RAG Configuration (rag.yaml)

Configure Retrieval-Augmented Generation (RAG) to enhance UFO² with external knowledge sources, online search, experience learning, and demonstration-based learning.

Overview

The rag.yaml file configures knowledge retrieval systems that augment UFO²'s capabilities beyond its base LLM knowledge. RAG helps UFO² make better decisions by providing:

Offline Documentation: Application manuals and documentation
Online Search: Real-time web search via Bing
Experience Learning: Learn from past successful executions
Demonstration Learning: Learn from user demonstrations

File Location: config/ufo/rag.yaml

Optional Configuration: RAG features are optional. UFO² works without them, but they can significantly improve performance on complex or domain-specific tasks.

Quick Start

Disable All RAG (Default)

# Minimal configuration - no external knowledge
RAG_OFFLINE_DOCS: False
RAG_ONLINE_SEARCH: False
RAG_EXPERIENCE: False
RAG_DEMONSTRATION: False

Enable Online Search Only

# Most useful for general tasks
RAG_OFFLINE_DOCS: False

RAG_ONLINE_SEARCH: True
BING_API_KEY: "YOUR_BING_API_KEY_HERE"
RAG_ONLINE_SEARCH_TOPK: 5
RAG_ONLINE_RETRIEVED_TOPK: 5

RAG_EXPERIENCE: False
RAG_DEMONSTRATION: False

Enable Experience Learning

# Learn from past executions
RAG_OFFLINE_DOCS: False
RAG_ONLINE_SEARCH: False

RAG_EXPERIENCE: True
RAG_EXPERIENCE_RETRIEVED_TOPK: 5

RAG_DEMONSTRATION: False

Enable All Features

# Maximum knowledge augmentation
RAG_OFFLINE_DOCS: True
RAG_OFFLINE_DOCS_RETRIEVED_TOPK: 1

RAG_ONLINE_SEARCH: True
BING_API_KEY: "YOUR_BING_API_KEY_HERE"
RAG_ONLINE_SEARCH_TOPK: 5
RAG_ONLINE_RETRIEVED_TOPK: 5

RAG_EXPERIENCE: True
RAG_EXPERIENCE_RETRIEVED_TOPK: 5

RAG_DEMONSTRATION: True
RAG_DEMONSTRATION_RETRIEVED_TOPK: 5

RAG Components

1. Offline Documentation

Retrieve relevant documentation from local knowledge bases (app manuals, guides, API docs).

Field	Type	Default	Description
`RAG_OFFLINE_DOCS`	Boolean	`False`	Enable offline documentation retrieval
`RAG_OFFLINE_DOCS_RETRIEVED_TOPK`	Integer	`1`	Number of documents to retrieve

Example:

RAG_OFFLINE_DOCS: True
RAG_OFFLINE_DOCS_RETRIEVED_TOPK: 1

!!!info "Use Case" - Application-specific tasks (Excel formulas, Word formatting) - Domain-specific workflows (accounting, design) - Requires pre-indexed documentation

Setup:

Place documentation in vectordb/docs/
Index documents: python -m learner
Enable in rag.yaml

2. Online Search

Search the web in real-time using Bing Search API.

Field	Type	Default	Description
`RAG_ONLINE_SEARCH`	Boolean	`False`	Enable online Bing search
`BING_API_KEY`	String	`""`	Bing Search API key
`RAG_ONLINE_SEARCH_TOPK`	Integer	`5`	Number of search results to fetch
`RAG_ONLINE_RETRIEVED_TOPK`	Integer	`5`	Number of results to include in prompt

Example:

RAG_ONLINE_SEARCH: True
BING_API_KEY: "abc123xyz..."
RAG_ONLINE_SEARCH_TOPK: 5
RAG_ONLINE_RETRIEVED_TOPK: 5

!!!tip "Getting Bing API Key" 1. Go to Azure Portal 2. Create a "Bing Search v7" resource 3. Copy the API key from "Keys and Endpoint" 4. Add to rag.yaml: BING_API_KEY: "your-key"

Use Cases:

Tasks requiring current information
Unfamiliar applications or features
Troubleshooting specific error messages
Finding how-to guides dynamically

Example Query Flow:

User Request: "Create a pivot table in Excel"
↓
Bing Search: "how to create pivot table in Excel"
↓
Retrieved: Top 5 results about pivot tables
↓
LLM receives context from search results
↓
Better action decisions

3. Experience Learning

Learn from UFO²'s own past successful task executions.

