RAG with Built-in Tools
Create powerful AI agents that combine organizational knowledge with specialized tools like web browsing, image generation, and code interpretation
RAG (Retrieval Augmented Generation) agents with built-in tools represent the most powerful no-code agents available on the Prisme.ai platform. These agents combine access to your organization’s knowledge with specialized capabilities that extend beyond conversation, enabling them to perform complex tasks, access external information, generate media, and process data.
Understanding RAG + Tools Agents
These advanced agents integrate three key capabilities:
Foundation Models
Powerful language models providing reasoning and generation capabilities
Knowledge Retrieval
Access to your organization’s documents and information
Specialized Tools
Built-in capabilities that extend functionality beyond conversation
This combination creates versatile, capable agents that can:
- Answer questions using your internal knowledge
- Retrieve up-to-date information from the web
- Generate visual content based on requirements
- Perform data analysis and calculations
- Create structured documents and outputs
- Execute multi-step processes with diverse requirements
Available Built-in Tools
Prisme.ai provides several powerful tools that can be activated without writing code:
Description: Access current information from the internet using Serper integration
Key Capabilities:
- Search for current information beyond the model’s knowledge cutoff
- Access specific websites for reference
- Verify facts and retrieve up-to-date data
- Gather content from public sources
Best For:
- Research and information gathering
- Validating time-sensitive information
- Supplementing internal knowledge with public data
- Competitive research and market intelligence
Configuration Options:
- Search domains to include/exclude
- Number of results to retrieve
- Safe search settings
- Result depth control
Description: Access current information from the internet using Serper integration
Key Capabilities:
- Search for current information beyond the model’s knowledge cutoff
- Access specific websites for reference
- Verify facts and retrieve up-to-date data
- Gather content from public sources
Best For:
- Research and information gathering
- Validating time-sensitive information
- Supplementing internal knowledge with public data
- Competitive research and market intelligence
Configuration Options:
- Search domains to include/exclude
- Number of results to retrieve
- Safe search settings
- Result depth control
Description: Create images based on text descriptions
Key Capabilities:
- Generate custom images from textual descriptions
- Create visual content in various styles
- Produce illustrations, diagrams, and visualizations
- Export in multiple formats and resolutions
Best For:
- Content creation and marketing
- Visual explanations and instructions
- Concept visualization
- Custom illustrations for documentation
Configuration Options:
- Image style and aesthetic
- Resolution settings
- Content safety filters
- Visual style guidelines
Description: Run code to perform calculations, data analysis, and visualizations
Key Capabilities:
- Execute Python code in a secure environment
- Perform complex calculations and data analysis
- Generate charts, graphs, and visualizations
- Process and transform structured data
Best For:
- Data analysis and reporting
- Scientific and mathematical calculations
- Visual data presentation
- Custom data transformations
Configuration Options:
- Available libraries and packages
- Execution time limits
- Memory allocation
- File handling permissions
When to Use RAG + Tools Agents
These advanced agents are ideal for scenarios that require a combination of:
Knowledge Access
Situations requiring specific organizational information
Current Information
Needs for up-to-date data beyond internal documentation
Visual Content
Requirements for custom images or visualizations
Data Processing
Calculations, analysis, or data transformation tasks
Multi-capability Workflows
Processes that combine different types of tasks
Complex Problem Solving
Scenarios requiring multiple approaches and resources
Example Use Cases
Purpose: Help users research topics by combining internal knowledge with current information and analysis.
Tool Utilization:
- Retrieves relevant internal research and documentation
- Searches the web for current information and trends
- Generates data visualizations to compare findings
- Creates structured research summaries
Example Interaction:
Purpose: Help users research topics by combining internal knowledge with current information and analysis.
Tool Utilization:
- Retrieves relevant internal research and documentation
- Searches the web for current information and trends
- Generates data visualizations to compare findings
- Creates structured research summaries
Example Interaction:
Purpose: Provide advanced technical assistance by combining product documentation with analytical capabilities.
