Documentation Index
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Welcome to ChemAgent
ChemAgent is a sophisticated AI-powered chemistry assistant that combines the power of large language models (LLMs), RDKit chemical informatics, and retrieval-augmented generation (RAG) to solve complex molecular tasks. Built on the LlaSMol fine-tuned models and a plan-and-execute agent architecture, ChemAgent handles chemistry queries with unprecedented accuracy and intelligence.Quick Start
Get up and running with ChemAgent in minutes
Installation
Set up your environment and install dependencies
Architecture
Understand how ChemAgent works under the hood
API Reference
Explore the complete API documentation
Key Capabilities
Name Conversion
Name Conversion
Convert between chemical naming conventions with ease:
- IUPAC ↔ SMILES
- SMILES ↔ Molecular Formula
- IUPAC ↔ Molecular Formula
Property Prediction
Property Prediction
Predict molecular properties using fine-tuned chemistry models:
- Solubility (ESOL)
- Lipophilicity (LIPO)
- Blood-brain barrier permeability (BBBP)
- Toxicity (ClinTox)
- HIV inhibition
- Side effects (SIDER)
Molecule Operations
Molecule Operations
Generate and analyze molecular structures:
- Molecule captioning and description
- Structure generation from text descriptions
- SMILES validation with detailed error reporting
- Chemistry parser with validity vectors
Chemical Reactions
Chemical Reactions
Plan and analyze chemical reactions:
- Forward synthesis prediction
- Retrosynthesis pathway planning
- Reaction validation
Image Processing
Image Processing
Extract chemical information from images using GPT-4o:
- Molecular structure recognition
- Chemical formula extraction
- Integration with chemistry queries
PubChem RAG
PubChem RAG
Enhance queries with contextual information:
- Automatic PubChem knowledge retrieval
- Chemistry term identification
- Context-aware analysis
How It Works
ChemAgent uses a sophisticated plan-and-execute architecture built with LangGraph:Query Planning
The agent analyzes your chemistry question and creates a step-by-step execution plan using GPT-4o.
Tool Execution
Each step is executed using specialized chemistry tools:
structure_chem_promptfor tagging IUPAC/SMILESanswer_chemistry_queryfor LlaSMol inferencevalidate_smiles_rdkitfor RDKit validation
Replanning
The agent evaluates results and replans if needed, adapting to validation errors or incomplete information.
Supported Models
ChemAgent leverages the LlaSMol family of fine-tuned chemistry models:- LlaSMol-Mistral-7B (default) — Best overall performance
- LlaSMol-Llama2-7B — Alternative base model
- LlaSMol-CodeLlama-7B — Code-optimized variant
- LlaSMol-Galactica-6.7B — Compact model option
LlaSMol models require a minimum of 15GB VRAM. For lower VRAM systems, set
LOW_VRAM=True in the configuration to disable model loading and use external API calls only.Architecture Highlights
Plan-and-Execute Agent
LangGraph-based orchestration with GPT-4o planning and replanning capabilities
LlaSMol Models
Fine-tuned 7B parameter models specialized for chemistry understanding
RDKit Integration
Robust SMILES validation and molecular structure verification
Optional RAG
PubChem knowledge retrieval for enhanced context
Next Steps
Quickstart
Run your first chemistry query
Core Concepts
Learn the fundamentals
Guides
Explore use cases