Update README.md

README.md

@@ -1,32 +1,296 @@
----
-license: mit
-dataset_info:
-  features:
-  - name: title
-    dtype: large_string
-  - name: source
-    dtype: large_string
-  - name: url
-    dtype: large_string
-  - name: category
-    dtype: large_string
-  - name: language
-    dtype: large_string
-  - name: content
-    dtype: large_string
-  - name: chunk_id
-    dtype: int64
-  - name: last_updated
-    dtype: large_string
-  splits:
-  - name: train
-    num_bytes: 976709227
-    num_examples: 784505
-  download_size: 497571067
-  dataset_size: 976709227
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+---
+license: mit
+dataset_info:
+  features:
+  - name: title
+    dtype: large_string
+  - name: source
+    dtype: large_string
+  - name: url
+    dtype: large_string
+  - name: category
+    dtype: large_string
+  - name: language
+    dtype: large_string
+  - name: content
+    dtype: large_string
+  - name: chunk_id
+    dtype: int64
+  - name: last_updated
+    dtype: large_string
+  splits:
+  - name: train
+    num_bytes: 976709227
+    num_examples: 784505
+  download_size: 497571067
+  dataset_size: 976709227
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+---
+
+
+# Dev Knowledge Base (Programming Documentation Dataset)
+
+A large-scale, structured dataset of programming documentation collected from official sources across languages, frameworks, tools, and AI ecosystems.
+
+Do Follow me on Github: https://github.com/nuhmanpk
+
+---
+
+## Overview
+
+This dataset contains cleaned and structured documentation content scraped from official developer docs across multiple domains such as:
+
+* Programming languages
+* Frameworks (frontend, backend)
+* DevOps & infrastructure tools
+* Databases
+* Machine learning & AI libraries
+
+All content is chunked (~800 characters) and optimized for:
+
+* Retrieval-Augmented Generation (RAG)
+* Developer copilots
+* Code assistants
+* Semantic search
+
+---
+
+## Dataset Structure
+
+Each row represents a chunk of documentation.
+
+| Column       | Description                                |
+| ------------ | ------------------------------------------ |
+| title        | Page title or endpoint                     |
+| source       | Source name (e.g., react, python, fastapi) |
+| url          | Original documentation URL                 |
+| category     | Type (language, framework, database, etc.) |
+| language     | Programming language                       |
+| content      | Cleaned text chunk                         |
+| chunk_id     | Chunk index within page                    |
+| chunk_length | Character length                           |
+| last_updated | Timestamp                                  |
+
+---
+
+## Sources Included
+
+### Languages
+
+python, javascript, typescript, go, rust, java, csharp, dart, swift, kotlin
+
+### Frontend & Frameworks
+
+react, nextjs, vue, nuxt, svelte, sveltekit, angular, astro, qwik, solidjs
+
+### Backend & APIs
+
+fastapi, django, flask, express, nestjs, hono, elysia
+
+### Runtime & Tooling
+
+nodejs, deno, bun, vite, webpack, turborepo, nx, pnpm, biome
+
+### UI Libraries
+
+tailwind, shadcn_ui, chakra_ui, mui
+
+### Mobile & Desktop
+
+react_native, expo, flutter, tauri, electron
+
+### Machine Learning & AI
+
+numpy, pandas, pytorch, tensorflow, scikit_learn, xgboost, lightgbm
+transformers, langchain, llamaindex, openai, vllm, ollama, haystack
+mastra, pydantic_ai, langfuse, mcp
+
+### Databases
+
+postgresql, mysql, sqlite, mongodb, redis, supabase, firebase
+planetscale, neon, convex, drizzle_orm, qdrant, turso
+
+### DevOps & Infrastructure
+
+docker, kubernetes, terraform, ansible
+github_actions, gitlab_ci, git, opentelemetry, inngest, temporal
+
+### Other
+
+claude_agent_sdk
+
+Full crawl configuration available here: 
+
+---
+
+## Chunk Distribution
+
+Example distribution after cleaning and removing Zig:
+
+| Source       | Chunks   |
+| ------------ | -------- |
+| python       | ~15,000  |
+| javascript   | ~4,000   |
+| go           | ~8,000   |
+| react        | ~3,000   |
+| nextjs       | ~4,000   |
+| docker       | ~4,000   |
+| kubernetes   | ~14,000  |
+| transformers | ~14,000  |
+| firebase     | ~300,000 |
+| redis        | ~17,000  |
+| git          | ~14,000  |
+| flutter      | ~14,000  |
+| supabase     | ~10,000  |
+
+Total: **millions of chunks across 80+ sources**
+
+---
+
+## How to Use (Hugging Face)
+
+### Install
+
+```bash
+pip install datasets
+```
+
+### Load Dataset
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("nuhmanpk/dev-knowledge-base")
+
+print(dataset["train"][0])
+```
+
+---
+
+## Example Use Cases
+
+### 1. Semantic Search
+
+```python
+from sentence_transformers import SentenceTransformer
+import numpy as np
+
+model = SentenceTransformer("all-MiniLM-L6-v2")
+
+docs = [x["content"] for x in dataset["train"][:1000]]
+embeddings = model.encode(docs)
+
+query = "how to build api with fastapi"
+q_emb = model.encode([query])
+
+scores = np.dot(embeddings, q_emb.T).squeeze()
+print(docs[scores.argmax()])
+```
+
+---
+
+### 2. RAG Pipeline
+
+```text
+User Query → Embed → Vector DB → Retrieve → LLM → Answer
+```
+
+Use with:
+
+* FAISS
+* Qdrant
+* Pinecone
+
+---
+
+### 3. Fine-tuning
+
+Convert to instruction format:
+
+```json
+{
+  "instruction": "Explain JWT authentication",
+  "input": "",
+  "output": "<documentation chunk>"
+}
+```
+
+---
+
+### 4. Developer Chatbot
+
+Build:
+
+* AI coding assistant
+* StackOverflow-style search
+* Internal dev knowledge system
+
+---
+
+## Data Processing Pipeline
+
+* Async crawling with rate limiting
+* HTML parsing (BeautifulSoup)
+* Navigation/content filtering
+* Chunking (~800 chars)
+* Cleaning & binary removal
+
+Crawler implementation: 
+
+---
+
+## Limitations
+
+* Some duplicate content may exist
+* Chunk-level context only (not full pages)
+* No semantic labeling yet
+* Some sources larger than others
+
+---
+
+## Future Improvements
+
+* Deduplication
+* Better chunking (semantic splitting)
+* Q/A generation
+* Code extraction
+* Metadata enrichment
+
+---
+
+## License
+
+This dataset is built from publicly available documentation.
+Refer to individual sources for licensing.
+
+---
+
+## Author
+
+https://github.com/nuhmanpk
+
+---
+
+## Quick Example
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("nuhmanpk/dev-knowledge-base")
+
+for row in ds["train"].select(range(3)):
+    print(row["source"], "→", row["content"][:150])
+```
+
+---
+
+## Summary
+
+A large, structured, and practical dataset for building developer-focused AI systems from code assistants to full RAG pipelines.
+
+---
+