mirror of
https://github.com/mims-harvard/ToolUniverse.git
synced 2026-09-19 07:31:47 +08:00
Shanghua Gao
9f7070ed7b
### **Visualization Suite** - 2D/3D molecular visualization with interactive HTML output - Protein structure rendering with multiple visualization styles - Scientific plotting with Plotly, Matplotlib, and NetworkX ### **Coding API** - Type-safe function calling: `from tooluniverse.tools import ToolName` - Dynamic tool access: `tu.tools.ToolName()` - Built-in caching and error handling ### **Health Check System** - New `tooluniverse-doctor` CLI tool - Automatic dependency validation and bulk fix commands ### **Expanded Tool Ecosystem** - 50+ new scientific tools - Clinical guidelines (NICE, WHO, Europe PMC)
186 lines
8.5 KiB
Python
186 lines
8.5 KiB
Python
#!/usr/bin/env python3
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"""
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PubChem Tools Example
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Demonstrates various PubChem database tools available in ToolUniverse
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"""
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from tooluniverse import ToolUniverse
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# =============================================================================
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# Tool Initialization
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# =============================================================================
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# Description: Initialize ToolUniverse and load all available tools
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# Syntax: tu = ToolUniverse(); tu.load_tools()
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tu = ToolUniverse()
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tu.load_tools()
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# =============================================================================
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# Test Data Setup
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# =============================================================================
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# Description: Define test compounds and parameters for PubChem queries
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# Note: These are example compounds for testing various PubChem tools
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# Valid compound identifiers
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VALID_CID = 1983 # Example compound CID
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VALID_NAME = "Aspirin" # Compound name for name-based queries
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VALID_SMILES = "C1=NC2=C(N1)C(=O)N=C(N2)N" # SMILES notation for structure queries
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VALID_SUBSTRUCTURE = "c1ccccc1" # Benzene ring substructure for substructure search
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VALID_THRESHOLD = 0.95 # Similarity threshold for similarity search
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INVALID_CID = -1 # Intentionally invalid CID for error testing
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# External reference types for cross-reference queries
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VALID_XREF_TYPES = ["RegistryID", "RN"]
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# =============================================================================
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# Method 1: Compound Properties by CID
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# =============================================================================
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# Description: Retrieve molecular properties using compound ID
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# Syntax: tu.run({"name": "PubChem_get_compound_properties_by_CID", "arguments": {"cid": 1983}})
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result1 = tu.run({"name": "PubChem_get_compound_properties_by_CID", "arguments": {"cid": VALID_CID}})
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# =============================================================================
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# Method 2: Associated Patents
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# =============================================================================
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# Description: Get patents associated with a compound
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# Syntax: tu.run({"name": "PubChem_get_associated_patents_by_CID", "arguments": {"cid": 1983}})
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result2 = tu.run({"name": "PubChem_get_associated_patents_by_CID", "arguments": {"cid": VALID_CID}})
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# =============================================================================
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# Method 3: Webpage Title Extraction
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# =============================================================================
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# Description: Extract title from PubChem patent webpage
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# Syntax: tu.run({"name": "get_webpage_title", "arguments": {"url": "https://pubchem.ncbi.nlm.nih.gov/patent/US6015577"}})
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result3 = tu.run({
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"name": "get_webpage_title",
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"arguments": {"url": "https://pubchem.ncbi.nlm.nih.gov/patent/US6015577"}
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})
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# =============================================================================
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# Method 4: CID Lookup by Name
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# =============================================================================
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# Description: Find compound ID using compound name
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# Syntax: tu.run({"name": "PubChem_get_CID_by_compound_name", "arguments": {"name": "Aspirin"}})
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result4 = tu.run({"name": "PubChem_get_CID_by_compound_name", "arguments": {"name": VALID_NAME}})
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# =============================================================================
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# Method 5: CID Lookup by SMILES
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# =============================================================================
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# Description: Find compound ID using SMILES notation
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# Syntax: tu.run({"name": "PubChem_get_CID_by_SMILES", "arguments": {"smiles": "C1=NC2=C(N1)C(=O)N=C(N2)N"}})
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result5 = tu.run({"name": "PubChem_get_CID_by_SMILES", "arguments": {"smiles": VALID_SMILES}})
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# =============================================================================
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# Method 6: Substructure Search
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# =============================================================================
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# Description: Search for compounds containing specific substructures
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# Syntax: tu.run({"name": "PubChem_search_compounds_by_substructure", "arguments": {"smiles": "c1ccccc1"}})
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result6 = tu.run({
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"name": "PubChem_search_compounds_by_substructure",
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"arguments": {"smiles": VALID_SUBSTRUCTURE}
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})
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# =============================================================================
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# Method 7: Similarity Search
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# =============================================================================
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# Description: Find compounds similar to a reference structure
