# serializer version: 1
# name: test_conditional_state_graph[memory]
  '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"additionalProperties": true, "title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "title": "Agent Outcome"}, "intermediate_steps": {"items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "title": "AgentState", "type": "object"}'
# ---
# name: test_conditional_state_graph[memory].1
  '{"$defs": {"AgentAction": {"description": "Represents a request to execute an action by an agent.\\n\\nThe action consists of the name of the tool to execute and the input to pass\\nto the tool. The log is used to pass along extra information about the action.", "properties": {"tool": {"title": "Tool", "type": "string"}, "tool_input": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}], "title": "Tool Input"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentAction", "default": "AgentAction", "title": "Type", "type": "string"}}, "required": ["tool", "tool_input", "log"], "title": "AgentAction", "type": "object"}, "AgentFinish": {"description": "Final return value of an ActionAgent.\\n\\nAgents return an AgentFinish when they have reached a stopping condition.", "properties": {"return_values": {"additionalProperties": true, "title": "Return Values", "type": "object"}, "log": {"title": "Log", "type": "string"}, "type": {"const": "AgentFinish", "default": "AgentFinish", "title": "Type", "type": "string"}}, "required": ["return_values", "log"], "title": "AgentFinish", "type": "object"}}, "properties": {"input": {"title": "Input", "type": "string"}, "agent_outcome": {"anyOf": [{"$ref": "#/$defs/AgentAction"}, {"$ref": "#/$defs/AgentFinish"}, {"type": "null"}], "title": "Agent Outcome"}, "intermediate_steps": {"items": {"maxItems": 2, "minItems": 2, "prefixItems": [{"$ref": "#/$defs/AgentAction"}, {"type": "string"}], "type": "array"}, "title": "Intermediate Steps", "type": "array"}}, "title": "AgentState", "type": "object"}'
# ---
# name: test_conditional_state_graph[memory].2
  '''
  {
    "nodes": [
      {
        "id": "__start__",
        "type": "runnable",
        "data": {
          "id": [
            "langgraph",
            "_internal",
            "_runnable",
            "RunnableCallable"
          ],
          "name": "__start__"
        }
      },
      {
        "id": "agent",
        "type": "runnable",
        "data": {
          "id": [
            "langchain",
            "schema",
            "runnable",
            "RunnableSequence"
          ],
          "name": "agent"
        }
      },
      {
        "id": "tools",
        "type": "runnable",
        "data": {
          "id": [
            "langgraph",
            "_internal",
            "_runnable",
            "RunnableCallable"
          ],
          "name": "tools"
        }
      },
      {
        "id": "__end__"
      }
    ],
    "edges": [
      {
        "source": "__start__",
        "target": "agent"
      },
      {
        "source": "agent",
        "target": "__end__",
        "data": "exit",
        "conditional": true
      },
      {
        "source": "agent",
        "target": "tools",
        "data": "continue",
        "conditional": true
      },
      {
        "source": "tools",
        "target": "agent"
      }
    ]
  }
  '''
# ---
# name: test_conditional_state_graph[memory].3
  '''
  graph TD;
  	__start__ --> agent;
  	agent -. &nbsp;exit&nbsp; .-> __end__;
  	agent -. &nbsp;continue&nbsp; .-> tools;
  	tools --> agent;
  
  '''
# ---
# name: test_message_graph[memory]
  '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAn `AIMessage` is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model and standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI (yielded when streaming).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`FunctionMessage` are an older version of the `ToolMessage` schema, and\\ndo not contain the `tool_call_id` field.\\n\\nThe `tool_call_id` field is used to associate the tool call request with the\\ntool call response. Useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from the user.\\n\\nA `HumanMessage` is a message that is passed in from a user to the model.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Instantiate a chat model and invoke it with the messages\\n    model = ...\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"additionalProperties": true, "description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"cache_creation\\": 200,\\n        \\"cache_read\\": 100,\\n    }\\n    ```\\n\\nMay also hold extra provider-specific keys.