feat(docs): add LlamaIndex integration documentation

docs/mint.json

@@ -106,6 +106,7 @@
         "v1/integrations/groq",
         "v1/integrations/haystack",
         "v1/integrations/langchain",
+        "v1/integrations/llamaindex",
         "v1/integrations/llama_stack",
         "v1/integrations/litellm",
         "v1/integrations/mistral",
@@ -174,6 +175,7 @@
         "v2/integrations/google_adk",
         "v2/integrations/google_generative_ai",
         "v2/integrations/langchain",
+        "v2/integrations/llamaindex",
         "v2/integrations/litellm",
         "v2/integrations/openai",
         "v2/integrations/agents_sdk",

docs/v1/integrations/llamaindex.mdx

@@ -0,0 +1,88 @@
+---
+title: 'LlamaIndex'
+description: 'AgentOps works seamlessly with LlamaIndex, a framework for building context-augmented generative AI applications with LLMs.'
+---
+
+import CodeTooltip from '/snippets/add-code-tooltip.mdx'
+import EnvTooltip from '/snippets/add-env-tooltip.mdx'
+
+[LlamaIndex](https://www.llamaindex.ai/) is a framework for building context-augmented generative AI applications with LLMs. AgentOps provides observability into your LlamaIndex applications through automatic instrumentation.
+
+<Steps>
+	<Step title="Install the AgentOps SDK">
+		<CodeGroup>
+			```bash pip 
+			pip install agentops
+			```
+			```bash poetry
+			poetry add agentops
+			```
+		</CodeGroup>
+	</Step>
+	<Step title="Install LlamaIndex AgentOps Instrumentation">
+		<CodeGroup>
+			```bash pip 
+			pip install llama-index-instrumentation-agentops
+			```
+			```bash poetry
+			poetry add llama-index-instrumentation-agentops
+			```
+		</CodeGroup>
+	</Step>
+	<Step title="Add 2 lines of code">
+		<CodeTooltip/>
+			<CodeGroup>
+				```python python
+				from llama_index.core import set_global_handler
+
+				# NOTE: Feel free to set your AgentOps environment variables (e.g., 'AGENTOPS_API_KEY')
+				# as outlined in the AgentOps documentation, or pass the equivalent keyword arguments
+				# anticipated by AgentOps' AOClient as **eval_params in set_global_handler.
+
+				set_global_handler("agentops")
+				```
+			</CodeGroup>
+		<EnvTooltip />
+      <CodeGroup>
+        ```python .env
+        AGENTOPS_API_KEY=<YOUR API KEY>
+        ```
+      </CodeGroup>
+      Read more about environment variables in [Advanced Configuration](/v1/usage/advanced-configuration)
+	</Step>
+	<Step title="Run your LlamaIndex application">
+		Execute your program and visit [app.agentops.ai/drilldown](https://app.agentops.ai/drilldown) to observe your LlamaIndex application! 🕵️
+		<Tip>
+			After your run, AgentOps prints a clickable url to console linking directly to your session in the Dashboard
+		</Tip> 
+		<div/>{/* Intentionally blank div for newline */}
+		<Frame type="glass" caption="Clickable link to session">
+			<img height="200" src="https://github.com/AgentOps-AI/agentops/blob/main/docs/images/link-to-session.gif?raw=true" />
+		</Frame>
+	</Step>
+</Steps>
+
+## Usage Pattern
+
+Here's a simple example of how to use AgentOps with LlamaIndex:
+
+```python
+from llama_index.core import set_global_handler
+import llama_index.core
+
+# Set the global handler to AgentOps
+set_global_handler("agentops")
+
+# Your LlamaIndex application code here
+# AgentOps will automatically track LLM calls and other operations
+```
+
+## Additional Resources
+
+For more detailed information about LlamaIndex's observability features and AgentOps integration, check out the [LlamaIndex documentation](https://docs.llamaindex.ai/en/stable/module_guides/observability/#agentops).
+
+<script type="module" src="/scripts/github_stars.js"></script>
+<script type="module" src="/scripts/scroll-img-fadein-animation.js"></script>
+<script type="module" src="/scripts/button_heartbeat_animation.js"></script>
+<script type="css" src="/styles/styles.css"></script>
+<script type="module" src="/scripts/adjust_api_dynamically.js"></script>

