Files
yusyus bdd61687c5 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>
2026-02-07 20:46:26 +03:00

598 lines
12 KiB
Markdown

# Continue.dev + Universal Context Example
Complete example showing how to use Skill Seekers to create IDE-agnostic context providers for Continue.dev across VS Code, JetBrains, and other IDEs.
## What This Example Does
- ✅ Generates framework documentation (Vue.js example)
- ✅ Creates HTTP context provider server
- ✅ Works across all IDEs (VS Code, IntelliJ, PyCharm, WebStorm, etc.)
- ✅ Single configuration, consistent results
## Quick Start
### 1. Generate Documentation
```bash
# Install Skill Seekers
pip install skill-seekers[mcp]
# Generate Vue.js documentation
skill-seekers scrape --config configs/vue.json
skill-seekers package output/vue --target markdown
```
### 2. Start Context Server
```bash
# Use the provided HTTP context server
python context_server.py
# Server runs on http://localhost:8765
# Serves documentation at /docs/{framework}
```
### 3. Configure Continue.dev
Edit `~/.continue/config.json`:
```json
{
"contextProviders": [
{
"name": "http",
"params": {
"url": "http://localhost:8765/docs/vue",
"title": "vue-docs",
"displayTitle": "Vue.js Documentation",
"description": "Vue.js framework expert knowledge"
}
}
]
}
```
### 4. Test in Any IDE
**VS Code:**
```bash
code my-vue-project/
# Open Continue panel (Cmd+L)
# Type: @vue-docs Create a Vue 3 component with Composition API
```
**IntelliJ IDEA:**
```bash
idea my-vue-project/
# Open Continue panel (Cmd+L)
# Type: @vue-docs Create a Vue 3 component with Composition API
```
**Result:** IDENTICAL suggestions in both IDEs!
## Expected Results
### Before (Without Context Provider)
**Prompt:** "Create a Vue component"
**Continue Output:**
```javascript
export default {
name: 'MyComponent',
data() {
return {
message: 'Hello'
}
}
}
```
❌ Uses Options API (outdated)
❌ No TypeScript
❌ No Composition API
❌ Generic patterns
### After (With Context Provider)
**Prompt:** "@vue-docs Create a Vue component"
**Continue Output:**
```typescript
<script setup lang="ts">
import { ref, computed } from 'vue'
interface Props {
title: string
count?: number
}
const props = withDefaults(defineProps<Props>(), {
count: 0
})
const message = ref('Hello')
const displayCount = computed(() => props.count * 2)
</script>
<template>
<div>
<h2>{{ props.title }}</h2>
<p>{{ message }} - Count: {{ displayCount }}</p>
</div>
</template>
<style scoped>
/* Component styles */
</style>
```
✅ Composition API with `<script setup>`
✅ TypeScript interfaces
✅ Proper props definition
✅ Vue 3 best practices
## Files in This Example
- `context_server.py` - HTTP context provider server (FastAPI)
- `quickstart.py` - Automation script for setup
- `requirements.txt` - Python dependencies
- `config.example.json` - Sample Continue.dev configuration
## Multi-IDE Testing
This example demonstrates IDE consistency:
### Test 1: VS Code
```bash
cd examples/continue-dev-universal
python context_server.py &
code test-project/
# In Continue: @vue-docs Create a component
# Note the exact code generated
```
### Test 2: IntelliJ IDEA
```bash
# Same server still running
idea test-project/
# In Continue: @vue-docs Create a component
# Code should be IDENTICAL to VS Code
```
### Test 3: PyCharm
```bash
# Same server still running
pycharm test-project/
# In Continue: @vue-docs Create a component
# Code should be IDENTICAL to both above
```
**Why it works:** Continue.dev uses the SAME `~/.continue/config.json` across all IDEs!
## Context Server Architecture
The `context_server.py` implements a simple HTTP server:
```python
from fastapi import FastAPI
from skill_seekers.cli.doc_scraper import load_skill
app = FastAPI()
@app.get("/docs/{framework}")
async def get_framework_docs(framework: str):
"""
Serve framework documentation as Continue context.
Args:
framework: Framework name (vue, react, django, etc.)
