How danish-m-qureshi/my-backup-advanced-predictive-analytics works
BirdCLEF+ 2026 is an autonomous research agent that uses a local LLM to generate and run bird-audio model experiments, compare results, and export a Kaggle submission. Its main loop is orchestrated across prompt/context assembly, code validation and sandbox execution, metric capture, and iterative analysis; fixed audio/data components and a model catalog support generated training code. The dashboard provides monitoring and controls. Some edges reflect the README’s documented architecture because the relevant implementation excerpts were not provided.
Main entry points: orchestrator.py Experiment Orchestrator · context_handler.py Prompt Context · app.py Dashboard Routes · executor.py Sandbox Executor
Components 21
Experiment Agent
- Experiment Orchestrator
agent/orchestrator.py - Prompt Context
agent/context_handler.py - Prompt Templates
agent/prompt_engine.py - Code Validation
agent/handlers/validate_code.py - Sandbox Executor
agent/executor.py - Metric Capture
agent/handlers/capture_metrics.py - Kaggle Export
agent/submission.py
Audio and Models
- Audio Preprocessing
pipelines/audio_pipeline.py - Dataset Profile
pipelines/dataset_profile.py - Training Data Loader
pipelines/data_loader.py - Model Architectures
pipelines/models.py - Model Registry
registry/registry.py
Study Records
- Experiment Memory
agent/memory.py - Study Logs
agent/logger.py - Study Report
agent/report.py
Dashboard
- Dashboard Routes
agent/ui/app.py - Study Browser
agent/ui/loaders.py - Process Controls
agent/ui/process_manager.py
Other components
- Researcher
- Local LLM
- Training Code
Connections 23
- Researcher → Experiment Orchestrator: starts study
README.md - Experiment Orchestrator → Prompt Context: builds prompts
README.md - Prompt Context → Prompt Templates: fills templates
agent/context_handler.py - Prompt Context → Local LLM: sends context
README.md - Experiment Orchestrator → Local LLM: requests generation
README.md - Experiment Orchestrator → Code Validation: validates code
agent/orchestrator.py - Experiment Orchestrator → Sandbox Executor: runs experiment
README.md - Sandbox Executor → Training Code: executes code
README.md - Training Code → Training Data Loader: loads datasets
README.md - Training Code → Model Architectures: uses models
README.md - Experiment Orchestrator → Metric Capture: captures results
README.md - Experiment Orchestrator → Experiment Memory: records experiments
README.md - Experiment Orchestrator → Study Logs: logs tasks
README.md - Experiment Orchestrator → Study Report: generates report
README.md - Experiment Orchestrator → Model Registry: uses catalog
README.md - Prompt Context → Model Registry: adds model details
agent/context_handler.py - Audio Preprocessing → Dataset Profile: profiles dataset
- Training Data Loader → Audio Preprocessing: augments samples
pipelines/data_loader.py - Experiment Orchestrator → Kaggle Export: exports best model
README.md - Researcher → Dashboard Routes: monitors studies
README.md - Dashboard Routes → Study Browser: reads study data
agent/ui/app.py - Dashboard Routes → Process Controls: controls runs
agent/ui/app.py - Dashboard Routes → Kaggle Export: requests export
agent/ui/app.py