Veterinary practices manage complex clinical workflows across multiple species, each with unique anatomy, physiology, and pharmacology. Chinese LLMs like DeepSeek V4, GLM-4, and Qwen3 can assist veterinarians by generating clinical documentation, suggesting differential diagnoses, checking drug interactions, and creating client-friendly educational materials. TokenEase's unified API provides veterinary practices with cost-effective access to these powerful models.
Transform examination findings, lab results, and procedures into structured veterinary medical records.
import requests
def generate_vet_record(exam_findings, history, diagnostics, species_breed):
response = requests.post(
"https://tokenease.io/v1/chat/completions",
headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
json={
"model": "deepseek-v4",
"messages": [
{"role": "system", "content": "You are a veterinary medical records specialist. Generate accurate SOAP notes following veterinary medical standards. Include species-specific considerations."},
{"role": "user", "content": f"Species/Breed: {species_breed}\nHistory: {history}\nFindings: {exam_findings}\nDiagnostics: {diagnostics}\n\nGenerate SOAP note."}
]
}
)
return response.json()["choices"][0]["message"]["content"]
history = "7-year-old MN Golden Retriever, presenting for lethargy and decreased appetite x 3 days. No vomiting or diarrhea. Drinking normally."
findings = "T: 39.2C, HR: 120, RR: 24. Pale MM. CRT 2.5s. Abdominal palpation: splenomegaly noted. No pain on palpation. LNs: mandibular mildly enlarged."
diagnostics = "CBC: HCT 28% (low), WBC 18,000 (high), platelets 85,000 (low). Chemistry: ALT 245 (high), ALP 180 (high). UA: 1.030, no active sediment."
record = generate_vet_record(findings, history, diagnostics, "Canine, Golden Retriever, 7Y MN")
Generate ranked differential diagnoses based on signalment, history, and clinical findings.
def generate_differentials(signalment, clinical_signs, diagnostic_results, prior_history):
response = requests.post(
"https://tokenease.io/v1/chat/completions",
headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
json={
"model": "qwen3-235b",
"messages": [
{"role": "system", "content": "Generate prioritized differential diagnoses for veterinary cases. Consider signalment, breed predispositions, and geographic relevance. Recommend next diagnostic steps."},
{"role": "user", "content": f"History: {prior_history}\nSignalment: {signalment}\nSigns: {clinical_signs}\nResults: {diagnostic_results}\n\nGenerate differentials."}
]
}
)
return response.json()["choices"][0]["message"]["content"]
signalment = "Feline, DSH, 12Y SF, indoor/outdoor, Midwest USA"
signs = "Weight loss 1.5kg over 2 months, polyuria/polydipsia, poor grooming, mild anemia"
results = "CBC: HCT 26%, mild non-regenerative anemia. Chemistry: BUN 45, Creatinine 2.8, SDMA 18, hyperglycemia 280. T4: 1.2 (low-normal). UA: USG 1.020, proteinuria 2+."
prior = "Previously healthy. Vaccines current. On flea prevention. Diet: dry kibble free choice."
diffs = generate_differentials(signalment, signs, results, prior)
Generate evidence-based treatment plans with dosing, monitoring schedules, and client instructions.
def generate_treatment_plan(diagnosis, patient_info, owner_constraints, practice_capabilities):
response = requests.post(
"https://tokenease.io/v1/chat/completions",
headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
json={
"model": "glm-4-plus",
"messages": [
{"role": "system", "content": "Generate veterinary treatment plans with appropriate drug dosing, monitoring, and client instructions. Consider owner compliance and financial constraints."},
{"role": "user", "content": f"Capabilities: {practice_capabilities}\nConstraints: {owner_constraints}\nPatient: {patient_info}\nDiagnosis: {diagnosis}\n\nGenerate treatment plan."}
]
}
)
return response.json()["choices"][0]["message"]["content"]
diagnosis = "Canine atopic dermatitis, secondary Malassezia dermatitis, mild otitis externa"
patient = "3Y MN Labrador, 32kg, otherwise healthy, no known drug allergies"
constraints = "Owner works full-time, prefers oral medications over frequent clinic visits. Budget-conscious."
