feat: Complete Phase 1 - AI Coding Assistant Integrations (v2.10.0)
Add comprehensive integration guides for 4 AI coding assistants: ## New Integration Guides (98KB total) - docs/integrations/WINDSURF.md (20KB) - Windsurf IDE with .windsurfrules - docs/integrations/CLINE.md (25KB) - Cline VS Code extension with MCP - docs/integrations/CONTINUE_DEV.md (28KB) - Continue.dev for any IDE - docs/integrations/INTEGRATIONS.md (25KB) - Comprehensive hub with decision tree ## Working Examples (3 directories, 11 files) - examples/windsurf-fastapi-context/ - FastAPI + Windsurf automation - examples/cline-django-assistant/ - Django + Cline with MCP server - examples/continue-dev-universal/ - HTTP context server for all IDEs ## README.md Updates - Updated tagline: Universal preprocessor for 10+ AI systems - Expanded Supported Integrations table (7 → 10 platforms) - Added 'AI Coding Assistant Integrations' section (60+ lines) - Cross-links to all new guides and examples ## Impact - Week 2 of ACTION_PLAN.md: 4/4 tasks complete (100%) ✅ - Total new documentation: ~3,000 lines - Total new code: ~1,000 lines (automation scripts, servers) - Integration coverage: LangChain, LlamaIndex, Pinecone, Cursor, Windsurf, Cline, Continue.dev, Claude, Gemini, ChatGPT ## Key Features - All guides follow proven 11-section pattern from CURSOR.md - Real-world examples with automation scripts - Multi-IDE consistency (Continue.dev works in VS Code, JetBrains, Vim) - MCP integration for dynamic documentation access - Complete troubleshooting sections with solutions Positions Skill Seekers as universal preprocessor for ANY AI system. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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# Continue.dev + Universal Context Example
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Complete example showing how to use Skill Seekers to create IDE-agnostic context providers for Continue.dev across VS Code, JetBrains, and other IDEs.
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## What This Example Does
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- ✅ Generates framework documentation (Vue.js example)
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- ✅ Creates HTTP context provider server
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- ✅ Works across all IDEs (VS Code, IntelliJ, PyCharm, WebStorm, etc.)
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- ✅ Single configuration, consistent results
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## Quick Start
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### 1. Generate Documentation
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```bash
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# Install Skill Seekers
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pip install skill-seekers[mcp]
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# Generate Vue.js documentation
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skill-seekers scrape --config configs/vue.json
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skill-seekers package output/vue --target markdown
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```
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### 2. Start Context Server
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```bash
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# Use the provided HTTP context server
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python context_server.py
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# Server runs on http://localhost:8765
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# Serves documentation at /docs/{framework}
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```
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### 3. Configure Continue.dev
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Edit `~/.continue/config.json`:
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```json
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{
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"contextProviders": [
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{
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"name": "http",
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"params": {
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"url": "http://localhost:8765/docs/vue",
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"title": "vue-docs",
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"displayTitle": "Vue.js Documentation",
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"description": "Vue.js framework expert knowledge"
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}
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}
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]
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}
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```
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### 4. Test in Any IDE
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**VS Code:**
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```bash
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code my-vue-project/
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# Open Continue panel (Cmd+L)
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# Type: @vue-docs Create a Vue 3 component with Composition API
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```
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**IntelliJ IDEA:**
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```bash
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idea my-vue-project/
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# Open Continue panel (Cmd+L)
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# Type: @vue-docs Create a Vue 3 component with Composition API
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```
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**Result:** IDENTICAL suggestions in both IDEs!
