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npentrel
282 lines
8.2 KiB
Plaintext
282 lines
8.2 KiB
Plaintext
<CodeGroup>
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```python Google
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from langchain.agents.middleware import wrap_tool_call
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from langchain.tools import tool
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from deepagents import create_deep_agent
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@tool
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def get_weather(city: str) -> str:
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"""Get the weather in a city."""
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return f"The weather in {city} is sunny."
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call_count = [0] # Use list to allow modification in nested function
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@wrap_tool_call
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def log_tool_calls(request, handler):
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"""Intercept and log every tool call - demonstrates cross-cutting concern."""
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call_count[0] += 1
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tool_name = request.name if hasattr(request, "name") else str(request)
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print(f"[Middleware] Tool call #{call_count[0]}: {tool_name}")
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print(f"[Middleware] Arguments: {request.args if hasattr(request, 'args') else 'N/A'}")
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# Execute the tool call
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result = handler(request)
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# Log the result
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print(f"[Middleware] Tool call #{call_count[0]} completed")
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return result
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agent = create_deep_agent(
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model="google_genai:gemini-3.6-flash",
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tools=[get_weather],
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middleware=[log_tool_calls],
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)
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```
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```python OpenAI
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from langchain.agents.middleware import wrap_tool_call
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from langchain.tools import tool
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from deepagents import create_deep_agent
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@tool
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def get_weather(city: str) -> str:
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"""Get the weather in a city."""
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return f"The weather in {city} is sunny."
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call_count = [0] # Use list to allow modification in nested function
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@wrap_tool_call
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def log_tool_calls(request, handler):
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"""Intercept and log every tool call - demonstrates cross-cutting concern."""
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call_count[0] += 1
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tool_name = request.name if hasattr(request, "name") else str(request)
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print(f"[Middleware] Tool call #{call_count[0]}: {tool_name}")
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print(f"[Middleware] Arguments: {request.args if hasattr(request, 'args') else 'N/A'}")
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# Execute the tool call
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result = handler(request)
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# Log the result
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print(f"[Middleware] Tool call #{call_count[0]} completed")
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return result
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agent = create_deep_agent(
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model="openai:gpt-5.5",
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tools=[get_weather],
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middleware=[log_tool_calls],
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)
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```
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```python Anthropic
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from langchain.agents.middleware import wrap_tool_call
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from langchain.tools import tool
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from deepagents import create_deep_agent
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@tool
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def get_weather(city: str) -> str:
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"""Get the weather in a city."""
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return f"The weather in {city} is sunny."
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call_count = [0] # Use list to allow modification in nested function
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@wrap_tool_call
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def log_tool_calls(request, handler):
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"""Intercept and log every tool call - demonstrates cross-cutting concern."""
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call_count[0] += 1
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tool_name = request.name if hasattr(request, "name") else str(request)
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print(f"[Middleware] Tool call #{call_count[0]}: {tool_name}")
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print(f"[Middleware] Arguments: {request.args if hasattr(request, 'args') else 'N/A'}")
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# Execute the tool call
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result = handler(request)
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# Log the result
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print(f"[Middleware] Tool call #{call_count[0]} completed")
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return result
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agent = create_deep_agent(
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model="anthropic:claude-sonnet-4-6",
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tools=[get_weather],
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middleware=[log_tool_calls],
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)
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```
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```python OpenRouter
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from langchain.agents.middleware import wrap_tool_call
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from langchain.tools import tool
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from deepagents import create_deep_agent
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@tool
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def get_weather(city: str) -> str:
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"""Get the weather in a city."""
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return f"The weather in {city} is sunny."
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call_count = [0] # Use list to allow modification in nested function
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@wrap_tool_call
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def log_tool_calls(request, handler):
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"""Intercept and log every tool call - demonstrates cross-cutting concern."""
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call_count[0] += 1
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tool_name = request.name if hasattr(request, "name") else str(request)
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print(f"[Middleware] Tool call #{call_count[0]}: {tool_name}")
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print(f"[Middleware] Arguments: {request.args if hasattr(request, 'args') else 'N/A'}")
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# Execute the tool call
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result = handler(request)
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# Log the result
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print(f"[Middleware] Tool call #{call_count[0]} completed")
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return result
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agent = create_deep_agent(
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model="openrouter:z-ai/glm-5.2",
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tools=[get_weather],
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middleware=[log_tool_calls],
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)
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```
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```python Fireworks
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from langchain.agents.middleware import wrap_tool_call
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from langchain.tools import tool
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from deepagents import create_deep_agent
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@tool
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def get_weather(city: str) -> str:
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"""Get the weather in a city."""
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return f"The weather in {city} is sunny."
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call_count = [0] # Use list to allow modification in nested function
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@wrap_tool_call
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def log_tool_calls(request, handler):
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"""Intercept and log every tool call - demonstrates cross-cutting concern."""
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call_count[0] += 1
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tool_name = request.name if hasattr(request, "name") else str(request)
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print(f"[Middleware] Tool call #{call_count[0]}: {tool_name}")
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print(f"[Middleware] Arguments: {request.args if hasattr(request, 'args') else 'N/A'}")
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# Execute the tool call
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result = handler(request)
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# Log the result
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print(f"[Middleware] Tool call #{call_count[0]} completed")
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return result
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agent = create_deep_agent(
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model="fireworks:accounts/fireworks/models/glm-5p2",
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tools=[get_weather],
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middleware=[log_tool_calls],
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)
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```
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```python Baseten
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from langchain.agents.middleware import wrap_tool_call
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from langchain.tools import tool
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from deepagents import create_deep_agent
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@tool
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def get_weather(city: str) -> str:
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"""Get the weather in a city."""
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return f"The weather in {city} is sunny."
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call_count = [0] # Use list to allow modification in nested function
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@wrap_tool_call
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def log_tool_calls(request, handler):
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"""Intercept and log every tool call - demonstrates cross-cutting concern."""
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call_count[0] += 1
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tool_name = request.name if hasattr(request, "name") else str(request)
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print(f"[Middleware] Tool call #{call_count[0]}: {tool_name}")
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print(f"[Middleware] Arguments: {request.args if hasattr(request, 'args') else 'N/A'}")
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# Execute the tool call
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result = handler(request)
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# Log the result
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print(f"[Middleware] Tool call #{call_count[0]} completed")
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return result
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agent = create_deep_agent(
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model="baseten:zai-org/GLM-5.2",
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tools=[get_weather],
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middleware=[log_tool_calls],
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)
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```
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```python Ollama
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from langchain.agents.middleware import wrap_tool_call
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from langchain.tools import tool
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from deepagents import create_deep_agent
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@tool
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def get_weather(city: str) -> str:
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"""Get the weather in a city."""
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return f"The weather in {city} is sunny."
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call_count = [0] # Use list to allow modification in nested function
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@wrap_tool_call
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def log_tool_calls(request, handler):
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"""Intercept and log every tool call - demonstrates cross-cutting concern."""
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call_count[0] += 1
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tool_name = request.name if hasattr(request, "name") else str(request)
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print(f"[Middleware] Tool call #{call_count[0]}: {tool_name}")
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print(f"[Middleware] Arguments: {request.args if hasattr(request, 'args') else 'N/A'}")
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# Execute the tool call
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result = handler(request)
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# Log the result
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print(f"[Middleware] Tool call #{call_count[0]} completed")
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return result
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agent = create_deep_agent(
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model="ollama:north-mini-code-1.0",
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tools=[get_weather],
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middleware=[log_tool_calls],
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)
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```
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</CodeGroup>
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