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[docs]: adding js/curl tabs (#1558)
* jsifying * x * z * x * fix background run output * reformatting * z * z * z * z * z * add tabs to stream debug * default urls
This commit is contained in:
Isaac Francisco
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# How to run multiple agents on the same thread
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In LangGraph Cloud, a thread is not explicitly associated with a particular agent.
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This means that you can run multiple agents on the same thread, which allows a different agent to continue from an initial agent's progress.
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In this example, we will create two agents and then call them both on the same thread.
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You'll see that the second agent will respond using information from the [checkpoint](https://langchain-ai.github.io/langgraph/concepts/low_level/#checkpointer-state) generated in the thread by the first agent as context.
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=== "Python"
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```python
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from langgraph_sdk import get_client
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client = get_client(url=<DEPLOYMENT_URL>)
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openai_assistant = await client.assistants.create(
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graph_id="agent", config={"configurable": {"model_name": "openai"}}
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)
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# There should always be a default assistant with no configuration
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assistants = await client.assistants.search()
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default_assistant = [a for a in assistants if not a["config"]][0]
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```
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=== "Javascript"
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```js
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import { Client } from "@langchain/langgraph-sdk";
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const client = new Client({ apiUrl: <DEPLOYMENT_URL> });
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const openAIAssistant = await client.assistants.create(
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{ graphId: "agent", config: {"configurable": {"model_name": "openai"}}}
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);
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const assistants = await client.assistants.search();
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const defaultAssistant = assistants.find(a => !a.config);
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```
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=== "CURL"
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```bash
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curl --request POST \
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--url <DEPLOYMENT_URL>/assistants \
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--header 'Content-Type: application/json' \
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--data '{
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"graph_id": "agent",
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"config": { "configurable": { "model_name": "openai" } }
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}' && \
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curl --request POST \
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--url <DEPLOYMENT_URL>/assistants/search \
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--header 'Content-Type: application/json' \
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--data '{
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"limit": 10,
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"offset": 0
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}' | jq -c 'map(select(.config == null or .config == {})) | .[0]'
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```
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We can see that these agents are different:
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=== "Python"
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```python
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print(openai_assistant)
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```
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=== "Javascript"
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```js
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console.log(openAIAssistant);
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```
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=== "CURL"
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```bash
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curl --request GET \
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--url <DEPLOYMENT_URL>/assistants/<OPENAI_ASSISTANT_ID>
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```
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Output:
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{
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"assistant_id": "db87f39d-b2b1-4da8-ac65-cf81beb3c766",
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"graph_id": "agent",
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"created_at": "2024-08-30T21:18:51.850581+00:00",
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"updated_at": "2024-08-30T21:18:51.850581+00:00",
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"config": {
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"configurable": {
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"model_name": "openai"
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}
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},
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"metadata": {}
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}
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=== "Python"
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```python
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print(default_assistant)
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```
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=== "Javascript"
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```js
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console.log(defaultAssistant);
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```
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=== "CURL"
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```bash
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curl --request GET \
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--url <DEPLOYMENT_URL>/assistants/<DEFAULT_ASSISTANT_ID>
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```
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Output:
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{
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"assistant_id": "fe096781-5601-53d2-b2f6-0d3403f7e9ca",
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"graph_id": "agent",
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"created_at": "2024-08-08T22:45:24.562906+00:00",
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"updated_at": "2024-08-08T22:45:24.562906+00:00",
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"config": {},
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"metadata": {
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"created_by": "system"
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}
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}
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We can now run the OpenAI assistant on the thread first.
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=== "Python"
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```python
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thread = await client.threads.create()
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input = {"messages": [{"role": "user", "content": "who made you?"}]}
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async for event in client.runs.stream(
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thread["thread_id"],
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openai_assistant["assistant_id"],
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input=input,
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stream_mode="updates",
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):
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print(f"Receiving event of type: {event.event}")
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print(event.data)
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print("\n\n")
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```
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=== "Javascript"
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```js
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const thread = await client.threads.create();
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let input = {"messages": [{"role": "user", "content": "who made you?"}]}
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const streamResponse = client.runs.stream(
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thread["thread_id"],
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openAIAssistant["assistant_id"],
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{
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input,
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streamMode: "updates"
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}
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);
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for await (const event of streamResponse) {
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console.log(`Receiving event of type: ${event.event}`);
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console.log(event.data);
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console.log("\n\n");
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}
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```
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=== "CURL"
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```bash
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thread_id=$(curl --request POST \
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--url <DEPLOYMENT_URL>/threads \
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--header 'Content-Type: application/json' \
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--data '{}' | jq -r '.thread_id') && \
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curl --request POST \
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--url "<DEPLOYMENT_URL>/threads/${thread_id}/runs/stream" \
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--header 'Content-Type: application/json' \
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--data '{
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"assistant_id": <OPENAI_ASSISTANT_ID>,
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"input": {
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"messages": [
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{
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"role": "human",
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"content": "who made you?"
