feat(marketing-agent): Implement multi-agent marketing system with memory capabilities and Streamlit UI

[didhd]

Amazon Bedrock AgentCore Samples Pull Request

Important

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Issue number: #(to be created)

Concise description of the PR

Add comprehensive marketing agent system that leverages AWS Bedrock and Strands framework to create a dynamic multi-agent workflow with task planning, execution, and specialized agents for research, SQL analysis, Python computation, and report generation. Includes persistent memory capabilities, web search integration, and professional markdown report output with visualizations.

User experience

Please share what the user experience looks like before and after this change

Before: No marketing agent example available in the repository.

After: Users can deploy and interact with a sophisticated marketing agent system that:

• Accepts natural language marketing requests via CLI or Streamlit UI
• Automatically plans and executes complex research workflows using specialized agents
• Maintains conversation memory and business context across sessions
• Generates professional marketing reports with data visualizations
• Supports both local development and AgentCore Runtime deployment

Checklist

If your change doesn't seem to apply, please leave them unchecked.

• I have reviewed the contributing guidelines
• Add your name to CONTRIBUTORS.md
• Have you checked to ensure there aren't other open Pull Requests for the same update/change?
• Are you uploading a dataset?
• Have you documented Introduction, Architecture Diagram, Prerequisites, Usage, Sample Prompts, and Clean Up steps in your example README?
• I agree to resolve any issues created for this example in the future.
• I have performed a self-review of this change
• Changes have been tested
• Changes are documented

Acknowledgment

By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of the project license.

[github-actions]

Latest scan for commit: f0da623 | Updated: 2025-10-03 19:19:48 UTC

Security Scan Results

Scan Metadata

• Project: ASH
• Scan executed: 2025-10-03T19:19:33+00:00
• ASH version: 3.0.0

Summary

Scanner Results

The table below shows findings by scanner, with status based on severity thresholds and dependencies:

Column Explanations:

Severity Levels (S/C/H/M/L/I):

• Suppressed (S): Security findings that have been explicitly suppressed/ignored and don't affect the scanner's pass/fail status
• Critical (C): The most severe security vulnerabilities requiring immediate remediation (e.g., SQL injection, remote code execution)
• High (H): Serious security vulnerabilities that should be addressed promptly (e.g., authentication bypasses, privilege escalation)
• Medium (M): Moderate security risks that should be addressed in normal development cycles (e.g., weak encryption, input validation issues)
• Low (L): Minor security concerns with limited impact (e.g., information disclosure, weak recommendations)
• Info (I): Informational findings for awareness with minimal security risk (e.g., code quality suggestions, best practice recommendations)

Other Columns:

• Time: Duration taken by each scanner to complete its analysis
• Action: Total number of actionable findings at or above the configured severity threshold that require attention

Scanner Results:

• PASSED: Scanner found no security issues at or above the configured severity threshold - code is clean for this scanner
• FAILED: Scanner found security vulnerabilities at or above the threshold that require attention and remediation
• MISSING: Scanner could not run because required dependencies/tools are not installed or available
• SKIPPED: Scanner was intentionally disabled or excluded from this scan
• ERROR: Scanner encountered an execution error and could not complete successfully

Severity Thresholds (Thresh Column):

• CRITICAL: Only Critical severity findings cause scanner to fail
• HIGH: High and Critical severity findings cause scanner to fail
• MEDIUM (MED): Medium, High, and Critical severity findings cause scanner to fail
• LOW: Low, Medium, High, and Critical severity findings cause scanner to fail
• ALL: Any finding of any severity level causes scanner to fail

Threshold Source: Values in parentheses indicate where the threshold is configured:

• (g) = global: Set in the global_settings section of ASH configuration
• (c) = config: Set in the individual scanner configuration section
• (s) = scanner: Default threshold built into the scanner itself

Statistics calculation:

• All statistics are calculated from the final aggregated SARIF report
• Suppressed findings are counted separately and do not contribute to actionable findings
• Scanner status is determined by comparing actionable findings to the threshold

