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Challenge

Build an Automated Biopython FASTA Cleanser and Langfuse Telemetry Monitor

Process multi-fasta uploads to detect contaminated reads, low complexity regions, and non-IUPAC bases. Track preprocessing latency and data drift using Langfuse operational telemetry.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Process multi-fasta uploads to detect contaminated reads, low complexity regions, and non-IUPAC bases. Track preprocessing latency and data drift using Langfuse operational telemetry.

Bioinformatics Pipeline Engineer

Stream FASTA records through Biopython SeqIO sequence parser.

Validate nucleotide characters against IUPAC standards and strip terminal adapter contamination.

Record pipeline latency, input sizes, and rejection rates into Langfuse traces.

Save sanitized sequences into an archive ready for downstream research pipelines.

Dashboard displaying processing metrics, invalid sequence alerts, and export options.

Generate synthetic multi-FASTA files with injected IUPAC anomalies, adapter dimers, and valid nucleotides. Starter examples below are synthetic. They are not downloaded records.

Biopython Uses Biopython's sequence parsing and alphabet validation facilities to inspect nucleotide strings.

langfuse, biopython, fastapi. Langfuse enables detailed operational trace tracking, error monitoring, and step-level latency visualization. Lightweight model for generating human-readable sequence error categorization prompts.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Accurately flags non-standard IUPAC characters in raw sequences.

Emits traces to Langfuse containing token count, character counts, and step latencies.

Provides clean sanitized FASTA outputs for valid records.

```json [ { "input": { "batch_id": "BATCH-01", "records": [ { "id": "read1", "seq": "ATCGGCTA" } ] }, "expected_output": { "batch_id": "BATCH-01", "passed_records": 1, "failed_records": 0, "langfuse_trace_logged": true } }, { "input": { "batch_id": "BATCH-02", "records": [ { "id": "read2", "seq": "ATC123Z$$" } ] }, "expected_output": { "batch_id": "BATCH-02", "passed_records": 0, "failed_records": 1, "error_reasons": [ "Invalid non-IUPAC characters" ], "langfuse_trace_logged": true } } ] ```

Standard pre-processing tool for FASTA files; completely devoid of protected health information. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Standard pre-processing tool for FASTA files; completely devoid of protected health information. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Accurately flags non-standard IUPAC characters in raw sequences. Emits traces to Langfuse containing token count, character counts, and step latencies. Provides clean sanitized FASTA outputs for valid records.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Stream FASTA records through Biopython SeqIO sequence parser. Validate nucleotide characters against IUPAC standards and strip terminal adapter contamination. Record pipeline latency, input sizes, and rejection rates into Langfuse traces. Save sanitized sequences into an archive ready for downstream research pipelines.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Accurately flags non-standard IUPAC characters in raw sequences. Emits traces to Langfuse containing token count, character counts, and step latencies. Provides clean sanitized FASTA outputs for valid records.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Dashboard displaying processing metrics, invalid sequence alerts, and export options.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Standard pre-processing tool for FASTA files; completely devoid of protected health information.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Stream FASTA records through Biopython SeqIO sequence parser.

  • Validate nucleotide characters against IUPAC standards and strip terminal adapter contamination.

  • Record pipeline latency, input sizes, and rejection rates into Langfuse traces.

  • Save sanitized sequences into an archive ready for downstream research pipelines.

Resources and assets

Reference links and supporting material

Dataset notes

Generate synthetic multi-FASTA files with injected IUPAC anomalies, adapter dimers, and valid nucleotides. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Langfuse

Open-source LLM observability and evals.

Evaluated output

No output checks are configured.

Evaluation checks
  • Stream FASTA records through Biopython SeqIO sequence parser. Validate nucleotide characters against IUPAC...
  • Accurately flags non-standard IUPAC characters in raw sequences. Emits traces to Langfuse containing token...
  • Dashboard displaying processing metrics, invalid sequence alerts, and export options.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 2 configured tools

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Observation
  • Langfuse · Optional
Reward / Eval
  • Langfuse · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build an Automated Biopython FASTA Cleanser and Langfuse Telemetry Monitor