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docs: concepts for cloud and doc-reorg (#2196)
Update langgraph documentation --------- Co-authored-by: Vadym Barda <vadym@langchain.dev> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Nuno Campos <nuno@langchain.dev> Co-authored-by: Chester Curme <chester.curme@gmail.com> Co-authored-by: William FH <13333726+hinthornw@users.noreply.github.com>
This commit is contained in:
Harrison Chase
co-authored by
Vadym Barda
Eugene Yurtsev
Nuno Campos
Chester Curme
William FH
Vadym Barda
Eugene Yurtsev
Nuno Campos
Chester Curme
William FH
parent
d6d6ab9b73
commit
d0e59f406b
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@@ -8,11 +8,17 @@ Testing locally ensures that there are no errors or conflicts with Python depend
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Install the proper packages:
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```shell
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pip install langgraph-cli
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```
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Ensure you have an API key, which you can create from the LangSmith UI (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:
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=== "pip"
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```bash
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pip install -U langgraph-cli
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```
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=== "Homebrew" (macOS only)
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```bash
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brew install langgraph-cli
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```
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|
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Ensure you have an API key, which you can create from the [LangSmith UI](https://smith.langchain.com) (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:
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```python
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LANGCHAIN_API_KEY = *********
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@@ -20,7 +26,7 @@ LANGCHAIN_API_KEY = *********
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## Start the API server
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Once you have downloaded the CLI, you can run the following command to start the API server for local testing:
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Once you have installed the CLI, you can run the following command to start the API server for local testing:
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```shell
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langgraph up
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@@ -22,6 +22,7 @@ LangGraph Cloud gives you best in class observability, testing, and hosting serv
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Learn how to deploy your app to LangGraph Cloud in these how to guides:
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- [How to deploy to LangGraph cloud](../deployment/cloud.md)
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- [How to interact with the deployment using RemoteGraph](../../how-tos/use-remote-graph.md)
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## Streaming
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@@ -1,5 +1,8 @@
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# How to stream debug events
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!!! info "Prerequisites"
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* [Streaming](../../concepts/streaming.md)
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This guide covers how to stream debug events from your graph (`stream_mode="debug"`). Streaming debug events produces responses containing `type` and `timestamp` keys. Debug events correspond to different steps in the graph's execution, and there are three different types of steps that will get streamed back to you:
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- `checkpoint`: These events will get streamed anytime the graph saves its state, which occurs after every super-step. Read more about checkpoints [here](https://langchain-ai.github.io/langgraph/concepts/low_level/#checkpointer)
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@@ -1,6 +1,9 @@
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# How to stream events
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This guide covers how to stream events from your graph (`stream_mode="events"`). Depending on the use case and user experience of your LangGraph application, your application may process event types differently. Read more about events in this [conceptual guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#astream_events-for-streaming-tokens-of-llm-calls).
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!!! info "Prerequisites"
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* [Streaming](../../concepts/streaming.md#streaming-llm-tokens-and-events-astream_events)
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This guide covers how to stream events from your graph (`stream_mode="events"`). Depending on the use case and user experience of your LangGraph application, your application may process event types differently.
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## Setup
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@@ -1,41 +1,9 @@
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# How to stream messages from your graph
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This guide covers how to stream messages from your graph. In order to use this mode, the state of the graph you are interacting with MUST have a `messages` key that is a list of messages.
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!!! info "Prerequisites"
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* [Streaming](../../concepts/streaming.md)
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E.g., the state should look something like:
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=== "Python"
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```python
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from typing import Annotated
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from typing_extensions import TypedDict
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from langgraph.graph import add_messages
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from langchain_core.messages import AnyMessage
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class State(TypedDict):
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messages: Annotated[list[AnyMessage], add_messages]
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```
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=== "Javascript"
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```js
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import { type BaseMessage } from "@langchain/core/messages";
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import { Annotation, messagesStateReducer } from "@langchain/langgraph";
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export const StateAnnotation = Annotation.Root({
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messages: Annotation<BaseMessage[]>({
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reducer: messagesStateReducer,
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default: () => [],
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}),
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});
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```
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Alternatively, you can use an instance or subclass of `from langgraph.graph import MessagesState` (`MessagesState` is equivalent to the implementation above). Or in Javascript: `import { MessagesAnnotation } from "@langchain/langgraph";`.
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With `stream_mode="messages"` two things will be streamed back:
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- It outputs messages produced by any chat model called inside (unless tagged in a special way)
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- It outputs messages returned from nodes (to allow for nodes to return `ToolMessages` and the like)
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This guide covers how to stream messages from your graph. With `stream_mode="messages"`, messages from any chat model invocations inside your graph nodes will be streamed back.
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Read more about how the `messages` streaming mode works [here](https://langchain-ai.github.io/langgraph/cloud/concepts/api/#modemessages)
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@@ -90,98 +58,6 @@ Output:
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'values': None
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}
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Let's also define a helper function for better formatting of the tool calls in messages (for CURL we will define a helper script called `process_stream.sh`)
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=== "Python"
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```python
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def format_tool_calls(tool_calls):
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if tool_calls:
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formatted_calls = []
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for call in tool_calls:
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formatted_calls.append(
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f"Tool Call ID: {call['id']}, Function: {call['name']}, Arguments: {call['args']}"
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)
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return "\n".join(formatted_calls)
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return "No tool calls"
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```
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=== "Javascript"
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```js
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function formatToolCalls(toolCalls) {
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if (toolCalls && toolCalls.length > 0) {
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const formattedCalls = toolCalls.map(call => {
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return `Tool Call ID: ${call.id}, Function: ${call.name}, Arguments: ${call.args}`;
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});
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return formattedCalls.join("\n");
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}
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return "No tool calls";
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}
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```
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=== "CURL"
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```bash
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# process_stream.sh
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format_tool_calls() {
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echo "$1" | jq -r 'map("Tool Call ID: \(.id), Function: \(.name), Arguments: \(.args)") | join("\n")'
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}
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process_data_item() {
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local data_item="$1"
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if echo "$data_item" | jq -e '.role == "user"' > /dev/null; then
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echo "Human: $(echo "$data_item" | jq -r '.content')"
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else
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local tool_calls=$(echo "$data_item" | jq -r '.tool_calls // []')
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local invalid_tool_calls=$(echo "$data_item" | jq -r '.invalid_tool_calls // []')
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local content=$(echo "$data_item" | jq -r '.content // ""')
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local response_metadata=$(echo "$data_item" | jq -r '.response_metadata // {}')
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if [ -n "$content" ] && [ "$content" != "null" ]; then
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echo "AI: $content"
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fi
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if [ "$tool_calls" != "[]" ]; then
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echo "Tool Calls:"
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format_tool_calls "$tool_calls"
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fi
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if [ "$invalid_tool_calls" != "[]" ]; then
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echo "Invalid Tool Calls:"
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format_tool_calls "$invalid_tool_calls"
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fi
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if [ "$response_metadata" != "{}" ]; then
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local finish_reason=$(echo "$response_metadata" | jq -r '.finish_reason // "N/A"')
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echo "Response Metadata: Finish Reason - $finish_reason"
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fi
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fi
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}
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while IFS=': ' read -r key value; do
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case "$key" in
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event)
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event="$value"
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;;
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data)
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if [ "$event" = "metadata" ]; then
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run_id=$(echo "$value" | jq -r '.run_id')
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echo "Metadata: Run ID - $run_id"
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echo "------------------------------------------------"
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elif [ "$event" = "messages/partial" ]; then
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echo "$value" | jq -c '.[]' | while read -r data_item; do
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process_data_item "$data_item"
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done
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echo "------------------------------------------------"
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fi
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;;
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esac
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done
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```
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## Stream graph in messages mode
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Now we can stream by messages, which will return complete messages (at the end of node execution) as well as tokens for any messages generated inside a node:
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@@ -192,41 +68,16 @@ Now we can stream by messages, which will return complete messages (at the end o
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input = {"messages": [{"role": "user", "content": "what's the weather in sf"}]}
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config = {"configurable": {"model_name": "openai"}}
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async for event in client.runs.stream(
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async for chunk in client.runs.stream(
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thread["thread_id"],
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assistant_id=assistant_id,
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input=input,
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config=config,
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stream_mode="messages",
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):
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if event.event == "metadata":
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print(f"Metadata: Run ID - {event.data['run_id']}")
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print("-" * 50)
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elif event.event == "messages/partial":
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for data_item in event.data:
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if "role" in data_item and data_item["role"] == "user":
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print(f"Human: {data_item['content']}")
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else:
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tool_calls = data_item.get("tool_calls", [])
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invalid_tool_calls = data_item.get("invalid_tool_calls", [])
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content = data_item.get("content", "")
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response_metadata = data_item.get("response_metadata", {})
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if content:
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print(f"AI: {content}")
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if tool_calls:
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print("Tool Calls:")
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print(format_tool_calls(tool_calls))
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if invalid_tool_calls:
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print("Invalid Tool Calls:")
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print(format_tool_calls(invalid_tool_calls))
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if response_metadata:
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finish_reason = response_metadata.get("finish_reason", "N/A")
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print(f"Response Metadata: Finish Reason - {finish_reason}")
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print("-" * 50)
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print(f"Receiving new event of type: {chunk.event}...")