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# Syntax: tu.run({"name": "PubChem_search_compounds_by_similarity", "arguments": {"smiles": "C1=NC2=C(N1)C(=O)N=C(N2)N", "threshold": 0.95}})
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result7 = tu.run({
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"name": "PubChem_search_compounds_by_similarity",
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"arguments": {"smiles": VALID_SMILES, "threshold": VALID_THRESHOLD}
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})
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# =============================================================================
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# Method 8: 2D Structure Image
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# =============================================================================
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# Description: Retrieve 2D molecular structure image
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# Syntax: tu.run({"name": "PubChem_get_compound_2D_image_by_CID", "arguments": {"cid": 1983, "image_size": "150x150"}})
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result8 = tu.run({
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"name": "PubChem_get_compound_2D_image_by_CID",
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"arguments": {"cid": VALID_CID, "image_size": "150x150"}
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})
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# =============================================================================
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# Method 9: Compound Synonyms
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# =============================================================================
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# Description: Get alternative names and synonyms for a compound
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# Syntax: tu.run({"name": "PubChem_get_compound_synonyms_by_CID", "arguments": {"cid": 1983}})
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result9 = tu.run({"name": "PubChem_get_compound_synonyms_by_CID", "arguments": {"cid": VALID_CID}})
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# =============================================================================
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# Method 10: External References
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# =============================================================================
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# Description: Get cross-references to external databases
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# Syntax: tu.run({"name": "PubChem_get_compound_xrefs_by_CID", "arguments": {"cid": 1983, "xref_types": ["RegistryID", "RN"]}})
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result10 = tu.run({
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"name": "PubChem_get_compound_xrefs_by_CID",
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"arguments": {"cid": VALID_CID, "xref_types": VALID_XREF_TYPES}
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})
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# =============================================================================
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# Method 11: Error Handling Example
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# =============================================================================
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# Description: Demonstrate error handling with invalid compound ID
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# Syntax: tu.run({"name": "PubChem_get_compound_properties_by_CID", "arguments": {"cid": -1}})
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result11 = tu.run({
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"name": "PubChem_get_compound_properties_by_CID",
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"arguments": {"cid": INVALID_CID}
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})
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# =============================================================================
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# Result Processing Examples
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# =============================================================================
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# Description: Different ways to process and handle various result types
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# Dictionary results (JSON data)
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if isinstance(result1, dict):
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if "error" in result1:
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# Handle error response
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pass
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else:
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# Process successful dictionary result
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# Access specific properties: result1.get("property_name")
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pass
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# List results (search results)
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if isinstance(result6, list):
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# Process list of compounds
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# Access individual items: result6[0], result6[1], etc.
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pass
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# String results (text data)
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if isinstance(result9, str):
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# Process text data (CSV, TXT format)
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# Split by lines: result9.split("\n")
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pass
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# Binary results (image data)
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if isinstance(result8, (bytes, bytearray)):
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# Process binary image data
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# Check PNG header: result8.startswith(b"\x89PNG")
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# Save to file: with open("structure.png", "wb") as f: f.write(result8)
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pass
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# =============================================================================
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# Summary of PubChem Tools
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# =============================================================================
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# Available PubChem tools provide comprehensive chemical information:
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# - Molecular properties and descriptors
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# - Patent and literature associations
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# - Structure-based searches (SMILES, substructure, similarity)
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# - Name-based compound identification
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# - 2D structure visualization
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# - Synonym and nomenclature data
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# - Cross-references to external databases
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#
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# Common patterns:
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# - Use CID for most compound-specific queries
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# - Use SMILES for structure-based searches
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# - Use compound names for text-based lookups
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# - Check for "error" key in dictionary responses
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# - Handle different result types (dict, list, str, bytes)
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#
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# Error handling:
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# - Invalid CIDs return error responses
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# - Network timeouts may occur for large searches
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# - Some tools may require specific parameter formats |