Agents

.agents/skills/strandsagents/references/openai.md

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+# OpenAI Integration
+
+## Basic Configuration
+
+```python
+from strands import Agent
+from strands.models import OpenAIModel
+
+# OpenAI with API key
+openai_model = OpenAIModel(
+    model_id="gpt-4o",
+    client_args={"api_key": "your-openai-api-key"},
+    params={"temperature": 0.7, "max_tokens": 2048}
+)
+agent = Agent(model=openai_model)
+response = agent("Hello, how are you?")
+```
+
+## Environment Variables
+
+Set your API key via environment variable:
+
+```bash
+export OPENAI_API_KEY="your-openai-api-key"
+```
+
+Then use without explicit key:
+
+```python
+from strands import Agent
+from strands.models import OpenAIModel
+
+openai_model = OpenAIModel(
+    model_id="gpt-4o",
+    params={"temperature": 0.7, "max_tokens": 2048}
+)
+agent = Agent(model=openai_model)
+```
+
+## Available Models
+
+- `gpt-4o` - Latest GPT-4 Optimized
+- `gpt-4o-mini` - Faster, cost-effective
+- `gpt-4-turbo` - GPT-4 Turbo
+- `gpt-3.5-turbo` - Fast and efficient
+
+## Model Parameters
+
+```python
+openai_model = OpenAIModel(
+    model_id="gpt-4o",
+    params={
+        "temperature": 0.7,      # 0.0-2.0, controls randomness
+        "max_tokens": 2048,      # Maximum response length
+        "top_p": 0.9,            # Nucleus sampling
+        "frequency_penalty": 0,  # -2.0 to 2.0
+        "presence_penalty": 0    # -2.0 to 2.0
+    }
+)
+```
+
+## Streaming Responses
+
+```python
+from strands import Agent
+from strands.models import OpenAIModel
+import asyncio
+
+async def stream_openai():
+    openai_model = OpenAIModel(
+        model_id="gpt-4o",
+        client_args={"api_key": "your-openai-api-key"}
+    )
+    agent = Agent(model=openai_model)
+
+    async for event in agent.stream_async("Tell me a story"):
+        if "data" in event:
+            print(event["data"], end="", flush=True)
+
+asyncio.run(stream_openai())
+```
+
+## With Custom Tools
+
+```python
+from strands import Agent, tool
+from strands.models import OpenAIModel
+
+@tool
+def get_weather(city: str) -> dict:
+    """Get weather for a city."""
+    return {
+        "status": "success",
+        "content": [{"text": f"Weather in {city}: Sunny, 22°C"}]
+    }
+
+openai_model = OpenAIModel(
+    model_id="gpt-4o",
+    client_args={"api_key": "your-openai-api-key"}
+)
+agent = Agent(model=openai_model, tools=[get_weather])
+response = agent("What's the weather in Paris?")
+```
+
+## Error Handling
+
+```python
+from strands import Agent
+from strands.models import OpenAIModel
+
+try:
+    openai_model = OpenAIModel(
+        model_id="gpt-4o",
+        client_args={"api_key": "your-openai-api-key"}
+    )
+    agent = Agent(model=openai_model)
+    response = agent("Hello!")
+except Exception as e:
+    print(f"Error: {e}")
+```
+
+## Best Practices
+
+1. **API Key Security**: Never hardcode API keys. Use environment variables or secure vaults.
+2. **Rate Limits**: OpenAI has rate limits. Implement retry logic for production.
+3. **Cost Management**: Monitor token usage via `result.metrics` to control costs.
+4. **Model Selection**: Use `gpt-4o-mini` for cost-effective tasks, `gpt-4o` for complex reasoning.
+5. **Temperature**: Lower (0.0-0.3) for deterministic outputs, higher (0.7-1.0) for creative tasks.

.agents/skills/strandsagents/references/quickstart.md

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+# Strands Agents - Quick Start
+
+## Installation
+
+```bash
+# Create and activate virtual environment
+python -m venv .venv
+source .venv/bin/activate  # On Windows: .venv\Scripts\activate
+
+# Install Strands and tools
+pip install strands-agents strands-agents-tools
+```
+
+## Basic Agent
+
+```python
+from strands import Agent
+
+# Default Bedrock model
+agent = Agent()
+response = agent("What is the capital of France?")
+print(response)
+```
+
+## Agent with Custom Model
+
+```python
+from strands import Agent
+from strands.models import BedrockModel
+
+agent = Agent(
+    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
+    system_prompt="You are a helpful coding assistant. Be concise and provide examples."
+)
+result = agent("How do I read a JSON file in Python?")
+print(result.message)
+print(result.stop_reason)  # "end_turn", "max_tokens", etc.
+print(result.metrics)  # Performance metrics
+```
+
+## Agent with Built-in Tools
+
+```python
+from strands import Agent
+from strands_tools import calculator
+
+agent = Agent(tools=[calculator])
+response = agent("What is the square root of 1764?")
+```
+
+## Agent with Initial State
+
+```python
+from strands import Agent
+
+agent = Agent(
+    messages=[
+        {"role": "user", "content": [{"text": "My name is Alice"}]},
+        {"role": "assistant", "content": [{"text": "Nice to meet you, Alice!"}]}
+    ],
+    state={"user_preference": "dark_mode"}
+)
+response = agent("What's my name?")  # Agent remembers: "Your name is Alice"
+```
+
+## Async Streaming
+
+```python
+from strands import Agent
+import asyncio
+
+async def stream_response():
+    agent = Agent()
+    async for event in agent.stream_async("Tell me a story"):
+        if "data" in event:
+            print(event["data"], end="", flush=True)
+
+asyncio.run(stream_response())
+```