mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-09-11 04:07:52 +02:00
docs: Add initial LangGraph Cloud docs (#725)
* Create Deploy docs. * Add LangGraph CLI docs. * Update API concepts page. * Create quick start page. * first draft (#695) * first draft * fmt * fmt * Revert "fmt" This reverts commite599030ab5. * Revert "fmt" This reverts commitec8fca977e. * var change * import lint * changed locations * second draft * fmt * Revert "fmt" This reverts commit68a1c5c872. * double texting lint * concepts (#704) * concepts * python sdk * docs structure * fmt * fmt * Small touch ups, rename Hosted LangGraph API to LangGraph Cloud. (#724) * Fix small typos. * Fix broken links in quick start page. * Add LangGraph Cloud reference docs. --------- Co-authored-by: Isaac Francisco <78627776+isahers1@users.noreply.github.com>
This commit is contained in:
Andrew Nguonly
co-authored by
Isaac Francisco
Isaac Francisco
parent
4a38dd45dc
commit
f27d8e16ad
@@ -0,0 +1,625 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "51466c8d-8ce4-4b3d-be4e-18fdbeda5f53",
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"metadata": {},
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"source": [
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"# How to kick off background runs\n",
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"\n",
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"This guide covers how to kick off background runs for your agent.\n",
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"This can be useful for long running jobs."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b8e6408a-b37e-428f-9567-077fa55d58e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Initialize the client\n",
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"from langgraph_sdk import get_client\n",
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"\n",
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"client = get_client()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "4947e9bc-111f-4991-8c41-1041da9bf0ba",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
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" 'graph_id': 'agent',\n",
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" 'config': {},\n",
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" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
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" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
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" 'metadata': {'created_by': 'system'}}]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# List available assistants\n",
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"assistants = await client.assistants.search()\n",
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"assistants"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "230c0464-a6e5-420f-9e38-ca514e5634ce",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
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" 'graph_id': 'agent',\n",
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" 'config': {},\n",
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" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
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" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
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" 'metadata': {'created_by': 'system'}}"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Get the first assistant, we will use this one\n",
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"assistant = assistants[0]\n",
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"assistant"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "56aa5159-5583-4134-9210-709b969bda6f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
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" 'created_at': '2024-05-18T00:50:26.367620+00:00',\n",
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" 'updated_at': '2024-05-18T00:50:26.367620+00:00',\n",
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" 'metadata': {}}"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Create a new thread\n",
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"thread = await client.threads.create()\n",
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"thread"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "147c3f98-f889-4f05-a090-6b31f2a0b291",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[]"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# If we list runs on this thread, we can see it is empty\n",
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"runs = await client.runs.list(thread['thread_id'])\n",
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"runs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8c7b44ef-4816-496d-88a1-2f7327cf576d",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Let's kick off a run\n",
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"input = {\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in sf\"}]}\n",
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"run = await client.runs.create(thread['thread_id'], assistant[\"assistant_id\"], input=input)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "d84b4d80-b0aa-4d9f-a05d-0744b2fe8f72",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'run_id': 'e843abcb-e478-421b-91e1-a8ae171b14f4',\n",
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" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
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" 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
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" 'created_at': '2024-05-18T00:50:27.618761+00:00',\n",
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" 'updated_at': '2024-05-18T00:50:27.618761+00:00',\n",
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" 'status': 'pending',\n",
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" 'metadata': {}}"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# The first time we poll it, we can see `status=pending`\n",
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"await client.runs.get(thread['thread_id'], run['run_id'])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "ce124bd3-f197-4b73-9ff6-bb36730dd003",
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"metadata": {
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"scrolled": true
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{
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"[{'event_id': '3ac6d963-442f-481c-9fde-b8a27bc0e277',\n",
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" 'name': 'tavily_search_results_json',\n",
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" 'content': 'whats the weather in sf',\n",
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||||
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||||
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|
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||||
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|
||||
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" 'name': 'should_continue',\n",
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" 'data': {'input': {'messages': [{'id': 'abc3581e-417b-4ca1-ab31-de7108e64b3b',\n",
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" 'name': None,\n",
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" 'type': 'human',\n",
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" 'content': 'whats the weather in sf',\n",
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" 'example': False,\n",
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|
||||
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|
||||
" 'content': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
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|
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" 'type': 'tool_use',\n",
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" 'input': {'query': 'weather in san francisco'}}],\n",
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" 'example': False,\n",
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" 'tool_calls': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
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" 'args': {'query': 'weather in san francisco'},\n",
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" 'name': 'tavily_search_results_json'}],\n",
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" 'response_metadata': {},\n",
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" 'invalid_tool_calls': []}]},\n",
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" 'output': 'continue'},\n",
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" 'metadata': {'graph_id': 'agent',\n",
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" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
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" 'created_by': 'system',\n",
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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" 'type': 'human',\n",
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" 'content': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
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|
||||
" 'type': 'tool_use',\n",
|
||||
" 'input': {'query': 'weather in san francisco'}}],\n",
|
||||
" 'example': False,\n",
|
||||
" 'tool_calls': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'args': {'query': 'weather in san francisco'},\n",
|
||||
" 'name': 'tavily_search_results_json'}],\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'invalid_tool_calls': []}]}},\n",
|
||||
" 'metadata': {'graph_id': 'agent',\n",
|
||||
" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
|
||||
" 'created_by': 'system',\n",
|
||||
" 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'},\n",
|
||||
" 'tags': ['seq:step:3']},\n",
|
||||
" {'event_id': '679c8ae7-5cd2-4462-936e-20f0ea45cfb8',\n",
|
||||
" 'run_id': 'e843abcb-e478-421b-91e1-a8ae171b14f4',\n",
|
||||
" 'received_at': '2024-05-18T00:50:29.560628+00:00',\n",
|
||||
" 'span_id': '4885d5a0-cd89-4f00-8558-e85b542a710c',\n",
|
||||
" 'event': 'on_chat_model_end',\n",
|
||||
" 'name': 'ChatAnthropic',\n",
