dylanebert
commited on
Commit
·
642907a
1
Parent(s):
18386c7
initial server
Browse files- README.md +87 -5
- __pycache__/app.cpython-311.pyc +0 -0
- app.py +367 -0
- requirements.txt +2 -0
README.md
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@@ -1,12 +1,94 @@
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---
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title: Research Tracker
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emoji:
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colorFrom:
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colorTo:
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sdk: gradio
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sdk_version: 5.38.2
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app_file: app.py
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pinned: false
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---
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-
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---
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title: Research Tracker MCP
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emoji: 🔬
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colorFrom: blue
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colorTo: purple
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sdk: gradio
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sdk_version: 5.38.2
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app_file: app.py
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pinned: false
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license: mit
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---
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# Research Tracker MCP Server
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A Gradio-based MCP (Model Context Protocol) server that provides research inference utilities for AI assistants and tools. This server offers public-facing APIs to extract and infer research metadata from various sources like papers, repositories, and project pages.
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## Features
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### MCP Tools Available
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- **`infer_authors`**: Extract author names from research papers, repositories, or project URLs
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- **`infer_paper_url`**: Find associated research papers from GitHub repos, project pages, or partial information
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- **`infer_code_repository`**: Locate code repositories from paper URLs or project information
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- **`infer_research_name`**: Extract formal paper/project titles from various inputs
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- **`classify_research_url`**: Classify URLs as Paper, Code, Model, Dataset, Space, or Project
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### Supported Input Types
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- **arXiv papers**: `https://arxiv.org/abs/2010.11929`
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- **GitHub repositories**: `https://github.com/google-research/vision_transformer`
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- **Hugging Face resources**: Models, Datasets, Spaces, Papers
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- **Project pages**: GitHub Pages, personal websites
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- **Research titles**: Natural language paper titles
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## Usage
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### As MCP Server
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This space can be used as an MCP server by AI assistants that support the MCP protocol. Configure your MCP client with:
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```json
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{
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"mcpServers": {
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"research-tracker": {
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"url": "https://YOUR_SPACE_NAME.hf.space/gradio_api/mcp/sse"
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}
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}
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}
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```
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### Web Interface
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The space also provides a web interface for testing the inference functions directly in your browser.
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## Architecture
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This MCP server delegates all inference logic to the [Research Tracker Backend](https://huggingface.co/spaces/dylanebert/research-tracker-backend) to ensure consistency and avoid code duplication. It serves as a public-facing interface for research inference utilities without requiring database access.
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## Examples
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### Infer Authors from arXiv Paper
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```python
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infer_authors("https://arxiv.org/abs/2010.11929")
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# Returns: ["Alexey Dosovitskiy", "Lucas Beyer", "Alexander Kolesnikov", ...]
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```
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### Find Paper from GitHub Repository
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```python
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infer_paper_url("https://github.com/google-research/vision_transformer")
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# Returns: "https://arxiv.org/abs/2010.11929"
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```
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### Classify URL Type
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```python
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classify_research_url("https://huggingface.co/google/vit-base-patch16-224")
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# Returns: "Model"
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```
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## Requirements
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- Python 3.11+
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- Gradio with MCP support
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- Internet connection for backend API calls
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## Development
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The server is built with:
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- **Gradio**: Web interface and MCP protocol support
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- **Requests**: HTTP client for backend communication
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- **Backend Integration**: Calls to research-tracker-backend API
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## License
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MIT License - Feel free to use and modify for your research needs.
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__pycache__/app.cpython-311.pyc
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app.py
ADDED
@@ -0,0 +1,367 @@
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"""
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Research Tracker MCP Server
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A Gradio-based MCP server that provides research inference utilities.
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Delegates inference logic to the research-tracker-backend for consistency.
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"""
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import os
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import requests
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import gradio as gr
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from typing import List, Dict, Any, Optional
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import logging
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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# Configuration
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BACKEND_URL = "https://dylanebert-research-tracker-backend.hf.space"
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HF_TOKEN = os.environ.get("HF_TOKEN")
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REQUEST_TIMEOUT = 30
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if not HF_TOKEN:
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logger.warning("HF_TOKEN not found in environment variables")
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def make_backend_request(endpoint: str, data: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Make a request to the research-tracker-backend.
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Args:
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endpoint: The backend endpoint to call (e.g., 'infer-authors')
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data: The data to send in the request body
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Returns:
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The response data from the backend
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Raises:
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Exception: If the request fails or returns an error
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"""
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url = f"{BACKEND_URL}/{endpoint}"
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {HF_TOKEN}" if HF_TOKEN else ""
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}
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try:
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response = requests.post(url, json=data, headers=headers, timeout=REQUEST_TIMEOUT)
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response.raise_for_status()
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return response.json()
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except requests.exceptions.Timeout:
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raise Exception(f"Request to {endpoint} timed out")
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except requests.exceptions.RequestException as e:
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raise Exception(f"Request to {endpoint} failed: {str(e)}")
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def infer_authors(input_data: str) -> List[str]:
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"""
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Infer authors from research paper or project information.
