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README.md

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+# DevOps Q&A Dataset Summary
+
+**Generated on:** 2026-01-17
+**Version:** 2.1 Final
+
+## 📊 Overview
+Based on user requirements, we have collected, validated, and deduplicated a high-quality dataset of DevOps Questions & Answers.
+
+| Metric | Value |
+|:--- |:--- |
+| **Total Unique Items** | **7,219** |
+| **Primary Source** | GitHub Repositories (Advanced Search) |
+| **Secondary Source** | Official Documentation (Docker, K8s, etc.) |
+| **Average Quality Score** | ~0.81 |
+| **Deduplication** | Exact (MD5) + Semantic (BGE-Small) |
+
+## 📁 File Manifest
+All files are located in `/opt/Data set/output/`:
+
+*   `devops_dataset.jsonl` - Main dataset (JSON Lines).
+*   `devops_dataset.parquet` - Optimized Parquet format for pandas/polars.
+*   `dataset_metadata.json` - Technical metadata (last run stats).
+
+## 🧩 Data Composition
+The dataset covers a wide range of DevOps topics, including but not limited to:
+*   **Kubernetes:** Troubleshooting, Configs, Best Practices.
+*   **Docker:** Composition, Optimization, Security.
+*   **IaC:** Terraform, Ansible, Pulumi.
+*   **CI/CD:** GitHub Actions, GitLab CI, Jenkins.
+*   **Monitoring:** Prometheus, Grafana, ELK.
+
+## 🚀 Usage Example (Python)
+```python
+import pandas as pd
+
+# Load the dataset
+df = pd.read_parquet('/opt/Data set/output/devops_dataset.parquet')
+
+# Inspect
+print(df.head())
+print(df['source'].value_counts())
+
+# Filter high quality
+high_quality = df[df['quality_score'] > 0.85]
+```
+
+## 🛠 Collection Details
+*   **Tools:** `devops_collector.py` (Custom Python Collector)
+*   **Validation:** Strict quality rules (length, spam, content safety).
+*   **Dedup:** Semantic embedding filtering enabled for new data.