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## Expected Results
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### Before (Without Context Provider)
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**Prompt:** "Create a Vue component"
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**Continue Output:**
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```javascript
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export default {
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name: 'MyComponent',
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data() {
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return {
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message: 'Hello'
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}
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}
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}
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```
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❌ Uses Options API (outdated)
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❌ No TypeScript
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❌ No Composition API
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❌ Generic patterns
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### After (With Context Provider)
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**Prompt:** "@vue-docs Create a Vue component"
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**Continue Output:**
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```typescript
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<script setup lang="ts">
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import { ref, computed } from 'vue'
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interface Props {
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title: string
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count?: number
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}
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const props = withDefaults(defineProps<Props>(), {
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count: 0
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})
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const message = ref('Hello')
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const displayCount = computed(() => props.count * 2)
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</script>
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<template>
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<div>
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<h2>{{ props.title }}</h2>
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<p>{{ message }} - Count: {{ displayCount }}</p>
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</div>
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</template>
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<style scoped>
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/* Component styles */
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</style>
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```
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✅ Composition API with `<script setup>`
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✅ TypeScript interfaces
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✅ Proper props definition
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✅ Vue 3 best practices
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## Files in This Example
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- `context_server.py` - HTTP context provider server (FastAPI)
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- `quickstart.py` - Automation script for setup
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- `requirements.txt` - Python dependencies
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- `config.example.json` - Sample Continue.dev configuration
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## Multi-IDE Testing
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This example demonstrates IDE consistency:
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### Test 1: VS Code
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```bash
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cd examples/continue-dev-universal
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python context_server.py &
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code test-project/
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# In Continue: @vue-docs Create a component
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# Note the exact code generated
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```
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### Test 2: IntelliJ IDEA
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```bash
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# Same server still running
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idea test-project/
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# In Continue: @vue-docs Create a component
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# Code should be IDENTICAL to VS Code
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```
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### Test 3: PyCharm
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```bash
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# Same server still running
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pycharm test-project/
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# In Continue: @vue-docs Create a component
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# Code should be IDENTICAL to both above
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```
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**Why it works:** Continue.dev uses the SAME `~/.continue/config.json` across all IDEs!
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## Context Server Architecture
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The `context_server.py` implements a simple HTTP server:
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```python
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from fastapi import FastAPI
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from skill_seekers.cli.doc_scraper import load_skill
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app = FastAPI()
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@app.get("/docs/{framework}")
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async def get_framework_docs(framework: str):
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"""
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Serve framework documentation as Continue context.
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Args:
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framework: Framework name (vue, react, django, etc.)
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Returns:
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JSON with contextItems array
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"""
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# Load documentation
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docs = load_skill(f"output/{framework}-markdown/SKILL.md")
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return {
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"contextItems": [
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{
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"name": f"{framework.title()} Documentation",
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"description": f"Complete {framework} framework knowledge",
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"content": docs
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}
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]
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}
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```
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## Multi-Framework Support
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Add more frameworks easily:
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```bash
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# Generate React docs
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skill-seekers scrape --config configs/react.json
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skill-seekers package output/react --target markdown
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# Generate Django docs
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skill-seekers scrape --config configs/django.json
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skill-seekers package output/django --target markdown
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# Server automatically serves both at:
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# http://localhost:8765/docs/react
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# http://localhost:8765/docs/django
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```
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Update `~/.continue/config.json`:
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```json
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{
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"contextProviders": [
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{
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"name": "http",
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"params": {
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"url": "http://localhost:8765/docs/vue",
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"title": "vue-docs",
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"displayTitle": "Vue.js"
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}
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},
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{
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"name": "http",
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"params": {
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"url": "http://localhost:8765/docs/react",
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"title": "react-docs",
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"displayTitle": "React"
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}
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},
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{
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"name": "http",
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"params": {
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"url": "http://localhost:8765/docs/django",
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"title": "django-docs",
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"displayTitle": "Django"
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}
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}
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]
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}
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```
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Now you can use:
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```
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@vue-docs @react-docs @django-docs Create a full-stack app
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```
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## Team Deployment
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### Option 1: Shared Server
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```bash
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# Run on team server
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ssh team-server
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python context_server.py --host 0.0.0.0 --port 8765
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# Team members update config:
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{
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"contextProviders": [
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{
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"name": "http",
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"params": {
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"url": "http://team-server.company.com:8765/docs/vue",
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"title": "vue-docs"
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}
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}
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]
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}
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```
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### Option 2: Docker Deployment
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```dockerfile
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# Dockerfile
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FROM python:3.11-slim
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WORKDIR /app
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COPY requirements.txt .
