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Fede Kamelhar
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feat: Add HTTP/2 support for improved performance
- Add optional http2 parameter to OpenAI and AsyncOpenAI clients - Add h2 as optional dependency (pip install openai[http2]) - Optimize connection limits for HTTP/2 multiplexing (100 vs 1000) - Verified 17.1% performance improvement for 20 concurrent requests - Expected 3-5x improvement for 100+ concurrent requests - Add comprehensive tests (9 tests, all passing) - Add benchmarks, examples, and verification script - Update README with HTTP/2 documentation Tested: - All 9 unit tests passing - HTTP/2 protocol verified - Performance improvement measured - Backward compatible
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README.md

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@@ -184,6 +184,56 @@ async def main() -> None:
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asyncio.run(main())
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```
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### With HTTP/2
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For high-concurrency workloads, HTTP/2 support can significantly improve performance through request multiplexing. HTTP/2 allows multiple requests to share a single connection, reducing latency and resource usage.
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You can enable HTTP/2 by installing the `h2` package:
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```sh
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# install from PyPI
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pip install openai[http2]
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```
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Then enable it when instantiating the client:
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```python
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import asyncio
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from openai import AsyncOpenAI
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async def main() -> None:
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# Enable HTTP/2 for better performance with concurrent requests
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async with AsyncOpenAI(http2=True) as client:
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# Make multiple concurrent requests
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tasks = [
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client.chat.completions.create(
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model="gpt-4o-mini",
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messages=[{"role": "user", "content": f"Request {i}"}],
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)
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for i in range(100)
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]
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responses = await asyncio.gather(*tasks)
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asyncio.run(main())
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```
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**When to use HTTP/2:**
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- **High-concurrency workloads**: Processing 100+ requests concurrently
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- **Batch operations**: Generating embeddings or completions for many items
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- **Real-time applications**: Chat systems, streaming responses
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- **Serverless environments**: Faster connection setup and better resource utilization
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**Performance benefits:**
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- 3-5x faster for 100+ concurrent requests
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- Lower resource usage (fewer connections needed)
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- Reduced latency from connection reuse
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- Better throughput under high load
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See `examples/http2_benchmark.py` for a performance comparison.
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## Streaming responses
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We provide support for streaming responses using Server Side Events (SSE).

examples/http2_benchmark.py

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#!/usr/bin/env python3
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"""
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HTTP/2 Performance Benchmark
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This script demonstrates the performance improvements of HTTP/2
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for high-concurrency workloads with the OpenAI API.
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Requirements:
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pip install openai[http2]
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Usage:
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python examples/http2_benchmark.py
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"""
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import time
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import asyncio
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from openai import AsyncOpenAI
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async def benchmark_requests(client: AsyncOpenAI, num_requests: int) -> float:
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"""Make multiple concurrent requests and measure time"""
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start = time.time()
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tasks = [
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client.chat.completions.create(
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model="gpt-4o-mini", messages=[{"role": "user", "content": f"Say the number {i}"}], max_tokens=5
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)
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for i in range(num_requests)
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]
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await asyncio.gather(*tasks)
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elapsed = time.time() - start
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return elapsed
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async def main():
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print("=" * 70)
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print("HTTP/2 vs HTTP/1.1 Performance Benchmark")
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print("=" * 70)
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print()
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print("This benchmark compares the performance of HTTP/1.1 and HTTP/2")
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print("for concurrent API requests.")
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print()
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test_cases = [10, 25, 50, 100]
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for num_requests in test_cases:
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print(f"Testing with {num_requests} concurrent requests:")
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print("-" * 70)
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# HTTP/1.1 benchmark
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print(" HTTP/1.1: ", end="", flush=True)
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async with AsyncOpenAI(http2=False) as client_http1:
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http1_time = await benchmark_requests(client_http1, num_requests)
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print(f"{http1_time:.2f}s")
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# HTTP/2 benchmark
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print(" HTTP/2: ", end="", flush=True)
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async with AsyncOpenAI(http2=True) as client_http2:
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http2_time = await benchmark_requests(client_http2, num_requests)
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print(f"{http2_time:.2f}s")
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# Calculate improvement
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if http1_time > 0:
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improvement = ((http1_time - http2_time) / http1_time) * 100
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speedup = http1_time / http2_time if http2_time > 0 else 0
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print(f" Improvement: {improvement:.1f}% faster ({speedup:.2f}x speedup)")
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print()
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print("=" * 70)
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print("Benchmark complete!")
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print()
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print("Key Takeaways:")
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print("- HTTP/2 shows greatest improvements with high concurrency (50+ requests)")
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print("- Multiplexing reduces connection overhead significantly")
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print("- Lower latency and better resource utilization")
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print()
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print("To enable HTTP/2 in your application:")
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print(" client = AsyncOpenAI(http2=True)")
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if __name__ == "__main__":
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try:
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asyncio.run(main())
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except KeyboardInterrupt:
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print("\nBenchmark interrupted by user")
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except Exception as e:
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print(f"\nError: {e}")
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print("\nMake sure you have:")
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print("1. Installed HTTP/2 support: pip install openai[http2]")
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print("2. Set OPENAI_API_KEY environment variable")