|
||||
" 'data': {'input': {'messages': [[{'id': None,\n",
|
||||
" 'name': None,\n",
|
||||
" 'type': 'human',\n",
|
||||
" 'content': 'whats the weather in sf',\n",
|
||||
" 'example': False,\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {}}]]},\n",
|
||||
" 'output': {'run': None,\n",
|
||||
" 'llm_output': None,\n",
|
||||
" 'generations': [[{'text': '',\n",
|
||||
" 'type': 'ChatGeneration',\n",
|
||||
" 'message': {'id': 'run-4885d5a0-cd89-4f00-8558-e85b542a710c',\n",
|
||||
" 'name': None,\n",
|
||||
" 'type': 'ai',\n",
|
||||
" 'content': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'type': 'tool_use',\n",
|
||||
" 'input': {'query': 'weather in san francisco'}}],\n",
|
||||
" 'example': False,\n",
|
||||
" 'tool_calls': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'args': {'query': 'weather in san francisco'},\n",
|
||||
" 'name': 'tavily_search_results_json'}],\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'invalid_tool_calls': []},\n",
|
||||
" 'generation_info': None}]]}},\n",
|
||||
" 'metadata': {'graph_id': 'agent',\n",
|
||||
" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
|
||||
" 'created_by': 'system',\n",
|
||||
" 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'ls_model_type': 'chat'},\n",
|
||||
" 'tags': ['seq:step:1']},\n",
|
||||
" {'event_id': '055fcf73-36e7-444b-990d-6263ec50925c',\n",
|
||||
" 'run_id': 'e843abcb-e478-421b-91e1-a8ae171b14f4',\n",
|
||||
" 'received_at': '2024-05-18T00:50:29.559491+00:00',\n",
|
||||
" 'span_id': '4885d5a0-cd89-4f00-8558-e85b542a710c',\n",
|
||||
" 'event': 'on_chat_model_stream',\n",
|
||||
" 'name': 'ChatAnthropic',\n",
|
||||
" 'data': {'chunk': {'id': 'run-4885d5a0-cd89-4f00-8558-e85b542a710c',\n",
|
||||
" 'name': None,\n",
|
||||
" 'type': 'AIMessageChunk',\n",
|
||||
" 'content': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'type': 'tool_use',\n",
|
||||
" 'input': {'query': 'weather in san francisco'}}],\n",
|
||||
" 'example': False,\n",
|
||||
" 'tool_calls': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'args': {'query': 'weather in san francisco'},\n",
|
||||
" 'name': 'tavily_search_results_json'}],\n",
|
||||
" 'tool_call_chunks': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'args': '{\"query\": \"weather in san francisco\"}',\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'index': 0}],\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'invalid_tool_calls': []}},\n",
|
||||
" 'metadata': {'graph_id': 'agent',\n",
|
||||
" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
|
||||
" 'created_by': 'system',\n",
|
||||
" 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'ls_model_type': 'chat'},\n",
|
||||
" 'tags': ['seq:step:1']},\n",
|
||||
" {'event_id': 'cf90f755-5a12-46bd-8f60-adc862388635',\n",
|
||||
" 'run_id': 'e843abcb-e478-421b-91e1-a8ae171b14f4',\n",
|
||||
" 'received_at': '2024-05-18T00:50:27.873602+00:00',\n",
|
||||
" 'span_id': '4885d5a0-cd89-4f00-8558-e85b542a710c',\n",
|
||||
" 'event': 'on_chat_model_start',\n",
|
||||
" 'name': 'ChatAnthropic',\n",
|
||||
" 'data': {'input': {'messages': [[{'id': None,\n",
|
||||
" 'name': None,\n",
|
||||
" 'type': 'human',\n",
|
||||
" 'content': 'whats the weather in sf',\n",
|
||||
" 'example': False,\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {}}]]}},\n",
|
||||
" 'metadata': {'graph_id': 'agent',\n",
|
||||
" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
|
||||
" 'created_by': 'system',\n",
|
||||
" 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'ls_model_type': 'chat'},\n",
|
||||
" 'tags': ['seq:step:1']}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 14,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# We can list events for the run\n",
|
||||
"await client.runs.list_events(thread['thread_id'], run['run_id'])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"id": "8fa206ed-515e-4607-9a80-bebafe76cc24",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'run_id': 'e843abcb-e478-421b-91e1-a8ae171b14f4',\n",
|
||||
" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
|
||||
" 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'created_at': '2024-05-18T00:50:27.618761+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:50:27.618761+00:00',\n",
|
||||
" 'status': 'success',\n",
|
||||
" 'metadata': {}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Eventually, it should finish and we should see `status=success`\n",
|
||||
"await client.runs.get(thread['thread_id'], run['run_id'])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"id": "8de4495f-7873-487c-b1a8-ad2a78a1ff35",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# We can get the final results\n",
|
||||
"results = await client.runs.list_events(thread['thread_id'], run['run_id'])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 21,
|
||||
"id": "9da76fce-66e4-4f1b-8c24-09759889e50e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# The results are sorted by time, so the most recent (final) step is the 0 index\n",
|
||||
"final_result = results[0]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 22,
|
||||
"id": "02279ff3-c153-4ec4-be4d-1613a0dff4ee",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'event_id': '1af2076e-8ec7-4f2e-bc2c-6fbbf586397c',\n",
|
||||
" 'run_id': 'e843abcb-e478-421b-91e1-a8ae171b14f4',\n",
|
||||
" 'received_at': '2024-05-18T00:50:35.557925+00:00',\n",
|
||||
" 'span_id': 'e843abcb-e478-421b-91e1-a8ae171b14f4',\n",
|
||||
" 'event': 'on_chain_end',\n",
|
||||
" 'name': 'LangGraph',\n",
|
||||
" 'data': {'output': {'messages': [{'id': '46b31c3a-01bf-4946-bd5a-fa6a7f6c97ce',\n",
|
||||
" 'name': None,\n",
|
||||
" 'type': 'human',\n",
|
||||
" 'content': 'whats the weather in sf',\n",
|
||||
" 'example': False,\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {}},\n",
|
||||
" {'id': 'run-4885d5a0-cd89-4f00-8558-e85b542a710c',\n",
|
||||
" 'name': None,\n",
|
||||
" 'type': 'ai',\n",
|
||||
" 'content': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'type': 'tool_use',\n",
|
||||
" 'input': {'query': 'weather in san francisco'}}],\n",
|
||||
" 'example': False,\n",
|
||||
" 'tool_calls': [{'id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'args': {'query': 'weather in san francisco'},\n",
|
||||
" 'name': 'tavily_search_results_json'}],\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'invalid_tool_calls': []},\n",
|
||||
" {'id': '045e936d-ee47-4236-95ff-793b6b32b590',\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'type': 'tool',\n",
|
||||
" 'content': '[{\"url\": \"https://www.weatherapi.com/\", \"content\": \"{\\'location\\': {\\'name\\': \\'San Francisco\\', \\'region\\': \\'California\\', \\'country\\': \\'United States of America\\', \\'lat\\': 37.78, \\'lon\\': -122.42, \\'tz_id\\': \\'America/Los_Angeles\\', \\'localtime_epoch\\': 1715993410, \\'localtime\\': \\'2024-05-17 17:50\\'}, \\'current\\': {\\'last_updated_epoch\\': 1715993100, \\'last_updated\\': \\'2024-05-17 17:45\\', \\'temp_c\\': 17.8, \\'temp_f\\': 64.0, \\'is_day\\': 1, \\'condition\\': {\\'text\\': \\'Partly cloudy\\', \\'icon\\': \\'//cdn.weatherapi.com/weather/64x64/day/116.png\\', \\'code\\': 1003}, \\'wind_mph\\': 15.0, \\'wind_kph\\': 24.1, \\'wind_degree\\': 300, \\'wind_dir\\': \\'WNW\\', \\'pressure_mb\\': 1013.0, \\'pressure_in\\': 29.9, \\'precip_mm\\': 0.0, \\'precip_in\\': 0.0, \\'humidity\\': 65, \\'cloud\\': 25, \\'feelslike_c\\': 17.8, \\'feelslike_f\\': 64.0, \\'vis_km\\': 16.0, \\'vis_miles\\': 9.0, \\'uv\\': 5.0, \\'gust_mph\\': 16.2, \\'gust_kph\\': 26.1}}\"}]',\n",
|
||||
" 'tool_call_id': 'toolu_018yyEfJHihdVfWypRNLqDug',\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {}},\n",
|
||||
" {'id': 'run-069f1ddd-64b3-451d-bb84-75dec23a7286',\n",
|
||||
" 'name': None,\n",
|
||||
" 'type': 'ai',\n",
|
||||
" 'content': \"The search results provide the current weather conditions in San Francisco. According to the data, as of 5:45pm on May 17, 2024, the weather in San Francisco is partly cloudy with a temperature of around 64°F (17.8°C). The wind is blowing from the west-northwest at 15 mph (24 km/h) with gusts up to 16 mph (26 km/h). The humidity is 65% and visibility is 9 miles (16 km). The UV index is 5.\\n\\nSo in summary, it's a partly cloudy spring day in San Francisco with mild temperatures and moderate winds. The weather seems pleasant for being outdoors during the daytime hours.\",\n",
|
||||
" 'example': False,\n",
|
||||
" 'tool_calls': [],\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'invalid_tool_calls': []}]}},\n",
|
||||
" 'metadata': {'graph_id': 'agent',\n",
|
||||
" 'thread_id': '6ada015b-b47a-4c4f-a5cd-580893cb6d0c',\n",
|
||||
" 'created_by': 'system',\n",
|
||||
" 'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'},\n",
|
||||
" 'tags': []}"
|
||||
]
|
||||
},
|
||||
"execution_count": 22,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"final_result"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 28,
|
||||
"id": "ddd6e698-4609-4389-b84a-bb8939fff08b",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\"The search results provide the current weather conditions in San Francisco. According to the data, as of 5:45pm on May 17, 2024, the weather in San Francisco is partly cloudy with a temperature of around 64°F (17.8°C). The wind is blowing from the west-northwest at 15 mph (24 km/h) with gusts up to 16 mph (26 km/h). The humidity is 65% and visibility is 9 miles (16 km). The UV index is 5.\\n\\nSo in summary, it's a partly cloudy spring day in San Francisco with mild temperatures and moderate winds. The weather seems pleasant for being outdoors during the daytime hours.\""
|
||||
]
|
||||
},
|
||||
"execution_count": 28,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# We can get the content of the final message\n",
|
||||
"final_result['data']['output']['messages'][-1]['content']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "535638f7-48a9-49bb-9a0b-57a5b36d0696",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -0,0 +1,200 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "68c0837d-c40a-4209-9f88-5d08c00c31b0",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# How to create agents with configuration\n",
|
||||
"\n",
|
||||
"One of the benefits of LangGraph API is that it lets you create agents with different configurations.\n",
