Discover Connected Crimes with Web Search

Overview

In Exercise 05, you learned to search internal documents using the Grounding Service. Your Evidence Analyst can now retrieve factual evidence from security logs, bank records, and termination letters without hallucination.

But investigations don't happen in a vacuum. What if similar crimes happened elsewhere? What if your suspects have public criminal records? What if this heist is part of a larger criminal network?

In this exercise, you'll add web search capabilities using Perplexity's sonar-pro model to gather external intelligence and discover patterns across the internet.

Understand Web Search with Sonar-Pro

Why Do We Need Web Search?

Your current investigation system is powerful but limited to internal data:

What You Can Do Now	What You Can't Do Yet
✅ Search museum's internal evidence documents	❌ Search public criminal databases
✅ Retrieve bank records, security logs	❌ Find similar crimes in other cities
✅ Analyze suspects based on internal evidence	❌ Check if suspects have public criminal records
✅ Ground responses in factual documents	❌ Discover criminal network connections
✅ Avoid hallucination for internal data	❌ Monitor online art markets for stolen items

The Problem: Real investigations combine internal evidence (what happened here) with external intelligence (what's happening elsewhere). Your agents need both!

Document Grounding vs. Web Search

You now have access to two complementary search capabilities:

Aspect	Document Grounding (Exercise 05)	Web Search (This Exercise)
Data Source	Internal documents (pre-uploaded)	Real-time web information
Coverage	Organization-specific evidence	Global public information
Freshness	Historical documents (static)	Current information (updated constantly)
Use Cases	Internal logs, private records, policies	News, criminal records, pattern analysis
Search Method	Vector similarity (semantic)	Web search + LLM synthesis
Source Control	You control what documents exist	Public internet (no control)
Tool	`call_grounding_service`	`call_sonar_pro_search`
Privacy	Private, secure	Public information only
When to Use	"What does our evidence say?"	"What do public records show?"

🎯 Key Insight: These are not alternatives — they work together! The best investigations use both internal evidence AND external intelligence.

What is Sonar-Pro?

Sonar-Pro is Perplexity's AI model with built-in web search capabilities. Unlike regular LLMs:

Regular LLM (e.g., GPT-4, Claude)	Sonar-Pro (Perplexity)
Knowledge cutoff (training data only)	Real-time web search
Can't access recent events	Finds current information
No source verification	Returns citations with URLs
"I think..." or "Based on my training"	"According to [source], dated [date]"
Static knowledge	Dynamic, up-to-date intelligence

How Sonar-Pro Works:

Your Query → Sonar-Pro searches web → Retrieves relevant pages → 
Synthesizes answer → Returns result with source citations

Example:

Query: "Marcus Chen security technician criminal record"
Sonar-Pro: Searches news articles, court records, public databases
Returns: "According to [police-records.gov], Marcus Chen was charged with unauthorized access in 2022. Source: https://..."

How Sonar-Pro Integrates with SAP AI Core

Sonar-Pro is called as a model through SAP's orchestration service, just like GPT-4 or Claude:

from litellm import completion

response = completion(
    model="sap/sonar-pro",  # Perplexity via SAP orchestration
    messages=[
        {"role": "system", "content": "Search for factual information"},
        {"role": "user", "content": "Your search query"}
    ]
)

Key Differences:

sap/gpt-4o → Regular reasoning LLM
sap/sonar-pro → Web search-enabled LLM
Both use the same completion() API!

Add The Web Search Tool

Step 1: Create the Sonar-Pro Search Tool

You'll create a tool that enables your agents to search the web for criminal patterns, suspect backgrounds, and related incidents.

👉 Open /project/Python/starter-project/investigator_crew.py

👉 Add this tool after the call_grounding_service tool (around line 50):

@tool("call_sonar_pro_search")
def call_sonar_pro_search(search_query: str) -> str:
    """Search the web using Perplexity's sonar-pro model for real-time information 
    about crimes, suspects, and criminal patterns. Use this to find similar incidents, 
    criminal networks, public records, or patterns that are not in internal documents.
    