docs/v2/integrations/llamaindex.mdx

@@ -0,0 +1,79 @@
+---
+title: 'LlamaIndex'
+description: 'AgentOps works seamlessly with LlamaIndex, a framework for building context-augmented generative AI applications with LLMs.'
+---
+
+[LlamaIndex](https://www.llamaindex.ai/) is a framework for building context-augmented generative AI applications with LLMs. AgentOps provides comprehensive observability into your LlamaIndex applications through automatic instrumentation, allowing you to monitor LLM calls, track performance, and analyze your application's behavior.
+
+## Installation
+
+Install AgentOps and the LlamaIndex AgentOps instrumentation package:
+
+<CodeGroup>
+  ```bash pip
+  pip install agentops llama-index-instrumentation-agentops
+  ```
+  ```bash poetry
+  poetry add agentops llama-index-instrumentation-agentops
+  ```
+  ```bash uv
+  uv add agentops llama-index-instrumentation-agentops
+  ```
+</CodeGroup>
+
+## Setting Up API Keys
+
+You'll need an AgentOps API key from your [AgentOps Dashboard](https://app.agentops.ai/):
+
+<CodeGroup>
+  ```bash Export to CLI
+  export AGENTOPS_API_KEY="your_agentops_api_key_here"
+  ```
+  ```txt Set in .env file
+  AGENTOPS_API_KEY="your_agentops_api_key_here"
+  ```
+</CodeGroup>
+
+## Usage
+
+Simply set the global handler to "agentops" at the beginning of your LlamaIndex application. AgentOps will automatically instrument LlamaIndex to track your LLM interactions and application performance.
+
+```python
+from llama_index.core import set_global_handler
+from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
+
+# Set the global handler to AgentOps
+# NOTE: Feel free to set your AgentOps environment variables (e.g., 'AGENTOPS_API_KEY')
+# as outlined in the AgentOps documentation, or pass the equivalent keyword arguments
+# anticipated by AgentOps' AOClient as **eval_params in set_global_handler.
+set_global_handler("agentops")
+
+# Your LlamaIndex application code here
+documents = SimpleDirectoryReader("data").load_data()
+index = VectorStoreIndex.from_documents(documents)
+
+# Create a query engine
+query_engine = index.as_query_engine()
+
+# Query your data - AgentOps will automatically track this
+response = query_engine.query("What is the main topic of these documents?")
+print(response)
+```
+
+## What Gets Tracked
+
+When you use AgentOps with LlamaIndex, the following operations are automatically tracked:
+
+- **LLM Calls**: All interactions with language models including prompts, completions, and token usage
+- **Embeddings**: Vector embedding generation and retrieval operations
+- **Query Operations**: Search and retrieval operations on your indexes
+- **Performance Metrics**: Response times, token costs, and success/failure rates
+
+## Additional Resources
+
+For more detailed information about LlamaIndex's observability features and AgentOps integration, check out the [LlamaIndex documentation](https://docs.llamaindex.ai/en/stable/module_guides/observability/#agentops).
+
+<script type="module" src="/scripts/github_stars.js"></script>
+<script type="module" src="/scripts/scroll-img-fadein-animation.js"></script>
+<script type="module" src="/scripts/button_heartbeat_animation.js"></script>
+<script type="css" src="/styles/styles.css"></script>

examples/llamaindex_examples/README.md

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+# LlamaIndex AgentOps Integration Example
+
+This example demonstrates how to use AgentOps with LlamaIndex for observability and monitoring of your context-augmented generative AI applications.
+
+## Setup
+
+1. Install required packages:
+```bash
+pip install agentops llama-index-instrumentation-agentops llama-index python-dotenv
+```
+
+2. Set your API keys:
+```bash
+export AGENTOPS_API_KEY="your_agentops_api_key"
+export OPENAI_API_KEY="your_openai_api_key"
+```
+
+## Files
+
+- `llamaindex_example.py` - Python script example
+- `llamaindex_example.ipynb` - Jupyter notebook example
+
+## Usage
+
+Run the Python script:
+```bash
+python llamaindex_example.py
+```
+
+Or open and run the Jupyter notebook:
+```bash
+jupyter notebook llamaindex_example.ipynb
+```
+
+After running, check your AgentOps dashboard for the recorded session.