AWS Bedrock AgentCore

# For local development with Strands Agents
pip install "valyu-agentcore[strands]"

# For AWS AgentCore Gateway/Runtime deployment
pip install "valyu-agentcore[agentcore]"

export VALYU_API_KEY="your-valyu-api-key"
export AWS_REGION="us-east-1"  # Optional, defaults to us-east-1

from valyu_agentcore import webSearch
from strands import Agent
from strands.models import BedrockModel

# Create an agent with Valyu search
agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    tools=[webSearch()],
)

# Ask anything
response = agent("What are the latest developments in quantum computing?")
print(response)

from valyu_agentcore import webSearch, financeSearch, secSearch, paperSearch
from strands import Agent
from strands.models import BedrockModel

# Financial research agent with multiple data sources
agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    tools=[
        webSearch(),      # Current news and web content
        financeSearch(),  # Stock prices and financial data
        secSearch(),      # SEC filings and disclosures
        paperSearch(),    # Academic research
    ],
)

response = agent("Analyze NVIDIA's competitive position in the AI chip market")
print(response)

from valyu_agentcore import ValyuTools
from strands import Agent
from strands.models import BedrockModel

tools = ValyuTools(max_num_results=5)

# Financial analysis agent
financial_agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    tools=tools.financial_tools(),  # Includes: financeSearch, secSearch, economicsSearch
)

# Research agent
research_agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    tools=tools.research_tools(),  # Includes: paperSearch, bioSearch, patentSearch
)

# All tools
complete_agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    tools=tools.all(),  # All 7 search tools
)

from valyu_agentcore import webSearch
from strands import Agent
from strands.models import BedrockModel

agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    tools=[webSearch()],
)

Your Agent → AgentCore Gateway → Valyu MCP Server → Valyu API
                   ↓
             Cognito Auth
             CloudTrail Logs
             API Key Secrets

from valyu_agentcore.gateway import setup_valyu_gateway, GatewayAgent

# One-time setup (creates Gateway + Cognito resources)
config = setup_valyu_gateway()
print(f"Gateway URL: {config.gateway_url}")

# Use the gateway-connected agent
with GatewayAgent.from_config() as agent:
    response = agent("Search for NVIDIA SEC filings")
    print(response)

from valyu_agentcore.gateway import add_valyu_target

# Add Valyu tools to your existing AgentCore Gateway
result = add_valyu_target(
    gateway_id="your-existing-gateway-id",
    region="us-east-1",
)
print(f"Target ID: {result['target_id']}")

# Deploy to AgentCore Runtime
cd examples/runtime
agentcore configure --entrypoint agent.py --non-interactive --name valyuagent
agentcore launch
agentcore invoke '{"prompt": "What is NVIDIA stock price?"}'

from valyu_agentcore import financeSearch

tool = financeSearch(
    api_key="val_xxx",           # Valyu API key (or use VALYU_API_KEY env var)
    search_type="all",           # "all", "web", "proprietary", or "news"
    max_num_results=10,          # Number of results (default: 5)
    max_price=0.50,              # Max cost per query in CPM
    relevance_threshold=0.7,     # Quality filter (0-1)
    excluded_sources=["reddit.com"],     # Domains to exclude
    included_sources=["reuters.com"],    # Restrict to specific domains
    category="quarterly earnings",       # Natural language search context
)

from valyu_agentcore import financeSearch, secSearch, webSearch
from strands import Agent
from strands.models import BedrockModel

FINANCIAL_ANALYST_PROMPT = """You are a senior financial analyst at a top investment firm.

When analyzing a company:
1. Use financeSearch for stock prices, earnings, and financial metrics
2. Use secSearch for 10-K/10-Q filings, risk factors, and disclosures
3. Use webSearch for recent news and market sentiment

Structure your analysis with:
- Executive Summary
- Financial Performance
- Key Risks
- Competitive Position
- Investment Thesis

Be specific with numbers and cite your sources."""

agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    system_prompt=FINANCIAL_ANALYST_PROMPT,
    tools=[financeSearch(), secSearch(), webSearch()],
)

response = agent("Analyze Apple's most recent quarterly earnings and outlook")

from valyu_agentcore import paperSearch, patentSearch, webSearch
from strands import Agent
from strands.models import BedrockModel

RESEARCH_ASSISTANT_PROMPT = """You are a research assistant specializing in technical literature review.

When researching a topic:
1. Use paperSearch for peer-reviewed academic papers (arXiv, PubMed)
2. Use patentSearch for prior art and IP landscape
3. Use webSearch for recent developments and news

Organize findings by:
- Key Papers (with citations)
- State of the Art
- Patent Landscape
- Recent Developments

Always cite sources with URLs."""

agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    system_prompt=RESEARCH_ASSISTANT_PROMPT,
    tools=[paperSearch(), patentSearch(), webSearch()],
)

response = agent("Survey recent advances in transformer architecture efficiency")

from valyu_agentcore import secSearch, financeSearch, webSearch, patentSearch
from strands import Agent
from strands.models import BedrockModel

DUE_DILIGENCE_PROMPT = """You are conducting due diligence for a potential investment or acquisition.

Generate a comprehensive report covering:
1. Company Overview - Use webSearch for background
2. Financial Analysis - Use financeSearch for metrics
3. Regulatory Filings - Use secSearch for SEC documents
4. IP Portfolio - Use patentSearch for patents
5. Market Position - Use webSearch for competitive analysis
6. Risk Factors - Synthesize from all sources

Be thorough and flag any red flags or concerns."""

agent = Agent(
    model=BedrockModel(model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"),
    system_prompt=DUE_DILIGENCE_PROMPT,
    tools=[secSearch(), financeSearch(), webSearch(), patentSearch()],
)

response = agent("Conduct due diligence on Anthropic for a potential investment")

aws cloudformation create-stack \
  --stack-name valyu-agentcore \
  --template-body file://cloudformation/valyu-gateway.yaml \
  --parameters \
    ParameterKey=ValyuApiKey,ParameterValue=your-api-key \
    ParameterKey=GatewayName,ParameterValue=valyu-search-gateway \
  --capabilities CAPABILITY_IAM

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "bedrock-agentcore:*",
        "cognito-idp:*"
      ],
      "Resource": "*"
    }
  ]
}

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "bedrock-agentcore:InvokeGateway",
        "bedrock-agentcore:ListTools"
      ],
      "Resource": "*"
    }
  ]
}