Setting Up Callbackmanager in LlamaIndex for Advanced Workflow

What is CallbackManager?

• Debugging: Quick checks on how your workflow performs.
• Insight Tracking: Measure the effectiveness of tasks or queries.
• Performance Optimization: Quickly identify bottlenecks.

Major Features of CallbackManager

• Event Tracking: Keep a close eye on events happening within your pipeline, be it querying, synthesizing, or chunking processes.
• Latency Measurement: Assess how long each step takes, offering insights on potential areas for improvement.
• Custom Callbacks: Integrate third-party tools and services for enhanced functionality.

Setting Up Your CallbackManager in LlamaIndex

Step 1: Install Necessary Packages

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pip install llama-index
pip install llama-index-callbacks-aim

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from llama_index.core.callbacks import CallbackManager
from llama_index.callbacks.aim import AimCallback

Step 2: Initialize AimCallback

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aim_callback = AimCallback(repo="./")  # Specify your repo path
callback_manager = CallbackManager([aim_callback])

Step 3: Integrate CallbackManager into Your Workflow

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from llama_index.core import SummaryIndex, SimpleDirectoryReader

docs = SimpleDirectoryReader('./data').load_data()  # Load your data
index = SummaryIndex.from_documents(docs, callback_manager=callback_manager)
query_engine = index.as_query_engine()  # Prepare your query engine

Step 4: Utilize the CallbackManager to Query Data

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response = query_engine.query("What are the key insights from the document?")
print(response)

Step 5: Analyzing the Data Logged with Aim

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aim up

Observability Options to Consider

• CHUNKING: Logs text splitting processes.
• NODE_PARSING: Logs how documents are parsed into nodes.
• EMBEDDING: Logs texts embedded.
• LLM: Logs responses from your LLM queries.
• QUERY: Keeps track of the query start and end times.
• RETRIEVE: Tracks nodes retrieved based on queries.
• SYNTHESIZE: Logs the execution of synthesize calls.

Best Practices

1. Understand and Leverage Events: Knowing the event types available makes a big difference in effectively tracking your workflows. Utilize events that matter to your data handling.
2. Measure Latency: Always measure how much time each task takes—you’d be surprised where delays can arise!
3. Debugging: Use debug handlers (like the provided
   1 LlamaDebugHandler
   ) to track down errors and ensure every piece of your workflow is functioning optimally.
4. Use Aim for Observability: Aim is a powerful observability solution! Ensure logging is set up clearly so you can analyze events effectively.
5. Testing: Make sure to continuously test your workflows with various datasets and inputs to ensure robustness.

Troubleshooting Common Issues

• Callback Not Working: Ensure that your CallbackManager is correctly instantiated and passed through to your processes.
• Missing Logs: Double-check that you’ve configured your logging correctly and that events are being called.
• Latency Looks Off: Use precise timing methods on your tasks to see where the problem might be occurring. Sometimes network latency can appear worse than it is if incorrect time tracking is applied.

Why LlamaIndex and Arsturn Go Hand-in-Hand

Benefits of Using Arsturn:

• No-Code Chatbot Builder: Implementing a custom conversational AI chatbot with your data is just a breeze, saving both time and costs.
• Efficient Engagement: Fellow brands are already enjoying higher conversions and deeper audience connections thanks to having a responsive chatbot!
• Analytics at Your Fingertips: Glean valuable insights about your audience’s interests and refine your strategy accordingly.
• Multi-Language Support: Support for around 95 languages means you can cater to a wide audience seamlessly!

Get Started with Arsturn Today!

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