|
||||
"This is useful when you want to:\n",
|
||||
"\n",
|
||||
"- Define a cognitive architecture once as a LangGraph\n",
|
||||
"- Let that LangGraph be configurable across some attributes (for example, system message or LLM to use)\n",
|
||||
"- Let users create agents with arbitrary configurations, save them, and then use them in the future\n",
|
||||
"\n",
|
||||
"In this guide we will show how to do that for the default agent we have built in.\n",
|
||||
"\n",
|
||||
"If you look at the agent we defined, you can see that inside the `call_model` node we have created the model based on some configuration. That node looks like:\n",
|
||||
"\n",
|
||||
"```python\n",
|
||||
"def call_model(state, config):\n",
|
||||
" messages = state[\"messages\"]\n",
|
||||
" model_name = config.get('configurable', {}).get(\"model_name\", \"anthropic\")\n",
|
||||
" model = _get_model(model_name)\n",
|
||||
" response = model.invoke(messages)\n",
|
||||
" # We return a list, because this will get added to the existing list\n",
|
||||
" return {\"messages\": [response]}\n",
|
||||
"```\n",
|
||||
"\n",
|
||||
"We are looking inside the config for a `model_name` parameter (which defaults to `anthropic` if none is found).\n",
|
||||
"That means that by default we are using Anthropic as our model provider.\n",
|
||||
"In this example we will see an example of how to create an example agent that is configured to use OpenAI.\n",
|
||||
"\n",
|
||||
"We've also communicated to the graph that it should expect configuration with this key. \n",
|
||||
"We've done this by passing `config_schema` when constructing the graph, eg:\n",
|
||||
"\n",
|
||||
"```python\n",
|
||||
"class GraphConfig(TypedDict):\n",
|
||||
" model_name: Literal[\"anthropic\", \"openai\"]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# Define a new graph\n",
|
||||
"workflow = StateGraph(AgentState, config_schema=GraphConfig)\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"id": "f69c9a4f-2ef9-4998-827b-fe86d12bfd76",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langgraph_sdk import get_client\n",
|
||||
"\n",
|
||||
"client = get_client()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"id": "9a37bfb5-7331-4004-8054-508838e54f18",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# First, let's check what valid configuration can be\n",
|
||||
"# We can do this by getting the default assistant\n",
|
||||
"# There should always be a default assistant with no configuration\n",
|
||||
"assistants = await client.assistants.search()\n",
|
||||
"assistants = [a for a in assistants if not a['config']]\n",
|
||||
"base_assistant = assistants[0]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 17,
|
||||
"id": "70193a08-127c-44b3-a102-10db260d7e3b",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'model_name': {'title': 'Model Name',\n",
|
||||
" 'enum': ['anthropic', 'openai'],\n",
|
||||
" 'type': 'string'}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 17,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# We can now call `.get_schemas` to get schemas associated with this graph\n",
|
||||
"schemas = await client.assistants.get_schemas(assistant_id=base_assistant[\"assistant_id\"])\n",
|
||||
"# There are multiple types of schemas\n",
|
||||
"# We can get the `config_schema` to look at the the configurable parameters\n",
|
||||
"schemas['config_schema']['definitions']['Configurable']['properties']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 18,
|
||||
"id": "99be5aee-9a6b-4515-b72f-ba135a893c65",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"assistant = await client.assistants.create(graph_id=\"agent\", config={\"configurable\": {\"model_name\": \"openai\"}})"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "4f10d346-69e6-44f4-8ff0-ef539ba938df",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can see that this assistant has saved the config"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 20,
|
||||
"id": "3898ca35-eb2c-4b12-97ea-e0cc6a7c6a2e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'assistant_id': '40a3a2bf-5319-4fae-a2ac-05e075615cdc',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {'configurable': {'model_name': 'openai'}},\n",
|
||||
" 'created_at': '2024-06-05T23:12:30.519458+00:00',\n",
|
||||
" 'updated_at': '2024-06-05T23:12:30.519458+00:00',\n",
|
||||
" 'metadata': {}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 20,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"assistant"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 21,
|
||||
"id": "68ed7a1b-74be-4560-8c55-c76d49d3d348",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"StreamPart(event='metadata', data={'run_id': '1ef23911-c23b-6d8c-b1dc-94bb982ca7b1'})\n",
|
||||
"StreamPart(event='values', data={'messages': [{'role': 'user', 'content': 'who made you?'}]})\n",
|
||||
"StreamPart(event='values', data={'messages': [{'content': 'who made you?', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'human', 'name': None, 'id': 'ed93c1c9-80d6-4f2b-a048-ef859ea533f9', 'example': False}, {'content': 'I was created by OpenAI, a research organization focused on developing and advancing artificial intelligence technology.', 'additional_kwargs': {}, 'response_metadata': {'finish_reason': 'stop'}, 'type': 'ai', 'name': None, 'id': 'run-6560cd65-5c9c-434b-8835-0baadc684760', 'example': False, 'tool_calls': [], 'invalid_tool_calls': [], 'usage_metadata': None}]})\n",
|
||||
"StreamPart(event='end', data=None)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"thread = await client.threads.create()\n",
|
||||
"input = {\"messages\": [{\"role\": \"user\", \"content\": \"who made you?\"}]}\n",
|
||||
"async for event in client.runs.stream(thread['thread_id'], assistant['assistant_id'], input=input):\n",
|
||||
" print(event)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "666d78f1-019a-433e-839e-52d2ebb3d9c8",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -0,0 +1,184 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Enqueue\n",
|
||||
"\n",
|
||||
"There are several strategies for handling concurrent runs in your graph. This notebook covers how to use the `enqueue` option - please see the other how-to guides in the \"Double Texting\" directory to learn about the other methods.\n",
|
||||
"\n",
|
||||
"First, let's import our required packages and instantiate our client, assistant, and thread."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_core.messages import convert_to_messages\n",
|
||||
"from langgraph_sdk import get_client"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = get_client()\n",
|
||||
"assistant = await client.assistants.create(\"agent\")\n",
|
||||
"thread = await client.threads.create()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# this run will be interrupted\n",
|
||||
"first_run = await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in sf?\"}]},\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"second_run = await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in nyc?\"}]},\n",
|
||||
" multitask_strategy=\"enqueue\",\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Verify that the thread has data from both runs"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# wait until the second run completes\n",
|
||||
"await client.runs.join(thread[\"thread_id\"], second_run[\"run_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"state = await client.threads.get_state(thread[\"thread_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"================================\u001b[1m Human Message \u001b[0m=================================\n",
|
||||
"\n",
|
||||
"whats the weather in sf?\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"[{'id': 'toolu_01Dez1sJre4oA2Y7NsKJV6VT', 'input': {'query': 'weather in san francisco'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}]\n",
|
||||
"Tool Calls:\n",
|
||||
" tavily_search_results_json (toolu_01Dez1sJre4oA2Y7NsKJV6VT)\n",
|
||||
" Call ID: toolu_01Dez1sJre4oA2Y7NsKJV6VT\n",
|
||||
" Args:\n",
|
||||
" query: weather in san francisco\n",
|
||||
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
|
||||
"Name: tavily_search_results_json\n",
|
||||
"\n",
|
||||
"[{\"url\": \"https://www.accuweather.com/en/us/san-francisco/94103/weather-forecast/347629\", \"content\": \"Get the current and future weather conditions for San Francisco, CA, including temperature, precipitation, wind, air quality and more. See the hourly and 10-day outlook, radar maps, alerts and allergy information.\"}]\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"According to AccuWeather, the current weather conditions in San Francisco are:\n",
|
||||
"\n",
|
||||
"Temperature: 57°F (14°C)\n",
|
||||
"Conditions: Mostly Sunny\n",
|
||||
"Wind: WSW 10 mph\n",
|
||||
"Humidity: 72%\n",
|
||||
"\n",
|
||||
"The forecast for the next few days shows partly sunny skies with highs in the upper 50s to mid 60s F (14-18°C) and lows in the upper 40s to low 50s F (9-11°C). Typical mild, dry weather for San Francisco this time of year.\n",
|
||||
"\n",
|
||||
"Some key details from the AccuWeather forecast:\n",
|
||||
"\n",
|
||||
"Today: Mostly sunny, high of 62°F (17°C)\n",
|
||||
"Tonight: Partly cloudy, low of 49°F (9°C) \n",
|
||||
"Tomorrow: Partly sunny, high of 59°F (15°C)\n",
|
||||
"Saturday: Mostly sunny, high of 64°F (18°C)\n",
|
||||
"Sunday: Partly sunny, high of 61°F (16°C)\n",
|
||||
"\n",
|
||||
"So in summary, expect seasonable spring weather in San Francisco over the next several days, with a mix of sun and clouds and temperatures ranging from the upper 40s at night to the low 60s during the days. Typical dry conditions with no rain in the forecast.\n",
|
||||
"================================\u001b[1m Human Message \u001b[0m=================================\n",
|
||||
"\n",
|
||||
"whats the weather in nyc?\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"[{'text': 'Here are the current weather conditions and forecast for New York City:', 'type': 'text'}, {'id': 'toolu_01FFft5Sx9oS6AdVJuRWWcGp', 'input': {'query': 'weather in new york city'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}]\n",
|
||||
"Tool Calls:\n",
|
||||
" tavily_search_results_json (toolu_01FFft5Sx9oS6AdVJuRWWcGp)\n",
