Xpersona

Crawler Summary

NutriOS answer-first brief

AI-powered nutrition planning system using Multi-Agent AI, RAG, CrewAI, LangChain, FastAPI, and Streamlit. NutriOS NutriOS is an AI-powered nutrition planning system that combines deterministic health calculations, Retrieval-Augmented Generation (RAG), prompt-engineered multi-agent workflows using CrewAI, and structured JSON outputs to generate personalized nutrition recommendations. The system uses ChromaDB and LangChain for knowledge retrieval, Groq-hosted LLMs for reasoning, and specialized AI agents responsible for nu Capability contract not published. No trust telemetry is available yet. Last updated 6/1/2026.

Freshness

Last checked 6/1/2026

Best For

NutriOS 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

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGITHUB REPOSSafety: 66/100

NutriOS

AI-powered nutrition planning system using Multi-Agent AI, RAG, CrewAI, LangChain, FastAPI, and Streamlit. NutriOS NutriOS is an AI-powered nutrition planning system that combines deterministic health calculations, Retrieval-Augmented Generation (RAG), prompt-engineered multi-agent workflows using CrewAI, and structured JSON outputs to generate personalized nutrition recommendations. The system uses ChromaDB and LangChain for knowledge retrieval, Groq-hosted LLMs for reasoning, and specialized AI agents responsible for nu

OpenClawself-declared

Public facts

3

Change events

0

Artifacts

0

Freshness

Jun 1, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 6/1/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Jun 1, 2026

Vendor

Amani Shikh Alashra

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 6/1/2026.

View Source

Setup snapshot

  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 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 Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Amani Shikh Alashra

profilemedium
Observed Jun 1, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Jun 1, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB REPOS

Extracted files

0

Examples

1

Snippets

0

Languages

python

Executable Examples

bash

git clone <repository-url>
cd NutriOS

python -m venv .venv
pip install -e ".[dev,streamlit-ui]"

# Configure your Groq API key in .env
python -m nutrios.rag

uvicorn nutrios.main:app --reload
streamlit run streamlit_app.py

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

AI-powered nutrition planning system using Multi-Agent AI, RAG, CrewAI, LangChain, FastAPI, and Streamlit. NutriOS NutriOS is an AI-powered nutrition planning system that combines deterministic health calculations, Retrieval-Augmented Generation (RAG), prompt-engineered multi-agent workflows using CrewAI, and structured JSON outputs to generate personalized nutrition recommendations. The system uses ChromaDB and LangChain for knowledge retrieval, Groq-hosted LLMs for reasoning, and specialized AI agents responsible for nu

Full README

NutriOS

NutriOS is an AI-powered nutrition planning system that combines deterministic health calculations, Retrieval-Augmented Generation (RAG), prompt-engineered multi-agent workflows using CrewAI, and structured JSON outputs to generate personalized nutrition recommendations.

The system uses ChromaDB and LangChain for knowledge retrieval, Groq-hosted LLMs for reasoning, and specialized AI agents responsible for nutrition analysis, meal planning, habit coaching, and result validation.

๐ŸŽฅ Demo

โ–ถ Watch Demo Video

System Flow

User Input
โ†’ Deterministic Calculations
โ†’ RAG Retrieval (ChromaDB + LangChain)
โ†’ Multi-Agent Workflow (CrewAI)
โ†’ Structured JSON Output
โ†’ Streamlit Visualization

๐Ÿš€ Features

Personalized Nutrition Planning

Users provide personal information such as:

  • Age
  • Weight
  • Height
  • Activity level
  • Dietary preferences
  • Allergies
  • Foods they dislike The system uses this information to generate tailored recommendations instead of generic responses.

Deterministic Health Calculations

Before AI processing begins, the backend performs standard health calculations using Python logic, including:

  • BMI (Body Mass Index)
  • BMR (Basal Metabolic Rate)
  • TDEE (Total Daily Energy Expenditure)
  • Calorie targets
  • Macronutrient distribution This creates a structured baseline before the AI workflow starts.

Retrieval-Augmented Generation

NutriOS uses ChromaDB and LangChain to search a local nutrition knowledge base. Relevant nutrition information is retrieved and passed to the AI workflow, helping the system generate recommendations based on reference material instead of relying only on model knowledge.

Multi-Agent AI Workflow

NutriOS uses a multi-agent workflow instead of relying on a single AI response. Each agent has a dedicated role:

  • Nutrition Expert โ€“ analyzes nutritional needs and targets.
  • Meal Planner โ€“ creates meal recommendations based on preferences and restrictions.
  • Habit Coach โ€“ suggests habits and lifestyle improvements.
  • Health Reviewer โ€“ reviews the final output for consistency and safety.

Prompt Engineering

Each agent uses a role-specific system prompt. This helps control agent behavior, separate responsibilities, and keep the generated plan more consistent.

Structured JSON Output

The AI output is converted into structured JSON data, allowing the Streamlit frontend to reliably render recommendations, metrics, plans, and insights in a clear visual format.

Real-Time AI Workspace

The frontend shows the AI workflow while it is running. Users can follow each agent through different execution states:

  • Waiting
  • Running
  • Completed This creates a more transparent AI workspace experience instead of showing only the final result.

๐Ÿ› ๏ธ Technology Stack

Backend

  • FastAPI
  • Python
  • Pydantic

AI & Orchestration

  • Groq API
  • Llama models
  • CrewAI
  • Multi-agent architecture
  • Prompt engineering

Knowledge Retrieval

  • ChromaDB
  • LangChain
  • Local RAG knowledge base

Frontend

  • Streamlit
  • Custom CSS

โšก Getting Started

To run the project locally:

git clone <repository-url>
cd NutriOS

python -m venv .venv
pip install -e ".[dev,streamlit-ui]"

# Configure your Groq API key in .env
python -m nutrios.rag

uvicorn nutrios.main:app --reload
streamlit run streamlit_app.py

๐Ÿ”ฎ Future Roadmap

  • Long-term coaching memory
  • Enhanced visualizations and dashboards
  • Interactive daily nutrition programs
  • Mobile application

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

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://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

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.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
Github OpenclewUpdated 4mo agoRank 65

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OPENCLAW
Github OpenclewUpdated 4mo agoRank 65

oceanbus-langchain

LangChain tools for OceanBus โ€” give your LangChain and CrewAI agents a global identity, encrypted messaging, and Yellow Pages service discovery with a single import.

OPENCLAWoceanbuslangchainlangchain-tools
Agent hubMore from this sourceOpenClaw agents
Machine Appendix

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://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-09T00:11:12.245Z"
    }
  },
  "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": "Amani Shikh Alashra",
    "href": "https://github.com/Amani-shikh-Alashra/NutriOS",
    "sourceUrl": "https://github.com/Amani-shikh-Alashra/NutriOS",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-06-01T00:29:55.280Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-06-01T00:29:55.280Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-amani-shikh-alashra-nutrios/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[]

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