feat: restore time travel

typescript-sdk/apps/dojo/scripts/generate-content-json.ts

@@ -140,57 +140,60 @@ async function getFeatureFrontendFiles(featureId: string) {
 }
 
 const integrationsFolderPath = '../../../integrations'
-const agentFilesMapper: Record<string, (agentKeys: string[]) => Record<string, string>> = {
+const agentFilesMapper: Record<string, (agentKeys: string[]) => Record<string, string[]>> = {
   'middleware-starter': () => ({
-    agentic_chat: path.join(__dirname, integrationsFolderPath, `/middleware-starter/src/index.ts`)
+    agentic_chat: [path.join(__dirname, integrationsFolderPath, `/middleware-starter/src/index.ts`)]
   }),
   'pydantic-ai': (agentKeys: string[]) => {
     return agentKeys.reduce((acc, agentId) => ({
       ...acc,
-      [agentId]: `https://github.com/pydantic/pydantic-ai/blob/main/examples/pydantic_ai_examples/ag_ui/api/${agentId}.py`
+      [agentId]: [`https://github.com/pydantic/pydantic-ai/blob/main/examples/pydantic_ai_examples/ag_ui/api/${agentId}.py`]
     }), {})
   },
   'server-starter': () => ({
-    agentic_chat: path.join(__dirname, integrationsFolderPath, `/server-starter/server/python/example_server/__init__.py`)
+    agentic_chat: [path.join(__dirname, integrationsFolderPath, `/server-starter/server/python/example_server/__init__.py`)]
   }),
   'server-starter-all-features': (agentKeys: string[]) => {
     return agentKeys.reduce((acc, agentId) => ({
       ...acc,
-      [agentId]: path.join(__dirname, integrationsFolderPath, `/server-starter/server/python/example_server/${agentId}.py`)
+      [agentId]: [path.join(__dirname, integrationsFolderPath, `/server-starter-all-features/server/python/example_server/${agentId}.py`)]
     }), {})
   },
   'mastra': () => ({
-    agentic_chat: path.join(__dirname, integrationsFolderPath, `/mastra/example/src/mastra/agents/weather-agent.ts`)
+    agentic_chat: [path.join(__dirname, integrationsFolderPath, `/mastra/example/src/mastra/agents/weather-agent.ts`)]
   }),
   'mastra-agent-lock': () => ({
-    agentic_chat: path.join(__dirname, integrationsFolderPath, `/mastra/example/src/mastra/agents/weather-agent.ts`)
+    agentic_chat: [path.join(__dirname, integrationsFolderPath, `/mastra/example/src/mastra/agents/weather-agent.ts`)]
   }),
   'vercel-ai-sdk': () => ({
-    agentic_chat: path.join(__dirname, integrationsFolderPath, `/vercel-ai-sdk/src/index.ts`)
+    agentic_chat: [path.join(__dirname, integrationsFolderPath, `/vercel-ai-sdk/src/index.ts`)]
   }),
   'langgraph': (agentKeys: string[]) => {
     return agentKeys.reduce((acc, agentId) => ({
       ...acc,
-      [agentId]: path.join(__dirname, integrationsFolderPath, `/langgraph/examples/agents/${agentId}/agent.py`)
+      [agentId]: [
+        path.join(__dirname, integrationsFolderPath, `/langgraph/examples/python/agents/${agentId}/agent.py`),
+        path.join(__dirname, integrationsFolderPath, `/langgraph/examples/typescript/src/agents/${agentId}/agent.ts`)
+      ]
     }), {})
   },
   'langgraph-fastapi': (agentKeys: string[]) => {
     return agentKeys.reduce((acc, agentId) => ({
       ...acc,
-      [agentId]: path.join(__dirname, integrationsFolderPath, `/langgraph/python/ag_ui_langgraph/examples/agents/${agentId}.py`)
+      [agentId]: [path.join(__dirname, integrationsFolderPath, `/langgraph/examples/python/agents/${agentId}/agent.py`)]
     }), {})
   },
   'agno': () => ({}),
   'llama-index': (agentKeys: string[]) => {
     return agentKeys.reduce((acc, agentId) => ({
       ...acc,
-      [agentId]: path.join(__dirname, integrationsFolderPath, `/llamaindex/server-py/server/routers/${agentId}.py`)
+      [agentId]: [path.join(__dirname, integrationsFolderPath, `/llamaindex/server-py/server/routers/${agentId}.py`)]
     }), {})
   },
   'crewai': (agentKeys: string[]) => {
     return agentKeys.reduce((acc, agentId) => ({
       ...acc,
-      [agentId]: path.join(__dirname, integrationsFolderPath, `/crewai/python/ag_ui_crewai/examples/${agentId}.py`)
+      [agentId]: [path.join(__dirname, integrationsFolderPath, `/crewai/python/ag_ui_crewai/examples/${agentId}.py`)]
     }), {})
   }
 }
@@ -202,14 +205,16 @@ async function runGenerateContent() {
     const agentsPerFeatures = agentConfig.agentKeys
 