|
||||
" Call ID: toolu_01FFft5Sx9oS6AdVJuRWWcGp\n",
|
||||
" Args:\n",
|
||||
" query: weather in new york city\n",
|
||||
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
|
||||
"Name: tavily_search_results_json\n",
|
||||
"\n",
|
||||
"[{\"url\": \"https://www.weatherapi.com/\", \"content\": \"{'location': {'name': 'New York', 'region': 'New York', 'country': 'United States of America', 'lat': 40.71, 'lon': -74.01, 'tz_id': 'America/New_York', 'localtime_epoch': 1718734479, 'localtime': '2024-06-18 14:14'}, 'current': {'last_updated_epoch': 1718733600, 'last_updated': '2024-06-18 14:00', 'temp_c': 29.4, 'temp_f': 84.9, 'is_day': 1, 'condition': {'text': 'Sunny', 'icon': '//cdn.weatherapi.com/weather/64x64/day/113.png', 'code': 1000}, 'wind_mph': 2.2, 'wind_kph': 3.6, 'wind_degree': 158, 'wind_dir': 'SSE', 'pressure_mb': 1025.0, 'pressure_in': 30.26, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 63, 'cloud': 0, 'feelslike_c': 31.3, 'feelslike_f': 88.3, 'windchill_c': 28.3, 'windchill_f': 82.9, 'heatindex_c': 29.6, 'heatindex_f': 85.3, 'dewpoint_c': 18.4, 'dewpoint_f': 65.2, 'vis_km': 16.0, 'vis_miles': 9.0, 'uv': 7.0, 'gust_mph': 16.5, 'gust_kph': 26.5}}\"}]\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"According to the weather data from WeatherAPI:\n",
|
||||
"\n",
|
||||
"Current Conditions in New York City (as of 2:00 PM local time):\n",
|
||||
"- Temperature: 85°F (29°C)\n",
|
||||
"- Conditions: Sunny\n",
|
||||
"- Wind: 2 mph (4 km/h) from the SSE\n",
|
||||
"- Humidity: 63%\n",
|
||||
"- Heat Index: 85°F (30°C)\n",
|
||||
"\n",
|
||||
"The forecast shows sunny and warm conditions persisting over the next few days:\n",
|
||||
"\n",
|
||||
"Today: Sunny, high of 85°F (29°C)\n",
|
||||
"Tonight: Clear, low of 68°F (20°C)\n",
|
||||
"Tomorrow: Sunny, high of 88°F (31°C) \n",
|
||||
"Thursday: Mostly sunny, high of 90°F (32°C)\n",
|
||||
"Friday: Partly cloudy, high of 87°F (31°C)\n",
|
||||
"\n",
|
||||
"So New York City is experiencing beautiful sunny weather with seasonably warm temperatures in the mid-to-upper 80s Fahrenheit (around 30°C). Humidity is moderate in the 60% range. Overall, ideal late spring/early summer conditions for being outdoors in the city over the next several days.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for m in convert_to_messages(state[\"values\"][\"messages\"]):\n",
|
||||
" m.pretty_print()"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
@@ -0,0 +1,685 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "51466c8d-8ce4-4b3d-be4e-18fdbeda5f53",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# How to have a human in the loop\n",
|
||||
"\n",
|
||||
"With it's built in persistence layer, LangGraph API is perfect for human-in-the-loop workflows.\n",
|
||||
"Here we cover a few such examples:\n",
|
||||
"\n",
|
||||
"1. Having a human in the loop to approve a tool call\n",
|
||||
"2. Having a human in the loop to edit a tool call\n",
|
||||
"3. Having a human in the loop to edit an old state and resume execution from there\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "521d975b-e94b-4c37-bfa1-82d969e2a4dc",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langgraph_sdk import get_client"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "27a1392b-86c3-464e-99a8-90ffc965f3ec",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = get_client()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "4947e9bc-111f-4991-8c41-1041da9bf0ba",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {},\n",
|
||||
" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'metadata': {'created_by': 'system'}}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# There should always be a default assistant with no configuration\n",
|
||||
"assistants = await client.assistants.search()\n",
|
||||
"assistants = [a for a in assistants if not a['config']]\n",
|
||||
"assistants"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "230c0464-a6e5-420f-9e38-ca514e5634ce",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {},\n",
|
||||
" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'metadata': {'created_by': 'system'}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"assistant = assistants[0]\n",
|
||||
"assistant"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "e0209129-239b-452e-a59a-47be716bbf8c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Approve a tool call"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "56aa5159-5583-4134-9210-709b969bda6f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'thread_id': '54ed0901-6767-46c9-a5f9-b65c1c5fd89c',\n",
|
||||
" 'created_at': '2024-05-18T22:46:16.724701+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T22:46:16.724701+00:00',\n",
|
||||
" 'metadata': {}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"thread = await client.threads.create()\n",
|
||||
"thread"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "147c3f98-f889-4f05-a090-6b31f2a0b291",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[]"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"runs = await client.runs.list(thread['thread_id'])\n",
|
||||
"runs"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "77dae6ad-bb7b-468d-b7fd-9b8a35f13ccb",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We now want to add a human-in-the-loop step before a tool is called.\n",
|
||||
"We can do this by adding `interrupt_before=[\"action\"]`, which tells us to interrupt before calling the action node.\n",
|
||||
"We can do this either when compiling the graph or when kicking off a run.\n",
|
||||
"Here we will do it when kicking of a run."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "7da70e20-1a4e-4df2-b996-1927f474c835",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Receiving new event of type: metadata...\n",
|
||||
"{'run_id': '3b77ef83-687a-4840-8858-0371f91a92c3'}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'agent': {'messages': [{'content': [{'id': 'toolu_01HwZqM1ptX6E15A5LAmyZTB', 'input': {'query': 'weather in san francisco'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-e5d17791-4d37-4ad2-815f-a0c4cba62585', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in san francisco'}, 'id': 'toolu_01HwZqM1ptX6E15A5LAmyZTB'}], 'invalid_tool_calls': []}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: end...\n",
|
||||
"None\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = {\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in sf\"}]}\n",
|
||||
"async for chunk in client.runs.stream(\n",
|
||||
" thread['thread_id'], assistant['assistant_id'], input=input, stream_mode=\"updates\", interrupt_before=['action']\n",
|
||||
"):\n",
|
||||
" print(f\"Receiving new event of type: {chunk.event}...\")\n",
|
||||
" print(chunk.data)\n",
|
||||
" print(\"\\n\\n\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "a36ac0d6-7843-4fab-909c-0b5b6e725a7f",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can now kick off a new run on the same thread with `None` as the input in order to just continue the existing thread."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "bded66c7-b56e-4db5-809f-fa5a31d8a012",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Receiving new event of type: metadata...\n",
|
||||
"{'run_id': 'a46f733d-cf5b-4ee3-9e07-08612468c8df'}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'action': {'messages': [{'content': '[{\"url\": \"https://www.weatherapi.com/\", \"content\": \"{\\'location\\': {\\'name\\': \\'San Francisco\\', \\'region\\': \\'California\\', \\'country\\': \\'United States of America\\', \\'lat\\': 37.78, \\'lon\\': -122.42, \\'tz_id\\': \\'America/Los_Angeles\\', \\'localtime_epoch\\': 1716072201, \\'localtime\\': \\'2024-05-18 15:43\\'}, \\'current\\': {\\'last_updated_epoch\\': 1716071400, \\'last_updated\\': \\'2024-05-18 15:30\\', \\'temp_c\\': 18.9, \\'temp_f\\': 66.0, \\'is_day\\': 1, \\'condition\\': {\\'text\\': \\'Partly cloudy\\', \\'icon\\': \\'//cdn.weatherapi.com/weather/64x64/day/116.png\\', \\'code\\': 1003}, \\'wind_mph\\': 18.6, \\'wind_kph\\': 29.9, \\'wind_degree\\': 280, \\'wind_dir\\': \\'W\\', \\'pressure_mb\\': 1015.0, \\'pressure_in\\': 29.96, \\'precip_mm\\': 0.0, \\'precip_in\\': 0.0, \\'humidity\\': 59, \\'cloud\\': 25, \\'feelslike_c\\': 18.9, \\'feelslike_f\\': 66.0, \\'vis_km\\': 16.0, \\'vis_miles\\': 9.0, \\'uv\\': 5.0, \\'gust_mph\\': 23.0, \\'gust_kph\\': 37.1}}\"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '8be98ff3-6d61-41c5-8384-8db6b7abdbfb', 'tool_call_id': 'toolu_01HwZqM1ptX6E15A5LAmyZTB'}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'agent': {'messages': [{'content': \"The weather in San Francisco is currently partly cloudy with a temperature of around 66°F (18.9°C). There are westerly winds of 18.6 mph (29.9 km/h) with gusts up to 23 mph (37.1 km/h). The humidity is 59% and visibility is good at 9 miles (16 km). UV levels are moderate at 5.0.\\n\\nIn summary, it's a nice partly cloudy spring day in San Francisco with comfortable temperatures and a moderate breeze. The weather conditions seem ideal for being outdoors and enjoying the city.\", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-7a8a2ff8-d0d6-4200-b0a5-926f2b6a4798', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: end...\n",
|
||||
"None\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = None\n",
|
||||
"async for chunk in client.runs.stream(\n",
|
||||
" thread['thread_id'], assistant['assistant_id'], input=input, stream_mode=\"updates\", interrupt_before=['action']\n",
|
||||
"):\n",
|
||||
" print(f\"Receiving new event of type: {chunk.event}...\")\n",
|
||||
" print(chunk.data)\n",
|
||||
" print(\"\\n\\n\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2072ce5a-8771-42f9-b2de-5d3a7a9c817b",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Edit a tool call\n",
|
||||
"\n",
|
||||
"What if we want to edit the tool call?\n",
|
||||
"We can also do that.\n",
|
||||
"Let's kick off another run, with the same `interrupt_before=['action']`"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "b226b687-02da-4eef-9286-46dba92b17ba",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Receiving new event of type: metadata...\n",
|
||||