\\n\\n!!! version-added \\"Added in `langchain-core` 0.3.9\\"", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"additionalProperties": true, "description": "Allowance for errors made by LLM.\\n\\nHere we add an `error` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"additionalProperties": true, "description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"reasoning\\": 200,\\n    }\\n    ```\\n\\nMay also hold extra provider-specific keys.\\n\\n!!! version-added \\"Added in `langchain-core` 0.3.9\\"", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Define a chat model and invoke it with the messages\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"additionalProperties": true, "description": "Represents an AI\'s request to call a tool.\\n\\nExample:\\n    ```python\\n    {\\"name\\": \\"foo\\", \\"args\\": {\\"a\\": 1}, \\"id\\": \\"123\\"}\\n    ```\\n\\n    This represents a request to call the tool named `\'foo\'` with arguments\\n    `{\\"a\\": 1}` and an identifier of `\'123\'`.\\n\\n!!! note \\"Factory function\\"\\n\\n    `tool_call` may also be used as a factory to create a `ToolCall`. Benefits\\n    include:\\n\\n    * Required arguments strictly validated at creation time", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"additionalProperties": true, "description": "A chunk of a tool call (yielded when streaming).\\n\\nWhen merging `ToolCallChunk` objects (e.g., via `AIMessageChunk.__add__`), all\\nstring attributes are concatenated. Chunks are only merged if their values of\\n`index` are equal and not `None`.\\n\\nExample:\\n```python\\nleft_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\nright_chunks = [ToolCallChunk(name=None, args=\\"1}\\", index=0)]\\n\\n(\\n    AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n    + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n).tool_call_chunks == [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":1}\', index=0)]\\n```", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`ToolMessage` objects contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\n`tool_call_id` is used to associate the tool call request with the tool call\\nresponse. Useful in situations where a chat model is able to request multiple tool\\ncalls in parallel.\\n\\nExample:\\n    A `ToolMessage` representing a result of `42` from a tool call with id\\n\\n    ```python\\n    from langchain_core.messages import ToolMessage\\n\\n    ToolMessage(content=\\"42\\", tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\")\\n    ```\\n\\nExample:\\n    A `ToolMessage` where only part of the tool output is sent to the model\\n    and the full output is passed in to artifact.\\n\\n    ```python\\n    from langchain_core.messages import ToolMessage\\n\\n    tool_output = {\\n        \\"stdout\\": \\"From the graph we can see that the correlation between \\"\\n        \\"x and y is ...\\",\\n        \\"stderr\\": None,\\n        \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n    }\\n\\n    ToolMessage(\\n        content=tool_output[\\"stdout\\"],\\n        artifact=tool_output,\\n        tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\",\\n    )\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"additionalProperties": true, "description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n    ```python\\n    {\\n        \\"input_tokens\\": 350,\\n        \\"output_tokens\\": 240,\\n        \\"total_tokens\\": 590,\\n        \\"input_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"cache_creation\\": 200,\\n            \\"cache_read\\": 100,\\n        },\\n        \\"output_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"reasoning\\": 200,\\n        },\\n    }\\n    ```\\n\\n!!! warning \\"Behavior changed in `langchain-core` 0.3.9\\"\\n\\n    Added `input_token_details` and `output_token_details`.\\n\\n!!! note \\"LangSmith SDK\\"\\n\\n    The LangSmith SDK also has a `UsageMetadata` class. While the two share fields,\\n    LangSmith\'s `UsageMetadata` has additional fields to capture cost information\\n    used by the LangSmith platform.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphInput", "type": "array"}'