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}
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]
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},
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"stream_mode": [
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"updates"
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]
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}' | \
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sed 's/\r$//' | \
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awk '
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/^event:/ {
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if (data_content != "") {
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print data_content "\n"
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}
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sub(/^event: /, "Receiving event of type: ", $0)
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printf "%s...\n", $0
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data_content = ""
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}
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/^data:/ {
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sub(/^data: /, "", $0)
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data_content = $0
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}
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END {
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if (data_content != "") {
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print data_content "\n\n"
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}
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}
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'
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```
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Output:
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Receiving event of type: metadata
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{'run_id': '1ef671c5-fb83-6e70-b698-44dba2d9213e'}
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Receiving event of type: updates
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{'agent': {'messages': [{'content': 'I was created by OpenAI, a research organization focused on developing and advancing artificial intelligence technology.', 'additional_kwargs': {}, 'response_metadata': {'finish_reason': 'stop', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_157b3831f5'}, 'type': 'ai', 'name': None, 'id': 'run-f5735b86-b80d-4c71-8dc3-4782b5a9c7c8', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]}}
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Now, we can run it on the default assistant and see that this second assistant is aware of the initial question, and can answer the question, "and you?":
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=== "Python"
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```python
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input = {"messages": [{"role": "user", "content": "and you?"}]}
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async for event in client.runs.stream(
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thread["thread_id"],
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default_assistant["assistant_id"],
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input=input,
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stream_mode="updates",
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):
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print(f"Receiving event of type: {event.event}")
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print(event.data)
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print("\n\n")
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```
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=== "Javascript"
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```js
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let input = {"messages": [{"role": "user", "content": "and you?"}]}
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const streamResponse = client.runs.stream(
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thread["thread_id"],
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defaultAssistant["assistant_id"],
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{
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input,
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streamMode: "updates"
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}
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);
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for await (const event of streamResponse) {
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console.log(`Receiving event of type: ${event.event}`);
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console.log(event.data);
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console.log("\n\n");
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}
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```
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=== "CURL"
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```bash
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curl --request POST \
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--url <DEPLOYMENT_URL>/threads/<THREAD_ID>/runs/stream \
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--header 'Content-Type: application/json' \
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--data '{
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"assistant_id": <DEFAULT_ASSISTANT_ID>,
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"input": {
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"messages": [
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{
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"role": "human",
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"content": "and you?"
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}
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]
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},
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"stream_mode": [
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"updates"
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]
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}' | \
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sed 's/\r$//' | \
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awk '
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/^event:/ {
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if (data_content != "") {
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print data_content "\n"
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}
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sub(/^event: /, "Receiving event of type: ", $0)
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printf "%s...\n", $0
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data_content = ""
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}
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/^data:/ {
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sub(/^data: /, "", $0)
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data_content = $0
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}
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END {
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if (data_content != "") {
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print data_content "\n\n"
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}
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}
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'
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```
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Output:
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Receiving event of type: metadata
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{'run_id': '1ef6722d-80b3-6fbb-9324-253796b1cd13'}
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Receiving event of type: updates
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{'agent': {'messages': [{'content': [{'text': 'I am an artificial intelligence created by Anthropic, not by OpenAI. I should not have stated that OpenAI created me, as that is incorrect. Anthropic is the company that developed and trained me using advanced language models and AI technology. I will be more careful about providing accurate information regarding my origins in the future.', 'type': 'text', 'index': 0}], 'additional_kwargs': {}, 'response_metadata': {'stop_reason': 'end_turn', 'stop_sequence': None}, 'type': 'ai', 'name': None, 'id': 'run-ebaacf62-9dd9-4165-9535-db432e4793ec', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': {'input_tokens': 302, 'output_tokens': 72, 'total_tokens': 374}}]}}
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