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print(chunk.data)
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print("\n\n")
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```
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=== "Javascript"
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@@ -251,43 +102,10 @@ Now we can stream by messages, which will return complete messages (at the end o
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streamMode: "messages"
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}
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);
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for await (const event of streamResponse) {
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if (event.event === "metadata") {
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console.log(`Metadata: Run ID - ${event.data.run_id}`);
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console.log("-".repeat(50));
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} else if (event.event === "messages/partial") {
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event.data.forEach(dataItem => {
|
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if (dataItem.role && dataItem.role === "user") {
|
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console.log(`Human: ${dataItem.content}`);
|
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} else {
|
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const toolCalls = dataItem.tool_calls || [];
|
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const invalidToolCalls = dataItem.invalid_tool_calls || [];
|
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const content = dataItem.content || "";
|
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const responseMetadata = dataItem.response_metadata || {};
|
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|
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if (content) {
|
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console.log(`AI: ${content}`);
|
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}
|
||||
|
||||
if (toolCalls.length > 0) {
|
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console.log("Tool Calls:");
|
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console.log(formatToolCalls(toolCalls));
|
||||
}
|
||||
|
||||
if (invalidToolCalls.length > 0) {
|
||||
console.log("Invalid Tool Calls:");
|
||||
console.log(formatToolCalls(invalidToolCalls));
|
||||
}
|
||||
|
||||
if (responseMetadata) {
|
||||
const finishReason = responseMetadata.finish_reason || "N/A";
|
||||
console.log(`Response Metadata: Finish Reason - ${finishReason}`);
|
||||
}
|
||||
}
|
||||
});
|
||||
console.log("-".repeat(50));
|
||||
}
|
||||
for await (const chunk of streamResponse) {
|
||||
console.log(`Receiving new event of type: ${chunk.event}...`);
|
||||
console.log(chunk.data);
|
||||
console.log("\n\n");
|
||||
}
|
||||
```
|
||||
|
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@@ -295,203 +113,198 @@ Now we can stream by messages, which will return complete messages (at the end o
|
||||
|
||||
```bash
|
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curl --request POST \
|
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--url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data "{
|
||||
\"assistant_id\": \"agent\",
|
||||
\"config\":{\"configurable\":{\"model_name\":\"openai\"}},
|
||||
\"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"What's the weather in sf\"}]},
|
||||
\"stream_mode\": [
|
||||
\"messages\"
|
||||
]
|
||||
}" | sed 's/\r$//' | ./process_stream.sh
|
||||
--url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data "{
|
||||
\"assistant_id\": \"agent\",
|
||||
\"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"what's the weather in la\"}]},
|
||||
\"stream_mode\": [
|
||||
\"messages\"
|
||||
]
|
||||
}" | \
|
||||
sed 's/\r$//' | \
|
||||
awk '
|
||||
/^event:/ {
|
||||
if (data_content != "") {
|
||||
print data_content "\n"
|
||||
}
|
||||
sub(/^event: /, "Receiving event of type: ", $0)
|
||||
printf "%s...\n", $0
|
||||
data_content = ""
|
||||
}
|
||||
/^data:/ {
|
||||
sub(/^data: /, "", $0)
|
||||
data_content = $0
|
||||
}
|
||||
END {
|
||||
if (data_content != "") {
|
||||
print data_content "\n"
|
||||
}
|
||||
}
|
||||
'
|
||||
```
|
||||
|
||||
|
||||
Output:
|
||||
|
||||
Metadata: Run ID - 1ef2fe5c-6a1d-6575-bc09-d7832711c17e
|
||||
--------------------------------------------------
|
||||
Invalid Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments:
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': ''}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current'}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather'}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in'}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San'}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San Francisco'}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San Francisco'}
|
||||
--------------------------------------------------
|
||||
Tool Calls:
|
||||
Tool Call ID: call_cg14F20jMBqWYrNgEkdWHwB3, Function: tavily_search_results_json, Arguments: {'query': 'current weather in San Francisco'}
|
||||
Response Metadata: Finish Reason - tool_calls
|
||||
--------------------------------------------------
|
||||
--------------------------------------------------
|
||||
AI: The
|
||||
--------------------------------------------------
|
||||
AI: The current
|
||||
--------------------------------------------------
|
||||
AI: The current weather
|
||||
--------------------------------------------------
|
||||
AI: The current weather in
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is over
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F).
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-s
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-south
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 k
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph).
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%,
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles).
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is 3
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is 3.
|
||||
--------------------------------------------------
|
||||
AI: The current weather in San Francisco is overcast with a temperature of 13.9°C (57.0°F). The wind is blowing from the south-southwest at 6.9 mph (11.2 kph). The humidity is at 81%, and the visibility is 16 km (9 miles). The UV index is 3.
|
||||
Response Metadata: Finish Reason - stop
|
||||
--------------------------------------------------
|
||||
Receiving new event of type: metadata...
|
||||
{"run_id": "1ef971e0-9a84-6154-9047-247b4ce89c4d", "attempt": 1}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/metadata...
|
||||
{
|
||||
"run-700157a5-df1a-4829-9e7c-1e07a1d934f7": {
|
||||
"metadata": {
|
||||
"graph_id": "agent",
|
||||
"langgraph_node": "agent",
|
||||
...
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
...
|
||||
|
||||
Receiving new event of type: messages/partial...
|
||||
[
|
||||
{
|
||||
"tool_calls": [
|
||||
{
|
||||
"name": "tavily_search_results_json",
|
||||
"args": {
|
||||
"query": "weather"
|
||||
},
|
||||
"id": "toolu_01RJGmVJtTxccoHHixGkGqaC",
|
||||
"type": "tool_call"
|
||||
}
|
||||
],
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/partial...
|
||||
[
|
||||
{
|
||||
"type": "ai",
|
||||
"tool_calls": [
|
||||
{
|
||||
"name": "tavily_search_results_json",
|
||||
"args": {
|
||||
"query": "weather in "
|
||||
},
|
||||
"id": "toolu_01RJGmVJtTxccoHHixGkGqaC",
|
||||
"type": "tool_call"
|
||||
}
|
||||
],
|
||||
...
|
||||
}
|
||||
]
|
||||
|
||||
...
|
||||
|
||||
Receiving new event of type: messages/partial...
|
||||
[
|
||||
{
|
||||
"type": "ai",
|
||||
"tool_calls": [
|
||||
{
|
||||
"name": "tavily_search_results_json",
|
||||
"args": {
|
||||
"query": "weather in san francisco"
|
||||
},
|
||||
"id": "toolu_01RJGmVJtTxccoHHixGkGqaC",
|
||||
"type": "tool_call"
|
||||
}
|
||||
],
|
||||
...
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/metadata...
|
||||
{
|
||||
"aa162b98-433d-4e3c-b204-0d41a6694156": {
|
||||
"metadata": {
|
||||
"graph_id": "agent",
|
||||
"langgraph_node": "action",
|
||||
...
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/complete...
|
||||
[
|
||||
{
|
||||
"content": "[{\"url\": \"https://www.weatherapi.com/\", \"content\": \"{'location': {'name': 'San Francisco', 'region': 'California', 'country': 'United States of America', 'lat': 37.775, 'lon': -122.4183, 'tz_id': 'America/Los_Angeles', 'localtime_epoch': 1730334046, 'localtime': '2024-10-30 17:20'}, 'current': {'last_updated_epoch': 1730333700, 'last_updated': '2024-10-30 17:15', 'temp_c': 12.3, 'temp_f': 54.2, 'is_day': 1, 'condition': {'text': 'Partly Cloudy', 'icon': '//cdn.weatherapi.com/weather/64x64/day/116.png', 'code': 1003}, 'wind_mph': 9.6, 'wind_kph': 15.5, 'wind_degree': 238, 'wind_dir': 'WSW', 'pressure_mb': 1021.0, 'pressure_in': 30.15, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 93, 'cloud': 57, 'feelslike_c': 11.2, 'feelslike_f': 52.2, 'windchill_c': 11.2, 'windchill_f': 52.2, 'heatindex_c': 12.3, 'heatindex_f': 54.2, 'dewpoint_c': 11.2, 'dewpoint_f': 52.1, 'vis_km': 10.0, 'vis_miles': 6.0, 'uv': 0.5, 'gust_mph': 12.9, 'gust_kph': 20.8}}\"}]",
|
||||
"type": "tool",
|
||||
"name": "tavily_search_results_json",
|
||||
"tool_call_id": "toolu_01RJGmVJtTxccoHHixGkGqaC",
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
Receiving new event of type: messages/metadata...
|
||||
{
|
||||
"run-f92646d2-6b13-4648-90c7-0280766bfaf2": {
|
||||
"metadata": {
|
||||
"graph_id": "agent",
|
||||
"langgraph_node": "agent",
|
||||
...
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/partial...
|
||||
[
|
||||
{
|
||||
"content": [
|
||||
{
|
||||
"text": "\n\nThe search",
|
||||
"type": "text",
|
||||
"index": 0
|
||||
}
|
||||
],
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/partial...
|
||||
[
|
||||
{
|
||||
"content": [
|
||||
{
|
||||
"text": "\n\nThe search results provide",
|
||||
"type": "text",
|
||||
"index": 0
|
||||
}
|
||||
],
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
|
||||
...
|
||||
|
||||
Receiving new event of type: messages/partial...
|
||||
[
|
||||
{
|
||||
"content": [
|
||||
{
|
||||
"text": "\n\nThe search results provide the current weather conditions in San Francisco. According to the data, as of 5:20pm on October 30, 2024, the weather in San Francisco is partly cloudy with a temperature of 54\\u00b0F (12\\u00b0C). The wind is blowing from the west-southwest at around 10 mph (15 km/h). The humidity is high at 93% and visibility is 6 miles (10 km). Overall, it seems to be a cool, partly cloudy day with moderate winds in San Francisco.",
|
||||
"type": "text",
|
||||
"index": 0
|
||||
}
|
||||
],
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
@@ -1,5 +1,8 @@
|
||||
# How to configure multiple streaming modes at the same time
|
||||
|
||||
!!! info "Prerequisites"
|
||||
* [Streaming](../../concepts/streaming.md)
|
||||
|
||||
This guide covers how to configure multiple streaming modes at the same time.
|
||||
|
||||
## Setup
|
||||
@@ -175,11 +178,6 @@ Output:
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/complete...
|
||||
[{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}]
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: debug...
|
||||
{'type': 'checkpoint', 'timestamp': '2024-06-24T21:34:06.117924+00:00', 'step': 0, 'payload': {'config': {'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'callbacks': [None], 'recursion_limit': 25, 'configurable': {'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'thread_ts': '1ef32717-bc81-68c8-8000-4e18ae7d67a5', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25'}, 'values': {'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}]}, 'metadata': {'source': 'loop', 'step': 0, 'writes': None}}}
|
||||
|
||||
@@ -305,11 +303,6 @@ Output:
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/complete...
|
||||
[{'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: debug...
|
||||
{'type': 'checkpoint', 'timestamp': '2024-06-24T21:34:06.124510+00:00', 'step': 1, 'payload': {'config': {'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'callbacks': [None], 'recursion_limit': 25, 'configurable': {'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'thread_ts': '1ef32717-bc91-6a34-8001-26353c117c25', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25'}, 'values': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}, {'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}, 'metadata': {'source': 'loop', 'step': 1, 'writes': {'agent': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}}}}
|
||||
|
||||
@@ -469,12 +462,7 @@ Output:
|
||||
{'event': 'on_chain_stream', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'name': 'LangGraph', 'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'data': {'chunk': ['values', {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}, {'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}, {'content': 'tool_call__begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': None, 'id': '639ca779-403d-4915-a066-327e1f634c8b', 'tool_call_id': 'tool_call_id'}, {'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}]}, 'parent_ids': []}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: messages/complete...