     const agentFilePaths = agentFilesMapper[agentConfig.id](agentConfig.agentKeys)
+
     // Per feature, assign all the frontend files like page.tsx as well as all agent files
     for (const featureId of agentsPerFeatures) {
+      const agentFilePathsForFeature = agentFilePaths[featureId] ?? []
       // @ts-expect-error -- redundant error about indexing of a new object.
       result[`${agentConfig.id}::${featureId}`] = [
         // Get all frontend files for the feature
         ...(await getFeatureFrontendFiles(featureId)),
         // Get the agent (python/TS) file
-        await getFile(agentFilePaths[featureId])
+        ...(await Promise.all(agentFilePathsForFeature.map(async f => await getFile(f))))
       ]
     }
   }

typescript-sdk/apps/dojo/src/app/[integrationId]/feature/tool_based_generative_ui/page.tsx

@@ -51,7 +51,7 @@ export default function ToolBasedGenerativeUI({ params }: ToolBasedGenerativeUIP
       agent="tool_based_generative_ui"
     >
       <div
-        className={`${isMobile ? 'h-screen' : 'min-h-full'} w-full relative overflow-hidden`}
+        className={`${isMobile ? 'h-screen' : 'min-h-full flex'} w-full relative overflow-hidden`}
         style={
           {
             // "--copilot-kit-primary-color": "#222",
@@ -336,7 +336,7 @@ function Haiku() {
     <div className="flex h-full w-full">
       {/* Thumbnail List */}
       {Boolean(generatedHaikus.length) && !isMobile && (
-        <div className="w-40 p-4 border-r border-gray-200 overflow-y-auto overflow-x-hidden max-w-1">
+        <div className="w-40 p-4 border-r border-gray-200 overflow-y-auto overflow-x-hidden">
           {generatedHaikus.map((haiku, index) => (
             <div
               key={index}

typescript-sdk/integrations/langgraph/examples/agents/agentic_chat/agent.py → typescript-sdk/integrations/langgraph/examples/python/agents/agentic_chat/agent.py

@@ -2,7 +2,8 @@
 A simple agentic chat flow using LangGraph instead of CrewAI.
 """
 
-from typing import Dict, List, Any, Optional
+from typing import List, Any
+import os
 
 # Updated imports for LangGraph
 from langchain_core.runnables import RunnableConfig
@@ -76,5 +77,16 @@ async def chat_node(state: AgentState, config: RunnableConfig):
 workflow.add_edge(START, "chat_node")
 workflow.add_edge("chat_node", END)
 
+# Conditionally use a checkpointer based on the environment
+# Check for multiple indicators that we're running in LangGraph dev/API mode
+is_fast_api = os.environ.get("LANGGRAPH_FAST_API", "false").lower() == "true"
+
 # Compile the graph
-agentic_chat_graph = workflow.compile()
+if is_fast_api:
+    # For CopilotKit and other contexts, use MemorySaver
+    from langgraph.checkpoint.memory import MemorySaver
+    memory = MemorySaver()
+    graph = workflow.compile(checkpointer=memory)
+else:
+    # When running in LangGraph API/dev, don't use a custom checkpointer
+    graph = workflow.compile()

typescript-sdk/integrations/langgraph/examples/agents/agentic_generative_ui/agent.py → typescript-sdk/integrations/langgraph/examples/python/agents/agentic_generative_ui/agent.py

@@ -2,9 +2,10 @@
 An example demonstrating agentic generative UI using LangGraph.
 """
 
-import json
 import asyncio
-from typing import Dict, List, Any, Optional, Literal
+from typing import List, Any
+import os
+
 # LangGraph imports
 from langchain_core.runnables import RunnableConfig
 from langgraph.graph import StateGraph, END, START
@@ -189,5 +190,16 @@ async def chat_node(state: AgentState, config: RunnableConfig):
 workflow.add_edge("start_flow", "chat_node")
 workflow.add_edge("chat_node", END)
 
+# Conditionally use a checkpointer based on the environment
+# Check for multiple indicators that we're running in LangGraph dev/API mode
+is_fast_api = os.environ.get("LANGGRAPH_FAST_API", "false").lower() == "true"
+
 # Compile the graph
-graph = workflow.compile()
+if is_fast_api:
+    # For CopilotKit and other contexts, use MemorySaver
+    from langgraph.checkpoint.memory import MemorySaver
+    memory = MemorySaver()
+    graph = workflow.compile(checkpointer=memory)
+else:
+    # When running in LangGraph API/dev, don't use a custom checkpointer
+    graph = workflow.compile()

typescript-sdk/integrations/langgraph/python/ag_ui_langgraph/examples/agents/dojo.py → typescript-sdk/integrations/langgraph/examples/python/agents/dojo.py