# ---
# name: test_message_graph[memory].1
  '{"$defs": {"AIMessage": {"additionalProperties": true, "description": "Message from an AI.\\n\\nAn `AIMessage` is returned from a chat model as a response to a prompt.\\n\\nThis message represents the output of the model and consists of both\\nthe raw output as returned by the model and standardized fields\\n(e.g., tool calls, usage metadata) added by the LangChain framework.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ai", "default": "ai", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}}, "required": ["content"], "title": "AIMessage", "type": "object"}, "AIMessageChunk": {"additionalProperties": true, "description": "Message chunk from an AI (yielded when streaming).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "AIMessageChunk", "default": "AIMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_calls": {"items": {"$ref": "#/$defs/ToolCall"}, "title": "Tool Calls", "type": "array"}, "invalid_tool_calls": {"items": {"$ref": "#/$defs/InvalidToolCall"}, "title": "Invalid Tool Calls", "type": "array"}, "usage_metadata": {"anyOf": [{"$ref": "#/$defs/UsageMetadata"}, {"type": "null"}], "default": null}, "tool_call_chunks": {"items": {"$ref": "#/$defs/ToolCallChunk"}, "title": "Tool Call Chunks", "type": "array"}, "chunk_position": {"anyOf": [{"const": "last", "type": "string"}, {"type": "null"}], "default": null, "title": "Chunk Position"}}, "required": ["content"], "title": "AIMessageChunk", "type": "object"}, "ChatMessage": {"additionalProperties": true, "description": "Message that can be assigned an arbitrary speaker (i.e. role).", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "chat", "default": "chat", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessage", "type": "object"}, "ChatMessageChunk": {"additionalProperties": true, "description": "Chat Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ChatMessageChunk", "default": "ChatMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "role": {"title": "Role", "type": "string"}}, "required": ["content", "role"], "title": "ChatMessageChunk", "type": "object"}, "FunctionMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`FunctionMessage` are an older version of the `ToolMessage` schema, and\\ndo not contain the `tool_call_id` field.\\n\\nThe `tool_call_id` field is used to associate the tool call request with the\\ntool call response. Useful in situations where a chat model is able\\nto request multiple tool calls in parallel.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "function", "default": "function", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessage", "type": "object"}, "FunctionMessageChunk": {"additionalProperties": true, "description": "Function Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "FunctionMessageChunk", "default": "FunctionMessageChunk", "title": "Type", "type": "string"}, "name": {"title": "Name", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "name"], "title": "FunctionMessageChunk", "type": "object"}, "HumanMessage": {"additionalProperties": true, "description": "Message from the user.\\n\\nA `HumanMessage` is a message that is passed in from a user to the model.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Instantiate a chat model and invoke it with the messages\\n    model = ...\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "human", "default": "human", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessage", "type": "object"}, "HumanMessageChunk": {"additionalProperties": true, "description": "Human Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "HumanMessageChunk", "default": "HumanMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "HumanMessageChunk", "type": "object"}, "InputTokenDetails": {"additionalProperties": true, "description": "Breakdown of input token counts.\\n\\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"cache_creation\\": 200,\\n        \\"cache_read\\": 100,\\n    }\\n    ```\\n\\nMay also hold extra provider-specific keys.\\n\\n!!! version-added \\"Added in `langchain-core` 0.3.9\\"", "properties": {"audio": {"title": "Audio", "type": "integer"}, "cache_creation": {"title": "Cache Creation", "type": "integer"}, "cache_read": {"title": "Cache Read", "type": "integer"}}, "title": "InputTokenDetails", "type": "object"}, "InvalidToolCall": {"additionalProperties": true, "description": "Allowance for errors made by LLM.\\n\\nHere we add an `error` key to surface errors made during generation\\n(e.g., invalid JSON arguments.)", "properties": {"type": {"const": "invalid_tool_call", "title": "Type", "type": "string"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "error": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Error"}, "index": {"anyOf": [{"type": "integer"}, {"type": "string"}], "title": "Index"}, "extras": {"additionalProperties": true, "title": "Extras", "type": "object"}}, "required": ["type", "id", "name", "args", "error"], "title": "InvalidToolCall", "type": "object"}, "OutputTokenDetails": {"additionalProperties": true, "description": "Breakdown of output token counts.