Crawler Summary

Trip-Planner-Agent answer-first brief

AI-powered travel planner built with CrewAI, Streamlit, and Ollama LLM. Generates personalized itineraries using multi-agent collaboration, real-time web search, and a user-friendly interface. ✈️ AI-Powered Trip Planner An intelligent travel planning app built with **CrewAI**, **Streamlit**, and **Ollama LLM**, designed to generate personalized travel itineraries based on user preferences. --- πŸš€ Features - 🧠 **AI-Powered Planning**: Multi-agent system (Location, Guide, Planner Experts) for holistic travel insights - πŸ—ΊοΈ **Comprehensive Itineraries**: Covers accommodations, transport, food, events, and bu Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 2/25/2026.

Freshness

Last checked 2/25/2026

Best For

Trip-Planner-Agent 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

Claim this agent
Agent DossierGITHUB REPOSSafety: 66/100

Trip-Planner-Agent

AI-powered travel planner built with CrewAI, Streamlit, and Ollama LLM. Generates personalized itineraries using multi-agent collaboration, real-time web search, and a user-friendly interface. ✈️ AI-Powered Trip Planner An intelligent travel planning app built with **CrewAI**, **Streamlit**, and **Ollama LLM**, designed to generate personalized travel itineraries based on user preferences. --- πŸš€ Features - 🧠 **AI-Powered Planning**: Multi-agent system (Location, Guide, Planner Experts) for holistic travel insights - πŸ—ΊοΈ **Comprehensive Itineraries**: Covers accommodations, transport, food, events, and bu

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

Feb 25, 2026

Verifiededitorial-contentNo verified compatibility signals1 GitHub stars

Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 2/25/2026.

1 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Feb 25, 2026

Vendor

Brijeshrakhasiya

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Unpublished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. 1 GitHub stars reported by the source. Last updated 2/25/2026.

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

Brijeshrakhasiya

profilemedium
Observed Feb 25, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Feb 25, 2026Source linkProvenance
Adoption (1)

Adoption signal

1 GitHub stars

profilemedium
Observed Feb 25, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source 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

5

Snippets

0

Languages

python

Executable Examples

bash

ollama pull llama3.2

### Setup

- Clone the repo

text

-  Install dependencies

text

-  Start Ollama

text

## Usage

1. Run the Streamlit application:

text

2. Open your browser to the provided local URL (typically http://localhost:8501)

3. Fill in the travel details:
   - From City
   - Destination City
   - Departure Date
   - Return Date
   - Interests (e.g., sightseeing, food, adventure)

4. Click "Generate Travel Plan" and wait for the AI to create your personalized itinerary

5. Download the travel plan as a text file

## Dependencies

- `crewai`: Multi-agent AI framework
- `crewai_tools`: Additional tools for CrewAI
- `langchain`: LLM framework integration
- `langchain_community`: Community tools for LangChain
- `langchain-ollama`: Ollama integration for LangChain
- `duckduckgo-search`: Web search functionality
- `langchain-google-genai`: Google Generative AI integration (optional)
- `streamlit`: Web application framework

## Project Structure

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 travel planner built with CrewAI, Streamlit, and Ollama LLM. Generates personalized itineraries using multi-agent collaboration, real-time web search, and a user-friendly interface. ✈️ AI-Powered Trip Planner An intelligent travel planning app built with **CrewAI**, **Streamlit**, and **Ollama LLM**, designed to generate personalized travel itineraries based on user preferences. --- πŸš€ Features - 🧠 **AI-Powered Planning**: Multi-agent system (Location, Guide, Planner Experts) for holistic travel insights - πŸ—ΊοΈ **Comprehensive Itineraries**: Covers accommodations, transport, food, events, and bu

Full README

✈️ AI-Powered Trip Planner

An intelligent travel planning app built with CrewAI, Streamlit, and Ollama LLM, designed to generate personalized travel itineraries based on user preferences.


πŸš€ Features

  • 🧠 AI-Powered Planning: Multi-agent system (Location, Guide, Planner Experts) for holistic travel insights
  • πŸ—ΊοΈ Comprehensive Itineraries: Covers accommodations, transport, food, events, and budgeting
  • 🌐 Live Web Search: DuckDuckGo integration for real-time travel data
  • πŸ–₯️ Streamlit Interface: Intuitive UI for entering travel details
  • πŸ“„ Downloadable Plans: Export itineraries as text files
  • 🌍 Multi-language Support: French responses for Francophone destinations

🧩 Architecture

Three specialized AI agents collaborate to deliver a complete travel plan:

| Agent | Role | |------------------|----------------------------------------------------------------------| | 🏨 Location Expert | Manages logistics: visas, weather, transport, accommodation, costs | | 🎯 Guide Expert | Recommends attractions, food, and activities based on interests | | πŸ“… Planner Expert | Compiles all data into a structured, day-by-day itinerary |