capabilities = "In-house cytology, basic lab, no dermatology specialist referral within 100 miles"
plan = generate_treatment_plan(diagnosis, patient, constraints, capabilities)
Check for drug interactions across species and verify dosing calculations for veterinary medications.
def check_vet_medications(drug_list, patient_profile, concurrent_conditions):
response = requests.post(
"https://tokenease.io/v1/chat/completions",
headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
json={
"model": "kimi-k2",
"messages": [
{"role": "system", "content": "Check veterinary drug interactions and verify dosing. Flag contraindications, monitoring requirements, and species-specific cautions."},
{"role": "user", "content": f"Conditions: {concurrent_conditions}\nPatient: {patient_profile}\nDrugs:\n{drug_list}\n\nCheck interactions and dosing."}
]
}
)
return response.json()["choices"][0]["message"]["content"]
drugs = """
- Carprofen 75mg PO SID (for OA pain)
- Enalapril 5mg PO SID (for CHF)
- Furosemide 20mg PO BID (for CHF)
- Gabapentin 100mg PO BID (for anxiety)
"""
patient = "Canine, Beagle, 8Y FS, 11kg, heart murmur grade III/VI, mild renal insufficiency (CRE 1.8)"
conditions = "Degenerative joint disease, compensated CHF, Stage 2 CKD, generalized anxiety"
check = check_vet_medications(drugs, patient, conditions)
Translate complex medical information into client-friendly explanations, discharge instructions, and preventive care reminders.
def generate_client_communication(medical_findings, diagnosis, treatment_plan, client_education_level):
response = requests.post(
"https://tokenease.io/v1/chat/completions",
headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
json={
"model": "deepseek-v4",
"messages": [
{"role": "system", "content": f"Explain veterinary medical information to pet owners at a {client_education_level} level. Be empathetic, clear, and actionable. Avoid jargon."},
{"role": "user", "content": f"Education: {client_education_level}\nPlan: {treatment_plan}\nDiagnosis: {diagnosis}\nFindings: {medical_findings}\n\nWrite client communication."}
]
}
)
return response.json()["choices"][0]["message"]["content"]
findings = "Your cat has elevated kidney values and diluted urine, suggesting her kidneys aren't concentrating urine properly."
diagnosis = "Chronic kidney disease, early stage (IRIS Stage 2)"
plan = "Switch to renal diet, subcutaneous fluids 100ml every other day, recheck bloodwork in 4 weeks, blood pressure check"
education = "general public"
communication = generate_client_communication(findings, diagnosis, plan, education)
Generate preventive care recommendations based on breed predispositions, age, and lifestyle factors.
def assess_breed_risks(breed, age, lifestyle, geographic_region, current_health_status):
response = requests.post(
"https://tokenease.io/v1/chat/completions",
headers={"Authorization": "Bearer YOUR_TOKENEASE_API_KEY"},
json={
"model": "qwen3-235b",
"messages": [
{"role": "system", "content": "Assess breed-specific health risks and generate preventive care recommendations. Consider age-related screening, lifestyle modifications, and early detection strategies."},
{"role": "user", "content": f"Health: {current_health_status}\nRegion: {geographic_region}\nLifestyle: {lifestyle}\nAge: {age}\nBreed: {breed}\n\nAssess risks and recommend prevention."}
]
}
)
return response.json()["choices"][0]["message"]["content"]
breed = "French Bulldog"
age = "4 years old"
lifestyle = "Apartment dwelling, limited exercise, indoor primarily, no other pets"
region = "Northeast USA, seasonal temperature extremes"
health = "Currently healthy. No respiratory issues. Weight 12kg (ideal). Brachycephalic but tolerates moderate activity."
assessment = assess_breed_risks(breed, age, lifestyle, region, health)
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