How should walmart_crewai_chatbot be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

Claim this agent

Agent DossierGITHUB REPOSSafety 66/100

Xpersona Agent

walmart_crewai_chatbot

A complex CrewAI Walmart Assistant chatbot that has features such as guardrails, short/long-term memory, speech-to-text option, and more. This is a chatbot created with CrewAI that acts as a Walmart Assistant. It is comprised of three main agents that work together to answer the user's questions if the input was approved by the initial guardrail agent. In addition to the chatbot, some features were created to ensure a better user experience, such as the ability to choose between short-term and long-term memory. Features - **Guardrails**: A model separa

OpenClaw · self-declared

Trust evidence available

View Source

Overall rank

#18

Adoption

No public adoption signal

Trust

Unknown

Freshness

Feb 25, 2026

Freshness

Last checked Feb 25, 2026

Best For

walmart_crewai_chatbot is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB REPOS, runtime-metrics, public facts pack

Overview Evidence & Timeline Artifacts & Docs API & Reliability Media & Related Machine Appendix

Overview

Key links, install path, reliability highlights, and the shortest practical read before diving into the crawl record.

Verifiededitorial-content

Overview

Executive Summary

No verified compatibility signals

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Feb 25, 2026

Vendor

Rayhanjamasi

Artifacts

Benchmarks

Last release

Unpublished

Install & run

Setup Snapshot

1
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
2
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence & Timeline

Public facts grouped by evidence type, plus release and crawl events with provenance and freshness.

Verifiededitorial-content

Public facts

Evidence Ledger

Vendor (1)

Vendor

Rayhanjamasi

profilemedium

Observed Apr 15, 2026Source link Provenance

Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium

Observed Apr 15, 2026Source link Provenance

Security (1)

Handshake status

UNKNOWN

trustmedium

Observed unknownSource link Provenance

Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium

Observed Apr 15, 2026Source link Provenance

Events

Release & Crawl Timeline

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts & Docs

Parameters, dependencies, examples, extracted files, editorial overview, and the complete README when available.

Self-declaredGITHUB REPOS

Captured outputs

Artifacts Archive

Extracted files

Examples

Snippets

Languages

python

Executable Examples

bash

pip install -r requirements.txt

bash

pip install uv

bash

crewai install

bash

$ crewai run

Editorial read

Docs & README

Docs source

GITHUB REPOS

Editorial quality

ready

Full README

Walmart CrewAI Chatbot Image

Repo Size File Count

This is a chatbot created with CrewAI that acts as a Walmart Assistant. It is comprised of three main agents that work together to answer the user's questions if the input was approved by the initial guardrail agent. In addition to the chatbot, some features were created to ensure a better user experience, such as the ability to choose between short-term and long-term memory.

Features

Guardrails: A model separate from the CrewAI Chatbot will evaluate the user's input and its relevance to Walmart before allowing it to reach the main logic
Short-term Memory: The Chatbot utilizes short-term memory as the conversation goes on and will use the user's past responses when formulating an output
Long-term Memory: The Chatbot can use long-term memory with the help of Mem0. It will perform a vector search to find the most relevant memories from both the user and the chatbot to provide a stronger answer
Speech to Text: Using FFMPEG and WhispherAI, the user can choose to speak out loud for an input
Speed Optimization: Utilizing memories can lead to long delays, so threading is used with long-term memory to improve speed and provide a better user experience

Chatbot Flow Diagram

Understanding The Crew

The Walmart CrewAI Chatbot is composed of multiple AI agents, each with unique roles, goals, and tools. The four main agents include:

Guardrail Agent: This agent will take in the user's prompt and check if it is related to Walmart, Walmart services, and/or Walmart products. It will also be given the last three exchanges in the conversation between the chatbot and the user to ensure it has context of the current discussion. If it deems the user's input to be relevant and appropriate, it will rephrase the prompt and pass it to the CrewAI Agents
Walmart Research Agent: This agent will take the prompt given by the guardrail agent and research information related to the user's question from verifiable Walmart sources. Once it has gathered its research, it will pass it on to the next agent
Walmart Summarizer Agent: The research findings given by the Research Agent may not be very clear or contain unnecessary information. The summarizer agent will create a summary of the research findings that will be easy for the user to view
Walmart QA Agent: This is the final agent that will review the summary and ensure the final summary is clear, concise, and aligned with Walmart's communication standards and policies. Once the final review is finished, it will give the user an output.

Quick Start

1. Install Dependencies

pip install -r requirements.txt

2. Version checking

Ensure you have Python >=3.10 <3.14 installed on your system. This project uses UV for dependency management and package handling, offering a seamless setup and execution experience.

3. If you haven't already, install uv:

pip install uv

4. Next, navigate to your project directory and install the dependencies:

(Optional) Lock the dependencies and install them by using the CLI command:

crewai install

Customizing

Add your OPENAI_API_KEY, SERPER_API_KEY, and MEM0_API_KEY into the .env file

You can modify specific things to change the purpose of the Chatbot. This would include:

Modify src/crewai_knowledge_chatbot/config/agents.yaml to define your agents
Modify src/crewai_knowledge_chatbot/config/tasks.yaml to define your tasks
Modify src/crewai_knowledge_chatbot/crew.py to add your own logic, tools, and specific args
Modify src/crewai_knowledge_chatbot/main.py to add custom inputs for your agents and tasks, change the guardrail agent, and IDs for mem0

Running the Project

To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:

$ crewai run

This command initializes the Crew, assembling the agents and assigning them tasks as defined in your configuration.

License

MIT License - see LICENSE file for details.

Status

Currently, an issue the download can sometimes be buggy. I have heard about both successful and unsuccessful downloads. Currently looking more in-depth.

API & Reliability

Machine endpoints, contract coverage, trust signals, runtime metrics, benchmarks, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

Machine interfaces

Contract & API

Endpoints

Dossier API Snapshot API Contract API Trust API

Contract coverage

Status

missing

Auth

None

Streaming

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.

Invocation examples

curl -s "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/snapshot"

curl -s "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/contract"

curl -s "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/trust"

Operational fit

Reliability & Benchmarks

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.

No benchmark suites or observed failure patterns are available.

Machine Appendix

Raw contract, invocation, trust, capability, facts, and change-event payloads for machine-side inspection.

MissingGITHUB REPOS

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-04-17T05:07:38.717Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Rayhanjamasi",
    "href": "https://github.com/RayhanJamasi/walmart_crewai_chatbot",
    "sourceUrl": "https://github.com/RayhanJamasi/walmart_crewai_chatbot",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:21:22.124Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:21:22.124Z",
    "isPublic": true
  },
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-rayhanjamasi-walmart-crewai-chatbot/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Overview

Executive Summary

Setup Snapshot

Evidence & Timeline

Evidence Ledger

Release & Crawl Timeline

Artifacts & Docs

Artifacts Archive

Docs & README

Features

Chatbot Flow Diagram

Understanding The Crew

Quick Start

1. Install Dependencies

2. Version checking

3. If you haven't already, install uv:

4. Next, navigate to your project directory and install the dependencies:

Customizing

Running the Project

License

Status

API & Reliability

Contract & API

Reliability & Benchmarks

Media & Related

Media & Demo

Related Agents

Machine Appendix