βš™οΈ Installation

πŸ“‹ Prerequisites

  • Python 3.8+
  • Ollama installed and running locally
  • Llama 3.2 model pulled via:
    ollama pull llama3.2
    

Setup

  • Clone the repo
   git clone https://github.com/BrijeshRakhasiya/Trip-Planner-Agent.git
  • Install dependencies
   pip install -r requirements.txt
  • Start Ollama
   ollama serve
   ollama pull llama3.2

Usage

  1. Run the Streamlit application:

    streamlit run app.py
    
  2. Open your browser to the provided local URL (typically http://localhost:8501)

  3. Fill in the travel details:

    • From City
    • Destination City
    • Departure Date
    • Return Date
    • Interests (e.g., sightseeing, food, adventure)
  4. Click "Generate Travel Plan" and wait for the AI to create your personalized itinerary

  5. Download the travel plan as a text file

Dependencies

  • crewai: Multi-agent AI framework
  • crewai_tools: Additional tools for CrewAI
  • langchain: LLM framework integration
  • langchain_community: Community tools for LangChain
  • langchain-ollama: Ollama integration for LangChain
  • duckduckgo-search: Web search functionality
  • langchain-google-genai: Google Generative AI integration (optional)
  • streamlit: Web application framework

Project Structure

β”œβ”€β”€ app.py                 # Main Streamlit application
β”œβ”€β”€ TravelAgents.py        # AI agent definitions
β”œβ”€β”€ TravelTasks.py         # Task definitions for agents
β”œβ”€β”€ TravelTools.py         # Custom tools (web search)
β”œβ”€β”€ requirements.txt       # Python dependencies
β”œβ”€β”€ output/                # Generated travel plans
β”‚   └── Travel_Plan_Rome.txt  # Sample output
β”œβ”€β”€ git_assets/            # UI screenshots
β”‚   β”œβ”€β”€ 1.png
β”‚   β”œβ”€β”€ 2.png
β”‚   └── 3.png
└── __pycache__/           # Python bytecode cache

Screenshots

Main Interface

Main Interface

Travel Plan Generation

Plan Generation

Sample Output

Sample Output

Sample Output

See output/Travel_Plan_Rome.txt for a sample travel plan generated for Rome, focusing on accommodation recommendations.

Technical Details

  • LLM: Uses Ollama with Llama 3.2 model running locally
  • Process: Sequential agent execution for comprehensive planning
  • Tools: DuckDuckGo web search for real-time information
  • Output Format: Markdown-structured travel itineraries
  • Language: Python 3.x with async capabilities

Configuration

The application uses the following configurations:

  • Max iterations per agent: 5
  • Verbose logging: Enabled
  • Full output: Enabled
  • Delegation: Disabled (agents work independently)

🧯 Troubleshooting

  • Ensure Ollama is running before starting the application
  • Check that the Llama 3.2 model is downloaded
  • Verify all dependencies are installed
  • 🌐 For web search issues, ensure internet connectivity

🌟 Future Enhancements

  • Support for multiple LLMs
  • Integration with booking APIs
  • Multi-language interface
  • Real-time flight/hotel pricing

πŸ“„ License

This project is licensed under the MIT License - see the LICENSE file for details.

πŸ™‹β€β™‚οΈ Author

Brijesh Rakhasiya
AI/ML Engineer Β· Data Scientist Β· Problem Solver


πŸ‘¨β€πŸ’» Developed by Brijesh Rakhasiya

Contract & API

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

MissingGITHUB REPOS

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://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/snapshot"
curl -s "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/contract"
curl -s "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/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_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation β€’ (~400 MCP servers for AI agents) β€’ AI Automation / AI Agent with MCPs β€’ AI Workflows & AI Agents β€’ MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 5d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
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://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-04-17T00:04:38.033Z"
    }
  },
  "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": "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": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Brijeshrakhasiya",
    "href": "https://github.com/BrijeshRakhasiya/Trip-Planner-Agent",
    "sourceUrl": "https://github.com/BrijeshRakhasiya/Trip-Planner-Agent",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T05:06:48.233Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-02-25T05:06:48.233Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "1 GitHub stars",
    "href": "https://github.com/BrijeshRakhasiya/Trip-Planner-Agent",
    "sourceUrl": "https://github.com/BrijeshRakhasiya/Trip-Planner-Agent",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T05:06:48.233Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/crewai-brijeshrakhasiya-trip-planner-agent/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub Β· 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
  }
]

Sponsored

Ads related to Trip-Planner-Agent and adjacent AI workflows.