"{'run_id': 'c7c8e313-dad9-47d9-bd03-e112c94eff9e'}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'agent': {'messages': [{'content': [{'id': 'toolu_01NGhKmeciaT7TfhBSwUT3mi', 'input': {'query': 'weather in los angeles'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3d417aa5-e9c1-4b76-90f8-597519c28af9', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles'}, 'id': 'toolu_01NGhKmeciaT7TfhBSwUT3mi'}], 'invalid_tool_calls': []}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: end...\n",
|
||||
"None\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = {\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in la?\"}]}\n",
|
||||
"async for chunk in client.runs.stream(\n",
|
||||
" thread['thread_id'], assistant['assistant_id'], input=input, stream_mode=\"updates\", interrupt_before=['action']\n",
|
||||
"):\n",
|
||||
" print(f\"Receiving new event of type: {chunk.event}...\")\n",
|
||||
" print(chunk.data)\n",
|
||||
" print(\"\\n\\n\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ab338423-c18d-446c-9aa3-3ad2f16d742a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can now inspect the state of the thread"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "bd9ca1f4-c3b0-4fa3-8c91-233a9129a142",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"thread_state = await client.threads.get_state(thread['thread_id'])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "31e82414-afd2-46c4-a605-ce3eb46df485",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Let's get the last message of the thread - this is the one we want to update"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "fe832ec1-7ae0-4d11-8408-d4da88d4dced",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"last_message = thread_state['values']['messages'][-1]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"id": "434253fe-7397-45e2-8be8-91d002088a96",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[{'id': 'toolu_01NGhKmeciaT7TfhBSwUT3mi',\n",
|
||||
" 'input': {'query': 'weather in los angeles'},\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'type': 'tool_use'}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 12,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"last_message['content']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6d007b31-c8a2-465c-bc78-a5909ca7931c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Let's now modify the tool call to say Louisiana"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"id": "55fcb316-450b-4b8c-9ae9-e7ee395acc55",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"last_message['tool_calls'] = [{\n",
|
||||
" 'id': last_message['tool_calls'][0]['id'],\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" # We change the query to say temperature\n",
|
||||
" 'args': {'query': 'weather in Louisiana'}\n",
|
||||
"}]\n",
|
||||
"# last_message['content'] = [{\n",
|
||||
"# 'id': last_message['content'][0]['id'],\n",
|
||||
"# 'name': 'tavily_search_results_json',\n",
|
||||
"# # We change the query to say temperature\n",
|
||||
"# 'input': {'query': 'weather in Louisiana'},\n",
|
||||
"# 'type': 'tool_use'\n",
|
||||
"# }]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d49be54e-5334-47be-8dfb-78b8a8155e98",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can now update the state - we only need to pass in the last updated message because our graph will handle the update."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"id": "0438f997-bad3-48f6-b532-9ac3a95263c2",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'configurable': {'thread_id': '54ed0901-6767-46c9-a5f9-b65c1c5fd89c',\n",
|
||||
" 'thread_ts': '1ef15688-1dbd-68f5-8007-75dc0e110124'}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 14,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"await client.threads.update_state(thread['thread_id'], values={\"messages\": [last_message]})"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c96668ab-80fa-4ae6-a90b-773a943ba331",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Let's now check the state of the thread again, and in particular the final message"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"id": "31936711-4af4-4bd1-ac10-9ce52922dd2f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[{'name': 'tavily_search_results_json',\n",
|
||||
" 'args': {'query': 'weather in Louisiana'},\n",
|
||||
" 'id': 'toolu_01NGhKmeciaT7TfhBSwUT3mi'}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"thread_state = await client.threads.get_state(thread['thread_id'])\n",
|
||||
"thread_state['values']['messages'][-1]['tool_calls']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "20aa8ff3-7876-4db2-9333-c5396cd637ac",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Great! We changed it. If we now resume execution (by kicking off a new run with null inputs on the same thread) it should use that new tool call."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"id": "8e2c4eeb-2888-4979-9877-aa4a53dec5ea",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Receiving new event of type: metadata...\n",
|
||||
"{'run_id': '1a1ebed1-3581-418a-81be-e834b40c5c82'}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'action': {'messages': [{'content': '[{\"url\": \"https://www.weatherapi.com/\", \"content\": \"{\\'location\\': {\\'name\\': \\'Louisiana\\', \\'region\\': \\'Missouri\\', \\'country\\': \\'USA United States of America\\', \\'lat\\': 39.44, \\'lon\\': -91.06, \\'tz_id\\': \\'America/Chicago\\', \\'localtime_epoch\\': 1716072393, \\'localtime\\': \\'2024-05-18 17:46\\'}, \\'current\\': {\\'last_updated_epoch\\': 1716072300, \\'last_updated\\': \\'2024-05-18 17:45\\', \\'temp_c\\': 29.0, \\'temp_f\\': 84.2, \\'is_day\\': 1, \\'condition\\': {\\'text\\': \\'Partly cloudy\\', \\'icon\\': \\'//cdn.weatherapi.com/weather/64x64/day/116.png\\', \\'code\\': 1003}, \\'wind_mph\\': 6.9, \\'wind_kph\\': 11.2, \\'wind_degree\\': 220, \\'wind_dir\\': \\'SW\\', \\'pressure_mb\\': 1011.0, \\'pressure_in\\': 29.86, \\'precip_mm\\': 0.0, \\'precip_in\\': 0.0, \\'humidity\\': 46, \\'cloud\\': 50, \\'feelslike_c\\': 31.4, \\'feelslike_f\\': 88.6, \\'vis_km\\': 16.0, \\'vis_miles\\': 9.0, \\'uv\\': 7.0, \\'gust_mph\\': 7.4, \\'gust_kph\\': 11.9}}\"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '728f8ac9-729e-4bf7-b560-b332a73c8f47', 'tool_call_id': 'toolu_01NGhKmeciaT7TfhBSwUT3mi'}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'agent': {'messages': [{'content': [{'text': 'The search results seem to be for the weather in Louisiana, Missouri rather than Los Angeles, California. Let me try the search again:', 'type': 'text'}, {'id': 'toolu_019YAXWMK33tG9DaxMzrowc8', 'input': {'query': 'weather in los angeles california'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}], 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-c42a3b14-2611-4a1d-8907-95dcdb18f07f', 'example': False, 'tool_calls': [{'name': 'tavily_search_results_json', 'args': {'query': 'weather in los angeles california'}, 'id': 'toolu_019YAXWMK33tG9DaxMzrowc8'}], 'invalid_tool_calls': []}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: end...\n",
|
||||
"None\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = None\n",
|
||||
"async for chunk in client.runs.stream(\n",
|
||||
" thread['thread_id'], assistant['assistant_id'], input=input, stream_mode=\"updates\", interrupt_before=['action']\n",
|
||||
"):\n",
|
||||
" print(f\"Receiving new event of type: {chunk.event}...\")\n",
|
||||
" print(chunk.data)\n",
|
||||
" print(\"\\n\\n\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "065f8165-43d8-4876-86af-0cfffd712fee",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Edit an old state\n",
|
||||
"\n",
|
||||
"Let's now imagine we want to go back in time and edit the tool call after we had already made it.\n",
|
||||
"In order to do this, we can get first get the full history of the thread."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 46,
|
||||
"id": "de050efd-73a4-441e-91e0-18e08f773a42",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"thread_history = await client.threads.get_history(thread['thread_id'], limit=100)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 47,
|
||||
"id": "07e15435-4a5f-4c2a-b748-0e0f7ab02a28",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"11"
|
||||
]
|
||||
},
|
||||
"execution_count": 47,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"len(thread_history)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "a292e721-36c4-41b8-85e4-378f0770652a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"After that, we can get the correct state we want to be in. The 0th index state is the most recent one, while the -1 index state is the first.\n",
|
||||
"In this case, we want to go to the state where the last message had the tool calls for `weather in los angeles`"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 48,
|
||||
"id": "132d207c-11cb-4efb-a330-88ebdfc612c8",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[{'name': 'tavily_search_results_json',\n",
|
||||
" 'args': {'query': 'weather in los angeles'},\n",
|
||||
" 'id': 'toolu_01FnuDKhUfagwoqhNfiTYTfS'}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 48,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"rewind_state = thread_history[3]\n",
|
||||
"rewind_state['values']['messages'][-1]['tool_calls']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 49,
|
||||
"id": "45e01ddf-2ccf-4029-b431-e5fce2235b59",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'configurable': {'thread_id': 'df85453d-cb86-48c8-ae84-12081faa1bdf',\n",
|
||||
" 'thread_ts': '1ef15582-3442-6db7-8006-9166bbb0e80f'}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 49,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"rewind_state['config']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d229468e-2f94-4b29-b56b-1d402554dcfb",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"If we want to, we can now resume execution from that place in time"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 50,
|
||||
"id": "94ebc63e-f2cf-4da1-bc8d-52c4731ab0c6",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Receiving new event of type: metadata...\n",
|
||||
