import requestsimport json# Call the eval endpointurl = "https://api.berri.ai/eval"data = {"instance_id": "44b52369-7852-487f-ba16-476f0ebeb372", "user_email": "krrish@berri.ai"}# Always pass in a .csv. Ensure all your questions are under a column called 'Questions'files = {'data_source': open('test_set.csv', 'rb')}response = requests.post(url, files=files, data=data)print(response.text)api_endpoint = response.json()
Endpoints
Run Testing
How to evaluate your Berri App/Instance
POST
/
eval
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import requestsimport json# Call the eval endpointurl = "https://api.berri.ai/eval"data = {"instance_id": "44b52369-7852-487f-ba16-476f0ebeb372", "user_email": "krrish@berri.ai"}# Always pass in a .csv. Ensure all your questions are under a column called 'Questions'files = {'data_source': open('test_set.csv', 'rb')}response = requests.post(url, files=files, data=data)print(response.text)api_endpoint = response.json()
This must be a .csv. Ensure all questions are under a column called
‘Questions’.
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import requestsimport json# Call the eval endpointurl = "https://api.berri.ai/eval"data = {"instance_id": "44b52369-7852-487f-ba16-476f0ebeb372", "user_email": "krrish@berri.ai"}# Always pass in a .csv. Ensure all your questions are under a column called 'Questions'files = {'data_source': open('test_set.csv', 'rb')}response = requests.post(url, files=files, data=data)print(response.text)api_endpoint = response.json()