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Chemeagle Guide
ASecurityMulti-agent system for chemical literature information extraction
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[](https://www.skillsdirectory.com/skills/brycewang-stanford-chemeagle-guide)---
name: chemeagle-guide
description: "Multi-agent system for chemical literature information extraction"
metadata:
openclaw:
emoji: "π¦
"
category: "domains"
subcategory: "chemistry"
keywords: ["ChemEagle", "chemical extraction", "literature mining", "reaction extraction", "chemistry NLP", "multi-agent"]
source: "https://github.com/CYF2000127/ChemEagle"
---
# ChemEagle Guide
## Overview
ChemEagle is a multi-agent system for extracting structured chemical information from scientific literature. It uses specialized agents for recognizing chemical entities, extracting reaction conditions, identifying product yields, and building structured databases from unstructured chemistry papers. Particularly useful for building reaction databases and automating systematic reviews in chemistry.
## Agent Pipeline
```
Chemistry Paper (PDF/text)
β
Document Parser Agent (section identification)
β
Chemical NER Agent
βββ Compound names β SMILES/InChI
βββ Reagents and catalysts
βββ Solvents and conditions
βββ Product identification
β
Reaction Extraction Agent
βββ Reactants β Products mapping
βββ Reaction conditions (T, P, time)
βββ Yields and selectivity
βββ Procedure steps
β
Validation Agent (cross-check extracted data)
β
Structured Output (JSON, CSV, database)
```
## Usage
```python
from chemeagle import ChemEagle
eagle = ChemEagle(llm_provider="anthropic")
# Extract from a chemistry paper
result = eagle.extract("paper.pdf")
# Extracted reactions
for rxn in result.reactions:
print(f"\nReaction {rxn.id}:")
print(f" Reactants: {rxn.reactants}")
print(f" Products: {rxn.products}")
print(f" Catalyst: {rxn.catalyst}")
print(f" Solvent: {rxn.solvent}")
print(f" Temperature: {rxn.temperature}")
print(f" Time: {rxn.time}")
print(f" Yield: {rxn.yield_percent}%")
print(f" SMILES: {rxn.product_smiles}")
# Extracted compounds
for compound in result.compounds:
print(f"{compound.name}: {compound.smiles}")
```
## Batch Processing
```python
# Process multiple papers
results = eagle.extract_batch(
input_dir="chemistry_papers/",
output_format="csv",
output_file="reactions_database.csv",
)
print(f"Papers processed: {results.papers_processed}")
print(f"Reactions extracted: {results.total_reactions}")
print(f"Unique compounds: {results.unique_compounds}")
```
## Chemical Entity Recognition
```python
# Standalone NER
entities = eagle.recognize_entities(
"The Suzuki coupling of 4-bromoanisole with phenylboronic "
"acid using Pd(PPh3)4 catalyst in THF/water at 80Β°C "
"gave 4-methoxybiphenyl in 95% yield."
)
for entity in entities:
print(f" [{entity.type}] {entity.text}")
if entity.smiles:
print(f" SMILES: {entity.smiles}")
# Output:
# [REACTANT] 4-bromoanisole β SMILES: COc1ccc(Br)cc1
# [REACTANT] phenylboronic acid β SMILES: OB(O)c1ccccc1
# [CATALYST] Pd(PPh3)4
# [SOLVENT] THF/water
# [CONDITION] 80Β°C
# [PRODUCT] 4-methoxybiphenyl β SMILES: COc1ccc(-c2ccccc2)cc1
# [YIELD] 95%
```
## Database Building
```python
# Build a searchable reaction database
from chemeagle import ReactionDatabase
db = ReactionDatabase("reactions.db")
# Add extracted reactions
db.add_from_extraction(result)
# Search by substrate
hits = db.search(reactant="bromoanisole", reaction_type="coupling")
for hit in hits:
print(f"{hit.reactants} β {hit.products} ({hit.yield_percent}%)")
print(f" Source: {hit.paper_doi}")
# Search by conditions
hits = db.search(catalyst="palladium", temperature_max=100)
# Export
db.export_csv("all_reactions.csv")
db.export_json("all_reactions.json")
```
## Use Cases
1. **Reaction mining**: Extract reactions from chemistry literature
2. **Database building**: Automated reaction database construction
3. **Systematic reviews**: Structured data from chemistry papers
4. **Synthesis planning**: Search conditions for target reactions
5. **Trend analysis**: Track reaction methodology evolution
## References
- [ChemEagle GitHub](https://github.com/CYF2000127/ChemEagle)
- [RDKit](https://www.rdkit.org/) β Chemistry toolkit
- [PubChem](https://pubchem.ncbi.nlm.nih.gov/) β Chemical database
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