|
||||
[{'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]
|
||||
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: debug...
|
||||
{'type': 'checkpoint', 'timestamp': '2024-06-24T21:34:06.134190+00:00', 'step': 3, 'payload': {'config': {'tags': [], 'metadata': {'created_by': 'system', 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'callbacks': [None], 'recursion_limit': 25, 'configurable': {'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25', 'user_id': '', 'graph_id': 'agent', 'thread_id': 'bfc68029-1f7b-400f-beab-6f9032a52da4', 'thread_ts': '1ef32717-bca9-6418-8003-8d0d0b06845c', 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'}, 'run_id': '1ef32717-bc30-6cf2-8a26-33f63567bc25'}, 'values': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': "What's the weather in SF?", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': '7da1bafa-f53c-4df8-ba63-8dd517140b9f', 'example': False}, {'content': 'begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-2424dd6d-5cf5-4244-8d98-357640ce6e12', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}, {'content': 'tool_call__begin', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': None, 'id': '639ca779-403d-4915-a066-327e1f634c8b', 'tool_call_id': 'tool_call_id'}, {'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}, 'metadata': {'source': 'loop', 'step': 3, 'writes': {'agent': {'some_bytes': 'c29tZV9ieXRlcw==', 'some_byte_array': 'c29tZV9ieXRlX2FycmF5', 'dict_with_bytes': {'more_bytes': 'bW9yZV9ieXRlcw=='}, 'messages': [{'content': 'end', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-0f2ef0a1-0fc7-445c-9df4-55e8bb284575', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}}}}
|
||||
|
||||
|
||||
@@ -1,6 +1,9 @@
|
||||
# How to stream state updates of your graph
|
||||
|
||||
This guide covers how to use `stream_mode="updates"` for your graph, which will stream the updates to the graph state that are made after each node is executed. This differs from using `stream_mode="values"`: instead of streaming the entire value of the state at each superstep, it only streams the updates from each of the nodes that made an update to the state at that superstep. Read [this conceptual guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#stream-and-astream) to learn more.
|
||||
!!! info "Prerequisites"
|
||||
* [Streaming](../../concepts/streaming.md)
|
||||
|
||||
This guide covers how to use `stream_mode="updates"` for your graph, which will stream the updates to the graph state that are made after each node is executed. This differs from using `stream_mode="values"`: instead of streaming the entire value of the state at each superstep, it only streams the updates from each of the nodes that made an update to the state at that superstep.
|
||||
|
||||
## Setup
|
||||
|
||||
@@ -146,24 +149,69 @@ Now we can stream by updates, which outputs updates made to the state by each no
|
||||
Output:
|
||||
|
||||
Receiving new event of type: metadata...
|
||||
{'run_id': 'cfc96c16-ed9a-44bd-b5bb-c30e3c0725f0'}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: data...
|
||||
{'agent': {'messages': [{'content': [{'id': 'toolu_0148tMmDK51iLQfG1yaNwRHM', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-1a9d32b0-7007-4a36-abde-8df812a0ed94', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_0148tMmDK51iLQfG1yaNwRHM'}], 'invalid_tool_calls': []}]}}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: data...
|
||||
{'action': {'messages': [{'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716062239, \'localtime\': \'2024-05-18 12:57\'}, \'current\': {\'last_updated_epoch\': 1716061500, \'last_updated\': \'2024-05-18 12:45\', \'temp_c\': 18.9, \'temp_f\': 66.0, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 2.2, \'wind_kph\': 3.6, \'wind_degree\': 10, \'wind_dir\': \'N\', \'pressure_mb\': 1017.0, \'pressure_in\': 30.02, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 18.9, \'feelslike_f\': 66.0, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 6.0, \'gust_mph\': 7.5, \'gust_kph\': 12.0}}"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': 'a36e8cd1-0e96-4417-9c15-f10a945d2b42', 'tool_call_id': 'toolu_0148tMmDK51iLQfG1yaNwRHM'}]}}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: data...
|
||||
{'agent': {'messages': [{'content': 'The weather in Los Angeles is currently overcast with a temperature of around 66°F (18.9°C). There are light winds from the north at around 2-3 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-d5c1c2f0-b12d-41ce-990b-f36570e7483d', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}}
|
||||
|
||||
|
||||
|
||||
{"run_id": "cfc96c16-ed9a-44bd-b5bb-c30e3c0725f0"}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: updates...
|
||||
{
|
||||
"agent": {
|
||||
"messages": [
|
||||
{
|
||||
"type": "ai",
|
||||
"tool_calls": [
|
||||
{
|
||||
"name": "tavily_search_results_json",
|
||||
"args": {
|
||||
"query": "weather in los angeles"
|
||||
},
|
||||
"id": "toolu_0148tMmDK51iLQfG1yaNwRHM"
|
||||
}
|
||||
],
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: updates...
|
||||
{
|
||||
"action": {
|
||||
"messages": [
|
||||
{
|
||||
"content": [
|
||||
{
|
||||
"url": "https://www.weatherapi.com/",
|
||||
"content": "{\"location\": {\"name\": \"Los Angeles\", \"region\": \"California\", \"country\": \"United States of America\", \"lat\": 34.05, \"lon\": -118.24, \"tz_id\": \"America/Los_Angeles\", \"localtime_epoch\": 1716062239, \"localtime\": \"2024-05-18 12:57\"}, \"current\": {\"last_updated_epoch\": 1716061500, \"last_updated\": \"2024-05-18 12:45\", \"temp_c\": 18.9, \"temp_f\": 66.0, \"is_day\": 1, \"condition\": {\"text\": \"Overcast\", \"icon\": \"//cdn.weatherapi.com/weather/64x64/day/122.png\", \"code\": 1009}, \"wind_mph\": 2.2, \"wind_kph\": 3.6, \"wind_degree\": 10, \"wind_dir\": \"N\", \"pressure_mb\": 1017.0, \"pressure_in\": 30.02, \"precip_mm\": 0.0, \"precip_in\": 0.0, \"humidity\": 65, \"cloud\": 100, \"feelslike_c\": 18.9, \"feelslike_f\": 66.0, \"vis_km\": 16.0, \"vis_miles\": 9.0, \"uv\": 6.0, \"gust_mph\": 7.5, \"gust_kph\": 12.0}}"
|
||||
}
|
||||
],
|
||||
"type": "tool",
|
||||
"name": "tavily_search_results_json",
|
||||
"tool_call_id": "toolu_0148tMmDK51iLQfG1yaNwRHM",
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: updates...
|
||||
{
|
||||
"agent": {
|
||||
"messages": [
|
||||
{
|
||||
"content": "The weather in Los Angeles is currently overcast with a temperature of around 66°F (18.9°C). There are light winds from the north at around 2-3 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.",
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: end...
|
||||
None
|
||||
@@ -1,6 +1,9 @@
|
||||
# How to stream full state of your graph
|
||||
|
||||
This guide covers how to use `stream_mode="values"`, which streams the value of the state at each superstep. This differs from using `stream_mode="updates"`: instead of streaming just the updates to the state from each node, it streams the entire graph state at that superstep. Read [this conceptual guide](https://langchain-ai.github.io/langgraph/concepts/low_level/#stream-and-astream) to learn more.
|
||||
!!! info "Prerequisites"
|
||||
* [Streaming](../../concepts/streaming.md)
|
||||
|
||||
This guide covers how to use `stream_mode="values"`, which streams the value of the state at each superstep. This differs from using `stream_mode="updates"`: instead of streaming just the updates to the state from each node, it streams the entire graph state at that superstep.
|
||||
|
||||
## Setup
|
||||
|
||||
@@ -133,30 +136,93 @@ Now we can stream by values, which streams the full state of the graph after eac
|
||||
Output:
|
||||
|
||||
Receiving new event of type: metadata...
|
||||
{'run_id': 'f08791ce-0a3d-44e0-836c-ff62cd2e2786'}
|
||||
|
||||
|
||||
|
||||
{"run_id": "f08791ce-0a3d-44e0-836c-ff62cd2e2786"}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: values...
|
||||
{'messages': [{'role': 'human', 'content': 'what's the weather in la'}]}
|
||||
|
||||
|
||||
|
||||
{
|
||||
"messages": [
|
||||
{
|
||||
"role": "human",
|
||||
"content": "what's the weather in la"
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: values...
|
||||
{'messages': [{'content': 'what's the weather in la', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'faa15565-8823-4aa1-87af-e21b40526fae', 'example': False}, {'content': [{'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3fe1db7a-6b8d-4d83-ba07-8657190ad811', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}], 'invalid_tool_calls': []}]}
|
||||
|
||||
|
||||
|
||||
{
|
||||
"messages": [
|
||||
{
|
||||
"content": "what's the weather in la",
|
||||
"type": "human",
|
||||
...
|
||||
},
|
||||
{
|
||||
"content": "",
|
||||
"type": "ai",
|
||||
"tool_calls": [
|
||||
{
|
||||
"name": "tavily_search_results_json",
|
||||
"args": {
|
||||
"query": "weather in los angeles"
|
||||
},
|
||||
"id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
|
||||
}
|
||||
],
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
...
|
||||
|
||||
Receiving new event of type: values...
|
||||
{'messages': [{'content': 'what's the weather in la', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'faa15565-8823-4aa1-87af-e21b40526fae', 'example': False}, {'content': [{'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3fe1db7a-6b8d-4d83-ba07-8657190ad811', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}], 'invalid_tool_calls': []}, {'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716310320, \'localtime\': \'2024-05-21 9:52\'}, \'current\': {\'last_updated_epoch\': 1716309900, \'last_updated\': \'2024-05-21 09:45\', \'temp_c\': 16.7, \'temp_f\': 62.1, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 8.1, \'wind_kph\': 13.0, \'wind_degree\': 250, \'wind_dir\': \'WSW\', \'pressure_mb\': 1015.0, \'pressure_in\': 29.97, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 16.7, \'feelslike_f\': 62.1, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 5.0, \'gust_mph\': 12.5, \'gust_kph\': 20.2}}"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '0d5dab31-5ff8-4ae2-a560-bc4bcba7c9d7', 'tool_call_id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}]}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: values...