    Args:
        search_query: The search query about crimes, suspects, or criminal patterns
    
    Returns:
        Search results with source citations from the web
    """
    from litellm import completion
    
    try:
        response = completion(
            model="sap/sonar-pro",  # Perplexity model with web search
            messages=[
                {
                    "role": "system",
                    "content": "You are a web search assistant specializing in criminal intelligence. Search for accurate, recent information and always provide source citations with URLs and dates."
                },
                {
                    "role": "user", 
                    "content": search_query
                }
            ],
            temperature=0.2,  # Lower temperature for factual search
        )
        
        result = response.choices[0].message.content
        return result
        
    except Exception as e:
        return f"Error calling sonar-pro web search: {str(e)}"

💡 Understanding the Web Search Tool:

1. Model Selection

model="sap/sonar-pro" - Uses Perplexity's web search-enabled model

Automatically searches the web and returns cited results

No additional configuration needed for basic web search

2. Search Configuration

temperature=0.2 - Lower temperature for factual, consistent results

System prompt guides the search focus (criminal intelligence)

User query contains the specific search (e.g., "Marcus Chen criminal history")

3. Response Format

Sonar-pro returns synthesized answers with web sources

Includes URLs, publication dates, and source reliability

Agent receives structured information to inform investigation

4. Error Handling

Returns error as string (agent can handle gracefully)

No exceptions raised (agent workflow continues)

Add The Intelligence Researcher Agent

Step 1: Add Agent Configuration

👉 Open /project/Python/starter-project/config/agents.yaml

👉 Add this configuration after the evidence_analyst_agent section:

intelligence_researcher_agent:
  role: >
    Open-Source Intelligence (OSINT) Researcher
  goal: >
    Search the web for similar art thefts, criminal patterns, and suspect backgrounds
    to determine if this heist is part of a larger criminal network. Use the 
    call_sonar_pro_search tool to find recent incidents, news reports, and public 
    criminal records for all three suspects: {suspect_names}.
  backstory: >
    You are an OSINT specialist who excels at finding patterns across multiple 
    crime scenes. You search public databases, news archives, and criminal records 
    to connect seemingly isolated incidents. Your expertise has uncovered several 
    international art theft rings, and you know how to distinguish professional 
    criminals from amateurs.
  llm: sap/gpt-4o

💡 Why This Agent Design?

Role: OSINT Researcher - Establishes expertise in public information gathering

Goal: Specific search objectives (patterns, backgrounds, networks) with explicit tool mention

Backstory: Provides context and authority for web-based investigations

LLM: Uses sap/gpt-4o for agent reasoning (the tool calls sonar-pro for searches)

Step 2: Add Task Configuration

👉 Open /project/Python/starter-project/config/tasks.yaml

👉 Add this configuration after the analyze_evidence_task and before the solve_crime task:

research_criminal_network:
  description: >
    Search the web for intelligence about the three suspects ({suspect_names}) and 
    related crimes. Use the call_sonar_pro_search tool to find:
    1. Public criminal records or prior convictions for each suspect
    2. Similar art theft incidents with the same modus operandi (insider job, no forced entry)
    3. Connections to known art theft rings or criminal networks
    4. News reports or public information about any of the suspects
    5. Recent museum heists in Europe with similar patterns
    
    Cross-reference your web findings with the internal evidence analyzed by the 
    evidence analyst. Focus on discovering whether this is an isolated incident or 
    part of a larger criminal operation.
  expected_output: >
    A comprehensive intelligence report containing:
    - Background checks for all three suspects with web sources
    - List of similar art thefts found online (dates, locations, MO)
    - Evidence of criminal network connections (if any)
    - Assessment: isolated incident vs. organized crime ring
    - All findings MUST include web sources with URLs and dates
  agent: intelligence_researcher_agent

Step 3: Add Agent and Task Methods to the Crew

👉 Open /project/Python/starter-project/investigator_crew.py

👉 Find the InvestigatorCrew class

👉 Add these methods after the analyze_evidence_task() method and BEFORE the lead_detective_agent() method:

    @agent
    def intelligence_researcher_agent(self) -> Agent:
        return Agent(
            config=self.agents_config['intelligence_researcher_agent'],
            verbose=True,
            tools=[call_sonar_pro_search]  # Web search tool
        )

    @task
    def research_criminal_network(self) -> Task:
        return Task(
            config=self.tasks_config['research_criminal_network'],
            context=[self.analyze_evidence_task()]  # Uses internal evidence to inform web searches
        )

💡 Method Positioning Matters!