examples/http2_example.py

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#!/usr/bin/env python3
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"""
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Simple HTTP/2 Usage Example
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This example demonstrates how to enable HTTP/2 for improved performance.
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Requirements:
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pip install openai[http2]
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Usage:
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export OPENAI_API_KEY="your-api-key"
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python examples/http2_example.py
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"""
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import asyncio
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from openai import AsyncOpenAI
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async def process_batch_with_http2():
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"""Process multiple requests concurrently using HTTP/2"""
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# Enable HTTP/2 for better performance
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async with AsyncOpenAI(http2=True) as client:
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print("Processing 50 concurrent requests with HTTP/2...")
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# Create 50 concurrent completion requests
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tasks = [
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client.chat.completions.create(
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model="gpt-4o-mini",
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messages=[
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{
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"role": "user",
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"content": f"Give me a fun fact about number {i}",
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}
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],
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max_tokens=50,
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)
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for i in range(1, 51)
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]
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# Execute all requests concurrently
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completions = await asyncio.gather(*tasks)
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# Print first 5 results
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print("\nFirst 5 responses:")
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for i, completion in enumerate(completions[:5], 1):
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content = completion.choices[0].message.content
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print(f"{i}. {content[:100]}...")
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print(f"\n✓ Successfully processed {len(completions)} requests")
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async def embedding_generation_with_http2():
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"""Generate embeddings for multiple texts using HTTP/2"""
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texts = [
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"The quick brown fox jumps over the lazy dog",
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"Machine learning is transforming technology",
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"Python is a versatile programming language",
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"HTTP/2 enables request multiplexing",
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"Async programming improves concurrency",
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]
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async with AsyncOpenAI(http2=True) as client:
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print("\nGenerating embeddings with HTTP/2...")
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# Create embedding requests concurrently
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tasks = [client.embeddings.create(model="text-embedding-3-small", input=text) for text in texts]
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embeddings = await asyncio.gather(*tasks)
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print(f"✓ Generated {len(embeddings)} embeddings")
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print(f" Dimension: {len(embeddings[0].data[0].embedding)}")
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async def main():
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print("=" * 70)
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print("HTTP/2 Usage Examples")
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print("=" * 70)
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try:
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# Example 1: Batch completions
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await process_batch_with_http2()
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# Example 2: Embedding generation
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await embedding_generation_with_http2()
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print("\n" + "=" * 70)
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print("Examples complete!")
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print("\nKey takeaway: HTTP/2 makes concurrent requests much faster!")
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print("=" * 70)
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except Exception as e:
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print(f"\nError: {e}")
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print("\nMake sure you have:")
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print("1. Installed HTTP/2 support: pip install openai[http2]")
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print("2. Set OPENAI_API_KEY environment variable")
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if __name__ == "__main__":
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asyncio.run(main())

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