mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-09-13 13:17:52 +02:00
@@ -6,7 +6,7 @@ There could be a few reasons you're seeing this error:
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1. You manually passed a malformed list of messages when invoking the graph, e.g. `graph.invoke({'messages': [AIMessage(..., tool_calls=[...])]})`
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2. The graph was interrupted before receiving updates from the `tools` node (i.e. a list of ToolMessages)
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and you invoked it with a an input that is not None or a ToolMessage,
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and you invoked it with an input that is not None or a ToolMessage,
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e.g. `graph.invoke({'messages': [HumanMessage(...)]}, config)`.
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This interrupt could have been triggered in one of the following ways:
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- You manually set `interrupt_before = ['tools']` in `create_react_agent`
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@@ -8,7 +8,7 @@ class State(TypedDict):
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some_key: str
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def bad_node(state: State):
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# Should return an dict with a value for "some_key", not a list
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# Should return a dict with a value for "some_key", not a list
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return ["whoops"]
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builder = StateGraph(State)
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@@ -29,7 +29,7 @@ InvalidUpdateError: Expected dict, got ['whoops']
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For troubleshooting, visit: https://python.langchain.com/docs/troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE
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```
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Nodes in your graph must return an dict containing one or more keys defined in your state.
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Nodes in your graph must return a dict containing one or more keys defined in your state.
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## Troubleshooting
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@@ -1,6 +1,6 @@
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# Connect an authentication provider
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In the [the last tutorial](resource_auth.md), you added [resource authorization](../../tutorials/auth/resource_auth.md) to give users private conversations. However, you are still using hard-coded tokens for authentication, which is not secure. Now you'll replace those tokens with real user accounts using [OAuth2](../auth/getting_started.md).
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In [the last tutorial](resource_auth.md), you added [resource authorization](../../tutorials/auth/resource_auth.md) to give users private conversations. However, you are still using hard-coded tokens for authentication, which is not secure. Now you'll replace those tokens with real user accounts using [OAuth2](../auth/getting_started.md).
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You'll keep the same [`Auth`](../../cloud/reference/sdk/python_sdk_ref.md#langgraph_sdk.auth.Auth) object and [resource-level access control](../../concepts/auth.md#single-owner-resources), but upgrade authentication to use Supabase as your identity provider. While Supabase is used in this tutorial, the concepts apply to any OAuth2 provider. You'll learn how to:
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@@ -190,7 +190,7 @@ await sign_up(email1, password)
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await sign_up(email2, password)
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```
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⚠️ Before continuing: Check your email and click both confirmation links. Supabase will will reject `/login` requests until after you have confirmed your users' email.
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⚠️ Before continuing: Check your email and click both confirmation links. Supabase will reject `/login` requests until after you have confirmed your users' email.
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Now test that users can only see their own data. Make sure the server is running (run `langgraph dev`) before proceeding. The following snippet requires the "anon public" key that you copied from the Supabase dashboard while [setting up the auth provider](#setup-auth-provider) previously.
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@@ -181,6 +181,6 @@ Congratulations! You've built a chatbot that only lets "authenticated" users acc
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Now that you can control who accesses your bot, you might want to:
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1. Continue the tutorial by going to [Make cnversations private](resource_auth.md) to learn about resource authorization.
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1. Continue the tutorial by going to [Make conversations private](resource_auth.md) to learn about resource authorization.
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2. Read more about [authentication concepts](../../concepts/auth.md).
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3. Check out the [API reference](../../cloud/reference/sdk/python_sdk_ref.md) for more authentication details.
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