Your class should now have this order:

appraiser_agent() method

appraise_loss_task() method

evidence_analyst_agent() method

analyze_evidence_task() method

👈 intelligence_researcher_agent() method (NEW!)

👈 research_criminal_network() method (NEW!)

lead_detective_agent() method (will be added in Exercise 07)

solve_crime() method (will be added in Exercise 07)

crew() method (stays at the end)

💡 Understanding Task Context:

context=[self.analyze_evidence_task()] means the Intelligence Researcher receives the Evidence Analyst's findings

This allows the researcher to use internal evidence to formulate better web searches

Example: Evidence says "Marcus fired on 2024-01-15" → Researcher searches "Marcus Chen security technician fired 2024 criminal"

Run Your Enhanced Investigation

👉 Run your crew to test the web search capability!

From repository root:

# macOS / Linux
python3 ./project/Python/starter-project/main.py

# Windows (PowerShell)
python .\project\Python\starter-project\main.py

From starter-project folder:

# macOS / Linux
python3 main.py

# Windows (PowerShell)
python main.py

⏱️ This may take 3-6 minutes as your agents:

Predict stolen item values (Appraiser with RPT-1)

Search internal evidence documents (Evidence Analyst with Grounding)

Search the web for criminal patterns (Intelligence Researcher with Sonar-Pro) ← NEW!

👉 Review the intelligence report from the web search:

Did it find similar crimes?
Do any suspects have public criminal records?
Is there evidence of a criminal network?

Understanding Web Search Integration

What Just Happened?

You created a complete multi-source intelligence gathering system that:

Searches Internal Documents (Grounding Service) - Evidence from within the museum
Searches External Web (Sonar-Pro) - Public information from across the internet
Combines Intelligence - Both sources inform the investigation

The Enhanced Investigation Flow

flowchart TD
    A[Appraiser Agent] --> B[Predict Values<br/>RPT-1 Tool]
    B --> C[Evidence Analyst] 
    C --> D[Search Internal Docs<br/>Grounding Service]
    D --> E[Intelligence Researcher]
    E --> F[Search Web<br/>Sonar-Pro]
    F --> G[Multi-Source Intelligence<br/>Internal + External]
    G --> H[Ready for Exercise 07:<br/>Lead Detective Solves Crime]

When to Use Each Search Type

Use Document Grounding (call_grounding_service) when:

✅ Searching organization-specific documents
✅ Accessing private/confidential information
✅ Finding internal evidence (logs, records, policies)
✅ You control the document collection
✅ Need semantic search across your own data

Use Web Search (call_sonar_pro_search) when:

✅ Searching public information
✅ Finding current events or recent news
✅ Checking criminal databases or public records
✅ Discovering patterns across multiple organizations
✅ Need real-time, up-to-date information

Use Both when:

✅ You need comprehensive intelligence (internal + external)
✅ Cross-referencing private evidence with public records
✅ Verifying internal findings against external sources
✅ Building a complete picture from multiple angles

Example Investigation Workflow

Internal Evidence (Grounding Service):

"SECURITY_LOG.txt shows Marcus Chen accessed Gallery 2C at 23:47 on the night of the theft. MARCUS_TERMINATION_LETTER.txt indicates he was fired for 'unauthorized access to secured areas' on 2024-01-15."

External Intelligence (Web Search):

"Web search reveals Marcus Chen was previously investigated for a museum break-in in Berlin (2023). News reports from kunstdiebstahl-news.de show two similar heists with identical MO: former security staff, no forced entry, fine art targets."

