AI SDK Software-Defined Controls Code Generator with DeepSeek R1
Transitioning control engineering from proprietary ladder logic to software-defined controls demands automated IEC 61131-3 refactoring. Build a streaming code conversion agent using Vercel AI SDK and DeepSeek R1 to transform legacy PLC routines into modular control services. The generator must achieve 90% zero-shot unit test pass rate.
What you are building
The core problem, expected build, and operating context for this challenge.
Utilize Vercel AI SDK with DeepSeek R1 reasoning capabilities to refactor legacy PLC Ladder Logic into executable, object-oriented IEC 61131-3 Structured Text.
How work is evaluated
Evaluates code conversion precision, AST syntax validity, and functional equivalence of refactored control code.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
syntax_validity
Ensures output structured text compiles with zero syntax errors
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
unit_test_pass_rate
Percentage of zero-shot functional simulation unit tests passed • target: 0.9 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Build a streaming TypeScript agent using Vercel AI SDK (`ai` package)
Leverage DeepSeek R1 reasoning tokens for complex industrial control logic refactoring
Convert legacy PLC Ladder Logic (Rung/RLL) to IEC 61131-3 Structured Text (ST) and C++
Validate code generation using strict syntax AST checkers and unit test harnesses
Reference links and supporting material
Legacy PLC ladder logic rungs and corresponding verified IEC 61131-3 Structured Text standard reference pairs.
Challenge setup
Evaluates code conversion precision, AST syntax validity, and functional equivalence of refactored control code.
Challenge input
JSON containing ladder_logic_rung (string) and I/O variable bindings
AI SDK
Assigned framework for Vercel AI SDK streaming integration.
DeepSeek R1
Assigned model for complex code refactoring logic.
Evaluated output
JSON containing structured_text (string), syntax_valid (bool), unit_tests_passed (bool)
- Ensures output structured text compiles with zero syntax errors
- Percentage of zero-shot functional simulation unit tests passed • target: 0.9 • range: 0-1
- Benchmark: PLC Code Refactoring Benchmark
- Unit Test Pass Rate target: 90%
- 1 public reference case
- JavaScript execution harness
- javascript sandbox (unavailable on Versalist)
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
- DeepSeek · Required
- Vercel AI SDK · Optional
- DeepSeek R1 · Optional
- Vercel AI SDK · Optional
Evaluation contract
- syntax_validity · Weight 1
- unit_test_pass_rate · Weight 1
Metrics
- unit_test_pass_rate · Target 0.9
Benchmarks
- PLC Code Refactoring Benchmark
- robotics
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing ladder_logic_rung (string) and I/O variable bindings
Output: JSON containing structured_text (string), syntax_valid (bool), unit_tests_passed (bool)
Execution harness: JavaScript
Evaluation tools
- AI SDK · Agent Framework
- DeepSeek R1 · Reasoning Model
Recipe freeze marker
No recipe freeze time is recorded.