@@ -5,13 +5,15 @@
 from dotenv import load_dotenv
 load_dotenv()
 
+os.environ["LANGGRAPH_FAST_API"] = "true"
+
 from ag_ui_langgraph import LangGraphAgent, add_langgraph_fastapi_endpoint
-from .human_in_the_loop import human_in_the_loop_graph
-from .predictive_state_updates import predictive_state_updates_graph
-from .shared_state import shared_state_graph
-from .tool_based_generative_ui import tool_based_generative_ui_graph
-from .agentic_chat import agentic_chat_graph
-from .agentic_generative_ui import graph
+from .human_in_the_loop.agent import graph as human_in_the_loop_graph
+from .predictive_state_updates.agent import graph as predictive_state_updates_graph
+from .shared_state.agent import graph as shared_state_graph
+from .tool_based_generative_ui.agent import graph as tool_based_generative_ui_graph
+from .agentic_chat.agent import graph as agentic_chat_graph
+from .agentic_generative_ui.agent import graph as agentic_generative_ui_graph
 
 app = FastAPI(title="LangGraph Dojo Example Server")
 
@@ -30,7 +32,7 @@
     "agentic_generative_ui": LangGraphAgent(
         name="agentic_generative_ui",
         description="An example for an agentic generative UI flow.",
-        graph=graph,
+        graph=agentic_generative_ui_graph,
     ),
     "human_in_the_loop": LangGraphAgent(
         name="human_in_the_loop",

typescript-sdk/integrations/langgraph/examples/agents/human_in_the_loop/agent.py → typescript-sdk/integrations/langgraph/examples/python/agents/human_in_the_loop/agent.py

@@ -4,15 +4,14 @@
 
 import json
 from typing import Dict, List, Any
+import os
 
 # LangGraph imports
 from langchain_core.runnables import RunnableConfig
 from langgraph.graph import StateGraph, END, START
 from langgraph.types import Command, interrupt
 from langgraph.graph import MessagesState
 
-from copilotkit.langgraph import copilotkit_emit_state, copilotkit_interrupt
-
 # LLM imports
 from langchain_openai import ChatOpenAI
 from langchain_core.messages import SystemMessage
@@ -181,7 +180,7 @@ async def chat_node(state: Dict[str, Any], config: RunnableConfig):
                     "steps": state["steps"],
                 }
             )
-    
+
     # If no tool calls or not plan_execution_steps, return to END with the updated messages
     return Command(
         goto=END,
@@ -207,7 +206,7 @@ async def process_steps_node(state: Dict[str, Any], config: RunnableConfig):
         user_response = interrupt({"steps": state["steps"]})
         # Store the user response in state for when the node restarts
         state["user_response"] = user_response
-    
+
     # Generate the creative completion response
     final_prompt = """
     Provide a textual description of how you are performing the task.
@@ -224,11 +223,11 @@ async def process_steps_node(state: Dict[str, Any], config: RunnableConfig):
 
     # Add the final response to messages
     messages = state["messages"] + [final_response]
-    
+
     # Clear the user_response from state to prepare for future interactions
     if "user_response" in state:
         state.pop("user_response")
-    
+
     # Return to END with the updated messages
     return Command(
         goto=END,
@@ -271,5 +270,16 @@ def should_continue(command: Command):
     },
 )
 
+# Conditionally use a checkpointer based on the environment
+# Check for multiple indicators that we're running in LangGraph dev/API mode
+is_fast_api = os.environ.get("LANGGRAPH_FAST_API", "false").lower() == "true"
+
 # Compile the graph
-human_in_the_loop_graph = workflow.compile()
+if is_fast_api:
+    # For CopilotKit and other contexts, use MemorySaver
+    from langgraph.checkpoint.memory import MemorySaver
+    memory = MemorySaver()
+    graph = workflow.compile(checkpointer=memory)
+else:
+    # When running in LangGraph API/dev, don't use a custom checkpointer
+    graph = workflow.compile()

typescript-sdk/integrations/langgraph/examples/agents/predictive_state_updates/agent.py → typescript-sdk/integrations/langgraph/examples/python/agents/predictive_state_updates/agent.py

@@ -2,9 +2,9 @@
 A demo of predictive state updates using LangGraph.
 """
 
-import json
 import uuid
-from typing import Dict, List, Any, Optional
+from typing import List, Any, Optional
+import os
 