Scanner	S	C	H	M	L	I	Time	Action	Result	Thresh
bandit	0	0	0	0	3	0	1.0s	0	PASSED	MED (g)
cdk-nag	0	0	0	0	0	0	28.0s	0	PASSED	MED (g)
cfn-nag	0	0	0	0	0	0	12ms	0	PASSED	MED (g)
checkov	0	1	0	0	0	0	7.6s	1	FAILED	MED (g)
detect-secrets	0	5	0	0	0	0	1.0s	5	FAILED	MED (g)
grype	0	0	0	0	0	0	<1ms	0	ERROR	MED (g)
npm-audit	0	0	0	0	0	0	162ms	0	PASSED	MED (g)
opengrep	0	0	0	0	0	0	<1ms	0	SKIPPED	MED (g)
semgrep	0	0	0	0	0	0	15.1s	0	PASSED	MED (g)
syft	0	0	0	0	0	0	2.0s	0	PASSED	MED (g)

Detailed Findings

Show 6 actionable findings

Finding 1: SECRET-SECRET-KEYWORD

• Severity: HIGH
• Scanner: detect-secrets
• Rule ID: SECRET-SECRET-KEYWORD
• Location: 02-use-cases/marketing-researcher-agent/Dockerfile:25

Description:
Secret of type 'Secret Keyword' detected in file '02-use-cases/marketing-researcher-agent/Dockerfile' at line 25

Code Snippet:

Secret of type Secret Keyword detected

---

Finding 2: SECRET-SECRET-KEYWORD

• Severity: HIGH
• Scanner: detect-secrets
• Rule ID: SECRET-SECRET-KEYWORD
• Location: 01-tutorials/utils.py:45

Description:
Secret of type 'Secret Keyword' detected in file '01-tutorials/utils.py' at line 45

Code Snippet:

Secret of type Secret Keyword detected

---

Finding 3: SECRET-SECRET-KEYWORD

• Severity: HIGH
• Scanner: detect-secrets
• Rule ID: SECRET-SECRET-KEYWORD
• Location: 01-tutorials/utils.py:38

Description:
Secret of type 'Secret Keyword' detected in file '01-tutorials/utils.py' at line 38

Code Snippet:

Secret of type Secret Keyword detected

---

Finding 4: SECRET-SECRET-KEYWORD

• Severity: HIGH
• Scanner: detect-secrets
• Rule ID: SECRET-SECRET-KEYWORD
• Location: 02-use-cases/marketing-researcher-agent/utils.py:41

Description:
Secret of type 'Secret Keyword' detected in file '02-use-cases/marketing-researcher-agent/utils.py' at line 41

Code Snippet:

Secret of type Secret Keyword detected

---

Finding 5: SECRET-SECRET-KEYWORD

• Severity: HIGH
• Scanner: detect-secrets
• Rule ID: SECRET-SECRET-KEYWORD
• Location: 02-use-cases/marketing-researcher-agent/utils.py:49

Description:
Secret of type 'Secret Keyword' detected in file '02-use-cases/marketing-researcher-agent/utils.py' at line 49

Code Snippet:

Secret of type Secret Keyword detected

---

Finding 6: CKV_DOCKER_2

• Severity: HIGH
• Scanner: checkov
• Rule ID: CKV_DOCKER_2
• Location: 02-use-cases/marketing-researcher-agent/Dockerfile:1-39

Description:
Ensure that HEALTHCHECK instructions have been added to container images

Code Snippet:

FROM public.ecr.aws/docker/library/python:3.13-slim
WORKDIR /app



COPY requirements.txt requirements.txt
# Install from requirements file
RUN pip install -r requirements.txt




RUN pip install aws-opentelemetry-distro>=0.10.0


# Set AWS region environment variable

ENV AWS_REGION=us-west-2
ENV AWS_DEFAULT_REGION=us-west-2


# Signal that this is running in Docker for host binding logic
ENV DOCKER_CONTAINER=1

ENV TAVILY_API_KEY="YOUR TAVILY KEY"

# Create non-root user
RUN useradd -m -u 1000 bedrock_agentcore
USER bedrock_agentcore

EXPOSE 8080
EXPOSE 8000

# Copy entire project (respecting .dockerignore)
COPY . .

# Use the full module path

CMD ["opentelemetry-instrument", "python", "-m", "main"]

---

Report generated by Automated Security Helper (ASH) at 2025-10-03T19:19:27+00:00