Combined Analysis (For Exercise 07):

Internal evidence proves Marcus was at the scene + Web intelligence shows a pattern of similar crimes = Strong case that Marcus is a repeat offender and likely part of an organized theft ring.

Key Takeaways

Web Search extends your investigation beyond internal documents to public intelligence
Sonar-Pro provides real-time web search with source citations
Multi-Source Intelligence combines internal evidence + external intelligence
Complementary Tools: Document grounding and web search work together, not in competition
Complete Investigation: Real detectives use both internal records AND external research
Pattern Discovery: Web search reveals connections that internal documents can't show

Next Steps

You now have a complete intelligence gathering system with:

✅ Structured data predictions (RPT-1)
✅ Internal document search (Grounding Service)
✅ External web intelligence (Sonar-Pro)

In the next exercise, you'll add the Lead Detective Agent who will synthesize findings from all three sources to solve the museum art theft mystery.

Troubleshooting

Issue: ModuleNotFoundError: No module named 'litellm'

Solution: LiteLLM should already be installed from Exercise 02. If not, run:
```
pip install litellm==1.82.6
```

Issue: Error: Model sap/sonar-pro not found

Solution: Verify that:
- Sonar-pro is available in your SAP AI Core Generative AI Hub model catalog
- Your resource group has access to Perplexity models
- Check SAP AI Launchpad → Generative AI Hub → Models for available models

Issue: Web search returns no results or very generic information

Solution: Make your search queries more specific:
- ❌ Bad: "art theft"
- ✅ Good: "Marcus Chen security technician unauthorized access criminal record Europe"
- Include suspect names, locations, and specific details

Issue: AttributeError: 'NoneType' object has no attribute 'content'

Solution: The sonar-pro API response structure might differ. Update error handling:

result = response.choices[0].message.content if response.choices else "No results"

Issue: Agent doesn't use the web search tool

Solution: Ensure:
- The tool is assigned: tools=[call_sonar_pro_search]
- The task description explicitly mentions using call_sonar_pro_search
- The agent's goal references web search or OSINT

Issue: Web search takes too long or times out

Solution:
- Sonar-pro queries can take 10-30 seconds per search
- This is normal for real-time web crawling
- If timeout occurs, increase LiteLLM timeout or retry

Resources

Next exercise

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Discover Connected Crimes with Web Search

Overview

Understand Web Search with Sonar-Pro

Why Do We Need Web Search?

Document Grounding vs. Web Search

What is Sonar-Pro?

How Sonar-Pro Integrates with SAP AI Core

Add The Web Search Tool

Step 1: Create the Sonar-Pro Search Tool

Add The Intelligence Researcher Agent

Step 1: Add Agent Configuration

Step 2: Add Task Configuration

Step 3: Add Agent and Task Methods to the Crew

Run Your Enhanced Investigation

Understanding Web Search Integration

What Just Happened?

The Enhanced Investigation Flow

When to Use Each Search Type

Example Investigation Workflow

Key Takeaways

Next Steps

Troubleshooting

Resources

FilesExpand file tree

06-discover-connected-crimes.md

Latest commit

History

06-discover-connected-crimes.md

File metadata and controls

Discover Connected Crimes with Web Search

Overview

Understand Web Search with Sonar-Pro

Why Do We Need Web Search?

Document Grounding vs. Web Search

What is Sonar-Pro?

How Sonar-Pro Integrates with SAP AI Core

Add The Web Search Tool

Step 1: Create the Sonar-Pro Search Tool

Add The Intelligence Researcher Agent

Step 1: Add Agent Configuration

Step 2: Add Task Configuration

Step 3: Add Agent and Task Methods to the Crew

Run Your Enhanced Investigation

Understanding Web Search Integration

What Just Happened?

The Enhanced Investigation Flow

When to Use Each Search Type

Example Investigation Workflow

Key Takeaways

Next Steps

Troubleshooting

Resources