Returns:
JSON with contextItems array
"""
# Load documentation
docs = load_skill(f"output/{framework}-markdown/SKILL.md")
return {
"contextItems": [
{
"name": f"{framework.title()} Documentation",
"description": f"Complete {framework} framework knowledge",
"content": docs
}
]
}
```
## Multi-Framework Support
Add more frameworks easily:
```bash
# Generate React docs
skill-seekers scrape --config configs/react.json
skill-seekers package output/react --target markdown
# Generate Django docs
skill-seekers scrape --config configs/django.json
skill-seekers package output/django --target markdown
# Server automatically serves both at:
# http://localhost:8765/docs/react
# http://localhost:8765/docs/django
```
Update `~/.continue/config.json`:
```json
{
"contextProviders": [
{
"name": "http",
"params": {
"url": "http://localhost:8765/docs/vue",
"title": "vue-docs",
"displayTitle": "Vue.js"
}
},
{
"name": "http",
"params": {
"url": "http://localhost:8765/docs/react",
"title": "react-docs",
"displayTitle": "React"
}
},
{
"name": "http",
"params": {
"url": "http://localhost:8765/docs/django",
"title": "django-docs",
"displayTitle": "Django"
}
}
]
}
```
Now you can use:
```
@vue-docs @react-docs @django-docs Create a full-stack app
```
## Team Deployment
### Option 1: Shared Server
```bash
# Run on team server
ssh team-server
python context_server.py --host 0.0.0.0 --port 8765
# Team members update config:
{
"contextProviders": [
{
"name": "http",
"params": {
"url": "http://team-server.company.com:8765/docs/vue",
"title": "vue-docs"
}
}
]
}
```
### Option 2: Docker Deployment
```dockerfile
# Dockerfile
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY context_server.py .
COPY output/ output/
EXPOSE 8765
CMD ["python", "context_server.py", "--host", "0.0.0.0"]
```
```bash
# Build and run
docker build -t skill-seekers-context .
docker run -d -p 8765:8765 skill-seekers-context
# Team uses: http://your-server:8765/docs/vue
```
### Option 3: Kubernetes Deployment
```yaml
# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: skill-seekers-context
spec:
replicas: 3
selector:
matchLabels:
app: skill-seekers-context
template:
metadata:
labels:
app: skill-seekers-context
spec:
containers:
- name: context-server
image: skill-seekers-context:latest
ports:
- containerPort: 8765
---
apiVersion: v1
kind: Service
metadata:
name: skill-seekers-context
spec:
selector:
app: skill-seekers-context
ports:
- port: 80
targetPort: 8765
type: LoadBalancer
```
## Customization
### Add Project-Specific Context
```python
# In context_server.py
@app.get("/project/conventions")
async def get_project_conventions():
"""Serve company-specific patterns."""
return {
"contextItems": [{
"name": "Project Conventions",
"description": "Company coding standards",
"content": """
# Company Coding Standards
## Vue Components
- Always use Composition API
- TypeScript is required
- Props must have interfaces
- Use Pinia for state management
## API Calls
- Use axios with interceptors
- All endpoints must be typed
- Error handling with try/catch
- Loading states required
"""
}]
}
```
Add to Continue config:
```json
{
"contextProviders": [
{
"name": "http",
"params": {
"url": "http://localhost:8765/docs/vue",
"title": "vue-docs"
}
},
{
"name": "http",
"params": {
"url": "http://localhost:8765/project/conventions",
"title": "conventions",
"displayTitle": "Company Standards"
}
}
]
}
```
Now use both:
```
@vue-docs @conventions Create a component following our standards
```
## Troubleshooting
### Issue: Context provider not showing
**Solution:** Check server is running
```bash
curl http://localhost:8765/docs/vue
# Should return JSON
# If not running:
python context_server.py
```
### Issue: Different results in different IDEs
**Solution:** Verify same config file
```bash
# All IDEs use same config
cat ~/.continue/config.json
# NOT project-specific configs
# (those would cause inconsistency)
```
### Issue: Documentation outdated
**Solution:** Re-generate and restart
```bash
skill-seekers scrape --config configs/vue.json
skill-seekers package output/vue --target markdown
# Restart server (will load new docs)
pkill -f context_server.py
python context_server.py
```
## Advanced Usage
### RAG Integration
```python
# rag_context_server.py
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAIEmbeddings
# Load vector store
embeddings = OpenAIEmbeddings()
vectorstore = Chroma(
persist_directory="./chroma_db",
embedding_function=embeddings
)
@app.get("/docs/search")
async def search_docs(query: str, k: int = 5):
"""RAG-powered search."""
results = vectorstore.similarity_search(query, k=k)
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)