The batch tool

Key Concepts: Managing Parallel Tool Use with LLMs

The Challenge of Parallel Tool Calls

• Ideal Scenario: A single LLM assistant message can contain multiple tool use blocks, allowing operations to run in parallel (e. g. , calculating two separate sums).
• Practical Difficulty: In practice, LLMs often fail to generate multiple tool use blocks in one response, even when the task is clearly parallel.
• The Goal: To reliably force the LLM to consolidate multiple parallel tasks into a single, predictable tool call.

The Batch Tool Solution

• Concept: Implement a custom "batch tool" as a wrapper around multiple other tools.
• Mechanism: Instead of asking the LLM to call Tool A and Tool B separately, the developer tricks the LLM into calling the single batch tool.
• Batch Tool Input: The input to the batch tool is a list of objects. Each object describes a single, underlying tool invocation (containing the tool's name and its arguments).

Implementation Steps (Developer Side)

• Define Schema: Create a schema for the batch tool that accepts a list of tool invocations.
• LLM Decision: When the LLM decides multiple tools are needed, it calls the batch tool, providing the list of required invocations.
• Implement run_batch Function:
• This function receives the list of invocations from the LLM.
• It iterates through the list.
• For each invocation, it parses the arguments (which are provided as JSON strings).
• It executes the requested underlying tool (e. g. , set_reminder).
• It collects the results from all executed tools and returns them as a single response.

Summary of the Trick

• The batch tool acts as a higher-level abstraction.
• The developer manually handles the parallel execution of the tools, effectively bypassing the LLM's tendency to generate multiple tool use blocks.

Takeaways

• LLMs often fail to generate multiple parallel tool use blocks in a single response, making reliable parallel execution difficult.
• The solution is to implement a custom "batch tool" that acts as a wrapper for multiple underlying tools.
• The LLM is prompted to call the single batch tool, providing a list of required tool invocations (name and arguments).
• The developer's run_batch function receives this list, executes the underlying tools, and returns all results as one consolidated response.