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92 changes: 91 additions & 1 deletion docs/guides/index.md
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# Tutorials
# Tutorials

Build unlimited training data and train state-of-the-art SWE-agents. This guide covers the complete workflow: from environment setup to model training and evaluation.

---

## 📋 Prerequisites

!!! info "System Requirements"
**Required:** Docker
**Tested on:** Ubuntu 22.04.4 LTS
**Not supported:** Windows, macOS

New to SWE-smith? Start with [Installation](../getting_started/installation.md) and [Quickstart](../getting_started/quickstart.md).

---

## 🎯 Quick Navigation

<div class="grid cards" markdown>

- :material-docker: **Build Environments**

---

Create reproducible Docker images for any repository. Capture dependencies, build containers, and validate with automated testing.

[:octicons-arrow-right-24: Get started](env_construction.md)

- :material-bug: **Create Instances**

---

Generate task instances using LM prompts, procedural modifications, PR mirroring, or combined techniques. Scale to thousands of bugs.

[:octicons-arrow-right-24: Generate bugs](create_instances.md)

- :material-check-circle: **Validate & Evaluate**

---

Filter candidates that break tests and verify proposed solutions. Built-in harnesses for validation and evaluation workflows.

[:octicons-arrow-right-24: Run harnesses](harnesses.md)

- :material-file-document: **Generate Issue Text**

---

Add natural language problem statements to task instances using LM generation or alternative methods.

[:octicons-arrow-right-24: Create issues](issue_gen.md)

- :material-speedometer: **Rate Difficulty** · Optional

---

Classify tasks as easy/medium/hard using a fine-tuned Qwen 2.5 Coder model. Compare against SWE-bench benchmarks.

[:octicons-arrow-right-24: Assess difficulty](difficulty_rating.md)

- :material-school: **Train SWE-agents**

---

Complete RSFT pipeline: generate trajectories, filter successful solutions, fine-tune models, and evaluate on SWE-bench.

[:octicons-arrow-right-24: Start training](train_swe_agent.md)

</div>

---

## Recommended Workflow

```mermaid
graph LR
A[Build Environments] --> B[Create Instances]
B --> C[Validate & Evaluate]
C --> D[Generate Issue Text]
D --> E[Rate Difficulty]
D --> F[Train SWE-agents]
E --> F
```

1. **Build Environments** → Set up Docker images
2. **Create Instances** → Generate synthetic bugs
3. **Validate & Evaluate** → Filter valid task instances
4. **Generate Issue Text** → Add problem descriptions
5. **Rate Difficulty** *(optional)* → Classify task complexity
6. **Train SWE-agents** → Fine-tune models with RSFT
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