Replies: 4 comments 1 reply
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would you mind providing the code directly instead of giving the image? |
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Hi
Thank you for your kind answer.
I was trying still hard but, can't get the answers
…On Fri, 25 Jul 2025 at 07:06, Tik1993 ***@***.***> wrote:
would you mind providing the code directly instead of giving the image?
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I cannot read the code from the image, so it would be better if you can upload the code directly to here |
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oh okay
Can you read it now?
%pip install -qU langgraph langsmith
%pip install -qU langchain-tavily
import os
import getpass
def _set_env(var: str):
if not os.environ.get(var):
os.environ[var] = getpass.getpass(f"{var}: ")
_set_env("TAVILY_API_KEY")
from langchain_tavily import TavilySearch
from langgraph.checkpoint.memory import InMemorySaver
memory = InMemorySaver()
tool = TavilySearch(max_result=2)
tools = [tool]
tool.invoke("What's a 'node' in LangGraph?")
from typing import Annotated
from typing_extensions import TypedDict
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
class State(TypedDict):
messages: Annotated[list, add_messages]
graph_builder = StateGraph(State)
import os
from langchain.chat_models import init_chat_model
os.environ["GOOGLE_API_KEY"] = ""
llm = init_chat_model("google_genai:gemini-2.0-flash")
llm_with_tools = llm.bind_tools(tools)
def chatbot(state: State):
return {"messages": [llm_with_tools.invoke(state["messages"])]}
graph_builder.add_node("chatbot", chatbot)
import json
from langchain_core.messages import ToolMessage
class BasicToolNode:
def __init__(self, tools: list) -> None:
self.tools_by_name = {tool.name: tool for tool in tools}
def __call__(self, inputs: dict):
if messages := inputs.get("messaeges", []):
message = messages[-1]
else:
raise ValueError("No message found in input")
outputs = []
for tool_call in message.tool_calls:
tool_result = self.tools_by_name[tool_call["name"]].invoke(
tool_call["args"]
)
outputs.append(
ToolMessage(
content=json.dumps(tool_result),
name=tool_call["name"],
tool_call_id = tool_call["id"],
)
)
return {"messages":outputs}
tool_node = BasicToolNode(tools=[tool])
graph_builder.add_node("tools", tool_node)
def route_tools(
state: State,
):
if messages := state.get("messages", []):
ai_message = messages[-1]
else:
raise ValueError(f"No messages found in input state to tool_edge: {
state}")
if hasattr(ai_message, "tool_calls") and ai_message.tool_calls:
return "tools"
return END
graph_builder.add_conditional_edges(
"chatbot",
route_tools,
{"tools": "tools", END:END},
)
graph_builder.add_edge("tools", "chatbot")
graph_builder.add_edge(START, "chatbot")
graph = graph_builder.compile()
from IPython.display import Image, display
try:
display(Image(graph.get_graph().draw_mermaid_png()))
except Exception:
pass
def stream_graph_updates(user_input: str):
for event in graph.stream({"messages":[{"role":"user", "content"
:user_input}]}):
for value in event.values():
print("Assistant:", value["messages"][-1].content)
while True:
try:
user_input = input("User: ")
if user_input.lower() in ["quit", "exit", "q"]:
print("Goodbye")
break
stream_graph_updates(user_input)
except:
user_input = "What do you know about LangGraph?"
print("User: " + user_input)
stream_graph_updates(user_input)
break
…On Fri, 25 Jul 2025 at 07:19, Tik1993 ***@***.***> wrote:
I cannot read the code from the image, so it would be better if you can
upload the code directly to here
—
Reply to this email directly, view it on GitHub
<#5645 (reply in thread)>,
or unsubscribe
<https://github.com/notifications/unsubscribe-auth/BUJUNQNIEDYJRTNH5NAY7ET3KFLWFAVCNFSM6AAAAACCIX3ZBKVHI2DSMVQWIX3LMV43URDJONRXK43TNFXW4Q3PNVWWK3TUHMYTGOBYGI4DKNA>
.
You are receiving this because you authored the thread.Message ID:
***@***.***
com>
|
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|
%pip install -qU langgraph langsmith
%pip install -qU langchain-tavily
import os
import getpass
def _set_env(var: str):
if not os.environ.get(var):
os.environ[var] = getpass.getpass(f"{var}: ")
_set_env("TAVILY_API_KEY")
from langchain_tavily import TavilySearch
from langgraph.checkpoint.memory import InMemorySaver
memory = InMemorySaver()
tool = TavilySearch(max_result=2)
tools = [tool]
tool.invoke("What's a 'node' in LangGraph?")