|
||||
{'messages': [{'content': 'what's the weather in la', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'faa15565-8823-4aa1-87af-e21b40526fae', 'example': False}, {'content': [{'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3fe1db7a-6b8d-4d83-ba07-8657190ad811', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}], 'invalid_tool_calls': []}, {'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716310320, \'localtime\': \'2024-05-21 9:52\'}, \'current\': {\'last_updated_epoch\': 1716309900, \'last_updated\': \'2024-05-21 09:45\', \'temp_c\': 16.7, \'temp_f\': 62.1, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 8.1, \'wind_kph\': 13.0, \'wind_degree\': 250, \'wind_dir\': \'WSW\', \'pressure_mb\': 1015.0, \'pressure_in\': 29.97, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 16.7, \'feelslike_f\': 62.1, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 5.0, \'gust_mph\': 12.5, \'gust_kph\': 20.2}}"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '0d5dab31-5ff8-4ae2-a560-bc4bcba7c9d7', 'tool_call_id': 'toolu_01E5mSaZWm5rWJnCqmt63v4g'}, {'content': 'Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-4d6d4c23-5aad-4042-b0d9-19407a9e08e3', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}
|
||||
|
||||
|
||||
|
||||
{
|
||||
"messages": [
|
||||
{
|
||||
"content": "what's the weather in la",
|
||||
"type": "human",
|
||||
...
|
||||
},
|
||||
{
|
||||
"content": "",
|
||||
"type": "ai",
|
||||
"tool_calls": [
|
||||
{
|
||||
"name": "tavily_search_results_json",
|
||||
"args": {
|
||||
"query": "weather in los angeles"
|
||||
},
|
||||
"id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
|
||||
}
|
||||
],
|
||||
...
|
||||
}
|
||||
{
|
||||
"content": [
|
||||
{
|
||||
"url": "https://www.weatherapi.com/",
|
||||
"content": "{\"location\": {\"name\": \"Los Angeles\", \"region\": \"California\", \"country\": \"United States of America\", \"lat\": 34.05, \"lon\": -118.24, \"tz_id\": \"America/Los_Angeles\", \"localtime_epoch\": 1716310320, \"localtime\": \"2024-05-21 9:52\"}, \"current\": {\"last_updated_epoch\": 1716309900, \"last_updated\": \"2024-05-21 09:45\", \"temp_c\": 16.7, \"temp_f\": 62.1, \"is_day\": 1, \"condition\": {\"text\": \"Overcast\", \"icon\": \"//cdn.weatherapi.com/weather/64x64/day/122.png\", \"code\": 1009}, \"wind_mph\": 8.1, \"wind_kph\": 13.0, \"wind_degree\": 250, \"wind_dir\": \"WSW\", \"pressure_mb\": 1015.0, \"pressure_in\": 29.97, \"precip_mm\": 0.0, \"precip_in\": 0.0, \"humidity\": 65, \"cloud\": 100, \"feelslike_c\": 16.7, \"feelslike_f\": 62.1, \"vis_km\": 16.0, \"vis_miles\": 9.0, \"uv\": 5.0, \"gust_mph\": 12.5, \"gust_kph\": 20.2}}"
|
||||
}
|
||||
],
|
||||
"type": "tool",
|
||||
"name": "tavily_search_results_json",
|
||||
"tool_call_id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
|
||||
...
|
||||
},
|
||||
{
|
||||
"content": "Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.",
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
|
||||
Receiving new event of type: end...
|
||||
None
|
||||
|
||||
@@ -228,40 +294,42 @@ If we want to just get the final result, we can use this endpoint and just keep
|
||||
|
||||
Output:
|
||||
|
||||
{'messages': [{'content': 'what's the weather in la',
|
||||
'additional_kwargs': {},
|
||||
'response_metadata': {},
|
||||
'type': 'human',
|
||||
'name': None,
|
||||
'id': 'e78c2f94-d810-42fc-a399-11f6bb1b1092',
|
||||
'example': False},
|
||||
{'content': [{'id': 'toolu_01SBMoAGr4U9x3ibztm2UUom',
|
||||
'input': {'query': 'weather in los angeles'},
|
||||
'name': 'tavily_search_results_json',
|
||||
'type': 'tool_use'}],
|
||||
'additional_kwargs': {},
|
||||
'response_metadata': {},
|
||||
'type': 'ai',
|
||||
'name': None,
|
||||
'id': 'run-80767ab8-09fc-40ec-9e45-657ddef5e0b1',
|
||||
'example': False,
|
||||
'tool_calls': [{'name': 'tavily_search_results_json',
|
||||
'args': {'query': 'weather in los angeles'},
|
||||
'id': 'toolu_01SBMoAGr4U9x3ibztm2UUom'}],
|
||||
'invalid_tool_calls': []},
|
||||
{'content': '[{"url": "https://www.weatherapi.com/", "content": "{\'location\': {\'name\': \'Los Angeles\', \'region\': \'California\', \'country\': \'United States of America\', \'lat\': 34.05, \'lon\': -118.24, \'tz_id\': \'America/Los_Angeles\', \'localtime_epoch\': 1716310320, \'localtime\': \'2024-05-21 9:52\'}, \'current\': {\'last_updated_epoch\': 1716309900, \'last_updated\': \'2024-05-21 09:45\', \'temp_c\': 16.7, \'temp_f\': 62.1, \'is_day\': 1, \'condition\': {\'text\': \'Overcast\', \'icon\': \'//cdn.weatherapi.com/weather/64x64/day/122.png\', \'code\': 1009}, \'wind_mph\': 8.1, \'wind_kph\': 13.0, \'wind_degree\': 250, \'wind_dir\': \'WSW\', \'pressure_mb\': 1015.0, \'pressure_in\': 29.97, \'precip_mm\': 0.0, \'precip_in\': 0.0, \'humidity\': 65, \'cloud\': 100, \'feelslike_c\': 16.7, \'feelslike_f\': 62.1, \'vis_km\': 16.0, \'vis_miles\': 9.0, \'uv\': 5.0, \'gust_mph\': 12.5, \'gust_kph\': 20.2}}"}]',
|
||||
'additional_kwargs': {},
|
||||
'response_metadata': {},
|
||||
'type': 'tool',
|
||||
'name': 'tavily_search_results_json',
|
||||
'id': 'af25e94a-c119-48c3-bbd3-096e42f472ac',
|
||||
'tool_call_id': 'toolu_01SBMoAGr4U9x3ibztm2UUom'},
|
||||
{'content': 'Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.',
|
||||
'additional_kwargs': {},
|
||||
'response_metadata': {},
|
||||
'type': 'ai',
|
||||
'name': None,
|
||||
'id': 'run-b90f0037-e56a-4f3b-ad92-00d10d079a9e',
|
||||
'example': False,
|
||||
'tool_calls': [],
|
||||
'invalid_tool_calls': []}]}
|
||||
{
|
||||
"messages": [
|
||||
{
|
||||
"content": "what's the weather in la",
|
||||
"type": "human",
|
||||
...
|
||||
},
|
||||
{
|
||||
"type": "ai",
|
||||
"tool_calls": [
|
||||
{
|
||||
"name": "tavily_search_results_json",
|
||||
"args": {
|
||||
"query": "weather in los angeles"
|
||||
},
|
||||
"id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
|
||||
}
|
||||
],
|
||||
...
|
||||
}
|
||||
{
|
||||
"content": [
|
||||
{
|
||||
"url": "https://www.weatherapi.com/",
|
||||
"content": "{\"location\": {\"name\": \"Los Angeles\", \"region\": \"California\", \"country\": \"United States of America\", \"lat\": 34.05, \"lon\": -118.24, \"tz_id\": \"America/Los_Angeles\", \"localtime_epoch\": 1716310320, \"localtime\": \"2024-05-21 9:52\"}, \"current\": {\"last_updated_epoch\": 1716309900, \"last_updated\": \"2024-05-21 09:45\", \"temp_c\": 16.7, \"temp_f\": 62.1, \"is_day\": 1, \"condition\": {\"text\": \"Overcast\", \"icon\": \"//cdn.weatherapi.com/weather/64x64/day/122.png\", \"code\": 1009}, \"wind_mph\": 8.1, \"wind_kph\": 13.0, \"wind_degree\": 250, \"wind_dir\": \"WSW\", \"pressure_mb\": 1015.0, \"pressure_in\": 29.97, \"precip_mm\": 0.0, \"precip_in\": 0.0, \"humidity\": 65, \"cloud\": 100, \"feelslike_c\": 16.7, \"feelslike_f\": 62.1, \"vis_km\": 16.0, \"vis_miles\": 9.0, \"uv\": 5.0, \"gust_mph\": 12.5, \"gust_kph\": 20.2}}"
|
||||
}
|
||||
],
|
||||
"type": "tool",
|
||||
"name": "tavily_search_results_json",
|
||||
"tool_call_id": "toolu_01E5mSaZWm5rWJnCqmt63v4g"
|
||||
...
|
||||
},
|
||||
{
|
||||
"content": "Based on the weather API results, the current weather in Los Angeles is overcast with a temperature of around 62°F (17°C). There are light winds from the west-southwest around 8-13 mph. The humidity is 65% and visibility is good at 9 miles. Overall, mild spring weather conditions in LA.",
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 405 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 884 KiB |
+260
-199
@@ -1,6 +1,8 @@
|
||||
# Quick Start
|
||||
|
||||
This quick start guide will cover how to build a simple agent that can look up things on the internet. We will then deploy it to LangGraph Cloud, use the LangGraph Studio to visualize and test it out, and use the LangGraph SDK to interact with it.
|
||||
In this tutorial you will build and deploy a simple chatbot agent that can look things up on the internet. You will be using [LangGraph Cloud](../concepts/langgraph_cloud.md), [LangGraph Studio](../concepts/langgraph_studio.md) to visualize and test it out, and [LangGraph SDK](./reference/sdk/python_sdk_ref.md) to interact with the deployed agent.
|
||||
|
||||
If you want to learn how to build an agent like this from scratch, take a look at the [LangGraph Quick Start tutorial](../tutorials/introduction.ipynb).