Field	Type	Default	Description
`RAG_EXPERIENCE`	Boolean	`False`	Enable experience learning
`RAG_EXPERIENCE_RETRIEVED_TOPK`	Integer	`5`	Number of past experiences to retrieve
`EXPERIENCE_SAVED_PATH`	String	Auto-generated	Path to experience database
`EXPERIENCE_PROMPT`	String	Auto-generated	Experience prompt template

Example:

RAG_EXPERIENCE: True
RAG_EXPERIENCE_RETRIEVED_TOPK: 5

!!!info "How It Works" 1. UFO² completes a task successfully 2. Task steps are saved to experience database 3. For future similar tasks, relevant past experiences are retrieved 4. LLM learns from successful patterns

Use Cases:

Repetitive tasks with slight variations
Learning organizational-specific workflows
Improving over time on common tasks

Example:

First Time: "Create a monthly sales report"
→ Task succeeds, 15 steps recorded

Second Time: "Create a quarterly sales report"
→ Retrieves "monthly report" experience
→ Adapts the pattern, faster execution

Default Paths:

# Auto-generated if not specified
EXPERIENCE_SAVED_PATH: "vectordb/experience"
EXPERIENCE_PROMPT: "ufo/prompts/share/experience/experience.yaml"

4. Demonstration Learning

Learn from user demonstrations (you show UFO² how to do a task).

Field	Type	Default	Description
`RAG_DEMONSTRATION`	Boolean	`False`	Enable demonstration learning
`RAG_DEMONSTRATION_RETRIEVED_TOPK`	Integer	`5`	Number of demonstrations to retrieve
`DEMONSTRATION_SAVED_PATH`	String	Auto-generated	Path to demonstration database
`DEMONSTRATION_PROMPT`	String	Auto-generated	Demonstration prompt template

Example:

RAG_DEMONSTRATION: True
RAG_DEMONSTRATION_RETRIEVED_TOPK: 5

!!!info "How It Works" 1. User demonstrates a task (UFO² records it) 2. Demonstration is saved with annotations 3. For similar future tasks, demonstrations are retrieved 4. LLM mimics the demonstrated behavior

Use Cases:

Complex, domain-specific workflows
Organizational-specific procedures
Tasks with many edge cases

Workflow:

1. Record Demonstration:
   python -m ufo --mode demonstration
   → Perform task manually
   → UFO² records your actions

2. Save Demonstration:
   → Stored in vectordb/demonstration/

3. Future Task:
   "Do the same report formatting"
   → Retrieves your demonstration
   → Replicates your steps

Default Paths:

# Auto-generated if not specified
DEMONSTRATION_SAVED_PATH: "vectordb/demonstration"
DEMONSTRATION_PROMPT: "ufo/prompts/share/demonstration/demonstration.yaml"

Complete Configuration Examples

Minimal (No RAG)

# config/ufo/rag.yaml
RAG_OFFLINE_DOCS: False
RAG_ONLINE_SEARCH: False
RAG_EXPERIENCE: False
RAG_DEMONSTRATION: False

Online Search Only

RAG_OFFLINE_DOCS: False

RAG_ONLINE_SEARCH: True
BING_API_KEY: "your-bing-api-key-here"
RAG_ONLINE_SEARCH_TOPK: 5
RAG_ONLINE_RETRIEVED_TOPK: 5

RAG_EXPERIENCE: False
RAG_DEMONSTRATION: False

Experience Learning Only

RAG_OFFLINE_DOCS: False
RAG_ONLINE_SEARCH: False

RAG_EXPERIENCE: True
RAG_EXPERIENCE_RETRIEVED_TOPK: 5
EXPERIENCE_SAVED_PATH: "vectordb/experience"
EXPERIENCE_PROMPT: "ufo/prompts/share/experience/experience.yaml"

RAG_DEMONSTRATION: False

Full RAG Setup

# Offline docs
RAG_OFFLINE_DOCS: True
RAG_OFFLINE_DOCS_RETRIEVED_TOPK: 1

# Online search
RAG_ONLINE_SEARCH: True
BING_API_KEY: "your-bing-api-key"
RAG_ONLINE_SEARCH_TOPK: 5
RAG_ONLINE_RETRIEVED_TOPK: 5

# Experience
RAG_EXPERIENCE: True
RAG_EXPERIENCE_RETRIEVED_TOPK: 5
EXPERIENCE_SAVED_PATH: "vectordb/experience"
EXPERIENCE_PROMPT: "ufo/prompts/share/experience/experience.yaml"

