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Replace hardcoded model IDs with Agent() defaults #326

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Replace hardcoded model IDs with Agent() defaults #326

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2 changes: 1 addition & 1 deletion docs/user-guide/concepts/agents/conversation-management.md
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Original file line number Diff line number Diff line change
Expand Up @@ -153,7 +153,7 @@ summarization_model = AnthropicModel(
max_tokens=1000,
params={"temperature": 0.1} # Low temperature for consistent summaries
)
custom_summarization_agent = Agent(model=summarization_model)
custom_summarization_agent = Agent()

conversation_manager = SummarizingConversationManager(
summary_ratio=0.4,
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9 changes: 2 additions & 7 deletions docs/user-guide/observability-evaluation/evaluation.md
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Expand Up @@ -68,7 +68,6 @@ from strands_tools import calculator

# Create agent with specific configuration
agent = Agent(
model="us.anthropic.claude-sonnet-4-20250514-v1:0",
system_prompt="You are a helpful assistant specialized in data analysis.",
tools=[calculator]
)
Expand All @@ -94,7 +93,7 @@ with open("test_cases.json", "r") as f:
test_cases = json.load(f)

# Create agent
agent = Agent(model="us.anthropic.claude-sonnet-4-20250514-v1:0")
agent = Agent()

# Run tests and collect results
results = []
Expand Down Expand Up @@ -134,11 +133,10 @@ from strands import Agent
import json

# Create the agent to evaluate
agent = Agent(model="anthropic.claude-3-5-sonnet-20241022-v2:0")
agent = Agent()

# Create an evaluator agent with a stronger model
evaluator = Agent(
model="us.anthropic.claude-sonnet-4-20250514-v1:0",
system_prompt="""
You are an expert AI evaluator. Your job is to assess the quality of AI responses based on:
1. Accuracy - factual correctness of the response
Expand Down Expand Up @@ -199,7 +197,6 @@ from strands import Agent
from strands_tools import calculator, file_read, current_time
# Create agent with multiple tools
agent = Agent(
model="us.anthropic.claude-sonnet-4-20250514-v1:0",
tools=[calculator, file_read, current_time],
record_direct_tool_call = True
)
Expand Down Expand Up @@ -322,12 +319,10 @@ class AgentEvaluator:
if __name__ == "__main__":
# Create agents with different configurations
agent1 = Agent(
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
system_prompt="You are a helpful assistant."
)

agent2 = Agent(
model="anthropic.claude-3-5-haiku-20241022-v1:0",
system_prompt="You are a helpful assistant."
)

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1 change: 0 additions & 1 deletion docs/user-guide/observability-evaluation/logs.md
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Expand Up @@ -159,7 +159,6 @@ The callback system is configured through the `callback_handler` parameter when
from strands.handlers.callback_handler import PrintingCallbackHandler

agent = Agent(
model="anthropic.claude-3-sonnet-20240229-v1:0",
callback_handler=PrintingCallbackHandler()
)
```
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3 changes: 0 additions & 3 deletions docs/user-guide/observability-evaluation/traces.md
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Expand Up @@ -110,7 +110,6 @@ from strands import Agent
# Option 1: Skip StrandsTelemetry if global tracer provider and/or meter provider are already configured
# (your existing OpenTelemetry setup will be used automatically)
agent = Agent(
model="us.anthropic.claude-sonnet-4-20250514-v1:0",
system_prompt="You are a helpful AI assistant"
)

Expand All @@ -135,7 +134,6 @@ strands_telemetry.setup_otlp_exporter().setup_console_exporter() # Chaining sup

# Create agent (tracing will be enabled automatically)
agent = Agent(
model="us.anthropic.claude-sonnet-4-20250514-v1:0",
system_prompt="You are a helpful AI assistant"
)

Expand Down Expand Up @@ -374,7 +372,6 @@ strands_telemetry.setup_console_exporter() # Print traces to console

# Create agent
agent = Agent(
model="us.anthropic.claude-sonnet-4-20250514-v1:0",
system_prompt="You are a helpful AI assistant"
)

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