|
||||
|
||||
## Set up requirements
|
||||
|
||||
@@ -10,146 +12,183 @@ This tutorial will use:
|
||||
- Tavily for the search engine - sign up and get an API key [here](https://app.tavily.com/)
|
||||
- LangSmith for hosting - sign up and get an API key [here](https://smith.langchain.com/)
|
||||
|
||||
## Set up local files
|
||||
## Create and configure your app
|
||||
|
||||
1. Create a new application with the following directory and files:
|
||||
First, let's set create all of the necessary files for our LangGraph application.
|
||||
|
||||
=== "Python"
|
||||
1. __Create application directory and files__
|
||||
|
||||
<my-app>/
|
||||
|-- agent.py # code for your LangGraph agent
|
||||
|-- requirements.txt # Python packages required for your graph
|
||||
|-- langgraph.json # configuration file for LangGraph
|
||||
|-- .env # environment files with API keys
|
||||
Create a new application `my-app` with the following file structure:
|
||||
|
||||
=== "Javascript"
|
||||
|
||||
<my-app>/
|
||||
|-- agent.ts # code for your LangGraph agent
|
||||
|-- package.json # Javascript packages required for your graph
|
||||
|-- langgraph.json # configuration file for LangGraph
|
||||
|-- .env # environment files with API keys
|
||||
|
||||
2. The `agent.py`/`agent.ts` file should contain code for defining your graph. The following code is a simple example, the important thing is that at some point in your file you compile your graph and assign the compiled graph to a variable (in this case the `graph` variable). This example code uses `create_react_agent`, a prebuilt agent. You can read more about it [here](../concepts/agentic_concepts.md#react-implementation).
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
from langchain_anthropic import ChatAnthropic
|
||||
from langchain_community.tools.tavily_search import TavilySearchResults
|
||||
from langgraph.prebuilt import create_react_agent
|
||||
|
||||
model = ChatAnthropic(model="claude-3-5-sonnet-20240620")
|
||||
|
||||
tools = [TavilySearchResults(max_results=2)]
|
||||
|
||||
graph = create_react_agent(model, tools)
|
||||
```shell
|
||||
mkdir my-app
|
||||
```
|
||||
|
||||
=== "Javascript"
|
||||
=== "Python"
|
||||
|
||||
```ts
|
||||
import { ChatAnthropic } from "@langchain/anthropic";
|
||||
import { TavilySearchResults } from "@langchain/community/tools/tavily_search";
|
||||
import { createReactAgent } from "@langchain/langgraph/prebuilt";
|
||||
my-app/
|
||||
|-- agent.py # code for your LangGraph agent
|
||||
|-- requirements.txt # Python packages required for your graph
|
||||
|-- langgraph.json # configuration file for LangGraph
|
||||
|-- .env # environment files with API keys
|
||||
|
||||
const model = new ChatAnthropic({
|
||||
model: "claude-3-5-sonnet-20240620",
|
||||
});
|
||||
=== "Javascript"
|
||||
|
||||
const tools = [
|
||||
new TavilySearchResults({ maxResults: 3, }),
|
||||
];
|
||||
my-app/
|
||||
|-- agent.ts # code for your LangGraph agent
|
||||
|-- package.json # Javascript packages required for your graph
|
||||
|-- langgraph.json # configuration file for LangGraph
|
||||
|-- .env # environment files with API keys
|
||||
|
||||
export const graph = createReactAgent({ llm: model, tools });
|
||||
```
|
||||
|
||||
3. The `requirements.txt`/`package.json` file should contain any dependencies for your graph(s). In this case we only require four packages for our graph to run:
|
||||
1. __Define your graph__
|
||||
|
||||
=== "Python"
|
||||
=== "Python"
|
||||
The `agent.py` file should contain code with your graph.
|
||||
|
||||
```python
|
||||
langgraph
|
||||
langchain_anthropic
|
||||
tavily-python
|
||||
langchain_community
|
||||
```
|
||||
=== "Javascript"
|
||||
The `agent.ts` file should contain code with your graph.
|
||||
|
||||
=== "Javascript"
|
||||
The following code example is a simple chatbot agent (similar to the one in the [previous tutorial](../tutorials/introduction.ipynb)). Specifically, it uses [create_react_agent][langgraph.prebuilt.chat_agent_executor.create_react_agent], a prebuilt [ReAct](../concepts/agentic_concepts.md#react-implementation)-style agent.
|
||||
|
||||
```js
|
||||
{
|
||||
"name": "my-app",
|
||||
"packageManager": "yarn@1.22.22",
|
||||
"dependencies": {
|
||||
"@langchain/community": "^0.2.31",
|
||||
"@langchain/core": "^0.2.31",
|
||||
"@langchain/langgraph": "0.2.0",
|
||||
"@langchain/openai": "^0.2.8"
|
||||
The `agent` file needs to have a variable with a [CompiledGraph][langgraph.graph.graph.CompiledGraph] (in this case the `graph` variable).
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
# agent.py
|
||||
from langchain_anthropic import ChatAnthropic
|
||||
from langchain_community.tools.tavily_search import TavilySearchResults
|
||||
from langgraph.prebuilt import create_react_agent
|
||||
|
||||
model = ChatAnthropic(model="claude-3-5-sonnet-20240620")
|
||||
|
||||
tools = [TavilySearchResults(max_results=2)]
|
||||
|
||||
# compiled graph
|
||||
graph = create_react_agent(model, tools)
|
||||
```
|
||||
|
||||
=== "Javascript"
|
||||
|
||||
```ts
|
||||
// agent.ts
|
||||
import { ChatAnthropic } from "@langchain/anthropic";
|
||||
import { TavilySearchResults } from "@langchain/community/tools/tavily_search";
|
||||
import { createReactAgent } from "@langchain/langgraph/prebuilt";
|
||||
|
||||
const model = new ChatAnthropic({
|
||||
model: "claude-3-5-sonnet-20240620",
|
||||
});
|
||||
|
||||
const tools = [
|
||||
new TavilySearchResults({ maxResults: 3, }),
|
||||
];
|
||||
|
||||
// compiled graph
|
||||
export const graph = createReactAgent({ llm: model, tools });
|
||||
```
|
||||
|
||||
1. __Specify dependencies__
|
||||
|
||||
=== "Python"
|
||||
You should add dependencies for your graph(s) to `requirements.txt`.
|
||||
|
||||
=== "Javascript"
|
||||
You should add dependencies for your graph(s) to `package.json`.
|
||||
|
||||
In this case we only require four packages for our graph to run:
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
langgraph
|
||||
langchain_anthropic
|
||||
tavily-python
|
||||
langchain_community
|
||||
```
|
||||
|
||||
=== "Javascript"
|
||||
|
||||
```js
|
||||
{
|
||||
"name": "my-app",
|
||||
"packageManager": "yarn@1.22.22",
|
||||
"dependencies": {
|
||||
"@langchain/community": "^0.3.11",
|
||||
"@langchain/core": "^0.3.16",
|
||||
"@langchain/langgraph": "0.2.18",
|
||||
"@langchain/anthropic": "^0.3.7"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
1. __Create LangGraph configuration file__
|
||||
|
||||
The [`langgraph.json`][langgraph.json] file is a configuration file that describes what graph(s) you are going to deploy. In this case we only have one graph: the compiled `graph` object from `agent.py` / `agent.ts`.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```json
|
||||
{
|
||||
"dependencies": ["."],
|
||||
"graphs": {
|
||||
"agent": "./agent.py:graph"
|
||||
},
|
||||
"env": ".env"
|
||||
}
|
||||
}
|
||||
```
|
||||
```
|
||||
|
||||
4. The [`langgraph.json`][langgraph.json] file is a configuration file that describes what graph(s) you are going to host. In this case we only have one graph to host: the compiled `graph` object from `agent.py`/`agent.ts`.
|
||||
=== "Javascript"
|
||||
|
||||
=== "Python"
|
||||
```json
|
||||
{
|
||||
"node_version": "20",
|
||||
"dockerfile_lines": [],
|
||||
"dependencies": ["."],
|
||||
"graphs": {
|
||||
"agent": "./src/agent.ts:graph"
|
||||
},
|
||||
"env": ".env"
|
||||
}
|
||||
```
|
||||
|
||||
```json
|
||||
{
|
||||
"dependencies": ["."],
|
||||
"graphs": {
|
||||
"agent": "./agent.py:graph"
|
||||
},
|
||||
"env": ".env"
|
||||
}
|
||||
```
|
||||
Learn more about the LangGraph CLI configuration file [here](./reference/cli.md#configuration-file).
|
||||
|
||||
=== "Javascript"
|
||||
1. __Specify environment variables__
|
||||
|
||||
```json
|
||||
{
|
||||
"node_version": "20",
|
||||
"dockerfile_lines": [],
|
||||
"dependencies": ["."],
|
||||
"graphs": {
|
||||
"agent": "./src/agent.ts:graph"
|
||||
},
|
||||
"env": ".env"
|
||||
}
|
||||
```
|
||||
The `.env` file should have any environment variables needed to run your graph. This will only be used for local testing, so if you are not testing locally you can skip this step.
|
||||
|
||||
Learn more about the LangGraph CLI configuration file [here](./reference/cli.md#configuration-file).
|
||||
!!! warning
|
||||
The `.env` file should NOT be included with the rest of source code in your Github repository. When creating a deployment using LangGraph Cloud, you will be able to specify the environment variables manually.
|
||||
|
||||
5. The `.env` file should have any environment variables needed to run your graph. This will only be used for local testing, so if you are not testing locally you can skip this step. NOTE: if you do add this, you should NOT check this into git. For this graph, we need two environment variables:
|
||||
For this graph, we need two environment variables:
|
||||
|
||||
```shell
|
||||
ANTHROPIC_API_KEY=...
|
||||
TAVILY_API_KEY=...
|
||||
```
|
||||
|
||||
Now that we have set everything up on our local file system, we are ready to host our graph.
|
||||
!!! tip
|
||||
Learn more about different application structure options [here](../how-tos/index.md#application-structure).
|
||||
|
||||
## Test the graph build locally
|
||||
Now that we have set everything up on our local file system, we are ready to test our graph locally.