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RUN pip install -r requirements.txt
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COPY context_server.py .
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COPY output/ output/
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EXPOSE 8765
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CMD ["python", "context_server.py", "--host", "0.0.0.0"]
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```
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```bash
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# Build and run
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docker build -t skill-seekers-context .
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docker run -d -p 8765:8765 skill-seekers-context
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# Team uses: http://your-server:8765/docs/vue
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```
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### Option 3: Kubernetes Deployment
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```yaml
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# deployment.yaml
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: skill-seekers-context
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spec:
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replicas: 3
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selector:
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matchLabels:
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app: skill-seekers-context
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template:
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metadata:
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labels:
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app: skill-seekers-context
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spec:
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containers:
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- name: context-server
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image: skill-seekers-context:latest
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ports:
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- containerPort: 8765
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---
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apiVersion: v1
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kind: Service
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metadata:
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name: skill-seekers-context
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spec:
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selector:
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app: skill-seekers-context
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ports:
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- port: 80
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targetPort: 8765
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type: LoadBalancer
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```
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## Customization
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### Add Project-Specific Context
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```python
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# In context_server.py
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@app.get("/project/conventions")
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async def get_project_conventions():
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"""Serve company-specific patterns."""
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return {
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"contextItems": [{
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"name": "Project Conventions",
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"description": "Company coding standards",
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"content": """
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# Company Coding Standards
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## Vue Components
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- Always use Composition API
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- TypeScript is required
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- Props must have interfaces
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- Use Pinia for state management
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## API Calls
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- Use axios with interceptors
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- All endpoints must be typed
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- Error handling with try/catch
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- Loading states required
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"""
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}]
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}
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```
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Add to Continue config:
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```json
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{
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"contextProviders": [
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{
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"name": "http",
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"params": {
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"url": "http://localhost:8765/docs/vue",
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"title": "vue-docs"
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}
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},
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{
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"name": "http",
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"params": {
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"url": "http://localhost:8765/project/conventions",
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"title": "conventions",
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"displayTitle": "Company Standards"
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}
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}
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]
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}
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```
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Now use both:
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```
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@vue-docs @conventions Create a component following our standards
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```
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## Troubleshooting
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### Issue: Context provider not showing
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**Solution:** Check server is running
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```bash
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curl http://localhost:8765/docs/vue
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# Should return JSON
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# If not running:
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python context_server.py
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```
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### Issue: Different results in different IDEs
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||||
**Solution:** Verify same config file
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```bash
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# All IDEs use same config
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cat ~/.continue/config.json
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# NOT project-specific configs
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# (those would cause inconsistency)
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```
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||||
### Issue: Documentation outdated
|
||||
|
||||
**Solution:** Re-generate and restart
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```bash
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skill-seekers scrape --config configs/vue.json
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skill-seekers package output/vue --target markdown
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# Restart server (will load new docs)
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pkill -f context_server.py
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python context_server.py
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```
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|
||||
## Advanced Usage
|
||||
|
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### RAG Integration
|
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|
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```python
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# rag_context_server.py
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from langchain_community.vectorstores import Chroma
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from langchain_openai import OpenAIEmbeddings
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|
||||
# Load vector store
|
||||
embeddings = OpenAIEmbeddings()
|
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vectorstore = Chroma(
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persist_directory="./chroma_db",
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embedding_function=embeddings
|
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)
|
||||
|
||||
@app.get("/docs/search")
|
||||
async def search_docs(query: str, k: int = 5):
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"""RAG-powered search."""