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This function attempts to extract author names from various inputs like
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paper URLs (arXiv, Hugging Face papers), project pages, or repository links.
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It uses the research-tracker-backend inference engine.
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Args:
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input_data: A URL, paper title, or other research-related input
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Returns:
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A list of author names, or empty list if no authors found
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Examples:
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>>> infer_authors("https://arxiv.org/abs/2103.00020")
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["Alexey Dosovitskiy", "Lucas Beyer", "Alexander Kolesnikov", ...]
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>>> infer_authors("https://github.com/google-research/vision_transformer")
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["Alexey Dosovitskiy", "Lucas Beyer", ...]
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"""
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if not input_data or not input_data.strip():
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return []
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try:
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# Create a minimal row data structure for the backend
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row_data = {
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"Name": None,
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"Authors": [],
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"Paper": input_data if "arxiv" in input_data or "huggingface.co/papers" in input_data else None,
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"Code": input_data if "github.com" in input_data else None,
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"Project": input_data if "github.io" in input_data else None,
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"Space": input_data if "huggingface.co/spaces" in input_data else None,
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"Model": input_data if "huggingface.co/models" in input_data else None,
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"Dataset": input_data if "huggingface.co/datasets" in input_data else None,
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}
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# If we can't classify the input, try it as a paper
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if not any(row_data.values()):
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row_data["Paper"] = input_data
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# Call the backend
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result = make_backend_request("infer-authors", row_data)
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# Extract authors from response
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authors = result.get("authors", [])
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if isinstance(authors, str):
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# Handle comma-separated string format
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authors = [author.strip() for author in authors.split(",") if author.strip()]
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elif not isinstance(authors, list):
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authors = []
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return authors
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except Exception as e:
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logger.error(f"Error inferring authors: {e}")
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return []
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def infer_paper_url(input_data: str) -> str:
|
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"""
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Infer the paper URL from various research-related inputs.
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This function attempts to find the associated research paper from
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inputs like GitHub repositories, project pages, or partial URLs.
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Args:
|
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input_data: A URL, repository link, or other research-related input
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Returns:
|
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The paper URL (typically arXiv or Hugging Face papers), or empty string if not found
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Examples:
|
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>>> infer_paper_url("https://github.com/google-research/vision_transformer")
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"https://arxiv.org/abs/2010.11929"
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>>> infer_paper_url("Vision Transformer")
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"https://arxiv.org/abs/2010.11929"
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"""
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if not input_data or not input_data.strip():
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return ""
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try:
|
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# Create row data structure
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row_data = {
|
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"Name": input_data if not input_data.startswith("http") else None,
|
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"Authors": [],
|
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"Paper": input_data if "arxiv" in input_data or "huggingface.co/papers" in input_data else None,
|
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"Code": input_data if "github.com" in input_data else None,
|
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"Project": input_data if "github.io" in input_data else None,
|
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"Space": input_data if "huggingface.co/spaces" in input_data else None,
|
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"Model": input_data if "huggingface.co/models" in input_data else None,
|
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"Dataset": input_data if "huggingface.co/datasets" in input_data else None,
|
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}
|
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|
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# Call the backend
|
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result = make_backend_request("infer-paper", row_data)
|
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|
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# Extract paper URL from response
|
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paper_url = result.get("paper", "")
|
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return paper_url if paper_url else ""
|
158 |
+
|
159 |
+
except Exception as e:
|
160 |
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logger.error(f"Error inferring paper: {e}")
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return ""
|
162 |
+
|
163 |
+
|
164 |
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def infer_code_repository(input_data: str) -> str:
|
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"""
|
166 |
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Infer the code repository URL from research-related inputs.
|
167 |
+
|
168 |
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This function attempts to find the associated code repository from
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169 |
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inputs like paper URLs, project pages, or partial information.
