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#!/usr/bin/env python3
"""
Simple example client for the RAG Pipeline API
Shows how to upload documents and query them
"""
import requests
import json
import sys
API_URL = "http://localhost:8000"
def check_status():
"""Check if the API is running and system status."""
try:
response = requests.get(f"{API_URL}/status")
status = response.json()
print("📊 System Status:")
print(f" Documents Processed: {status['documents_processed']}")
print(f" Vector Store Count: {status['vector_store_count']}")
print(f" Embedding Model: {status.get('embedding_model', 'Not loaded')}")
return status
except requests.exceptions.ConnectionError:
print("❌ Error: Cannot connect to API. Is the server running?")
print(" Start it with: uvicorn api:app --reload")
sys.exit(1)
def upload_documents(pdf_paths, chunk_size=800, chunk_overlap=200):
"""Upload and process PDF documents."""
print(f"\n📤 Uploading {len(pdf_paths)} document(s)...")
files = []
for pdf_path in pdf_paths:
try:
files.append(('files', (open(pdf_path, 'rb'))))
except FileNotFoundError:
print(f"❌ Error: File not found: {pdf_path}")
return None
data = {
'chunk_size': chunk_size,
'chunk_overlap': chunk_overlap
}
try:
response = requests.post(f"{API_URL}/upload", files=files, data=data)
# Close file handles
for _, file_tuple in files:
file_tuple[1].close()
if response.status_code == 200:
result = response.json()
print(f"✅ Success!")
print(f" Documents Loaded: {result['documents_loaded']}")
print(f" Chunks Created: {result['chunks_created']}")
print(f" Vector Store Count: {result['vector_store_count']}")
return result
else:
print(f"❌ Error: {response.status_code}")
print(response.json())
return None
except Exception as e:
print(f"❌ Error uploading: {str(e)}")
return None
def query(query_text, session_id=None, top_k=5, use_memory=True, metadata_filters=None):
"""Query the RAG system."""
print(f"\n❓ Query: {query_text}")
payload = {
"query": query_text,
"top_k": top_k,
"use_memory": use_memory
}
if session_id:
payload["session_id"] = session_id
if metadata_filters:
payload["metadata_filters"] = metadata_filters
try:
response = requests.post(f"{API_URL}/query", json=payload)
if response.status_code == 200:
result = response.json()
print(f"\n💡 Answer:")
print(f" {result['answer']}")
print(f"\n📄 Sources ({len(result['sources'])}):")
for i, source in enumerate(result['sources'][:3], 1):
print(f" {i}. Score: {source['score']:.4f}")
print(f" Preview: {source['preview'][:100]}...")
print(f"\n🆔 Session ID: {result['session_id']}")
return result
else:
print(f"❌ Error: {response.status_code}")
print(response.json())
return None
except Exception as e:
print(f"❌ Error querying: {str(e)}")
return None
def get_chat_history(session_id):
"""Get chat history for a session."""
try:
response = requests.get(f"{API_URL}/chat-history/{session_id}")
if response.status_code == 200:
return response.json()
else:
print(f"❌ Error: {response.status_code}")
return None
except Exception as e:
print(f"❌ Error: {str(e)}")
return None
if __name__ == "__main__":
print("🚀 RAG Pipeline API Client\n")
# Check status
status = check_status()
# If no documents processed, upload some
if not status['documents_processed']:
print("\n⚠️ No documents processed. Uploading documents...")
pdf_paths = ["data/pdf/NIPS-2017-attention-is-all-you-need-Paper.pdf"]
upload_result = upload_documents(pdf_paths)
if not upload_result:
print("❌ Failed to upload documents. Exiting.")
sys.exit(1)
# Example queries
session_id = "example-session"
print("\n" + "="*60)
print("Example Queries")
print("="*60)
# Query 1
result1 = query("What is attention mechanism?", session_id=session_id)
# Query 2 (with memory)
result2 = query("Who are the authors?", session_id=session_id)
# Query 3 (follow-up using memory)
result3 = query("Tell me more about it", session_id=session_id)
# Show chat history
print("\n" + "="*60)
print("Chat History")
print("="*60)
history = get_chat_history(session_id)
if history:
print(f"Total messages: {history['message_count']}")
for i, msg in enumerate(history['history'], 1):
role = msg.get('role', 'unknown')
content = msg.get('content', '')[:100]
print(f"{i}. [{role}]: {content}...")
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