\\n\\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\\n\\nExample:\\n    ```python\\n    {\\n        \\"audio\\": 10,\\n        \\"reasoning\\": 200,\\n    }\\n    ```\\n\\nMay also hold extra provider-specific keys.\\n\\n!!! version-added \\"Added in `langchain-core` 0.3.9\\"", "properties": {"audio": {"title": "Audio", "type": "integer"}, "reasoning": {"title": "Reasoning", "type": "integer"}}, "title": "OutputTokenDetails", "type": "object"}, "SystemMessage": {"additionalProperties": true, "description": "Message for priming AI behavior.\\n\\nThe system message is usually passed in as the first of a sequence\\nof input messages.\\n\\nExample:\\n    ```python\\n    from langchain_core.messages import HumanMessage, SystemMessage\\n\\n    messages = [\\n        SystemMessage(content=\\"You are a helpful assistant! Your name is Bob.\\"),\\n        HumanMessage(content=\\"What is your name?\\"),\\n    ]\\n\\n    # Define a chat model and invoke it with the messages\\n    print(model.invoke(messages))\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "system", "default": "system", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessage", "type": "object"}, "SystemMessageChunk": {"additionalProperties": true, "description": "System Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "SystemMessageChunk", "default": "SystemMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content"], "title": "SystemMessageChunk", "type": "object"}, "ToolCall": {"additionalProperties": true, "description": "Represents an AI\'s request to call a tool.\\n\\nExample:\\n    ```python\\n    {\\"name\\": \\"foo\\", \\"args\\": {\\"a\\": 1}, \\"id\\": \\"123\\"}\\n    ```\\n\\n    This represents a request to call the tool named `\'foo\'` with arguments\\n    `{\\"a\\": 1}` and an identifier of `\'123\'`.\\n\\n!!! note \\"Factory function\\"\\n\\n    `tool_call` may also be used as a factory to create a `ToolCall`. Benefits\\n    include:\\n\\n    * Required arguments strictly validated at creation time", "properties": {"name": {"title": "Name", "type": "string"}, "args": {"additionalProperties": true, "title": "Args", "type": "object"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "type": {"const": "tool_call", "title": "Type", "type": "string"}}, "required": ["name", "args", "id"], "title": "ToolCall", "type": "object"}, "ToolCallChunk": {"additionalProperties": true, "description": "A chunk of a tool call (yielded when streaming).\\n\\nWhen merging `ToolCallChunk` objects (e.g., via `AIMessageChunk.__add__`), all\\nstring attributes are concatenated. Chunks are only merged if their values of\\n`index` are equal and not `None`.\\n\\nExample:\\n```python\\nleft_chunks = [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":\', index=0)]\\nright_chunks = [ToolCallChunk(name=None, args=\\"1}\\", index=0)]\\n\\n(\\n    AIMessageChunk(content=\\"\\", tool_call_chunks=left_chunks)\\n    + AIMessageChunk(content=\\"\\", tool_call_chunks=right_chunks)\\n).tool_call_chunks == [ToolCallChunk(name=\\"foo\\", args=\'{\\"a\\":1}\', index=0)]\\n```", "properties": {"name": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Name"}, "args": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Args"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Id"}, "index": {"anyOf": [{"type": "integer"}, {"type": "null"}], "title": "Index"}, "type": {"const": "tool_call_chunk", "title": "Type", "type": "string"}}, "required": ["name", "args", "id", "index"], "title": "ToolCallChunk", "type": "object"}, "ToolMessage": {"additionalProperties": true, "description": "Message for passing the result of executing a tool back to a model.\\n\\n`ToolMessage` objects contain the result of a tool invocation. Typically, the result\\nis encoded inside the `content` field.\\n\\n`tool_call_id` is used to associate the tool call request with the tool call\\nresponse. Useful in situations where a chat model is able to request multiple tool\\ncalls in parallel.\\n\\nExample:\\n    A `ToolMessage` representing a result of `42` from a tool call with id\\n\\n    ```python\\n    from langchain_core.messages import ToolMessage\\n\\n    ToolMessage(content=\\"42\\", tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\")\\n    ```\\n\\nExample:\\n    A `ToolMessage` where only part of the tool output is sent to the model\\n    and the full output is passed in to artifact.