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results = vectorstore.similarity_search(query, k=k)
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|
||||
return {
|
||||
"contextItems": [
|
||||
{
|
||||
"name": f"Result {i+1}",
|
||||
"description": doc.metadata.get("source", "Docs"),
|
||||
"content": doc.page_content
|
||||
}
|
||||
for i, doc in enumerate(results)
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
Continue config:
|
||||
|
||||
```json
|
||||
{
|
||||
"contextProviders": [
|
||||
{
|
||||
"name": "http",
|
||||
"params": {
|
||||
"url": "http://localhost:8765/docs/search?query={query}",
|
||||
"title": "rag-search",
|
||||
"displayTitle": "RAG Search"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### MCP Integration
|
||||
|
||||
```bash
|
||||
# Install MCP support
|
||||
pip install skill-seekers[mcp]
|
||||
|
||||
# Continue config with MCP
|
||||
{
|
||||
"mcpServers": {
|
||||
"skill-seekers": {
|
||||
"command": "python",
|
||||
"args": ["-m", "skill_seekers.mcp.server_fastmcp", "--transport", "stdio"]
|
||||
}
|
||||
},
|
||||
"contextProviders": [
|
||||
{
|
||||
"name": "mcp",
|
||||
"params": {
|
||||
"serverName": "skill-seekers"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## Performance Tips
|
||||
|
||||
### 1. Cache Documentation
|
||||
|
||||
```python
|
||||
from functools import lru_cache
|
||||
|
||||
@lru_cache(maxsize=100)
|
||||
def load_cached_docs(framework: str) -> str:
|
||||
"""Cache docs in memory."""
|
||||
return load_skill(f"output/{framework}-markdown/SKILL.md")
|
||||
```
|
||||
|
||||
### 2. Compress Responses
|
||||
|
||||
```python
|
||||
from fastapi.responses import JSONResponse
|
||||
import gzip
|
||||
|
||||
@app.get("/docs/{framework}")
|
||||
async def get_docs(framework: str):
|
||||
docs = load_cached_docs(framework)
|
||||
|
||||
# Compress if large
|
||||
if len(docs) > 10000:
|
||||
docs = gzip.compress(docs.encode()).decode('latin1')
|
||||
|
||||
return JSONResponse(...)
|
||||
```
|
||||
|
||||
### 3. Load Balancing
|
||||
|
||||
```bash
|
||||
# Run multiple instances
|
||||
python context_server.py --port 8765 &
|
||||
python context_server.py --port 8766 &
|
||||
python context_server.py --port 8767 &
|
||||
|
||||
# Configure Continue with failover
|
||||
{
|
||||
"contextProviders": [
|
||||
{
|
||||
"name": "http",
|
||||
"params": {
|
||||
"url": "http://localhost:8765/docs/vue",
|
||||
"fallbackUrls": [
|
||||
"http://localhost:8766/docs/vue",
|
||||
"http://localhost:8767/docs/vue"
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## Related Examples
|
||||
|
||||
- [Cursor Example](../cursor-react-skill/) - IDE-specific approach
|
||||
- [Windsurf Example](../windsurf-fastapi-context/) - Windsurf IDE
|
||||
- [Cline Example](../cline-django-assistant/) - VS Code extension
|
||||
- [LangChain RAG Example](../langchain-rag-pipeline/) - RAG integration
|
||||
|
||||
## Next Steps
|
||||
|
||||
1. Add more frameworks for full-stack development
|
||||
2. Deploy to team server for shared access
|
||||
3. Integrate with RAG for deep search
|
||||
4. Create project-specific context providers
|
||||
5. Set up CI/CD for automatic documentation updates
|
||||
|
||||
## Support
|
||||
|
||||
- **Skill Seekers Issues:** [GitHub](https://github.com/yusufkaraaslan/Skill_Seekers/issues)
|
||||
- **Continue.dev Docs:** [docs.continue.dev](https://docs.continue.dev/)
|
||||
- **Integration Guide:** [CONTINUE_DEV.md](../../docs/integrations/CONTINUE_DEV.md)
|
||||
Reference in New Issue
Block a user