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e34506d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 | #!/usr/bin/env python3
"""
Example script demonstrating how to use the AWS S3 storage utilities.
"""
import os
from dotenv import load_dotenv
from app.utils.aws_storage import AWSS3Storage
def aws_storage_example():
"""
Example of using the AWSS3Storage class to save and retrieve pitch data.
"""
# Load environment variables
load_dotenv()
# Check if AWS credentials are configured
if not all([
os.getenv('AWS_ACCESS_KEY_ID'),
os.getenv('AWS_SECRET_ACCESS_KEY'),
os.getenv('AWS_S3_BUCKET_NAME')
]):
print("AWS credentials not properly configured. Example will not work.")
return
# Initialize S3 storage
s3_storage = AWSS3Storage()
# Example pitch data
example_script_id = f"example_pitch_{os.urandom(4).hex()}"
example_elevator_pitch = "We're revolutionizing logistics with AI-powered optimization."
example_full_pitch = """
Our company, LogiTech AI, is addressing the critical inefficiencies in global supply chains.
The Problem:
Current logistics solutions fail to adapt in real-time to changing conditions, resulting in delays, wasted resources, and environmental impact.
Our Solution:
Our platform uses machine learning to dynamically optimize shipping routes and packaging in real-time, responding to disruptions within minutes instead of hours.
Market Opportunity:
The global logistics optimization market is projected to reach $30B by 2026, growing at 16% CAGR.
Traction:
We've already partnered with 3 Fortune 500 retailers for pilot programs, reducing their shipping costs by an average of 23%.
Team:
Our founding team combines 25+ years of logistics experience with cutting-edge AI expertise from MIT and Stanford.
We're seeking $2M in funding to scale our technology and expand our customer base in the e-commerce sector.
"""
# Example competitors and market insights
example_competitors = """
## Competitor Analysis
### OptimizeShip
A logistics optimization platform focused on route planning.
**Strengths:**
- Strong route optimization algorithms
- Established market presence
**Weaknesses:**
- Lacks real-time adaptation
- No packaging optimization
### PackTech
Specializes in packaging optimization for shipping.
**Strengths:**
- Deep expertise in packaging materials
- Integration with major e-commerce platforms
**Weaknesses:**
- No route optimization capabilities
- Limited AI implementation
"""
example_market_insights = """
## Market Insights
The logistics optimization market is experiencing rapid growth due to:
1. Increasing e-commerce sales globally
2. Rising shipping costs and supply chain disruptions
3. Growing emphasis on sustainability in shipping
4. Advancements in AI and machine learning technologies
Major trends include:
- Integration of IoT devices for real-time tracking
- Demand for environmentally-friendly shipping solutions
- Consolidation among logistics technology providers
"""
print("=== AWS S3 Storage Example ===")
print(f"Using bucket: {s3_storage.bucket_name}")
print(f"Example script ID: {example_script_id}")
# Step 1: Save pitch data
print("\n--- Step 1: Saving pitch data ---")
save_result = s3_storage.save_pitch_data(
script_id=example_script_id,
elevator_pitch=example_elevator_pitch,
full_pitch=example_full_pitch,
competitors_data=example_competitors,
market_insights=example_market_insights
)
if save_result["success"]:
print(f"✅ Successfully saved pitch data")
print(f"S3 path: {save_result['s3_path']}")
else:
print(f"❌ Failed to save pitch data: {save_result['message']}")
return
# Step 2: Retrieve pitch data
print("\n--- Step 2: Retrieving pitch data ---")
retrieve_result = s3_storage.get_pitch_data(example_script_id)
if retrieve_result["success"]:
pitch_data = retrieve_result["data"]
print("✅ Successfully retrieved pitch data")
print(f"Retrieved script ID: {pitch_data['script_id']}")
print(f"Created at: {pitch_data['created_at']}")
print("\nElevator pitch preview:")
print(f""{pitch_data['elevator_pitch']}"")
else:
print(f"❌ Failed to retrieve pitch data: {retrieve_result['message']}")
# Step 3: List pitches
print("\n--- Step 3: Listing pitches ---")
list_result = s3_storage.list_pitches(limit=5)
if list_result["success"]:
pitches = list_result["pitches"]
print(f"✅ Successfully listed pitches. Total count: {list_result['count']}")
if list_result["count"] > 0:
print("\nRecent pitches:")
for i, pitch in enumerate(pitches[:5], 1): # Show up to 5 pitches
print(f"{i}. {pitch['script_id']} (modified: {pitch['last_modified'].split('T')[0]})")
else:
print(f"❌ Failed to list pitches: {list_result['message']}")
print("\n=== Example Complete ===")
print(f"You can view this example pitch using the command:")
print(f"python -m app.scripts_storage.get_pitch_details {example_script_id}")
if __name__ == "__main__":
aws_storage_example() |