Elasticsearch

Learn how to use Elasticsearch with Composio

Overview

SLUG: ELASTICSEARCH

Description

Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. It provides real-time search and analytics for all types of data.

Authentication Details

username
stringRequired
password
stringRequired
full
stringRequired
full
stringRequired
generic_api_key
stringRequired

Connecting to Elasticsearch

Create an auth config

Use the dashboard to create an auth config for the Elasticsearch toolkit. This allows you to connect multiple Elasticsearch accounts to Composio for agents to use.

1

Select App

Navigate to Elasticsearch.

2

Configure Auth Config Settings

Select among the supported auth schemes of and configure them here.

3

Create and Get auth config ID

Click “Create Elasticsearch Auth Config”. After creation, copy the displayed ID starting with ac_. This is your auth config ID. This is not a sensitive ID — you can save it in environment variables or a database. This ID will be used to create connections to the toolkit for a given user.

Connect Your Account

Using Basic Auth

1from composio import Composio
2from composio.types import auth_scheme
3
4# Replace these with your actual values
5elasticsearch_auth_config_id = "ac_YOUR_ELASTICSEARCH_CONFIG_ID"
6user_id = "user@example.com"
7username = "your_elasticsearch_username"
8password = "your_elasticsearch_password"
9
10composio = Composio()
11
12# Create a new connected account for Elasticsearch using Basic Auth
13connection_request = composio.connected_accounts.initiate(
14 user_id=user_id,
15 auth_config_id=elasticsearch_auth_config_id,
16 config=auth_scheme.basic_auth(
17 username=username,
18 password=password
19 )
20)
21
22# Basic authentication is immediate - no redirect needed
23print(f"Successfully connected Elasticsearch for user {user_id}")
24
25# You can verify the connection using:
26# connected_account = composio.connected_accounts.get(user_id=user_id, app_id="ELASTICSEARCH")

Using API Key

1from composio import Composio
2
3# Replace these with your actual values
4elasticsearch_auth_config_id = "ac_YOUR_ELASTICSEARCH_CONFIG_ID" # Auth config ID created above
5user_id = "0000-0000-0000" # UUID from database/app
6
7composio = Composio()
8
9def authenticate_toolkit(user_id: str, auth_config_id: str):
10 # Replace this with a method to retrieve an API key from the user.
11 # Or supply your own.
12 user_api_key = input("[!] Enter API key")
13
14 connection_request = composio.connected_accounts.initiate(
15 user_id=user_id,
16 auth_config_id=auth_config_id,
17 config={"auth_scheme": "API_KEY", "val": user_api_key}
18 )
19
20 # API Key authentication is immediate - no redirect needed
21 print(f"Successfully connected Elasticsearch for user {user_id}")
22 print(f"Connection status: {connection_request.status}")
23
24 return connection_request.id
25
26
27connection_id = authenticate_toolkit(user_id, elasticsearch_auth_config_id)
28
29# You can verify the connection using:
30connected_account = composio.connected_accounts.get(connection_id)
31print(f"Connected account: {connected_account}")

Tools

Executing tools

To prototype you can execute some tools to see the responses and working on the Elasticsearch toolkit’s playground

Python
1from composio import Composio
2from openai import OpenAI
3import json
4
5openai = OpenAI()
6composio = Composio()
7
8# User ID must be a valid UUID format
9user_id = "0000-0000-0000" # Replace with actual user UUID from your database
10
11tools = composio.tools.get(user_id=user_id, toolkits=["ELASTICSEARCH"])
12
13print("[!] Tools:")
14print(json.dumps(tools))
15
16def invoke_llm(task = "What can you do?"):
17 completion = openai.chat.completions.create(
18 model="gpt-4o",
19 messages=[
20 {
21 "role": "user",
22 "content": task, # Your task here!
23 },
24 ],
25 tools=tools,
26 )
27
28 # Handle Result from tool call
29 result = composio.provider.handle_tool_calls(user_id=user_id, response=completion)
30 print(f"[!] Completion: {completion}")
31 print(f"[!] Tool call result: {result}")
32
33invoke_llm()

Tool List

Tool Name: Get Index Schema

Description

Tool to get the complete schema/mapping of a specific elasticsearch index. use when you need to understand the structure, field types, and mappings of an index.

Action Parameters

index_name
stringRequired

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: List Indices

Description

Tool to list all available elasticsearch indices. use when you need to get a list of indices in your elasticsearch cluster, optionally filtering by pattern, health status, or other criteria.

Action Parameters

expand_wildcards
string
health
string
include_primary_shards_only
boolean
index
string
sort_by
string

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: Query Index

Description

Tool to query an elasticsearch index with various filters, time ranges, and pagination support. use when you need to search for documents in an index with complex filtering criteria.

Action Parameters

fields
array
from
integer
highlight
boolean
include_aggregations
boolean
index_name
stringRequired
query
string
range_filters
array
size
integerDefaults to 10
sort
array
term_filters
array
time_filter
object

Action Response

data
objectRequired
error
string
successful
booleanRequired