Process Multiple Prompts in Parallel with Anthropic Claude Batch API

Workflow Name

Process Multiple Prompts in Parallel with Anthropic Claude Batch API

Key Features and Highlights

This workflow enables batch submission of multiple prompt requests to the Anthropic Claude model, automatically polling for processing status and ultimately retrieving all results in bulk. It supports parallel handling of multiple conversations or queries in a single run, significantly improving the efficiency and automation level of batch requests. The workflow includes built-in mechanisms for request data construction, response parsing, and example usage combined with Chat Memory, allowing users flexible invocation.

Core Problems Addressed

• Traditional sequential requests to large language models are time-consuming and inefficient;
• The need to send multiple prompts in batch while uniformly managing request statuses and results;
• Complex processes for constructing request payloads and parsing responses;
• Flexible matching and filtering between requests and responses.

By leveraging Anthropic API’s batch processing interface, this workflow enables one-click submission of multiple requests with automatic polling for results, effectively solving the complexity and response management challenges in batch calls.

Application Scenarios

• Customer service systems requiring simultaneous intelligent responses to multiple user questions or conversations;
• Multi-task processing such as batch text generation, summarization, and tagging;
• Automated workflows for batch data analysis and natural language processing;
• Comparative testing of multiple models or API versions;
• Any automation scenario demanding efficient invocation of the Anthropic Claude batch API.

Main Process Steps

1. Trigger Execution: Initiated via the “Execute Workflow Trigger” node, receiving an array of batch requests and the Anthropic API version number.
2. Construct Batch Request: Build request payloads conforming to the Anthropic batch API format, integrating Chat Memory or single query data.
3. Submit Batch Request: Call the Anthropic batch API endpoint to submit multiple prompt requests.
4. Poll Status: Periodically poll the batch task status to determine completion.
5. Retrieve Results: Upon completion, call the result URL endpoint to obtain batch response data.
6. Parse Response: Split and parse JSONL-formatted data into structured results.
7. Filter and Output Results: Filter results by custom IDs for convenient subsequent use.
8. Example Demonstration: Includes built-in examples showcasing data population and result display based on Chat Memory and single queries.

Involved Systems or Services

• Anthropic Claude API: Core batch messaging interface with parameterized version control.
• n8n Nodes:
  • HTTP Request: for submitting requests, polling status, and fetching results.
  • Code: for request payload construction and response parsing.
  • Wait: to implement polling intervals.
  • Set, Filter, Merge, and other data processing nodes.
  • Langchain Memory Manager: for managing conversational history data.
• Execution Trigger: Supports invocation by other workflows or manual triggering.

Target Users and Value

• AI developers and automation engineers requiring efficient batch calls to the Anthropic Claude API;
• Enterprises or teams handling large volumes of natural language tasks, such as customer service, content generation, and data analysis;
• Technical personnel aiming to simplify batch request management and improve API call efficiency;
• Application developers seeking to combine conversational memory with batch calls for complex dialogue scenarios.

This workflow greatly simplifies the complexity of batch calling the Anthropic Claude API, enhancing automation and response efficiency. It is a powerful tool for building efficient intelligent dialogue and text processing systems.