|
||||
|
||||
### Using LangGraph Studio Desktop (recommended)
|
||||
## Test the app locally
|
||||
|
||||
|
||||
To test the LangGraph app before deploying it using LangGraph Cloud, you can use [LangGraph Studio](../concepts/langgraph_studio.md) or start the [LangGraph server](../concepts/langgraph_server.md) locally.
|
||||
|
||||
Testing your graph locally is easy with LangGraph Studio Desktop. LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications
|
||||
## Using local server
|
||||
|
||||
With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with [LangSmith](https://smith.langchain.com) so you can collaborate with teammates to debug failure modes.
|
||||
You can also test your app by running [LangGraph server](../concepts/langgraph_server.md) locally. This is useful to make sure you have configured our [CLI configuration file][langgraph.json] correctly and can interact with your graph.
|
||||
|
||||
### Using the LangGraph CLI
|
||||
|
||||
Before deploying to the cloud, we probably want to test the building of our graph locally. This is useful to make sure we have configured our [CLI configuration file][langgraph.json] correctly and our graph runs.
|
||||
|
||||
In order to do this we can first install the LangGraph CLI
|
||||
To run the server locally, you need to first install the LangGraph CLI:
|
||||
|
||||
```shell
|
||||
pip install langgraph-cli
|
||||
```
|
||||
|
||||
We can then test our API server locally. This requires access to LangGraph closed beta. In order to run the server locally, you will need to add your `LANGSMITH_API_KEY` to the .env file so we can validate you have access to LangGraph closed beta.
|
||||
You can then test our API server locally. In order to run the server locally, you will need to add your `LANGSMITH_API_KEY` to the `.env` file.
|
||||
|
||||
```shell
|
||||
langgraph up
|
||||
@@ -160,10 +199,21 @@ This will start up the LangGraph API server locally. If this runs successfully,
|
||||
```shell
|
||||
Ready!
|
||||
- API: http://localhost:8123
|
||||
2024-06-26 19:20:41,056:INFO:uvicorn.access 127.0.0.1:44138 - "GET /ok HTTP/1.1" 200
|
||||
```
|
||||
|
||||
You can now test this out! **Note: this local server is intended SOLELY for local testing purposes and is not performant enough for production applications, so please do not use it as such.** To test it out, you can go to another terminal window and run:
|
||||
First, let's verify that the server is running correctly by calling `/ok` endpoint:
|
||||
|
||||
```shell
|
||||
curl --request GET --url http://localhost:8123/ok
|
||||
```
|
||||
|
||||
Output:
|
||||
|
||||
```
|
||||
{"ok": "true"}
|
||||
```
|
||||
|
||||
Now we're ready to test the app with the real inputs!
|
||||
|
||||
```shell
|
||||
curl --request POST \
|
||||
@@ -175,36 +225,56 @@ curl --request POST \
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "How are you?"
|
||||
"content": "What is the weather in NYC?"
|
||||
}
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"config": {
|
||||
"configurable": {}
|
||||
},
|
||||
"multitask_strategy": "reject",
|
||||
"stream_mode": [
|
||||
"values"
|
||||
]
|
||||
"stream_mode": "updates"
|
||||
}'
|
||||
```
|
||||
|
||||
If you get back a valid response, then all is functioning properly!
|
||||
Output:
|
||||
|
||||
## Deploy to Cloud
|
||||
```
|
||||
...
|
||||
|
||||
### Push your code to GitHub
|
||||
data: {
|
||||
"agent": {
|
||||
"messages": [
|
||||
{
|
||||
"content": "The search results from Tavily provide the current weather conditions in New York City, including temperature, wind speed, precipitation, humidity, and cloud cover. According to the results, as of 3:00pm on October 30th, 2024, it is overcast in NYC with a temperature of around 66°F (19°C), light winds from the southwest around 8 mph (13 km/h), and 66% humidity.\n\nSo in summary, the current weather in NYC is overcast with mild temperatures in the mid 60sF and light winds, based on the search results. Let me know if you need any other details!",
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
Turn the `<my-app>` directory into a GitHub repo. You can use the GitHub CLI if you like, or just create a repo manually (if unfamiliar, instructions [here](https://docs.github.com/en/migrations/importing-source-code/using-the-command-line-to-import-source-code/adding-locally-hosted-code-to-github)).
|
||||
You can see that our agent responds with the up-to-date search results!
|
||||
|
||||
### Deploy from GitHub with LangGraph Cloud
|
||||
### Using LangGraph Studio Desktop
|
||||
|
||||
Once you have created your github repository with a Python file containing your compiled graph as well as a `langgraph.json` file containing the configuration for hosting your graph, you can head over to LangSmith and click on the 🚀 icon on the left navbar to create a new deployment. Then click the `+ New Deployment` button.
|
||||
You can also test your app locally with [LangGraph Studio](../concepts/langgraph_studio.md). LangGraph Studio offers a new way to develop LLM applications by providing a specialized agent IDE that enables visualization, interaction, and debugging of complex agentic applications.
|
||||
|
||||
|
||||
With visual graphs and the ability to edit state, you can better understand agent workflows and iterate faster. LangGraph Studio integrates with LangSmith allowing you to collaborate with teammates to debug failure modes.
|
||||
|
||||
**_If you have not deployed to LangGraph Cloud before:_** there will be a button that shows up saying Import from GitHub. You’ll need to follow that flow to connect LangGraph Cloud to GitHub.
|
||||
LangGraph Studio is available as a [desktop app](https://studio.langchain.com/) for MacOS users. Once you have installed the app, you can select `my-app` directory, which will automatically start the server locally and load the graph in the UI.
|
||||
|
||||
To interact with your chatbot agent in LangGraph Studio, you can add a new message in the `Input` section and press `Submit`.
|
||||
|
||||
|
||||
|
||||
## Deploy to LangGraph Cloud
|
||||
|
||||
Once you've tested your graph locally and verified that it works as expected, you can deploy it to the LangGraph Cloud.
|
||||
|
||||
First, you'll need to turn the `my-app` directory into a GitHub repo and [push it to GitHub](https://docs.github.com/en/migrations/importing-source-code/using-the-command-line-to-import-source-code/adding-locally-hosted-code-to-github).
|
||||
|
||||
Once you have created your GitHub repository with a Python file containing your compiled graph as well as a `langgraph.json` with the configuration, you can head over to [LangSmith](https://smith.langchain.com/) and click on the graph icon (`LangGraph Cloud`) on the bottom of the left navbar. This will open the LangGraph deployments page. On this page, click the `+ New Deployment` button in the top right corner.
|
||||
|
||||
|
||||
|
||||
**_If you have not deployed to LangGraph Cloud before:_** there will be a button that shows up saying `Import from GitHub`. You’ll need to follow that flow to connect LangGraph Cloud to GitHub.
|
||||
|
||||
**_Once you have set up your GitHub connection:_** the new deployment page will look as follows:
|
||||
|
||||
@@ -213,53 +283,43 @@ Once you have created your github repository with a Python file containing your
|
||||
To deploy your application, you should do the following:
|
||||
|
||||
1. Select your GitHub username or organization from the selector
|
||||
2. Search for your repo to deploy in the search bar and select it
|
||||
3. Choose any name
|
||||
4. In the `LangGraph API config file` field, enter the path to your `langgraph.json` file (which in this case is just `langgraph.json`)
|
||||
5. For Git Reference, you can select either the git branch for the code you want to deploy, or the exact commit SHA.
|
||||
6. If your chain relies on environment variables, add those in. They will be propagated to the underlying server so your code can access them. In this case, we need `ANTHROPIC_API_KEY` and `TAVILY_API_KEY`.
|
||||
|
||||
Putting this all together, you should have something as follows for your deployment details:
|
||||
|
||||
|
||||
1. Search for your repo to deploy in the search bar and select it
|
||||
1. Choose a name for your deployment
|
||||
1. In the `Git Branch` field, you can specify either the branch for the code you want to deploy, or the exact commit SHA.
|
||||
1. In the `LangGraph API config file` field, enter the path to your `langgraph.json` file (which in this case is just `langgraph.json`)
|
||||
1. If your application needs environment variables, add those in the `Environment Variables` section. They will be propagated to the underlying server so your code can access them. In this case, we will need `ANTHROPIC_API_KEY` and `TAVILY_API_KEY`.
|
||||
|
||||
Hit `Submit` and your application will start deploying!
|
||||
|
||||
## Inspect Traces + Monitor Service
|
||||
|
||||
### Deployments View
|
||||
|
||||
After your deployment is complete, your deployments page should look as follows:
|
||||
|
||||
|
||||
|
||||
You can see that by default, you get access to the `Trace Count` monitoring chart and `Recent Traces` run view. These are powered by LangSmith.
|
||||
## Interact with your deployment
|
||||
|
||||
You can click on `All Charts` to view all monitoring info for your server, or click on `See tracing project` to get more information on an individual trace.
|
||||
### Using LangGraph Studio (Cloud)
|
||||
|
||||
### Access the Docs
|
||||
|
||||
You can access the docs by clicking on the API docs link, which should send you to a page that looks like this:
|
||||
|
||||
|
||||
|
||||
You won’t actually be able to test any of the API endpoints without authorizing first. To do so, grab your Langsmith API key and add it at the top where it says `API KEY (X-API-KEY)`. You should now be able to select any of the API endpoints, click `Test Request`, enter the parameters you would like to pass, and then click `Send` to view the results of the API call.
|
||||
|
||||
## Interact with your deployment via LangGraph Studio
|
||||
|
||||
If you click on your deployment you should see a blue button in the top right that says `LangGraph Studio`. Clicking on this button will take you to a page that looks like this:
|
||||
|
||||
|
||||
|
||||
On this page you can test out your graph by passing in starting states and clicking `Start Run` (this should behave identically to calling `.invoke`). You will then be able to look into the execution thread for each run and explore the steps your graph is taking to produce its output.
|
||||
On the deployment page for your application,, you should see a button in the top right corner that says `LangGraph Studio`. Clicking on this button will take you to the web version of LangGraph Studio. This is the same UI that you interacted with when [testing the app locally](#using-langgraph-studio-recommended), but instead of using a local LangGraph server, it uses the one from your LangGraph Cloud deployment.
|
||||
|
||||
|
||||
|
||||
## Use with the SDK
|
||||
### Using LangGraph SDK
|
||||
|
||||
Once you have tested that your hosted graph works as expected using LangGraph Studio, you can start using your hosted graph all over your organization by using the LangGraph SDK. Let's see how we can access our hosted graph and execute our run from a python file.
