opus 4 and Claude Sonnet 4 — to handle user queries, based on their complexity and nature, maintaining scalability and context awareness with Anthropic web search function and Think tool.

Key Advantages

  1. 🔁 Dynamic Model Selection

    • Automatically routes each user query to either Claude Sonnet 4 (for routine tasks) or Claude Opus 4 (for complex reasoning), ensuring optimal performance and cost-efficiency.

  2. 🧠 AI Agent with Tool Use

    • The AI agent can utilize a web search tool to retrieve up-to-date information and a Think tool for complex reasoning processes — improving response quality.

  3. 📎 Memory Integration

    • Uses session-based memory to maintain conversational context, making interactions more coherent and human-like.

  4. 🧮 Built-in Calculation Tool

    • Handles numeric queries using an integrated calculator tool, reducing the need for external processing.

  5. 📤 Structured Output Parser

    • Ensures outputs are always well-structured and formatted in JSON, which improves consistency and downstream integrations.

  6. 🌐 Web Search Capability

    • Supports real-time information retrieval for current events, statistics, or details not available in the AI’s base knowledge.

Components Overview

  • Trigger: Listens for new chat messages.

  • Routing Agent: Analyzes the message and returns the best model to use.

  • AI Agent: Handles the conversation, decides when to use tools.

  • Tools:

    • web_search for internet queries
    • Think for reasoning
    • Calculator for math tasks

  • Models Used:

    • claude-sonnet-4-20250514: Optimized for general and business logic tasks.
    • claude-opus-4-20250514: Best for deep, strategic, and analytical queries.

How It Works

  1. Dynamic Model Selection

    • The workflow begins when a chat message is received. The Anthropic Routing Agent analyzes the user's query to determine the most suitable model (either Claude Sonnet 4 or Claude Opus 4) based on the query's complexity and requirements.
    • The routing agent uses predefined criteria to decide:
      • Claude Sonnet 4: Best for standard tasks like real-time workflow routing, data validation, and routine business logic.
      • Claude Opus 4: Reserved for complex scenarios requiring deep reasoning, advanced analysis, or high-impact decisions.

  2. Query Processing and Response Generation

    • The selected model processes the query, leveraging tools like web_search for real-time information retrieval, Think for internal reasoning, and Calculator for numerical tasks.
    • The AI Agent coordinates these tools, ensuring the response is accurate and context-aware. A Simple Memory node retains session context for coherent multi-turn conversations.
    • The final response is formatted and returned to the user without intermediate steps or metadata.

Set Up Steps

  1. Node Configuration

    • Trigger: Configure the "When chat message received" node to handle incoming user queries.
    • Routing Agent: Set up the "Anthropic Routing Agent" with the system message defining model selection logic. Ensure it outputs a JSON object with prompt and model fields.
    • AI Model Nodes: Link the "Sonnet 4 or Opus 4" node to dynamically use the selected model. The "Sonnet 3.7" node powers the routing agent itself.

  2. Tool Integration

    • Attach the "web_search" HTTP tool to enable internet searches, ensuring the API endpoint and headers (e.g., anthropic-version) are correctly configured.
    • Connect auxiliary tools (Think, Calculator) to the "AI Agent" for extended functionality.
    • Add the "Simple Memory" node to maintain conversation history.

  3. Credentials

    • Provide an Anthropic API key to all nodes requiring authentication (e.g., model nodes, web search).

  4. Testing

    • Activate the workflow and test with sample queries to verify:
      • Correct model selection (e.g., Sonnet for simple queries, Opus for complex ones).
      • Proper tool usage (e.g., web searches trigger when needed).
      • Memory retention across chat turns.

  5. Deployment

    • Once validated, set the workflow to active for live interactions.

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