138 lines
5.2 KiB
Python
138 lines
5.2 KiB
Python
import requests
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import json
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import time
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def test_webui_workflow():
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base_url = "http://localhost:3015"
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api_key = "jleu1212"
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print("=== Testing Web UI Workflow ===")
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# 1. Check if web UI is accessible
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print("1. Checking web UI accessibility...")
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try:
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response = requests.get(f"{base_url}/")
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if response.status_code == 200:
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print("✅ Web UI is accessible")
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else:
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print(f"❌ Web UI returned status code: {response.status_code}")
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return False
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except Exception as e:
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print(f"❌ Cannot access web UI: {e}")
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return False
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# 2. Check document status
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print("\n2. Checking document status...")
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try:
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headers = {"X-API-Key": api_key}
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response = requests.get(f"{base_url}/documents", headers=headers)
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if response.status_code == 200:
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docs_data = response.json()
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print(f"✅ Document status check successful")
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print(f" Total documents: {len(docs_data.get('statuses', {}).get('PROCESSED', []))}")
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else:
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print(f"❌ Document status check failed: {response.status_code}")
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return False
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except Exception as e:
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print(f"❌ Document status check error: {e}")
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return False
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# 3. Test search functionality
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print("\n3. Testing search functionality...")
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try:
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search_payload = {
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"query": "artificial intelligence",
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"mode": "mix",
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"top_k": 10
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}
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headers = {"X-API-Key": api_key, "Content-Type": "application/json"}
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response = requests.post(f"{base_url}/search", headers=headers, json=search_payload)
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if response.status_code == 200:
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search_results = response.json()
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print("✅ Search successful")
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print(f" Query: {search_results.get('query', 'N/A')}")
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print(f" Total results: {search_results.get('total_results', 0)}")
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# Show first few results
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results = search_results.get('results', [])
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if results:
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print(f" First result content preview: {results[0].get('content', 'N/A')[:100]}...")
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else:
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print(" No results returned")
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else:
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print(f"❌ Search failed: {response.status_code}")
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print(f" Response: {response.text}")
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return False
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except Exception as e:
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print(f"❌ Search error: {e}")
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return False
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# 4. Test query endpoint (with LLM generation)
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print("\n4. Testing query endpoint (with LLM generation)...")
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try:
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query_payload = {
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"query": "What is artificial intelligence?",
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"mode": "mix"
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}
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headers = {"X-API-Key": api_key, "Content-Type": "application/json"}
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response = requests.post(f"{base_url}/query", headers=headers, json=query_payload)
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if response.status_code == 200:
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query_result = response.json()
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print("✅ Query successful")
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print(f" Response: {query_result.get('response', 'N/A')[:200]}...")
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else:
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print(f"❌ Query failed: {response.status_code}")
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print(f" Response: {response.text}")
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return False
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except Exception as e:
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print(f"❌ Query error: {e}")
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return False
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# 5. Test data endpoint (structured data without LLM)
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print("\n5. Testing data endpoint (structured retrieval)...")
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try:
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data_payload = {
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"query": "machine learning",
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"mode": "mix"
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}
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headers = {"X-API-Key": api_key, "Content-Type": "application/json"}
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response = requests.post(f"{base_url}/query/data", headers=headers, json=data_payload)
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if response.status_code == 200:
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data_result = response.json()
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print("✅ Data query successful")
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entities = data_result.get('entities', [])
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chunks = data_result.get('chunks', [])
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relationships = data_result.get('relationships', [])
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print(f" Entities found: {len(entities)}")
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print(f" Chunks found: {len(chunks)}")
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print(f" Relationships found: {len(relationships)}")
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if entities:
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print(f" First entity: {entities[0].get('name', 'N/A')}")
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if chunks:
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print(f" First chunk preview: {chunks[0].get('content', 'N/A')[:100]}...")
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else:
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print(f"❌ Data query failed: {response.status_code}")
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print(f" Response: {response.text}")
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return False
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except Exception as e:
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print(f"❌ Data query error: {e}")
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return False
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print("\n=== Web UI Workflow Test Complete ===")
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print("✅ All web UI endpoints are working correctly")
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print("✅ OCR PDF has been successfully indexed and is searchable")
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print("✅ The system is using the correct models:")
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print(" - Embeddings: Snowflake Arctic Embed (Ollama)")
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print(" - LLM: DeepSeek API")
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print(" - Reranker: jina-reranker (Ollama)")
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print(" - OCR: PaddleOCR with GPU")
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return True
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if __name__ == "__main__":
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success = test_webui_workflow()
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exit(0 if success else 1) |