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npentrel
233 lines
8.5 KiB
Plaintext
233 lines
8.5 KiB
Plaintext
<CodeGroup>
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```python Google
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from langchain.agents import create_agent
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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def get_weather(city: str) -> str:
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"""Get weather for a given city."""
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return f"It's always sunny in {city}!"
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agent = create_agent(
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model="google_genai:gemini-3.6-flash",
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tools=[get_weather],
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checkpointer=InMemorySaver()
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)
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config = {"configurable": {"thread_id": str(uuid7())}}
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stream = agent.stream_events( # [!code highlight]
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{"messages": [{"role": "user", "content": "What is the weather in SF?"}]},
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config=config,
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version="v3", # [!code highlight]
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)
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for kind, item in stream.interleave("messages", "tool_calls"): # [!code highlight]
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if kind == "messages":
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for token in item.text:
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print(token, end="", flush=True)
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elif kind == "tool_calls":
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print(f"\nTool call: {item.tool_name}({item.input})")
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for delta in item.output_deltas:
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print(delta, end="", flush=True)
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print(f"\nTool result: {item.output}")
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final_state = stream.output # [!code highlight]
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```
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```python OpenAI
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from langchain.agents import create_agent
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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def get_weather(city: str) -> str:
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"""Get weather for a given city."""
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return f"It's always sunny in {city}!"
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agent = create_agent(
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model="openai:gpt-5.5",
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tools=[get_weather],
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checkpointer=InMemorySaver()
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)
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config = {"configurable": {"thread_id": str(uuid7())}}
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stream = agent.stream_events( # [!code highlight]
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{"messages": [{"role": "user", "content": "What is the weather in SF?"}]},
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config=config,
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version="v3", # [!code highlight]
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)
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for kind, item in stream.interleave("messages", "tool_calls"): # [!code highlight]
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if kind == "messages":
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for token in item.text:
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print(token, end="", flush=True)
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elif kind == "tool_calls":
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print(f"\nTool call: {item.tool_name}({item.input})")
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for delta in item.output_deltas:
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print(delta, end="", flush=True)
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print(f"\nTool result: {item.output}")
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final_state = stream.output # [!code highlight]
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```
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```python Anthropic
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from langchain.agents import create_agent
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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def get_weather(city: str) -> str:
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"""Get weather for a given city."""
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return f"It's always sunny in {city}!"
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agent = create_agent(
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model="anthropic:claude-sonnet-4-6",
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tools=[get_weather],
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checkpointer=InMemorySaver()
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)
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config = {"configurable": {"thread_id": str(uuid7())}}
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stream = agent.stream_events( # [!code highlight]
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{"messages": [{"role": "user", "content": "What is the weather in SF?"}]},
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config=config,
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version="v3", # [!code highlight]
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)
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for kind, item in stream.interleave("messages", "tool_calls"): # [!code highlight]
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if kind == "messages":
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for token in item.text:
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print(token, end="", flush=True)
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elif kind == "tool_calls":
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print(f"\nTool call: {item.tool_name}({item.input})")
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for delta in item.output_deltas:
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print(delta, end="", flush=True)
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print(f"\nTool result: {item.output}")
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final_state = stream.output # [!code highlight]
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```
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```python OpenRouter
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from langchain.agents import create_agent
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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def get_weather(city: str) -> str:
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"""Get weather for a given city."""
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return f"It's always sunny in {city}!"
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agent = create_agent(
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model="openrouter:z-ai/glm-5.2",
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tools=[get_weather],
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checkpointer=InMemorySaver()
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)
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config = {"configurable": {"thread_id": str(uuid7())}}
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stream = agent.stream_events( # [!code highlight]
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{"messages": [{"role": "user", "content": "What is the weather in SF?"}]},
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config=config,
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version="v3", # [!code highlight]
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)
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for kind, item in stream.interleave("messages", "tool_calls"): # [!code highlight]
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if kind == "messages":
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for token in item.text:
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print(token, end="", flush=True)
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elif kind == "tool_calls":
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print(f"\nTool call: {item.tool_name}({item.input})")
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for delta in item.output_deltas:
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print(delta, end="", flush=True)
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print(f"\nTool result: {item.output}")
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final_state = stream.output # [!code highlight]
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```
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```python Fireworks
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from langchain.agents import create_agent
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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def get_weather(city: str) -> str:
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"""Get weather for a given city."""
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return f"It's always sunny in {city}!"
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agent = create_agent(
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model="fireworks:accounts/fireworks/models/glm-5p2",
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tools=[get_weather],
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checkpointer=InMemorySaver()
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)
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config = {"configurable": {"thread_id": str(uuid7())}}
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stream = agent.stream_events( # [!code highlight]
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{"messages": [{"role": "user", "content": "What is the weather in SF?"}]},
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config=config,
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version="v3", # [!code highlight]
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)
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for kind, item in stream.interleave("messages", "tool_calls"): # [!code highlight]
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if kind == "messages":
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for token in item.text:
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print(token, end="", flush=True)
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elif kind == "tool_calls":
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print(f"\nTool call: {item.tool_name}({item.input})")
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for delta in item.output_deltas:
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print(delta, end="", flush=True)
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print(f"\nTool result: {item.output}")
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final_state = stream.output # [!code highlight]
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```
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```python Baseten
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from langchain.agents import create_agent
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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def get_weather(city: str) -> str:
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"""Get weather for a given city."""
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return f"It's always sunny in {city}!"
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agent = create_agent(
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model="baseten:zai-org/GLM-5.2",
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tools=[get_weather],
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checkpointer=InMemorySaver()
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)
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config = {"configurable": {"thread_id": str(uuid7())}}
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stream = agent.stream_events( # [!code highlight]
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{"messages": [{"role": "user", "content": "What is the weather in SF?"}]},
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config=config,
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version="v3", # [!code highlight]
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)
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for kind, item in stream.interleave("messages", "tool_calls"): # [!code highlight]
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if kind == "messages":
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for token in item.text:
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print(token, end="", flush=True)
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elif kind == "tool_calls":
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print(f"\nTool call: {item.tool_name}({item.input})")
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for delta in item.output_deltas:
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print(delta, end="", flush=True)
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print(f"\nTool result: {item.output}")
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final_state = stream.output # [!code highlight]
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```
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```python Ollama
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from langchain.agents import create_agent
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from langchain_core.utils.uuid import uuid7
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from langgraph.checkpoint.memory import InMemorySaver
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def get_weather(city: str) -> str:
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"""Get weather for a given city."""
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return f"It's always sunny in {city}!"
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agent = create_agent(
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model="ollama:north-mini-code-1.0",
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tools=[get_weather],
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checkpointer=InMemorySaver()
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)
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config = {"configurable": {"thread_id": str(uuid7())}}
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stream = agent.stream_events( # [!code highlight]
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{"messages": [{"role": "user", "content": "What is the weather in SF?"}]},
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config=config,
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version="v3", # [!code highlight]
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)
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for kind, item in stream.interleave("messages", "tool_calls"): # [!code highlight]
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if kind == "messages":
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for token in item.text:
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print(token, end="", flush=True)
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elif kind == "tool_calls":
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print(f"\nTool call: {item.tool_name}({item.input})")
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for delta in item.output_deltas:
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print(delta, end="", flush=True)
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print(f"\nTool result: {item.output}")
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final_state = stream.output # [!code highlight]
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```
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</CodeGroup>
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