from typing import Annotated
from typing_extensions import TypedDict
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
class State(TypedDict):
messages: Annotated[list, add_messages]
graph_builder = StateGraph(State)
import os
from langchain.chat_models import init_chat_model
os.environ["GOOGLE_API_KEY"] = ""
llm = init_chat_model("google_genai:gemini-2.0-flash")
llm_with_tools = llm.bind_tools(tools)
def chatbot(state: State):
return {"messages": [llm_with_tools.invoke(state["messages"])]}
graph_builder.add_node("chatbot", chatbot)
import json
from langchain_core.messages import ToolMessage
class BasicToolNode:
def __init__(self, tools: list) -> None:
self.tools_by_name = {tool.name: tool for tool in tools}
def __call__(self, inputs: dict):
if messages := inputs.get("messaeges", []):
message = messages[-1]
else:
raise ValueError("No message found in input")
outputs = []
for tool_call in message.tool_calls:
tool_result = self.tools_by_name[tool_call["name"]].invoke(
tool_call["args"]
)
outputs.append(
ToolMessage(
content=json.dumps(tool_result),
name=tool_call["name"],
tool_call_id = tool_call["id"],
)
)
return {"messages":outputs}
tool_node = BasicToolNode(tools=[tool])
graph_builder.add_node("tools", tool_node)
def route_tools(
state: State,
):
if messages := state.get("messages", []):
ai_message = messages[-1]
else:
raise ValueError(f"No messages found in input state to tool_edge:
{state}")
if hasattr(ai_message, "tool_calls") and ai_message.tool_calls:
return "tools"
return END
graph_builder.add_conditional_edges(
"chatbot",
route_tools,
{"tools": "tools", END:END},
)
graph_builder.add_edge("tools", "chatbot")
graph_builder.add_edge(START, "chatbot")
graph = graph_builder.compile()
from IPython.display import Image, display
try:
display(Image(graph.get_graph().draw_mermaid_png()))
except Exception:
pass
def stream_graph_updates(user_input: str):
for event in graph.stream({"messages":[{"role":"user",
"content":user_input}]}):
for value in event.values():
print("Assistant:", value["messages"][-1].content)
while True:
try:
user_input = input("User: ")
if user_input.lower() in ["quit", "exit", "q"]:
print("Goodbye")
break
stream_graph_updates(user_input)
except:
user_input = "What do you know about LangGraph?"
print("User: " + user_input)
stream_graph_updates(user_input)
break
…On Fri, 25 Jul 2025 at 07:23, jason hwang ***@***.***> wrote:
oh okay
Can you read it now?
%pip install -qU langgraph langsmith
%pip install -qU langchain-tavily
import os
import getpass
def _set_env(var: str):
if not os.environ.get(var):
os.environ[var] = getpass.getpass(f"{var}: ")
_set_env("TAVILY_API_KEY")
from langchain_tavily import TavilySearch
from langgraph.checkpoint.memory import InMemorySaver
memory = InMemorySaver()
tool = TavilySearch(max_result=2)
tools = [tool]
tool.invoke("What's a 'node' in LangGraph?")
from typing import Annotated
from typing_extensions import TypedDict
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
class State(TypedDict):
messages: Annotated[list, add_messages]
graph_builder = StateGraph(State)
import os
from langchain.chat_models import init_chat_model
os.environ["GOOGLE_API_KEY"] = ""
llm = init_chat_model("google_genai:gemini-2.0-flash")
llm_with_tools = llm.bind_tools(tools)
def chatbot(state: State):
return {"messages": [llm_with_tools.invoke(state["messages"])]}
graph_builder.add_node("chatbot", chatbot)
import json
from langchain_core.messages import ToolMessage
class BasicToolNode:
def __init__(self, tools: list) -> None:
self.tools_by_name = {tool.name: tool for tool in tools}
def __call__(self, inputs: dict):
if messages := inputs.get("messaeges", []):
message = messages[-1]
else:
raise ValueError("No message found in input")
outputs = []
for tool_call in message.tool_calls:
tool_result = self.tools_by_name[tool_call["name"]].invoke(
tool_call["args"]
)
outputs.append(
ToolMessage(
content=json.dumps(tool_result),
name=tool_call["name"],
tool_call_id = tool_call["id"],
)
)
return {"messages":outputs}
tool_node = BasicToolNode(tools=[tool])
graph_builder.add_node("tools", tool_node)
def route_tools(
state: State,
):
if messages := state.get("messages", []):
ai_message = messages[-1]
else:
raise ValueError(f"No messages found in input state to tool_edge:
{state}")
if hasattr(ai_message, "tool_calls") and ai_message.tool_calls:
return "tools"
return END
graph_builder.add_conditional_edges(
"chatbot",
route_tools,
{"tools": "tools", END:END},
)
graph_builder.add_edge("tools", "chatbot")
graph_builder.add_edge(START, "chatbot")
graph = graph_builder.compile()
from IPython.display import Image, display
try:
display(Image(graph.get_graph().draw_mermaid_png()))
except Exception:
pass
def stream_graph_updates(user_input: str):
for event in graph.stream({"messages":[{"role":"user", "content"
:user_input}]}):
for value in event.values():
print("Assistant:", value["messages"][-1].content)
while True:
try:
user_input = input("User: ")
if user_input.lower() in ["quit", "exit", "q"]:
print("Goodbye")
break
stream_graph_updates(user_input)
except:
user_input = "What do you know about LangGraph?"
print("User: " + user_input)
stream_graph_updates(user_input)
break
On Fri, 25 Jul 2025 at 07:19, Tik1993 ***@***.***> wrote:
> I cannot read the code from the image, so it would be better if you can
> upload the code directly to here
>
> —
> Reply to this email directly, view it on GitHub
> <#5645 (reply in thread)>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/BUJUNQNIEDYJRTNH5NAY7ET3KFLWFAVCNFSM6AAAAACCIX3ZBKVHI2DSMVQWIX3LMV43URDJONRXK43TNFXW4Q3PNVWWK3TUHMYTGOBYGI4DKNA>
> .
> You are receiving this because you authored the thread.Message ID:
> ***@***.***
> com>
>
|
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I get confused a lot when adding nodes into langgraph. I still don't know what the problem is.
Can you guys help me?
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