# Demonstration
RAG_DEMONSTRATION: True
RAG_DEMONSTRATION_RETRIEVED_TOPK: 5
DEMONSTRATION_SAVED_PATH: "vectordb/demonstration"
DEMONSTRATION_PROMPT: "ufo/prompts/share/demonstration/demonstration.yaml"

Setting Up Each RAG Component

Setup: Offline Documentation

Step 1: Prepare documentation

# Place docs in vectordb/docs/
New-Item -ItemType Directory -Path "vectordb\docs\excel" -Force
Copy-Item "C:\path\to\excel_guide.pdf" "vectordb\docs\excel\"

Step 2: Index documents

python -m learner --index-docs

Step 3: Enable in config

RAG_OFFLINE_DOCS: True
RAG_OFFLINE_DOCS_RETRIEVED_TOPK: 1

Setup: Online Search

Step 1: Get Bing API key

Go to Azure Portal
Create resource → Search for "Bing Search v7"
Create the resource
Go to "Keys and Endpoint"
Copy Key 1

Step 2: Add to config

RAG_ONLINE_SEARCH: True
BING_API_KEY: "your-copied-key-here"
RAG_ONLINE_SEARCH_TOPK: 5
RAG_ONLINE_RETRIEVED_TOPK: 5

Step 3: Test

from config.config_loader import get_ufo_config

config = get_ufo_config()
print(f"Bing search enabled: {config.rag.online_search}")
print(f"API key set: {bool(config.rag.BING_API_KEY)}")

Setup: Experience Learning

Step 1: Enable in config

RAG_EXPERIENCE: True
RAG_EXPERIENCE_RETRIEVED_TOPK: 5

Step 2: Run tasks normally

python -m ufo --request "Create a sales report"

Step 3: Successful tasks are auto-saved

Experience saved to: vectordb/experience/

Step 4: Future tasks retrieve experiences

# Similar task will use past experience
python -m ufo --request "Create a quarterly report"

Setup: Demonstration Learning

Step 1: Record demonstration

python -m ufo --mode demonstration --task "format_monthly_report"

Step 2: Perform task manually

UFO² records your every action
Add annotations/comments

Step 3: Save demonstration

Demonstration saved to: vectordb/demonstration/

Step 4: Enable in config

RAG_DEMONSTRATION: True
RAG_DEMONSTRATION_RETRIEVED_TOPK: 5

Step 5: Use demonstrations

python -m ufo --request "Format the report like I showed you"

Programmatic Access

from config.config_loader import get_ufo_config

config = get_ufo_config()

# Check RAG settings
if config.rag.online_search:
    print(f"Online search enabled")
    print(f"Top K: {config.rag.online_search_topk}")
    
if config.rag.experience:
    print(f"Experience learning enabled")
    print(f"Experience path: {config.rag.EXPERIENCE_SAVED_PATH}")

if config.rag.offline_docs:
    print(f"Offline docs enabled")

# Access specific fields
bing_key = config.rag.BING_API_KEY
exp_topk = config.rag.experience_retrieved_topk

Performance Considerations

Impact on Speed

RAG Type	Speed Impact	When to Use
Offline Docs	Low	Always (if indexed)
Online Search	Medium	For unfamiliar tasks
Experience	Low	Always (improves over time)
Demonstration	Low	For specific workflows

Impact on Cost

RAG Type	Cost Impact	Notes
Offline Docs	None	One-time indexing cost
Online Search	Low	Bing API: ~$3/1000 queries
Experience	None	Free storage
Demonstration	None	Free storage

!!!tip "Recommended Configuration" For most users: yaml RAG_ONLINE_SEARCH: True # Useful for general tasks RAG_EXPERIENCE: True # Improves over time RAG_OFFLINE_DOCS: False # Unless you have specific docs RAG_DEMONSTRATION: False # Unless training specific workflows

Troubleshooting

Issue 1: Bing Search Not Working

!!!bug "Error Message" BingSearchError: Invalid API key

**Solutions**:
1. Verify API key is correct
2. Check key has not expired
3. Ensure Bing Search v7 resource is active
4. Check Azure subscription is active

Issue 2: Experience Not Retrieved

!!!bug "Symptom" UFO² doesn't seem to learn from past tasks

**Solutions**:
1. Check experience database exists:
   ```powershell
   Test-Path "vectordb\experience"
   ```
2. Verify tasks completed successfully
3. Check similarity threshold (may be too strict)
4. Increase `RAG_EXPERIENCE_RETRIEVED_TOPK`