Tool Utilization:
- Retrieves relevant product documentation and troubleshooting guides
- Generates diagrams to explain technical concepts
- Runs code to demonstrate solutions or analyze logs
- Searches for updates or known issues
Example Interaction:
Purpose: Assist in creating rich content by combining knowledge, research, and media generation.
Tool Utilization:
- Retrieves brand guidelines and existing content
- Searches for current trends and information
- Generates custom images and visualizations
- Analyzes content performance data
Example Interaction:
Purpose: Help analyze financial data by combining documentation, calculations, and visualizations.
Tool Utilization:
- Retrieves financial policies and procedures
- Runs calculations on financial data
- Creates visual representations of financial trends
- Searches for market benchmarks and comparisons
Example Interaction:
Creating RAG + Tools Agents
Building these advanced agents involves a structured process:
Define Agent Purpose and Requirements
Clearly specify what your agent needs to accomplish.
Key considerations:
- Primary use cases and scenarios
- Required knowledge sources
- Necessary tools and capabilities
- User expectations and needs
- Success criteria and metrics
Prepare Knowledge Resources
Assemble and organize the information your agent needs.
Activities include:
- Document collection and curation
- Content organization and structuring
- Metadata creation for improved retrieval
- Validation of information accuracy
- Knowledge base configuration
Select and Configure Tools
Determine which built-in tools your agent requires.
For each tool:
- Enable required capabilities
- Configure settings and parameters
- Define usage boundaries and limitations
- Set up authentication if required
- Test individual tool functionality
Create System Instructions
Develop comprehensive guidance for your agent.
Key components:
- Agent role and purpose definition
- Knowledge utilization guidelines
- Tool selection and usage criteria
- Response formatting requirements
- Error handling and limitations
Develop Tool Usage Instructions
Provide specific guidance for when and how to use each tool.
Include for each tool:
- When to use (clear criteria)
- How to use effectively
- Result interpretation guidance
- Error handling approaches
- User communication during tool use
Test and Refine
Validate and iteratively improve your agent.
Testing approach:
- Scenario-based evaluation
- Tool usage verification
- Knowledge retrieval assessment
- Edge case testing
- Real user feedback collection
Implementation in AI Knowledge
Creating a RAG + Tools agent in Prisme.ai’s AI Knowledge is straightforward:
Start by creating a new agent in the AI Store.
Steps:
- Navigate to AI Knowledge
- Click “Create New Agent”
- Provide name and basic description
Start by creating a new agent in the AI Store.
Steps:
- Navigate to AI Knowledge
- Click “Create New Agent”
- Provide name and basic description
Link your agent to relevant knowledge sources.
Configuration options:
- Select existing knowledge bases
- Configure retrieval settings
- Set relevance thresholds
- Configure enhance User Query and Post Query if needed
Activate and configure the tools your agent needs.
For each tool:
- Toggle tool activation
- Configure enabling manual tool selection
- Test individual functionality
Define comprehensive guidance for your agent.
Key elements to include:
- Agent purpose and identity
- Knowledge base usage guidelines
- Tool selection criteria
- Response formatting requirements
- Error handling procedures
- Limitations and constraints
Validate and make your agent available to users.