|
170 |
+
|
171 |
+
Args:
|
172 |
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input_data: A URL, paper link, or other research-related input
|
173 |
+
|
174 |
+
Returns:
|
175 |
+
The code repository URL (typically GitHub), or empty string if not found
|
176 |
+
|
177 |
+
Examples:
|
178 |
+
>>> infer_code_repository("https://arxiv.org/abs/2010.11929")
|
179 |
+
"https://github.com/google-research/vision_transformer"
|
180 |
+
|
181 |
+
>>> infer_code_repository("Vision Transformer")
|
182 |
+
"https://github.com/google-research/vision_transformer"
|
183 |
+
"""
|
184 |
+
if not input_data or not input_data.strip():
|
185 |
+
return ""
|
186 |
+
|
187 |
+
try:
|
188 |
+
# Create row data structure
|
189 |
+
row_data = {
|
190 |
+
"Name": input_data if not input_data.startswith("http") else None,
|
191 |
+
"Authors": [],
|
192 |
+
"Paper": input_data if "arxiv" in input_data or "huggingface.co/papers" in input_data else None,
|
193 |
+
"Code": input_data if "github.com" in input_data else None,
|
194 |
+
"Project": input_data if "github.io" in input_data else None,
|
195 |
+
"Space": input_data if "huggingface.co/spaces" in input_data else None,
|
196 |
+
"Model": input_data if "huggingface.co/models" in input_data else None,
|
197 |
+
"Dataset": input_data if "huggingface.co/datasets" in input_data else None,
|
198 |
+
}
|
199 |
+
|
200 |
+
# Call the backend
|
201 |
+
result = make_backend_request("infer-code", row_data)
|
202 |
+
|
203 |
+
# Extract code URL from response
|
204 |
+
code_url = result.get("code", "")
|
205 |
+
return code_url if code_url else ""
|
206 |
+
|
207 |
+
except Exception as e:
|
208 |
+
logger.error(f"Error inferring code: {e}")
|
209 |
+
return ""
|
210 |
+
|
211 |
+
|
212 |
+
def infer_research_name(input_data: str) -> str:
|
213 |
+
"""
|
214 |
+
Infer the research paper or project name from various inputs.
|
215 |
+
|
216 |
+
This function attempts to extract the formal name/title of a research
|
217 |
+
paper or project from URLs, repositories, or partial information.
|
218 |
+
|
219 |
+
Args:
|
220 |
+
input_data: A URL, repository link, or other research-related input
|
221 |
+
|
222 |
+
Returns:
|
223 |
+
The research name/title, or empty string if not found
|
224 |
+
|
225 |
+
Examples:
|
226 |
+
>>> infer_research_name("https://arxiv.org/abs/2010.11929")
|
227 |
+
"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale"
|
228 |
+
|
229 |
+
>>> infer_research_name("https://github.com/google-research/vision_transformer")
|
230 |
+
"Vision Transformer"
|
231 |
+
"""
|
232 |
+
if not input_data or not input_data.strip():
|
233 |
+
return ""
|
234 |
+
|
235 |
+
try:
|
236 |
+
# Create row data structure
|
237 |
+
row_data = {
|
238 |
+
"Name": None,
|
239 |
+
"Authors": [],
|
240 |
+
"Paper": input_data if "arxiv" in input_data or "huggingface.co/papers" in input_data else None,
|
241 |
+
"Code": input_data if "github.com" in input_data else None,
|
242 |
+
"Project": input_data if "github.io" in input_data else None,
|
243 |
+
"Space": input_data if "huggingface.co/spaces" in input_data else None,
|
244 |
+
"Model": input_data if "huggingface.co/models" in input_data else None,
|
245 |
+
"Dataset": input_data if "huggingface.co/datasets" in input_data else None,
|
246 |
+
}
|
247 |
+
|
248 |
+
# Call the backend
|
249 |
+
result = make_backend_request("infer-name", row_data)
|
250 |
+
|
251 |
+
# Extract name from response
|
252 |
+
name = result.get("name", "")
|
253 |
+
return name if name else ""
|
254 |
+
|
255 |
+
except Exception as e:
|
256 |
+
logger.error(f"Error inferring name: {e}")
|
257 |
+
return ""
|
258 |
+
|
259 |
+
|
260 |
+
def classify_research_url(url: str) -> str:
|
261 |
+
"""
|
262 |
+
Classify the type of research-related URL or input.
|
263 |
+
|
264 |
+
This function determines what type of research resource a given URL
|
265 |
+
or input represents (paper, code, model, dataset, etc.).
