#!/usr/bin/env python3"""Simple RAG endpoint for azul-browseProvides a minimal RAG API without heavy dependencies""" from http.server import HTTPServer, BaseHTTPRequestHandlerimport jsonimport osfrom pathlib import Path class SimpleRAGHandler(BaseHTTPRequestHandler):    # Simple in-memory document store    documents = []     def do_GET(self):        if self.path == '/health':            self.send_response(200)            self.send_header('Content-type', 'application/json')            self.end_headers()            self.wfile.write(json.dumps({"status": "ok"}).encode())        else:            self.send_response(404)            self.end_headers()     def do_POST(self):        if self.path == '/query':            content_length = int(self.headers['Content-Length'])            post_data = self.rfile.read(content_length)             try:                request = json.loads(post_data.decode('utf-8'))                query = request.get('query', '')                top_k = request.get('top_k', 5)                 # Simple keyword matching (no embeddings needed)                results = self.search_documents(query, top_k)                 response = {                    'answer': None,                    'sources': results,                    'context': [r['content'] for r in results]                }                 self.send_response(200)                self.send_header('Content-type', 'application/json')                self.end_headers()                self.wfile.write(json.dumps(response).encode())            except Exception as e:                self.send_error(500, str(e))        elif self.path == '/ingest':            content_length = int(self.headers['Content-Length'])            post_data = self.rfile.read(content_length)             try:                request = json.loads(post_data.decode('utf-8'))                docs = request.get('documents', [])                 for doc in docs:                    self.documents.append({                        'content': doc.get('content', ''),                        'metadata': doc.get('metadata', {}),                        'score': 1.0                    })                 self.send_response(200)                self.send_header('Content-type', 'application/json')                self.end_headers()                self.wfile.write(json.dumps({                    'status': 'ok',                    'count': len(docs)                }).encode())            except Exception as e:                self.send_error(500, str(e))        else:            self.send_response(404)            self.end_headers()     @classmethod    def search_documents(cls, query, top_k):        """Simple keyword-based search"""        query_lower = query.lower()        query_words = set(query_lower.split())         # Score documents by keyword overlap        scored_docs = []        for doc in cls.documents:            content_lower = doc['content'].lower()            content_words = set(content_lower.split())             # Simple relevance: count matching words            matches = len(query_words & content_words)            if matches > 0:                score = matches / len(query_words)                scored_docs.append({                    'content': doc['content'][:200],  # Truncate for display                    'metadata': doc['metadata'],                    'score': score                })         # Sort by score and return top_k        scored_docs.sort(key=lambda x: x['score'], reverse=True)        return scored_docs[:top_k]     def log_message(self, format, *args):        # Suppress default logging        pass def load_sample_documents():    """Load some sample documents for testing"""    SimpleRAGHandler.documents = [        {            'content': 'Azul is a terminal web browser written in Rust with AI-powered features including chat, RAG, and memory integration.',            'metadata': {'source': 'README', 'type': 'project'},            'score': 1.0        },        {            'content': 'mem-layer is a graph-based memory management system for AI models. It stores nodes and relationships in a graph database.',            'metadata': {'source': 'docs', 'type': 'integration'},            'score': 1.0        },        {            'content': 'The browser supports multiple search engines including DuckDuckGo, Wikipedia, arXiv, and Google Scholar.',            'metadata': {'source': 'features', 'type': 'documentation'},            'score': 1.0        },        {            'content': 'Press r to open RAG panel, m for memory panel, c for chat, and ? for help.',            'metadata': {'source': 'keybindings', 'type': 'documentation'},            'score': 1.0        },    ] def run_server(port=8765):    """Run the simple RAG server"""    load_sample_documents()     server_address = ('127.0.0.1', port)    httpd = HTTPServer(server_address, SimpleRAGHandler)     print(f'Simple RAG server running on http://127.0.0.1:{port}')    print('Endpoints:')    print('  GET  /health - Health check')    print('  POST /query  - Search documents')    print('  POST /ingest - Add documents')    print('\nPress Ctrl+C to stop')     try:        httpd.serve_forever()    except KeyboardInterrupt:        print('\nShutting down...')        httpd.shutdown() if __name__ == '__main__':    import sys    port = int(sys.argv[1]) if len(sys.argv) > 1 else 8766    run_server(port)