Final steps:
- Run comprehensive tests via Auto Test Feature
- Make adjustments based on results
- Define access permissions
- Publish to intended audience
- Set up monitoring and feedback collection
Tool-Specific Instructions
To maximize the effectiveness of each built-in tool, include specific guidance in your system instructions:
Web Browsing Tool Instructions
Web Browsing Tool Instructions
When to Use:
How to Use Effectively:
Example Prompt Section:
Image Generation Tool Instructions
Image Generation Tool Instructions
When to Use:
How to Use Effectively:
Example Prompt Section:
Code Interpreter Tool Instructions
Code Interpreter Tool Instructions
When to Use:
How to Use Effectively:
Example Prompt Section:
Best Practices for RAG + Tools Agents
Clear Tool Selection Logic
Provide explicit criteria for when to use each tool
Example:
User Communication During Tool Use
Keep users informed about tool usage and processes
Example:
Integrate Knowledge and Tool Outputs
Combine information from different sources coherently
Example:
Handle Tool Failures Gracefully
Provide alternative approaches when tools don’t work as expected
Example:
Troubleshooting Common Issues
Knowledge Retrieval Problems
Knowledge Retrieval Problems
Symptoms:
- Agent fails to find relevant information
- Responses ignore available knowledge
- Retrieved information is incorrect or outdated
Solutions:
- Verify knowledge base configuration and content
- Improve document chunking and organization
- Enhance retrieval instructions in system prompt
- Add more specific examples of knowledge utilization
- Test with focused queries to validate retrieval
Inappropriate Tool Selection
Inappropriate Tool Selection
Symptoms:
- Agent uses tools when unnecessary
- Agent fails to use tools when needed
- Consistent selection of suboptimal tools
Solutions:
- Refine tool selection criteria in system instructions
- Provide explicit examples of when to use each tool
- Add clear guidance for choosing between similar tools
- Include decision tree for tool selection logic
- Test with scenarios that require tool selection decisions
Poor Tool Usage
Poor Tool Usage
Symptoms:
- Ineffective web searches returning irrelevant results
- Low-quality image generation
- Code that errors or produces incorrect results
Solutions:
- Improve tool-specific instructions and examples
- Add more detailed guidance on effective tool usage
- Provide templates for common tool operations
- Include error handling instructions for each tool
- Test each tool independently with focused scenarios
Response Integration Issues
Response Integration Issues
Symptoms:
- Disjointed responses that fail to synthesize information
- Tool outputs presented without context or interpretation
- Failure to connect retrieved knowledge with tool results
Solutions:
- Enhance instructions for information synthesis
- Add examples of well-integrated responses
- Include specific guidance on combining knowledge and tool outputs
- Provide templates for presenting multi-source information
- Test with scenarios requiring information integration
Performance Issues
Performance Issues
Symptoms:
- Slow response times
- Tool execution timeouts
- Memory errors during complex operations
Solutions:
- Optimize tool usage guidelines for efficiency
- Add instructions for breaking complex tasks into manageable steps
- Provide fallback options for resource-intensive operations
- Include guidelines for managing large datasets
- Test with progressively complex scenarios to identify limits
Advanced Configuration Techniques
For organizations seeking to maximize the effectiveness of their RAG + Tools agents, consider these advanced approaches:
Tool Chaining
Configure agents to use tools in sequence for complex workflows
Implementation:
Tool chaining enables sophisticated multi-step processes that combine different capabilities.
Contextual Tool Configuration
Adapt tool behavior based on user type or request context
Implementation:
Contextual configuration improves relevance for different user groups.
Hybrid Knowledge Approach
Strategically combine internal knowledge with web information
Implementation:
This approach ensures accurate internal information while benefiting from external context.
Progressive Disclosure
Structure responses to present essential information first
Implementation:
Progressive disclosure improves usability by preventing information overload.
Enterprise Integration Considerations
Governance and Compliance
Governance and Compliance
When deploying RAG + Tools agents in enterprise environments, consider:
- Usage Policies: Define clear guidelines for appropriate tool usage
- Content Review: Establish processes for reviewing agent outputs
- Audit Trails: Implement logging for tool usage and information sources
- Access Controls: Limit specific tools to appropriate user groups
- Compliance Checks: Ensure tool outputs meet regulatory requirements
Implementation Example:
Security Considerations
Security Considerations
Protect sensitive information when using tools:
- Data Handling: Establish clear rules for handling sensitive information
- Tool Boundaries: Define what data can be processed by each tool
- Output Scrubbing: Implement checks for sensitive information in outputs
- Authentication: Manage service credentials securely
- User Permissions: Align tool access with user authorization levels
Implementation Example:
Scalability Planning
Scalability Planning
Prepare for widespread adoption and usage:
- Resource Management: Monitor and optimize tool usage patterns
- Usage Quotas: Implement appropriate limits for resource-intensive tools
- Caching Strategies: Cache common tool results when appropriate
- Load Balancing: Distribute tool processing across resources
- Performance Monitoring: Track response times and resource utilization
Implementation Example:
Next Steps
Ready to create your own RAG + Tools agent? Continue with these resources: