Parsera

Learn how to use Parsera with Composio

Overview

SLUG: PARSERA

Description

Parsera is a lightweight Python library for scraping websites using large language models (LLMs).

Authentication Details

generic_api_key
stringRequired

Connecting to Parsera

Create an auth config

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

1

Select App

Navigate to Parsera.

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 Parsera 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 API Key

1from composio import Composio
2
3# Replace these with your actual values
4parsera_auth_config_id = "ac_YOUR_PARSERA_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": {"generic_api_key": user_api_key}}
18 )
19
20 # API Key authentication is immediate - no redirect needed
21 print(f"Successfully connected Parsera 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, parsera_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 Parsera 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=["PARSERA"])
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: Extract Markdown

Description

Tool to extract markdown content from a file or url.

Action Parameters

file_path
string
url
string

Action Response

data
objectRequired
error
string
successful
booleanRequired

Tool Name: Parse Content with Parsera

Description

Tool to parse and extract structured data from provided html or text. use after obtaining raw content.

Action Parameters

attributes
object
content
stringRequired
content_type
stringRequired
options
object
output_format
stringDefaults to json
prompt
string

Action Response

data
objectRequired
error
string
successful
booleanRequired