|
||||
You can also interact with your deployed LangGraph application programmatically, using [LangGraph SDK](./reference/sdk/python_sdk_ref.md).
|
||||
|
||||
First, make sure you have the SDK installed by calling `pip install langgraph_sdk`.
|
||||
First, make sure you have the SDK installed:
|
||||
|
||||
=== "Python"
|
||||
|
||||
```shell
|
||||
pip install langgraph_sdk
|
||||
```
|
||||
|
||||
=== "Javascript"
|
||||
|
||||
```shell
|
||||
yarn add @langchain/langgraph-sdk
|
||||
```
|
||||
|
||||
Before using, you need to get the URL of your LangGraph deployment. You can find this in the `Deployment` view. Click the URL to copy it to the clipboard.
|
||||
|
||||
@@ -278,8 +338,8 @@ The first thing to do when using the SDK is to setup our client, access our assi
|
||||
|
||||
client = get_client(url=<DEPLOYMENT_URL>)
|
||||
# get default assistant
|
||||
assistants = await client.assistants.search()
|
||||
assistant = [a for a in assistants if not a["config"]][0]
|
||||
assistants = await client.assistants.search(metadata={"created_by": "system"})
|
||||
assistant = assistants[0]
|
||||
# create thread
|
||||
thread = await client.threads.create()
|
||||
print(thread)
|
||||
@@ -292,8 +352,8 @@ The first thing to do when using the SDK is to setup our client, access our assi
|
||||
|
||||
const client = new Client({ apiUrl: <DEPLOYMENT_URL> });
|
||||
// get default assistant
|
||||
const assistants = await client.assistants.search();
|
||||
const assistant = assistants.find(a => !a.config);
|
||||
const assistants = await client.assistants.search({ metadata: {"created_by": "system"} })
|
||||
const assistant = assistants[0];
|
||||
// create thread
|
||||
const thread = await client.threads.create();
|
||||
console.log(thread)
|
||||
@@ -307,8 +367,9 @@ The first thing to do when using the SDK is to setup our client, access our assi
|
||||
--header 'Content-Type: application/json' \
|
||||
--data '{
|
||||
"limit": 10,
|
||||
"offset": 0
|
||||
}' | jq -c 'map(select(.config == null or .config == {})) | .[0]' && \
|
||||
"offset": 0,
|
||||
"metadata": {"created_by": "system"}
|
||||
}' &&
|
||||
curl --request POST \
|
||||
--url <DEPLOYMENT_URL>/threads \
|
||||
--header 'Content-Type: application/json' \
|
||||
@@ -320,32 +381,35 @@ We can then execute a run on the thread:
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
input = {"messages":[{"role": "user", "content": "Hello! My name is Bagatur and I am 26 years old."}]}
|
||||
input = {
|
||||
"messages": [{"role": "user", "content": "What is the weather in NYC?"}]
|
||||
}
|
||||
|
||||
async for chunk in client.runs.stream(
|
||||
thread['thread_id'],
|
||||
assistant["assistant_id"],
|
||||
input=input,
|
||||
stream_mode="updates",
|
||||
):
|
||||
if chunk.data and chunk.event != "metadata":
|
||||
thread["thread_id"],
|
||||
assistant["assistant_id"],
|
||||
input=input,
|
||||
stream_mode="updates",
|
||||
):
|
||||
if chunk.data:
|
||||
print(chunk.data)
|
||||
```
|
||||
|
||||
=== "Javascript"
|
||||
|
||||
```js
|
||||
const input = { "messages":[{ "role": "user", "content": "Hello! My name is Bagatur and I am 26 years old." }] };
|
||||
const input = { "messages": [{ "role": "user", "content": "What is the weather in NYC?" }] };
|
||||
|
||||
const streamResponse = client.runs.stream(
|
||||
thread["thread_id"],
|
||||
assistant["assistant_id"],
|
||||
{
|
||||
input,
|
||||
streamMode: "updates"
|
||||
}
|
||||
);
|
||||
for await (const chunk of streamResponse) {
|
||||
if (chunk.data && chunk.event !== "metadata" ) {
|
||||
if (chunk.data) {
|
||||
console.log(chunk.data);
|
||||
}
|
||||
}
|
||||
@@ -357,43 +421,40 @@ We can then execute a run on the thread:
|
||||
curl --request POST \
|
||||
--url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data "{
|
||||
\"assistant_id\": <ASSISTANT_ID>,
|
||||
\"input\": {\"messages\": [{\"role\": \"human\", \"content\": \"Hello! My name is Bagatur and I am 26 years old.\"}]},
|
||||
}" | sed 's/\r$//' | awk '
|
||||
/^event:/ { event = $2 }
|
||||
/^data:/ {
|
||||
json_data = substr($0, index($0, $2))
|
||||
|
||||
if (event != "metadata") {
|
||||
print json_data
|
||||
}
|
||||
--data '{
|
||||
"assistant_id": <ASSISTANT_ID>,
|
||||
"input": {
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What is the weather in NYC?"
|
||||
}
|
||||
]
|
||||
},
|
||||
"stream_mode": "updates"
|
||||
}'
|
||||
```
|
||||
|
||||
|
||||
Output:
|
||||
|
||||
{'agent': {'messages': [{'content': "Hi Bagatur! It's nice to meet you. How can I assist you today?", 'additional_kwargs': {}, 'response_metadata': {'finish_reason': 'stop', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_9cb5d38cf7'}, 'type': 'ai', 'name': None, 'id': 'run-c89118b7-1b1e-42b9-a85d-c43fe99881cd', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}
|
||||
```
|
||||
...
|
||||
|
||||
## What's Next
|
||||
data: {
|
||||
"agent": {
|
||||
"messages": [
|
||||
{
|
||||
"content": "The search results from Tavily provide the current weather conditions in New York City, including temperature, wind speed, precipitation, humidity, and cloud cover. According to the results, as of 3:00pm on October 30th, 2024, it is overcast in NYC with a temperature of around 66°F (19°C), light winds from the southwest around 8 mph (13 km/h), and 66% humidity.\n\nSo in summary, the current weather in NYC is overcast with mild temperatures in the mid 60sF and light winds, based on the search results. Let me know if you need any other details!",
|
||||
"type": "ai",
|
||||
...
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
## Next steps
|
||||
|
||||
Congratulations! If you've worked your way through this tutorial you are well on your way to becoming a LangGraph Cloud expert. Here are some other resources to check out to help you out on the path to expertise:
|
||||
|
||||
### LangGraph Cloud How-tos
|
||||
|
||||
If you want to learn more about streaming from hosted graphs, check out the Streaming [how-to guides](how-tos/index.md#streaming).
|
||||
|
||||
To learn more about double-texting and all the ways you can handle it in your application, read up on these [how-to guides](how-tos/index.md#double-texting).
|
||||
|
||||
To learn about how to include different human-in-the-loop behavior in your graph, take a look at [these how-tos](how-tos/index.md#human-in-the-loop).
|
||||
|
||||
### LangGraph Tutorials
|
||||
|
||||
Before hosting, you have to write a graph to host. Here are some tutorials to get you more comfortable with writing LangGraph graphs and give you inspiration for the types of graphs you want to host.
|
||||
|
||||
[This tutorial](../tutorials/customer-support/customer-support.ipynb) walks you through how to write a customer support bot using LangGraph.
|
||||
|
||||
If you are interested in writing a SQL agent, check out [this tutorial](../tutorials/sql-agent.ipynb).
|
||||
|
||||
Check out the [LangGraph tutorials](../tutorials/index.md) page to read about more exciting use cases.
|
||||
* [LangGraph How-to guides](../how-tos/index.md)
|
||||
* [LangGraph Tutorials](../tutorials/index.md)
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,23 +1,38 @@
|
||||
# LangGraph CLI
|
||||
The LangGraph CLI includes commands to build and run a LangGraph Cloud API server locally in [Docker](https://www.docker.com/). For development and testing, use the CLI to deploy a local API server.
|
||||
|
||||
The LangGraph command line interface includes commands to build and run a LangGraph Cloud API server locally in [Docker](https://www.docker.com/). For development and testing, you can use the CLI to deploy a local API server as an alternative to the [Studio desktop app](../../concepts/langgraph_studio.md).
|
||||
|
||||
## Installation
|
||||
|
||||
1. Ensure that Docker is installed (e.g. `docker --version`).
|
||||
2. Install the `langgraph-cli` Python package (e.g. `pip install langgraph-cli`).
|
||||
2. Install the `langgraph-cli` package:
|
||||
|
||||
=== "pip"
|
||||
```bash
|
||||
pip install langgraph-cli
|
||||
```
|
||||
|
||||
=== "Homebrew (MacOS only)"