"{'run_id': 'a1cc9263-ef0a-4c04-9194-6f01624d0ef0'}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'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\\': 1716071728, \\'localtime\\': \\'2024-05-18 15:35\\'}, \\'current\\': {\\'last_updated_epoch\\': 1716071400, \\'last_updated\\': \\'2024-05-18 15:30\\', \\'temp_c\\': 20.0, \\'temp_f\\': 68.0, \\'is_day\\': 1, \\'condition\\': {\\'text\\': \\'Partly cloudy\\', \\'icon\\': \\'//cdn.weatherapi.com/weather/64x64/day/116.png\\', \\'code\\': 1003}, \\'wind_mph\\': 2.2, \\'wind_kph\\': 3.6, \\'wind_degree\\': 226, \\'wind_dir\\': \\'SW\\', \\'pressure_mb\\': 1016.0, \\'pressure_in\\': 29.99, \\'precip_mm\\': 0.0, \\'precip_in\\': 0.0, \\'humidity\\': 61, \\'cloud\\': 50, \\'feelslike_c\\': 20.0, \\'feelslike_f\\': 68.0, \\'vis_km\\': 16.0, \\'vis_miles\\': 9.0, \\'uv\\': 6.0, \\'gust_mph\\': 12.6, \\'gust_kph\\': 20.3}}\"}]', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'tool', 'name': 'tavily_search_results_json', 'id': '7137b2e5-566b-418b-b642-b3c6b64c5224', 'tool_call_id': 'toolu_01FnuDKhUfagwoqhNfiTYTfS'}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'agent': {'messages': [{'content': 'The search results show the current weather conditions in Los Angeles. As of 3:30pm on May 18, 2024, the weather in Los Angeles is partly cloudy with a temperature around 68°F (20°C). Winds are light from the southwest around 2-3 mph. The humidity is 61% and visibility is good at 9 miles. Overall, it appears to be a nice spring day in LA with partly sunny skies and comfortable temperatures in the upper 60s.', 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-3966b68a-c381-4933-a852-e6a4697c962c', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: end...\n",
|
||||
"None\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = None\n",
|
||||
"async for chunk in client.runs.stream(\n",
|
||||
" thread['thread_id'], \n",
|
||||
" assistant['assistant_id'], \n",
|
||||
" input=input, \n",
|
||||
" stream_mode=\"updates\", \n",
|
||||
" interrupt_before=['action'],\n",
|
||||
" config=rewind_state['config']\n",
|
||||
"):\n",
|
||||
" print(f\"Receiving new event of type: {chunk.event}...\")\n",
|
||||
" print(chunk.data)\n",
|
||||
" print(\"\\n\\n\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "492f1d37-0979-4210-8dd7-bc70cdc308f3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -0,0 +1,175 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Interrupt\n",
|
||||
"\n",
|
||||
"There are several strategies for handling concurrent runs in your graph. This notebook covers how to use the `interrupt` option - please see the other how-to guides in the \"Double Texting\" directory to learn about the other methods.\n",
|
||||
"\n",
|
||||
"First, let's import our required packages and instantiate our client, assistant, and thread."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import asyncio\n",
|
||||
"\n",
|
||||
"from langchain_core.messages import convert_to_messages\n",
|
||||
"from langgraph_sdk import get_client"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = get_client()\n",
|
||||
"assistant = await client.assistants.create(\"agent\")\n",
|
||||
"thread = await client.threads.create()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# the first run will be interrupted\n",
|
||||
"interrupted_run = await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in sf?\"}]},\n",
|
||||
")\n",
|
||||
"await asyncio.sleep(2)\n",
|
||||
"run = await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in nyc?\"}]},\n",
|
||||
" multitask_strategy=\"interrupt\",\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# wait until the second run completes\n",
|
||||
"await client.runs.join(thread[\"thread_id\"], run[\"run_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can see that the thread has partial data from the first run + data from the second run"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"state = await client.threads.get_state(thread[\"thread_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"================================\u001b[1m Human Message \u001b[0m=================================\n",
|
||||
"\n",
|
||||
"whats the weather in sf?\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"[{'id': 'toolu_01MjNtVJwEcpujRGrf3x6Pih', 'input': {'query': 'weather in san francisco'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}]\n",
|
||||
"Tool Calls:\n",
|
||||
" tavily_search_results_json (toolu_01MjNtVJwEcpujRGrf3x6Pih)\n",
|
||||
" Call ID: toolu_01MjNtVJwEcpujRGrf3x6Pih\n",
|
||||
" Args:\n",
|
||||
" query: weather in san francisco\n",
|
||||
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
|
||||
"Name: tavily_search_results_json\n",
|
||||
"\n",
|
||||
"[{\"url\": \"https://www.wunderground.com/hourly/us/ca/san-francisco/KCASANFR2002/date/2024-6-18\", \"content\": \"High 64F. Winds W at 10 to 20 mph. A few clouds from time to time. Low 49F. Winds W at 10 to 20 mph. Temp. San Francisco Weather Forecasts. Weather Underground provides local & long-range weather ...\"}]\n",
|
||||
"================================\u001b[1m Human Message \u001b[0m=================================\n",
|
||||
"\n",
|
||||
"whats the weather in nyc?\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"[{'id': 'toolu_01KtE1m1ifPLQAx4fQLyZL9Q', 'input': {'query': 'weather in new york city'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}]\n",
|
||||
"Tool Calls:\n",
|
||||
" tavily_search_results_json (toolu_01KtE1m1ifPLQAx4fQLyZL9Q)\n",
|
||||
" Call ID: toolu_01KtE1m1ifPLQAx4fQLyZL9Q\n",
|
||||
" Args:\n",
|
||||
" query: weather in new york city\n",
|
||||
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
|
||||
"Name: tavily_search_results_json\n",
|
||||
"\n",
|
||||
"[{\"url\": \"https://www.accuweather.com/en/us/new-york/10021/june-weather/349727\", \"content\": \"Get the monthly weather forecast for New York, NY, including daily high/low, historical averages, to help you plan ahead.\"}]\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"The search results provide weather forecasts and information for New York City. Based on the top result from AccuWeather, here are some key details about the weather in NYC:\n",
|
||||
"\n",
|
||||
"- This is a monthly weather forecast for New York City for the month of June.\n",
|
||||
"- It includes daily high and low temperatures to help plan ahead.\n",
|
||||
"- Historical averages for June in NYC are also provided as a reference point.\n",
|
||||
"- More detailed daily or hourly forecasts with precipitation chances, humidity, wind, etc. can be found by visiting the AccuWeather page.\n",
|
||||
"\n",
|
||||
"So in summary, the search provides a convenient overview of the expected weather conditions in New York City over the next month to give you an idea of what to prepare for if traveling or making plans there. Let me know if you need any other details!\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for m in convert_to_messages(state[\"values\"][\"messages\"]):\n",
|
||||
" m.pretty_print()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Verify that the original, interrupted run was interrupted"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'interrupted'"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"(await client.runs.get(thread[\"thread_id\"], interrupted_run[\"run_id\"]))[\"status\"]"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
@@ -0,0 +1,172 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Reject\n",
|
||||
"\n",
|
||||
"There are several strategies for handling concurrent runs in your graph. This notebook covers how to use the `reject` option - please see the other how-to guides in the \"Double Texting\" directory to learn about the other methods.\n",
|
||||
"\n",
|
||||
"First, let's import our required packages and instantiate our client, assistant, and thread."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import httpx\n",
|
||||
"from langchain_core.messages import convert_to_messages\n",
|
||||
"from langgraph_sdk import get_client"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = get_client()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"assistant = await client.assistants.create(\"agent\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"thread = await client.threads.create()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"run = await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in sf?\"}]},\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Failed to start concurrent run Client error '409 Conflict' for url 'http://localhost:8123/threads/f9e7088b-8028-4e5c-88d2-9cc9a2870e50/runs'\n",
|
||||
"For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/409\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"try:\n",
|
||||
" await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in nyc?\"}]},\n",
|
||||
" multitask_strategy=\"reject\",\n",
|
||||
" )\n",
|
||||
"except httpx.HTTPStatusError as e:\n",
|
||||
" print(\"Failed to start concurrent run\", e)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can verify that the original thread finished executing:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# wait until the original run completes\n",
|
||||
"await client.runs.join(thread[\"thread_id\"], run[\"run_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"state = await client.threads.get_state(thread[\"thread_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"================================\u001b[1m Human Message \u001b[0m=================================\n",
|
||||
"\n",
|
||||
"whats the weather in sf?\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"[{'id': 'toolu_01CyewEifV2Kmi7EFKHbMDr1', 'input': {'query': 'weather in san francisco'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}]\n",
|
||||
"Tool Calls:\n",
|
||||
" tavily_search_results_json (toolu_01CyewEifV2Kmi7EFKHbMDr1)\n",
|
||||
" Call ID: toolu_01CyewEifV2Kmi7EFKHbMDr1\n",
|
||||
" Args:\n",
|
||||
" query: weather in san francisco\n",
|
||||
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
|
||||
"Name: tavily_search_results_json\n",
|
||||
"\n",
|
||||
"[{\"url\": \"https://www.accuweather.com/en/us/san-francisco/94103/june-weather/347629\", \"content\": \"Get the monthly weather forecast for San Francisco, CA, including daily high/low, historical averages, to help you plan ahead.\"}]\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"According to the search results from Tavily, the current weather in San Francisco is:\n",
|
||||
"\n",
|
||||
"The average high temperature in San Francisco in June is around 65°F (18°C), with average lows around 54°F (12°C). June tends to be one of the cooler and foggier months in San Francisco due to the marine layer of fog that often blankets the city during the summer months.\n",
|
||||
"\n",
|
||||
"Some key points about the typical June weather in San Francisco:\n",
|
||||
"\n",
|
||||
"- Mild temperatures with highs in the 60s F and lows in the 50s F\n",
|
||||
"- Foggy mornings that often burn off to sunny afternoons\n",
|
||||
"- Little to no rainfall, as June falls in the dry season\n",
|
||||
"- Breezy conditions, with winds off the Pacific Ocean\n",
|
||||
"- Layers are recommended for changing weather conditions\n",
|
||||
"\n",
|
||||
"So in summary, you can expect mild, foggy mornings giving way to sunny but cool afternoons in San Francisco this time of year. The marine layer keeps temperatures moderate compared to other parts of California in June.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for m in convert_to_messages(state[\"values\"][\"messages\"]):\n",
|
||||
" m.pretty_print()"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
@@ -0,0 +1,155 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Rollback\n",
|
||||
"\n",
|
||||
"There are several strategies for handling concurrent runs in your graph. This notebook covers how to use the `rollback` option - please see the other how-to guides in the \"Double Texting\" directory to learn about the other methods.\n",
|
||||
"\n",
|
||||
"First, let's import our required packages and instantiate our client, assistant, and thread."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import asyncio\n",
|
||||
"\n",
|
||||
"import httpx\n",
|
||||
"from langchain_core.messages import convert_to_messages\n",
|
||||
"from langgraph_sdk import get_client"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = get_client()\n",
|
||||
"assistant = await client.assistants.create(\"agent\")\n",
|
||||
"thread = await client.threads.create()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# the first run will be interrupted\n",
|
||||
"rolled_back_run = await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in sf?\"}]},\n",
|
||||
")\n",
|
||||
"await asyncio.sleep(2)\n",
|
||||
"run = await client.runs.create(\n",
|
||||
" thread[\"thread_id\"],\n",
|
||||
" assistant[\"assistant_id\"],\n",
|
||||
" input={\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in nyc?\"}]},\n",
|
||||
" multitask_strategy=\"rollback\",\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# wait until the second run completes\n",
|
||||
"await client.runs.join(thread[\"thread_id\"], run[\"run_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can see that the thread has data only from the second run"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"state = await client.threads.get_state(thread[\"thread_id\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"================================\u001b[1m Human Message \u001b[0m=================================\n",
|
||||
"\n",
|
||||
"whats the weather in nyc?\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"[{'id': 'toolu_01JzPqefao1gxwajHQ3Yh3JD', 'input': {'query': 'weather in nyc'}, 'name': 'tavily_search_results_json', 'type': 'tool_use'}]\n",
|
||||
"Tool Calls:\n",
|
||||
" tavily_search_results_json (toolu_01JzPqefao1gxwajHQ3Yh3JD)\n",
|
||||
" Call ID: toolu_01JzPqefao1gxwajHQ3Yh3JD\n",
|
||||
" Args:\n",
|
||||
" query: weather in nyc\n",
|
||||
"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
|
||||
"Name: tavily_search_results_json\n",
|
||||
"\n",
|
||||
"[{\"url\": \"https://www.weatherapi.com/\", \"content\": \"{'location': {'name': 'New York', 'region': 'New York', 'country': 'United States of America', 'lat': 40.71, 'lon': -74.01, 'tz_id': 'America/New_York', 'localtime_epoch': 1718734479, 'localtime': '2024-06-18 14:14'}, 'current': {'last_updated_epoch': 1718733600, 'last_updated': '2024-06-18 14:00', 'temp_c': 29.4, 'temp_f': 84.9, 'is_day': 1, 'condition': {'text': 'Sunny', 'icon': '//cdn.weatherapi.com/weather/64x64/day/113.png', 'code': 1000}, 'wind_mph': 2.2, 'wind_kph': 3.6, 'wind_degree': 158, 'wind_dir': 'SSE', 'pressure_mb': 1025.0, 'pressure_in': 30.26, 'precip_mm': 0.0, 'precip_in': 0.0, 'humidity': 63, 'cloud': 0, 'feelslike_c': 31.3, 'feelslike_f': 88.3, 'windchill_c': 28.3, 'windchill_f': 82.9, 'heatindex_c': 29.6, 'heatindex_f': 85.3, 'dewpoint_c': 18.4, 'dewpoint_f': 65.2, 'vis_km': 16.0, 'vis_miles': 9.0, 'uv': 7.0, 'gust_mph': 16.5, 'gust_kph': 26.5}}\"}]\n",
|
||||
"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
|
||||
"\n",
|
||||
"The weather API results show that the current weather in New York City is sunny with a temperature of around 85°F (29°C). The wind is light at around 2-3 mph from the south-southeast. Overall it looks like a nice sunny summer day in NYC.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for m in convert_to_messages(state[\"values\"][\"messages\"]):\n",
|
||||
" m.pretty_print()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Verify that the original, rolled back run was deleted"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Original run was correctly deleted\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"try:\n",
|
||||
" await client.runs.get(thread[\"thread_id\"], rolled_back_run[\"run_id\"])\n",
|
||||
"except httpx.HTTPStatusError as _:\n",
|
||||
" print(\"Original run was correctly deleted\")"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
@@ -0,0 +1,184 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "68c0837d-c40a-4209-9f88-5d08c00c31b0",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# How to run multiple agents on the same thread\n",
|
||||
"\n",
|
||||
"In LangGraph API, a thread is not explicitly associated with a particular agent.\n",
|
||||
"This means that you can run multiple agents on the same thread.\n",
|
||||
"In this example, we will create two agents and then call them both on the same thread."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "e06be1f6-07a5-4e93-8497-02473fc65d4f",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langgraph_sdk import get_client\n",
|
||||
"\n",
|
||||
"client = get_client()\n",
|
||||
"\n",
|
||||
"openai_assistant = await client.assistants.create(graph_id=\"agent\", config={\"configurable\": {\"model_name\": \"openai\"}})\n",
|
||||
"\n",
|
||||
"# There should always be a default assistant with no configuration\n",
|
||||
"assistants = await client.assistants.search()\n",
|
||||
"default_assistant = [a for a in assistants if not a['config']][0]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "4f10d346-69e6-44f4-8ff0-ef539ba938df",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can see that these agents are different"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "3898ca35-eb2c-4b12-97ea-e0cc6a7c6a2e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'assistant_id': '13ecc353-a9a9-474b-a824-b6a343cd74b1',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {'configurable': {'model_name': 'openai'}},\n",
|
||||
" 'created_at': '2024-05-21T16:22:59.258447+00:00',\n",
|
||||
" 'updated_at': '2024-05-21T16:22:59.258447+00:00',\n",
|
||||
" 'metadata': {}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"openai_assistant"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "a8fa67b2-cb4f-43d3-a1fc-f8b3936c16b6",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {},\n",
|
||||
" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'metadata': {'created_by': 'system'}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"default_assistant"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "5e655e61-c2ee-488a-90f6-6189c84841da",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We can now run it on the OpenAI assistant first."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"id": "68ed7a1b-74be-4560-8c55-c76d49d3d348",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"StreamPart(event='metadata', data={'run_id': 'f90b3029-8669-4d70-976c-b70368e355d8'})\n",
|
||||
"StreamPart(event='updates', data={'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'}, 'type': 'ai', 'name': None, 'id': 'run-9801a5ba-2f3c-43de-89cf-c740debf36fc', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}})\n",
|
||||
"StreamPart(event='end', data=None)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"thread = await client.threads.create()\n",
|
||||
"input = {\"messages\": [{\"role\": \"user\", \"content\": \"who made you?\"}]}\n",
|
||||
"async for event in client.runs.stream(thread['thread_id'], openai_assistant['assistant_id'], input=input, stream_mode='updates'):\n",
|
||||
" print(event)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c53709e9-ddb2-4429-9042-456eb6c91244",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Now, we can run it on a different Anthropic-based assistant."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"id": "666d78f1-019a-433e-839e-52d2ebb3d9c8",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"StreamPart(event='metadata', data={'run_id': 'c3521302-48ae-4c29-a0f2-5eb865cbc6d7'})\n",
|
||||
"StreamPart(event='updates', data={'agent': {'messages': [{'content': \"I am an AI assistant created by Anthropic to be helpful, harmless, and honest. I don't actually have a physical form or visual representation - I exist as a language model trained to have natural conversations.\", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-4d05ffd7-0505-43e1-a068-0207c56b7665', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}})\n",
|
||||
"StreamPart(event='end', data=None)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = {\"messages\": [{\"role\": \"user\", \"content\": \"and you?\"}]}\n",
|
||||
"async for event in client.runs.stream(thread['thread_id'], default_assistant['assistant_id'], input=input, stream_mode='updates'):\n",
|
||||
" print(event)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "4c26df68-c447-4a88-bc94-59df42b117b5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,219 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "51466c8d-8ce4-4b3d-be4e-18fdbeda5f53",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# How to stream updates from your graph\n",