|
266 |
+
|
267 |
+
Args:
|
268 |
+
url: The URL or input to classify
|
269 |
+
|
270 |
+
Returns:
|
271 |
+
The field type: "Paper", "Code", "Space", "Model", "Dataset", "Project", or "Unknown"
|
272 |
+
|
273 |
+
Examples:
|
274 |
+
>>> classify_research_url("https://arxiv.org/abs/2010.11929")
|
275 |
+
"Paper"
|
276 |
+
|
277 |
+
>>> classify_research_url("https://github.com/google-research/vision_transformer")
|
278 |
+
"Code"
|
279 |
+
|
280 |
+
>>> classify_research_url("https://huggingface.co/google/vit-base-patch16-224")
|
281 |
+
"Model"
|
282 |
+
"""
|
283 |
+
if not url or not url.strip():
|
284 |
+
return "Unknown"
|
285 |
+
|
286 |
+
try:
|
287 |
+
# Call the backend
|
288 |
+
result = make_backend_request("infer-field", {"value": url})
|
289 |
+
|
290 |
+
# Extract field from response
|
291 |
+
field = result.get("field", "Unknown")
|
292 |
+
return field if field else "Unknown"
|
293 |
+
|
294 |
+
except Exception as e:
|
295 |
+
logger.error(f"Error classifying URL: {e}")
|
296 |
+
return "Unknown"
|
297 |
+
|
298 |
+
|
299 |
+
# Create Gradio interface
|
300 |
+
def create_demo():
|
301 |
+
"""Create the Gradio demo interface for testing."""
|
302 |
+
|
303 |
+
with gr.Blocks(title="Research Tracker MCP Server") as demo:
|
304 |
+
gr.Markdown("# Research Tracker MCP Server")
|
305 |
+
gr.Markdown("Test the research inference utilities that are available through MCP.")
|
306 |
+
|
307 |
+
with gr.Tab("Authors"):
|
308 |
+
with gr.Row():
|
309 |
+
author_input = gr.Textbox(
|
310 |
+
label="Input (URL, paper title, etc.)",
|
311 |
+
placeholder="https://arxiv.org/abs/2010.11929",
|
312 |
+
lines=1
|
313 |
+
)
|
314 |
+
author_output = gr.JSON(label="Authors")
|
315 |
+
author_btn = gr.Button("Infer Authors")
|
316 |
+
author_btn.click(infer_authors, inputs=author_input, outputs=author_output)
|
317 |
+
|
318 |
+
with gr.Tab("Paper"):
|
319 |
+
with gr.Row():
|
320 |
+
paper_input = gr.Textbox(
|
321 |
+
label="Input (GitHub repo, project name, etc.)",
|
322 |
+
placeholder="https://github.com/google-research/vision_transformer",
|
323 |
+
lines=1
|
324 |
+
)
|
325 |
+
paper_output = gr.Textbox(label="Paper URL")
|
326 |
+
paper_btn = gr.Button("Infer Paper")
|
327 |
+
paper_btn.click(infer_paper_url, inputs=paper_input, outputs=paper_output)
|
328 |
+
|
329 |
+
with gr.Tab("Code"):
|
330 |
+
with gr.Row():
|
331 |
+
code_input = gr.Textbox(
|
332 |
+
label="Input (paper URL, project name, etc.)",
|
333 |
+
placeholder="https://arxiv.org/abs/2010.11929",
|
334 |
+
lines=1
|
335 |
+
)
|
336 |
+
code_output = gr.Textbox(label="Code Repository URL")
|
337 |
+
code_btn = gr.Button("Infer Code")
|
338 |
+
code_btn.click(infer_code_repository, inputs=code_input, outputs=code_output)
|
339 |
+
|
340 |
+
with gr.Tab("Name"):
|
341 |
+
with gr.Row():
|
342 |
+
name_input = gr.Textbox(
|
343 |
+
label="Input (URL, repo, etc.)",
|
344 |
+
placeholder="https://github.com/google-research/vision_transformer",
|
345 |
+
lines=1
|
346 |
+
)
|
347 |
+
name_output = gr.Textbox(label="Research Name/Title")
|
348 |
+
name_btn = gr.Button("Infer Name")
|
349 |
+
name_btn.click(infer_research_name, inputs=name_input, outputs=name_output)
|
350 |
+
|
351 |
+
with gr.Tab("Classify"):
|
352 |
+
with gr.Row():
|
353 |
+
classify_input = gr.Textbox(
|
354 |
+
label="URL to classify",
|
355 |
+
placeholder="https://huggingface.co/google/vit-base-patch16-224",
|
356 |
+
lines=1
|
357 |
+
)
|
358 |
+
classify_output = gr.Textbox(label="URL Type")
|
359 |
+
classify_btn = gr.Button("Classify URL")
|
360 |
+
classify_btn.click(classify_research_url, inputs=classify_input, outputs=classify_output)
|
361 |
+
|
362 |
+
return demo
|
363 |
+
|
364 |
+
|
365 |
+
if __name__ == "__main__":
|
366 |
+
demo = create_demo()
|
367 |
+
demo.launch(mcp_server=True, share=False)
|
requirements.txt
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
gradio[mcp]==5.38.2
|
2 |
+
requests==2.32.4
|