Issue 3: Offline Docs Not Indexed

!!!bug "Error Message" No offline documents found

**Solutions**:
1. Run indexing:
   ```powershell
   python -m learner --index-docs
   ```
2. Check documents are in `vectordb/docs/`
3. Verify supported formats (PDF, TXT, MD)

Issue 4: Too Much Context

!!!bug "Symptom" Token limits exceeded, slow responses

**Solution**: Reduce Top-K values
```yaml
RAG_ONLINE_RETRIEVED_TOPK: 3  # Instead of 5
RAG_EXPERIENCE_RETRIEVED_TOPK: 3
RAG_DEMONSTRATION_RETRIEVED_TOPK: 3
```

Best Practices

When to Enable Each Component

Scenario	Recommended RAG
General automation	Online Search
Repetitive tasks	Experience Learning
Domain-specific workflows	Offline Docs + Demonstration
Learning over time	Experience
New to UFO²	Online Search only
Production deployment	Experience + Offline Docs

Top-K Selection

Field	Recommended Range	Notes
`RAG_ONLINE_SEARCH_TOPK`	3-10	More = better context, slower
`RAG_ONLINE_RETRIEVED_TOPK`	3-5	Balance quality vs tokens
`RAG_EXPERIENCE_RETRIEVED_TOPK`	3-5	Most relevant experiences
`RAG_DEMONSTRATION_RETRIEVED_TOPK`	1-3	Usually need few examples
`RAG_OFFLINE_DOCS_RETRIEVED_TOPK`	1-2	Docs are usually long

Environment Variables

Store API keys securely:

# Use environment variable instead of hardcoded key
BING_API_KEY: "${BING_API_KEY}"

Set environment variable:

Windows PowerShell:

$env:BING_API_KEY = "your-key-here"

Windows (Persistent):

[System.Environment]::SetEnvironmentVariable('BING_API_KEY', 'your-key', 'User')

Summary

!!!success "Key Takeaways" ✅ RAG is optional - UFO² works without it
✅ Online Search - Most useful for general tasks (needs Bing API key)
✅ Experience - Free, improves over time automatically
✅ Offline Docs - Great for domain-specific knowledge
✅ Demonstration - Best for complex, specific workflows
✅ Start simple - Enable Online Search first, add others as needed

**Enhance UFO² with knowledge retrieval!** 🧠

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

RAG Configuration (rag.yaml)

Overview

Quick Start

Disable All RAG (Default)

Enable Online Search Only

Enable Experience Learning

Enable All Features

RAG Components

1. Offline Documentation

2. Online Search

3. Experience Learning

4. Demonstration Learning

Complete Configuration Examples

Minimal (No RAG)

Online Search Only

Experience Learning Only

Full RAG Setup

Setting Up Each RAG Component

Setup: Offline Documentation

Setup: Online Search

Setup: Experience Learning

Setup: Demonstration Learning

Programmatic Access

Performance Considerations

Impact on Speed

Impact on Cost

Troubleshooting

Issue 1: Bing Search Not Working

Issue 2: Experience Not Retrieved

Issue 3: Offline Docs Not Indexed

Issue 4: Too Much Context

Best Practices

When to Enable Each Component

Top-K Selection

Environment Variables

Related Documentation

Summary

FilesExpand file tree

rag_config.md

Latest commit

History

rag_config.md

File metadata and controls

RAG Configuration (rag.yaml)

Overview

Quick Start

Disable All RAG (Default)

Enable Online Search Only

Enable Experience Learning

Enable All Features

RAG Components

1. Offline Documentation

2. Online Search

3. Experience Learning

4. Demonstration Learning

Complete Configuration Examples

Minimal (No RAG)

Online Search Only

Experience Learning Only

Full RAG Setup

Setting Up Each RAG Component

Setup: Offline Documentation

Setup: Online Search

Setup: Experience Learning

Setup: Demonstration Learning

Programmatic Access

Performance Considerations

Impact on Speed

Impact on Cost

Troubleshooting

Issue 1: Bing Search Not Working

Issue 2: Experience Not Retrieved

Issue 3: Offline Docs Not Indexed

Issue 4: Too Much Context

Best Practices

When to Enable Each Component

Top-K Selection

Environment Variables

Related Documentation

Summary