Spaces:
Sleeping
Sleeping
| import requests | |
| import json | |
| import re | |
| URL = "http://127.0.0.1:8000" | |
| print("1. Registration...") | |
| r = requests.post(f"{URL}/register", data={"username": "testuser_hf2", "password": "password123"}) | |
| print(r.status_code) | |
| print("2. Login...") | |
| session = requests.Session() | |
| r = session.post(f"{URL}/login", data={"username": "testuser_hf2", "password": "password123"}) | |
| print(r.status_code) | |
| print("3. Getting API Key from dashboard...") | |
| r = session.get(f"{URL}/dashboard") | |
| api_key = re.search(r'id="apiKeyInput"\s+value="(dk_[^"]+)"', r.text) | |
| if api_key: | |
| API_KEY = api_key.group(1) | |
| print("Found API Key:", API_KEY) | |
| else: | |
| print("Failed to find API KEY") | |
| exit() | |
| print("4. Upload Document...") | |
| # Uploading a sample TXT | |
| files = {'file': ('hf_launch.txt', b'Project DocKey v2 Launch Notes:\nDocKey has successfully migrated exclusively to Hugging Face embeddings using BAAI/bge-large-en-v1.5.\nThe system is much more responsive now.', 'text/plain')} | |
| r = session.post(f"{URL}/upload", files=files) | |
| print(r.status_code) | |
| print("5. Chat / RAG...") | |
| # This will trigger embedding generation + retrieval + SmolLM generation | |
| headers = {"Authorization": f"Bearer {API_KEY}"} | |
| r = requests.post(f"{URL}/api/chat", json={"query": "What embeddings model did DocKey migrate to?"}, headers=headers) | |
| print(r.status_code) | |
| try: | |
| print("Response:", r.json()) | |
| except Exception as e: | |
| print("Error parsing chat response:", r.text[:200]) | |