# LlamaIndex
## 1. Install Required Libraries
First, you need to install the necessary packages:
{% hint style="info" %}
Integry requires Python version 3.12 or higher
{% endhint %}
* **Integry** enables seamless integration of structured tools and functions from over 300 apps
* **LlamaIndex** integrate tools and automate workflows using large language models.
```python
pip install integry llama-index
```
## 2. Initialize Integry & Agent
Import the necessary Libraries
```python
import os
from integry import Integry
from llama_index.core.tools import FunctionTool, ToolMetadata
from llama_index.llms.openai import OpenAI
from llama_index.core.agent import ReActAgent
```
`user_id` is how you define users in your app or agent. By default, your email used during your Integry signup can act as a user\_id as well. Function Calls and Integrations are linked to this id.
For example:
```python
user_id = "joe@example.com" #replace with your email used during sign up
```
Below code snippet initializes the Integry class to interact with the Integry API using the App-Key and App-Secret.
You can view and copy your App-Key and App-Secret from the [Workspace Settings](https://app.integry.io/platform/workspace/security/).
Workspace Settings
To begin using Integry, you first set the App Key and App Secret as environment variables. Here is a quick way
```python
os.environ["INTEGRY_APP_KEY"] = "your_app_key_here"
os.environ["INTEGRY_APP_SECRET"] = "your_app_secret_here"
```
Initializing the Integry object
```python
integry = Integry(
app_key=os.environ.get("INTEGRY_APP_KEY"),
app_secret=os.environ.get("INTEGRY_APP_SECRET"),
)
```
Now initializing the instance of the OpenAI class to interact with OpenAI's GPT-4o model. You can get the API Key from the [OpenAI Platform](https://platform.openai.com/api-keys)
```python
llm = OpenAI(model="gpt-4o", temperature=0, api_key=os.environ.get("OPENAI_API_KEY"))
```
## 3. Register the Integry Function as a Tool
Perfect! Before you can use the functions available in Integry, you need to add the app to Integry. Slack, however, is pre-added to your Integry account, so there’s no need to add it manually.
To enable the assistant to call the function, we register it with the LlamaIndex agents. Now that everything is set up, we will send a message in Slack using the Integry slack-post-message function.
```python
slack_post_message = await integry.functions.get("slack-post-message", user_id)
tools = [
slack_post_message.get_llamaindex_tool(FunctionTool.from_defaults, ToolMetadata, user_id)
]
agent = ReActAgent.from_tools(tools=tools, llm=llm, verbose=True)
```
## 4. **Connect Your Slack Account**
To allow the agent to send a message on Slack on your user's behalf, the user must connect their Slack account. To connect a Slack account against the provided user ID, execute the following snippet.
```python
slack = await integry.apps.get("slack", user_id)
print(slack.login_url)
```
This will print a URL which can be opened in a web browser to connect Slack.
## 5. Execute Agent
This will execute the agent and send a **Hello** message to the Slack channel.
```python
task = "Say hello to my team on slack in random channnel."
result = await agent.achat(task)
```
This will send the message to the slack channel. Here is reference image.
The message has been sent successfully in slack #random channel. You can verify the successful message delivery by checking the highlighted content in the response below.
> Running step db7c63d6-741c-4ecb-bae5-d1220531a8ed. Step input: Say hello to my team on slack in random channnel.
Thought: The current language of the user is English. I need to use a tool to help me post a message on Slack.
Action: slack-post-message
Action Input: {'channel': 'random', 'text': 'Hello team!'}
Observation: network_code=200 output={'ok': True, 'channel': 'C086HKZMTSS', 'ts': '1736428195.718639', 'message': {'user': 'U086GBQHLG0', 'type': 'message', 'ts': '1736428195.718639', 'bot_id': 'B086E311JTB', 'app_id': 'A6FQL4KQC', 'text': 'Hello team!', 'team': 'T086682UW57', 'bot_profile': {'id': 'B086E311JTB', 'app_id': 'A6FQL4KQC', 'name': 'Integry', 'icons': {'image_36': 'https://slack-files2.s3-us-west-2.amazonaws.com/avatars/2017-08-09/225182834294_8020ddc74d7822b48ea1_36.png', 'image_48': 'https://slack-files2.s3-us-west-2.amazonaws.com/avatars/2017-08-09/225182834294_8020ddc74d7822b48ea1_48.png', 'image_72': 'https://slack-files2.s3-us-west-2.amazonaws.com/avatars/2017-08-09/225182834294_8020ddc74d7822b48ea1_72.png'}, 'deleted': False, 'updated': 1734709233, 'team_id': 'T086682UW57'}, 'blocks': [{'type': 'rich_text', 'block_id': '+Q2I', 'elements': [{'type': 'rich_text_section', 'elements': [{'type': 'text', 'text': 'Hello team!'}]}]}]}}
> Running step 59722c62-8391-4ad3-9331-6fc1dff36822. Step input: None
Thought: I can answer without using any more tools. I'll use the user's language to answer.
Answer: I have successfully sent a "Hello team!" message to the random channel on Slack.
[^1]: This success response show's that message has been sent successfully in slack channel.
---
# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.integry.ai/functions/agent-frameworks/llamaindex.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.