\\n\\n    ```python\\n    from langchain_core.messages import ToolMessage\\n\\n    tool_output = {\\n        \\"stdout\\": \\"From the graph we can see that the correlation between \\"\\n        \\"x and y is ...\\",\\n        \\"stderr\\": None,\\n        \\"artifacts\\": {\\"type\\": \\"image\\", \\"base64_data\\": \\"/9j/4gIcSU...\\"},\\n    }\\n\\n    ToolMessage(\\n        content=tool_output[\\"stdout\\"],\\n        artifact=tool_output,\\n        tool_call_id=\\"call_Jja7J89XsjrOLA5r!MEOW!SL\\",\\n    )\\n    ```", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "tool", "default": "tool", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessage", "type": "object"}, "ToolMessageChunk": {"additionalProperties": true, "description": "Tool Message chunk.", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"const": "ToolMessageChunk", "default": "ToolMessageChunk", "title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}, "tool_call_id": {"title": "Tool Call Id", "type": "string"}, "artifact": {"default": null, "title": "Artifact"}, "status": {"default": "success", "enum": ["success", "error"], "title": "Status", "type": "string"}}, "required": ["content", "tool_call_id"], "title": "ToolMessageChunk", "type": "object"}, "UsageMetadata": {"additionalProperties": true, "description": "Usage metadata for a message, such as token counts.\\n\\nThis is a standard representation of token usage that is consistent across models.\\n\\nExample:\\n    ```python\\n    {\\n        \\"input_tokens\\": 350,\\n        \\"output_tokens\\": 240,\\n        \\"total_tokens\\": 590,\\n        \\"input_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"cache_creation\\": 200,\\n            \\"cache_read\\": 100,\\n        },\\n        \\"output_token_details\\": {\\n            \\"audio\\": 10,\\n            \\"reasoning\\": 200,\\n        },\\n    }\\n    ```\\n\\n!!! warning \\"Behavior changed in `langchain-core` 0.3.9\\"\\n\\n    Added `input_token_details` and `output_token_details`.\\n\\n!!! note \\"LangSmith SDK\\"\\n\\n    The LangSmith SDK also has a `UsageMetadata` class. While the two share fields,\\n    LangSmith\'s `UsageMetadata` has additional fields to capture cost information\\n    used by the LangSmith platform.", "properties": {"input_tokens": {"title": "Input Tokens", "type": "integer"}, "output_tokens": {"title": "Output Tokens", "type": "integer"}, "total_tokens": {"title": "Total Tokens", "type": "integer"}, "input_token_details": {"$ref": "#/$defs/InputTokenDetails"}, "output_token_details": {"$ref": "#/$defs/OutputTokenDetails"}}, "required": ["input_tokens", "output_tokens", "total_tokens"], "title": "UsageMetadata", "type": "object"}}, "default": null, "items": {"oneOf": [{"$ref": "#/$defs/AIMessage"}, {"$ref": "#/$defs/HumanMessage"}, {"$ref": "#/$defs/ChatMessage"}, {"$ref": "#/$defs/SystemMessage"}, {"$ref": "#/$defs/FunctionMessage"}, {"$ref": "#/$defs/ToolMessage"}, {"$ref": "#/$defs/AIMessageChunk"}, {"$ref": "#/$defs/HumanMessageChunk"}, {"$ref": "#/$defs/ChatMessageChunk"}, {"$ref": "#/$defs/SystemMessageChunk"}, {"$ref": "#/$defs/FunctionMessageChunk"}, {"$ref": "#/$defs/ToolMessageChunk"}]}, "title": "LangGraphOutput", "type": "array"}'
# ---
# name: test_message_graph[memory].2
  '''
  {
    "nodes": [
      {
        "id": "__start__",
        "type": "runnable",
        "data": {
          "id": [
            "langgraph",
            "_internal",
            "_runnable",
            "RunnableCallable"
          ],
          "name": "__start__"
        }
      },
      {
        "id": "agent",
        "type": "runnable",
        "data": {
          "id": [
            "tests",
            "test_large_cases",
            "FakeFunctionChatModel"
          ],
          "name": "agent"
        }
      },
      {
        "id": "tools",
        "type": "runnable",
        "data": {
          "id": [
            "langgraph",
            "prebuilt",
            "tool_node",
            "ToolNode"
          ],
          "name": "tools"
        }
      },
      {
        "id": "__end__"
      }
    ],
    "edges": [
      {
        "source": "__start__",
        "target": "agent"
      },
      {
        "source": "agent",
        "target": "__end__",
        "data": "end",
        "conditional": true
      },
      {
        "source": "agent",
        "target": "tools",
        "data": "continue",
        "conditional": true
      },
      {
        "source": "tools",
        "target": "agent"
      }
    ]
  }
  '''
# ---
# name: test_message_graph[memory].3
  '''