|
||||
"\n",
|
||||
"There are multiple different streaming modes.\n",
|
||||
"\n",
|
||||
"- `values`: This streaming mode streams back values of the graph. This is the **full state of the graph** after each node is called.\n",
|
||||
"- `updates`: This streaming mode streams back updates to the graph. This is the **update to the state of the graph** after each node is called.\n",
|
||||
"- `messages`: This streaming mode streams back messages - both complete messages (at the end of a node) as well as **tokens** for any messages generated inside a node. This mode is primarily meant for powering chat applications.\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"This notebook covers `streaming_mode=\"updates\"`."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "521d975b-e94b-4c37-bfa1-82d969e2a4dc",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langgraph_sdk import get_client"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "27a1392b-86c3-464e-99a8-90ffc965f3ec",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = get_client()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "4947e9bc-111f-4991-8c41-1041da9bf0ba",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {},\n",
|
||||
" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'metadata': {'created_by': 'system'}}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# There should always be a default assistant with no configuration\n",
|
||||
"assistants = await client.assistants.search()\n",
|
||||
"assistants = [a for a in assistants if not a['config']]\n",
|
||||
"assistants"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "230c0464-a6e5-420f-9e38-ca514e5634ce",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {},\n",
|
||||
" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'metadata': {'created_by': 'system'}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"assistant = assistants[0]\n",
|
||||
"assistant"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "56aa5159-5583-4134-9210-709b969bda6f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'thread_id': '1eee9bd4-ec61-4300-a38a-2e13b8925d39',\n",
|
||||
" 'created_at': '2024-05-18T19:57:36.509105+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T19:57:36.509105+00:00',\n",
|
||||
" 'metadata': {}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"thread = await client.threads.create()\n",
|
||||
"thread"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "147c3f98-f889-4f05-a090-6b31f2a0b291",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[]"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"runs = await client.runs.list(thread['thread_id'])\n",
|
||||
"runs"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "7da70e20-1a4e-4df2-b996-1927f474c835",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Receiving new event of type: metadata...\n",
|
||||
"{'run_id': 'cfc96c16-ed9a-44bd-b5bb-c30e3c0725f0'}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'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': []}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'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'}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: data...\n",
|
||||
"{'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': []}]}}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: end...\n",
|
||||
"None\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = {\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in la\"}]}\n",
|
||||
"async for chunk in client.runs.stream(thread['thread_id'], assistant['assistant_id'], input=input, stream_mode=\"updates\", ):\n",
|
||||
" print(f\"Receiving new event of type: {chunk.event}...\")\n",
|
||||
" print(chunk.data)\n",
|
||||
" print(\"\\n\\n\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "53800469-354a-4739-8e77-b88044c772d5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -0,0 +1,258 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "51466c8d-8ce4-4b3d-be4e-18fdbeda5f53",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# How to stream values from your graph\n",
|
||||
"\n",
|
||||
"There are multiple different streaming modes.\n",
|
||||
"\n",
|
||||
"- `values`: This streaming mode streams back values of the graph. This is the **full state of the graph** after each node is called.\n",
|
||||
"- `updates`: This streaming mode streams back updates to the graph. This is the **update to the state of the graph** after each node is called.\n",
|
||||
"- `messages`: This streaming mode streams back messages - both complete messages (at the end of a node) as well as **tokens** for any messages generated inside a node. This mode is primarily meant for powering chat applications.\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"This notebook covers `streaming_mode=\"values\"`."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "521d975b-e94b-4c37-bfa1-82d969e2a4dc",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langgraph_sdk import get_client"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "27a1392b-86c3-464e-99a8-90ffc965f3ec",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = get_client()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "4947e9bc-111f-4991-8c41-1041da9bf0ba",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {},\n",
|
||||
" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'metadata': {'created_by': 'system'}}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# There should always be a default assistant with no configuration\n",
|
||||
"assistants = await client.assistants.search()\n",
|
||||
"assistants = [a for a in assistants if not a['config']]\n",
|
||||
"assistants"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "230c0464-a6e5-420f-9e38-ca514e5634ce",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
|
||||
" 'graph_id': 'agent',\n",
|
||||
" 'config': {},\n",
|
||||
" 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
|
||||
" 'metadata': {'created_by': 'system'}}"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"assistant = assistants[0]\n",
|
||||
"assistant"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "7da70e20-1a4e-4df2-b996-1927f474c835",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Receiving new event of type: metadata...\n",
|
||||
"{'run_id': 'f08791ce-0a3d-44e0-836c-ff62cd2e2786'}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: values...\n",
|
||||
"{'messages': [{'role': 'human', 'content': 'whats the weather in la'}]}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: values...\n",
|
||||
"{'messages': [{'content': 'whats 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': []}]}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: values...\n",
|
||||
"{'messages': [{'content': 'whats 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'}]}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: values...\n",
|
||||
"{'messages': [{'content': 'whats 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': []}]}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"Receiving new event of type: end...\n",
|
||||
"None\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"input = {\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in la\"}]}\n",
|
||||
"thread = await client.threads.create()\n",
|
||||
"async for chunk in client.runs.stream(thread['thread_id'], assistant['assistant_id'], input=input):\n",
|
||||
" print(f\"Receiving new event of type: {chunk.event}...\")\n",
|
||||
" print(chunk.data)\n",
|
||||
" print(\"\\n\\n\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "43e4432d-e96c-4ae4-8085-866fb57bbcb3",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"If we want to just get the final result, we can use this endpoint and just keep track of the last value we received"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "d2560481-d161-4d4f-b385-4977696c4aa1",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"input = {\"messages\": [{\"role\": \"human\", \"content\": \"whats the weather in la\"}]}\n",
|
||||
"thread = await client.threads.create()\n",
|
||||
"final_answer = None\n",
|
||||
"async for chunk in client.runs.stream(thread['thread_id'], assistant['assistant_id'], input=input):\n",
|
||||
" if chunk.event == \"values\":\n",
|
||||
" final_answer = chunk.data"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "9c2d60ea-450f-45cd-b867-0cbb162528f6",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'messages': [{'content': 'whats the weather in la',\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'type': 'human',\n",
|
||||
" 'name': None,\n",
|
||||
" 'id': 'e78c2f94-d810-42fc-a399-11f6bb1b1092',\n",
|
||||
" 'example': False},\n",
|
||||
" {'content': [{'id': 'toolu_01SBMoAGr4U9x3ibztm2UUom',\n",
|
||||
" 'input': {'query': 'weather in los angeles'},\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'type': 'tool_use'}],\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'type': 'ai',\n",
|
||||
" 'name': None,\n",
|
||||
" 'id': 'run-80767ab8-09fc-40ec-9e45-657ddef5e0b1',\n",
|
||||
" 'example': False,\n",
|
||||
" 'tool_calls': [{'name': 'tavily_search_results_json',\n",
|
||||
" 'args': {'query': 'weather in los angeles'},\n",
|
||||
" 'id': 'toolu_01SBMoAGr4U9x3ibztm2UUom'}],\n",
|
||||
" 'invalid_tool_calls': []},\n",
|
||||
" {'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}}\"}]',\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'type': 'tool',\n",
|
||||
" 'name': 'tavily_search_results_json',\n",
|
||||
" 'id': 'af25e94a-c119-48c3-bbd3-096e42f472ac',\n",
|
||||
" 'tool_call_id': 'toolu_01SBMoAGr4U9x3ibztm2UUom'},\n",
|
||||
" {'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.',\n",
|
||||
" 'additional_kwargs': {},\n",
|
||||
" 'response_metadata': {},\n",
|
||||
" 'type': 'ai',\n",
|
||||
" 'name': None,\n",
|
||||
" 'id': 'run-b90f0037-e56a-4f3b-ad92-00d10d079a9e',\n",
|
||||
" 'example': False,\n",
|
||||
" 'tool_calls': [],\n",
|
||||
" 'invalid_tool_calls': []}]}"
|
||||
]
|
||||
},
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"final_answer"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "39cedbff-0a7f-4a3e-bfc1-595797358769",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Reference in New Issue
Block a user