Nova AI Interface

What is Nova?

Nova is Camber’s AI interface and your primary way to interact with the CamberCloud platform. It turns natural language into actionable outputs like code, analysis, and visualizations, while coordinating specialized agents that can run tools, execute workflows, and launch high-performance compute.

Prerequisites: Active CamberCloud account with platform access. No coding experience required.

Core Capabilities

Below are Nova’s five primary capabilities. Click on any expandable section to see examples and detailed information.

1. Job Execution Management

Nova provides intelligent control over computational jobs:

• Natural language job control: Launch, monitor job status and progress, or cancel
• Batch operations: Simultaneous multi-job execution
• Smart resource optimization: Workload-based recommendations

2. File System Integration

Seamless interaction with CamberCloud’s distributed file system (Stash):

• File operations: Direct read/write and drag-and-drop uploads
• Smart management: Create, organize, and delete
• Automated processing: File format detection and data parsing

3. App Discovery and Execution

Intelligent application recommendation and deployment:

• Smart suggestions: Problem-based app recommendations
• Guided configuration: Parameter optimization and automatic setup
• Seamless execution: Direct launch from conversation
• Result analysis: Interpretation and next-step guidance

4. Integrated Coding Agent

Full-featured execution environment with:

• Intelligent code generation: Data analysis and visualization
• Resource-aware execution: Run on selected compute nodes
• Automated workflows: Pipelines with dependency management

5. Persistent Chat History and Artifacts

All interactions and generated content are automatically preserved:

• Chat history: Complete conversation continuity
• Artifact preservation in your Stash “chats” folder:
  • Generated code scripts
  • Data visualizations and plots
  • Analysis results and reports
  • Intermediate computational outputs

Getting Started

Access Nova through the CamberCloud platform interface. Simply type what you need in natural language, and Nova will guide you through the optimal workflow using CamberCloud’s resources.

Quick Start Examples

How to Talk to Nova

Nova understands natural language, but knowing how to communicate clearly will help you get better results faster.

Nova can interpret:

• Goals: What you want to accomplish
• Context: Your data, files, and previous work
• Constraints: Resource limits, time requirements, specific methods
• Preferences: Output formats, visualization styles, level of detail

Prompting Patterns

Goal-First Prompts — Start with what you want to achieve, then add details.

Analyze my sales data to find seasonal trends.
Use the sales_2024.csv file in my stash.
Create visualizations showing monthly patterns.

Specify Your Data — Tell Nova exactly where your data lives.

Using the protein.pdb file in stash://myusername/simulations/,
run a GROMACS energy minimization.

Request Specific Outputs — Be clear about what you want back.

Generate a summary report with:
- Key statistics (mean, median, std dev)
- A histogram of the distribution
- Top 10 outliers with explanations
Save everything to my stash.

Iterative Refinement — Build on previous results with follow-up questions.

# First prompt
Analyze gene expression data from rnaseq_results.csv

# Follow-up
Focus on genes with log2 fold change > 2

# Another follow-up
Create a volcano plot highlighting the significant genes

Common Scenarios

Data Analysis:

@nova What can you tell me about the dataset in
stash://myusername/data/experiment_results.csv?
I want to understand the distribution and identify any anomalies.

Running Applications:

@nova Run a variant calling pipeline on my FASTQ files
in stash://myusername/genomics/samples/.
Use the GRCh38 reference genome.

Job Management:

@nova What's the status of my running jobs?
Show me the logs for job 12345.

What Nova Can’t Do

• Access external systems not connected via Data Connectors
• Modify production databases without explicit confirmation
• Run indefinitely long computations (jobs have time limits)
• Access other users’ private data

Troubleshooting

Nova seems confused:

• Break your request into smaller steps
• Be more explicit about file paths and data sources
• Check that your data connectors are properly configured

Results aren’t what you expected:

• Ask Nova to explain its approach
• Provide more context about your domain
• Specify the exact method or algorithm you want

Jobs are failing:

• Ask Nova to check the job logs
• Verify your input files exist and are accessible
• Try a smaller test case first

Code Generation

Nova can generate Python code, create visualizations, and build data analysis scripts through natural language requests. Describe what you want to accomplish, and Nova generates executable code:

@nova Write a Python script that loads my CSV data,
calculates summary statistics, and creates a histogram

Nova generates the code, explains what it does, and can run it on CamberCloud compute resources.

Common Patterns

Data Analysis:

@nova Analyze the dataset in stash://myusername/data.csv
Show me correlations between all numeric columns

Visualization:

@nova Create a scatter plot of column A vs column B
from my experiment_results.csv file
Color points by the 'category' column

Data Processing:

@nova Write code to:
1. Load all CSV files from stash://myusername/raw_data/
2. Merge them on the 'sample_id' column
3. Filter rows where value > 100
4. Save the result to stash://myusername/processed/

Running Generated Code

Nova can execute generated code on CamberCloud compute nodes:

@nova Run this analysis on a SMALL node with GPU

Results and visualizations are saved to your Stash chats/ folder.

Best Practices

Be Specific — Instead of “Analyze my data”, try:

Analyze the RNA-seq counts in stash://myusername/rnaseq/counts.csv
Identify genes with log2 fold change > 2 and adjusted p-value < 0.05
Create a volcano plot highlighting significant genes

Provide Context — Tell Nova about your domain and goals:

I'm studying protein-ligand binding. Using the docking results
in stash://myusername/docking/, identify the top 10 compounds
by binding affinity and explain why they might be good candidates.

Iterate Progressively — Build on previous results:

# Start simple
@nova Show me the first 10 rows of my dataset

# Then refine
@nova Filter to only include samples from Group A

# Then analyze
@nova Calculate mean and standard deviation for each metric

Specify Resources — For compute-intensive tasks:

@nova Run this simulation on a MEDIUM node with GPU

Ask for Explanations:

@nova Explain your methodology for this analysis
@nova Why did you choose this statistical test?

Save Important Results:

@nova Save these results as a PDF report to my stash

Use Agents for Repeated Tasks — If you find yourself asking similar questions, create an AI Agent trained on your domain with a knowledge base of your protocols, and share it with your team.

Related Documentation

• Apps Catalog - Browse available applications
• Stash File System - Learn about file management
• Job Attributes Reference - Understand job configuration options
• AI Agents - Build custom domain experts

Ready to get started? Start a conversation with Nova today.