  graph TD;
  	__start__ --> agent;
  	agent -. &nbsp;end&nbsp; .-> __end__;
  	agent -. &nbsp;continue&nbsp; .-> tools;
  	tools --> agent;
  
  '''
# ---
# name: test_prebuilt_tool_chat
  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of a chat model.\\n\\nExamples include [`HumanMessage`][langchain.messages.HumanMessage],\\n[`AIMessage`][langchain.messages.AIMessage], and\\n[`SystemMessage`][langchain.messages.SystemMessage].", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "deprecated": true, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
# ---
# name: test_prebuilt_tool_chat.1
  '{"$defs": {"BaseMessage": {"additionalProperties": true, "description": "Base abstract message class.\\n\\nMessages are the inputs and outputs of a chat model.\\n\\nExamples include [`HumanMessage`][langchain.messages.HumanMessage],\\n[`AIMessage`][langchain.messages.AIMessage], and\\n[`SystemMessage`][langchain.messages.SystemMessage].", "properties": {"content": {"anyOf": [{"type": "string"}, {"items": {"anyOf": [{"type": "string"}, {"additionalProperties": true, "type": "object"}]}, "type": "array"}], "title": "Content"}, "additional_kwargs": {"additionalProperties": true, "title": "Additional Kwargs", "type": "object"}, "response_metadata": {"additionalProperties": true, "title": "Response Metadata", "type": "object"}, "type": {"title": "Type", "type": "string"}, "name": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Name"}, "id": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": null, "title": "Id"}}, "required": ["content", "type"], "title": "BaseMessage", "type": "object"}}, "deprecated": true, "description": "The state of the agent.", "properties": {"messages": {"items": {"$ref": "#/$defs/BaseMessage"}, "title": "Messages", "type": "array"}, "remaining_steps": {"title": "Remaining Steps", "type": "integer"}}, "required": ["messages"], "title": "AgentState", "type": "object"}'
# ---
# name: test_prebuilt_tool_chat.2
  '''
  {
    "nodes": [
      {
        "id": "__start__",
        "type": "runnable",
        "data": {
          "id": [
            "langgraph",
            "_internal",
            "_runnable",
            "RunnableCallable"
          ],
          "name": "__start__"
        }
      },
      {
        "id": "agent",
        "type": "runnable",
        "data": {
          "id": [
            "langgraph",
            "_internal",
            "_runnable",
            "RunnableCallable"
          ],
          "name": "agent"
        }
      },
      {
        "id": "tools",
        "type": "runnable",
        "data": {
          "id": [
            "langgraph",
            "prebuilt",
            "tool_node",
            "ToolNode"
          ],
          "name": "tools"
        }
      },
      {
        "id": "__end__"
      }
    ],
    "edges": [
      {
        "source": "__start__",
        "target": "agent"
      },
      {
        "source": "agent",
        "target": "__end__",
        "conditional": true
      },
      {
        "source": "agent",
        "target": "tools",
        "conditional": true
      },
      {
        "source": "tools",
        "target": "agent"
      }
    ]
  }
  '''
# ---
# name: test_prebuilt_tool_chat.3
  '''
  graph TD;
  	__start__ --> agent;
  	agent -.-> __end__;
  	agent -.-> tools;
  	tools --> agent;
  
  '''
# ---
# name: test_send_react_interrupt_control[memory]
  '''
  ---
  config:
    flowchart:
      curve: linear
  ---
  graph TD;
  	__start__([<p>__start__</p>]):::first
  	agent(agent)
  	foo(foo)
  	__end__([<p>__end__</p>]):::last
  	__start__ --> agent;
  	agent -.-> foo;
  	foo --> __end__;
  	classDef default fill:#f2f0ff,line-height:1.2
  	classDef first fill-opacity:0
  	classDef last fill:#bfb6fc
  
  '''
# ---
# name: test_weather_subgraph[memory]
  '''
  ---
  config:
    flowchart:
      curve: linear
  ---
  graph TD;
  	__start__([<p>__start__</p>]):::first
  	router_node(router_node)
  	normal_llm_node(normal_llm_node)
  	__end__([<p>__end__</p>]):::last
  	__start__ --> router_node;
  	router_node -.-> normal_llm_node;
  	router_node -.-> weather_graph\3amodel_node;
  	normal_llm_node --> __end__;
  	weather_graph\3aweather_node --> __end__;
  	subgraph weather_graph
  	weather_graph\3amodel_node(model_node)
  	weather_graph\3aweather_node(weather_node<hr/><small><em>__interrupt = before</em></small>)
  	weather_graph\3amodel_node --> weather_graph\3aweather_node;
  	end
  	classDef default fill:#f2f0ff,line-height:1.2
  	classDef first fill-opacity:0
  	classDef last fill:#bfb6fc
  
  '''
# ---