 # LangGraph imports
 from langchain_core.runnables import RunnableConfig
@@ -174,5 +174,17 @@ async def chat_node(state: AgentState, config: RunnableConfig):
 workflow.add_edge("start_flow", "chat_node")
 workflow.add_edge("chat_node", END)
 
+# Conditionally use a checkpointer based on the environment
+# Check for multiple indicators that we're running in LangGraph dev/API mode
+is_fast_api = os.environ.get("LANGGRAPH_FAST_API", "false").lower() == "true"
+
 # Compile the graph
-predictive_state_updates_graph = workflow.compile()
+if is_fast_api:
+    # For CopilotKit and other contexts, use MemorySaver
+    from langgraph.checkpoint.memory import MemorySaver
+    memory = MemorySaver()
+    graph = workflow.compile(checkpointer=memory)
+else:
+    # When running in LangGraph API/dev, don't use a custom checkpointer
+    graph = workflow.compile()
+

typescript-sdk/integrations/langgraph/examples/agents/shared_state/agent.py → typescript-sdk/integrations/langgraph/examples/python/agents/shared_state/agent.py

@@ -5,6 +5,7 @@
 import json
 from enum import Enum
 from typing import Dict, List, Any, Optional
+import os
 
 # LangGraph imports
 from langchain_core.runnables import RunnableConfig
@@ -297,5 +298,16 @@ async def chat_node(state: Dict[str, Any], config: RunnableConfig):
 workflow.add_edge("start_flow", "chat_node")
 workflow.add_edge("chat_node", END)
 
+# Conditionally use a checkpointer based on the environment
+# Check for multiple indicators that we're running in LangGraph dev/API mode
+is_fast_api = os.environ.get("LANGGRAPH_FAST_API", "false").lower() == "true"
+
 # Compile the graph
-shared_state_graph = workflow.compile()
+if is_fast_api:
+    # For CopilotKit and other contexts, use MemorySaver
+    from langgraph.checkpoint.memory import MemorySaver
+    memory = MemorySaver()
+    graph = workflow.compile(checkpointer=memory)
+else:
+    # When running in LangGraph API/dev, don't use a custom checkpointer
+    graph = workflow.compile()

typescript-sdk/integrations/langgraph/examples/agents/tool_based_generative_ui/agent.py → typescript-sdk/integrations/langgraph/examples/python/agents/tool_based_generative_ui/agent.py

@@ -2,7 +2,8 @@
 An example demonstrating tool-based generative UI using LangGraph.
 """
 
-from typing import Dict, List, Any, Optional
+from typing import List, Any
+import os
 
 # LangGraph imports
 from langchain_core.runnables import RunnableConfig
@@ -124,6 +125,18 @@ async def chat_node(state: AgentState, config: RunnableConfig):
 workflow.add_edge(START, "chat_node")
 workflow.add_edge("chat_node", END)
 
+# Conditionally use a checkpointer based on the environment
+# Check for multiple indicators that we're running in LangGraph dev/API mode
+is_fast_api = os.environ.get("LANGGRAPH_FAST_API", "false").lower() == "true"
+
 # Compile the graph
-tool_based_generative_ui_graph = workflow.compile()
+if is_fast_api:
+    # For CopilotKit and other contexts, use MemorySaver
+    from langgraph.checkpoint.memory import MemorySaver
+    memory = MemorySaver()
+    graph = workflow.compile(checkpointer=memory)
+else:
+    # When running in LangGraph API/dev, don't use a custom checkpointer
+    graph = workflow.compile()
+
 

typescript-sdk/integrations/langgraph/examples/langgraph.json → typescript-sdk/integrations/langgraph/examples/python/langgraph.json

@@ -3,12 +3,12 @@
   "dockerfile_lines": [],
   "dependencies": ["."],
   "graphs": {
-    "agentic_chat": "./agents/agentic_chat/agent.py:agentic_chat_graph",
+    "agentic_chat": "./agents/agentic_chat/agent.py:graph",
     "agentic_generative_ui": "./agents/agentic_generative_ui/agent.py:graph",
-    "human_in_the_loop": "./agents/human_in_the_loop/agent.py:human_in_the_loop_graph",
-    "predictive_state_updates": "./agents/predictive_state_updates/agent.py:predictive_state_updates_graph",
-    "shared_state": "./agents/shared_state/agent.py:shared_state_graph",
-    "tool_based_generative_ui": "./agents/tool_based_generative_ui/agent.py:tool_based_generative_ui_graph"
+    "human_in_the_loop": "./agents/human_in_the_loop/agent.py:graph",
+    "predictive_state_updates": "./agents/predictive_state_updates/agent.py:graph",
+    "shared_state": "./agents/shared_state/agent.py:graph",
+    "tool_based_generative_ui": "./agents/tool_based_generative_ui/agent.py:graph"
   },
   "env": ".env"
 }