|
||||
```bash
|
||||
brew install langgraph-cli
|
||||
```
|
||||
|
||||
3. Run the command `langgraph --help` to confirm that the CLI is installed.
|
||||
|
||||
[](){#langgraph.json}
|
||||
|
||||
## Configuration File
|
||||
|
||||
The LangGraph CLI requires a JSON configuration file with the following keys:
|
||||
|
||||
| Key | Description |
|
||||
| --- | ----------- |
|
||||
| `dependencies` | **Required**. Array of dependencies for LangGraph Cloud API server. Dependencies can be one of the following: (1) `"."`, which will look for local Python packages, (2) `pyproject.toml`, `setup.py` or `requirements.txt` in the app directory `"./local_package"`, or (3) a package name. |
|
||||
| `graphs` | **Required**. Mapping from graph ID to path where the compiled graph or a function that makes a graph is defined. Example: <ul><li>`./your_package/your_file.py:variable`, where `variable` is an instance of `langgraph.graph.state.CompiledStateGraph`</li><li>`./your_package/your_file.py:make_graph`, where `make_graph` is a function that takes a config dictionary (`langchain_core.runnables.RunnableConfig`) and creates an instance of `langgraph.graph.state.StateGraph` / `langgraph.graph.state.CompiledStateGraph`.</li></ul> |
|
||||
| `env` | Path to `.env` file or a mapping from environment variable to its value. |
|
||||
| `python_version` | `3.11` or `3.12`. Defaults to `3.11`. |
|
||||
| `pip_config_file`| Path to `pip` config file. |
|
||||
| `dockerfile_lines` | Array of additional lines to add to Dockerfile following the import from parent image. |
|
||||
| Key | Description |
|
||||
|--------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| `dependencies` | **Required**. Array of dependencies for LangGraph Cloud API server. Dependencies can be one of the following: (1) `"."`, which will look for local Python packages, (2) `pyproject.toml`, `setup.py` or `requirements.txt` in the app directory `"./local_package"`, or (3) a package name. |
|
||||
| `graphs` | **Required**. Mapping from graph ID to path where the compiled graph or a function that makes a graph is defined. Example: <ul><li>`./your_package/your_file.py:variable`, where `variable` is an instance of `langgraph.graph.state.CompiledStateGraph`</li><li>`./your_package/your_file.py:make_graph`, where `make_graph` is a function that takes a config dictionary (`langchain_core.runnables.RunnableConfig`) and creates an instance of `langgraph.graph.state.StateGraph` / `langgraph.graph.state.CompiledStateGraph`.</li></ul> |
|
||||
| `env` | Path to `.env` file or a mapping from environment variable to its value. |
|
||||
| `python_version` | `3.11` or `3.12`. Defaults to `3.11`. |
|
||||
| `pip_config_file` | Path to `pip` config file. |
|
||||
| `dockerfile_lines` | Array of additional lines to add to Dockerfile following the import from parent image. |
|
||||
|
||||
<div class="admonition tip">
|
||||
<p class="admonition-title">Note</p>
|
||||
@@ -27,101 +42,134 @@ The LangGraph CLI requires a JSON configuration file with the following keys:
|
||||
</div>
|
||||
|
||||
Example:
|
||||
|
||||
```json
|
||||
{
|
||||
"dependencies": [
|
||||
"langchain_openai",
|
||||
"./your_package"
|
||||
],
|
||||
"graphs": {
|
||||
"my_graph_id": "./your_package/your_file.py:variable"
|
||||
},
|
||||
"env": "./.env"
|
||||
"dependencies": ["langchain_openai", "./your_package"],
|
||||
"graphs": {
|
||||
"my_graph_id": "./your_package/your_file.py:variable"
|
||||
},
|
||||
"env": "./.env"
|
||||
}
|
||||
```
|
||||
|
||||
Example:
|
||||
|
||||
```json
|
||||
{
|
||||
"python_version": "3.11",
|
||||
"dependencies": [
|
||||
"langchain_openai",
|
||||
"."
|
||||
],
|
||||
"graphs": {
|
||||
"my_graph_id": "./your_package/your_file.py:make_graph"
|
||||
},
|
||||
"env": {
|
||||
"OPENAI_API_KEY": "secret-key"
|
||||
}
|
||||
"python_version": "3.11",
|
||||
"dependencies": ["langchain_openai", "."],
|
||||
"graphs": {
|
||||
"my_graph_id": "./your_package/your_file.py:make_graph"
|
||||
},
|
||||
"env": {
|
||||
"OPENAI_API_KEY": "secret-key"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Commands
|
||||
|
||||
The base command for the LangGraph CLI is `langgraph`.
|
||||
|
||||
**Usage**
|
||||
|
||||
```
|
||||
langgraph [OPTIONS] COMMAND [ARGS]
|
||||
```
|
||||
|
||||
### `build`
|
||||
|
||||
Build LangGraph Cloud API server Docker image.
|
||||
|
||||
**Usage**
|
||||
|
||||
```
|
||||
langgraph build [OPTIONS]
|
||||
```
|
||||
|
||||
**Options**
|
||||
|
||||
| Option | Default | Description |
|
||||
| ------ | ------- | ----------- |
|
||||
| `--platform TEXT` | | Target platform(s) to build the Docker image for. Example: `langgraph build --platform linux/amd64,linux/arm64` |
|
||||
| `-t, --tag TEXT` | | **Required**. Tag for the Docker image. Example: `langgraph build -t my-image` |
|
||||
| `--pull / --no-pull` | `--pull` | Build with latest remote Docker image. Use `--no-pull` for running the LangGraph Cloud API server with locally built images. |
|
||||
| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
|
||||
| `--help` | | Display command documentation. |
|
||||
| Option | Default | Description |
|
||||
|----------------------|------------------|------------------------------------------------------------------------------------------------------------------------------|
|
||||
| `--platform TEXT` | | Target platform(s) to build the Docker image for. Example: `langgraph build --platform linux/amd64,linux/arm64` |
|
||||
| `-t, --tag TEXT` | | **Required**. Tag for the Docker image. Example: `langgraph build -t my-image` |
|
||||
| `--pull / --no-pull` | `--pull` | Build with latest remote Docker image. Use `--no-pull` for running the LangGraph Cloud API server with locally built images. |
|
||||
| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
|
||||
| `--help` | | Display command documentation. |
|
||||
|
||||
### `up`
|
||||
|
||||
Start langgraph API server. For local testing, requires a LangSmith API key with access to LangGraph Cloud closed beta. Requires a license key for production use.
|
||||
|
||||
**Usage**
|
||||
|
||||
```
|
||||
langgraph up [OPTIONS]
|
||||
```
|
||||
|
||||
**Options**
|
||||
|
||||
| Option | Default | Description |
|
||||
| ------ | ------- | ----------- |
|
||||
| `--wait` | | Wait for services to start before returning. Implies --detach |
|
||||
| `--postgres-uri TEXT` | Local database | Postgres URI to use for the database. |
|
||||
| `--watch` | | Restart on file changes |
|
||||
| `--debugger-base-url TEXT` | `http://127.0.0.1:[PORT]` | URL used by the debugger to access LangGraph API. |
|
||||
| `--debugger-port INTEGER` | | Pull the debugger image locally and serve the UI on specified port |
|
||||
| `--verbose` | | Show more output from the server logs. |
|
||||
| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
|
||||
| `-d, --docker-compose FILE` | | Path to docker-compose.yml file with additional services to launch. |
|
||||
| `-p, --port INTEGER` | `8123` | Port to expose. Example: `langgraph test --port 8000` |
|
||||
| `--pull / --no-pull` | `pull` | Pull latest images. Use --no-pull for running the server with locally-built images. Example: `langgraph up --no-pull` |
|
||||
| `--recreate / --no-recreate` | `no-recreate` | Recreate containers even if their configuration and image haven't changed |
|
||||
| `--help` | | Display command documentation. |
|
||||
| Option | Default | Description |
|
||||
|------------------------------|---------------------------|-----------------------------------------------------------------------------------------------------------------------|
|
||||
| `--wait` | | Wait for services to start before returning. Implies --detach |
|
||||
| `--postgres-uri TEXT` | Local database | Postgres URI to use for the database. |
|
||||
| `--watch` | | Restart on file changes |
|
||||
| `--debugger-base-url TEXT` | `http://127.0.0.1:[PORT]` | URL used by the debugger to access LangGraph API. |
|
||||
| `--debugger-port INTEGER` | | Pull the debugger image locally and serve the UI on specified port |
|
||||
| `--verbose` | | Show more output from the server logs. |
|
||||
| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
|
||||
| `-d, --docker-compose FILE` | | Path to docker-compose.yml file with additional services to launch. |
|
||||
| `-p, --port INTEGER` | `8123` | Port to expose. Example: `langgraph test --port 8000` |
|
||||
| `--pull / --no-pull` | `pull` | Pull latest images. Use --no-pull for running the server with locally-built images. Example: `langgraph up --no-pull` |
|
||||
| `--recreate / --no-recreate` | `no-recreate` | Recreate containers even if their configuration and image haven't changed |
|
||||
| `--help` | | Display command documentation. |
|
||||
|
||||
### `test`
|
||||
Test your LangGraph in the cloud. The only function you can call from the SDK after testing your graph is `client.runs.stream(thread_id=None, ...)`
|
||||
### `dockerfile`
|
||||
|
||||
Generate a Dockerfile for building a LangGraph Cloud API server Docker image.
|
||||
|
||||
**Usage**
|
||||
|
||||
```
|
||||
langgraph test [OPTIONS]
|
||||
langgraph dockerfile [OPTIONS] SAVE_PATH
|
||||
```
|
||||
|
||||
**Options**
|
||||
|
||||
| Option | Default | Description |
|
||||
| ------ | ------- | ----------- |
|
||||
| `--verbose` | | Show more output from the server logs. |
|
||||
| `-c, --config FILE` | `langgraph.json` | Path to configuration file declaring dependencies, graphs and environment variables. |
|
||||
| `-p, --port INTEGER` | `8123` | Port to expose. Example: `langgraph test --port 8000` |
|
||||
| `--pull / --no-pull` | `pull` | Pull latest images. Use --no-pull for running the server with locally-built images. Example: `langgraph up --no-pull` |
|
||||
| `--help` | | Display command documentation. |
|
||||
| Option | Default | Description |
|
||||
|---------------------|------------------|-----------------------------------------------------------------------------------------------------------------|
|
||||
| `-c, --config FILE` | `langgraph.json` | Path to the [configuration file](#configuration-file) declaring dependencies, graphs and environment variables. |
|
||||
| `--help` | | Show this message and exit. |
|
||||
|
||||
Example:
|
||||
|
||||
```bash
|
||||
langgraph dockerfile -c langgraph.json Dockerfile
|
||||
```
|
||||
|
||||
Would generate something like the following:
|
||||
|
||||
```text
|
||||
FROM langchain/langgraph-api:3.11
|
||||
|
||||
ADD ./pipconf.txt /pipconfig.txt
|
||||
|
||||
RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt langchain_community langchain_anthropic langchain_openai wikipedia scikit-learn
|
||||
|
||||
ADD ./graphs /deps/__outer_graphs/src
|
||||
RUN set -ex && \
|
||||
for line in '[project]' \
|
||||
'name = "graphs"' \
|
||||
'version = "0.1"' \
|
||||
'[tool.setuptools.package-data]' \
|
||||
'"*" = ["**/*"]'; do \
|
||||
echo "$line" >> /deps/__outer_graphs/pyproject.toml; \
|
||||
done
|
||||
|
||||
RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt -e /deps/*
|
||||
|
||||
ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_graphs/src/agent.py:graph", "storm": "/deps/__outer_graphs/src/storm.py:graph"}'
|
||||
```
|
||||
|
||||
You can then customize, build images, push, and deploy from this file.
|
||||
|
||||
Reference in New Issue
Block a user