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(feat) update /daily metrics

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ishaan-jaff 2024-02-27 18:33:59 -08:00
parent 7cabc6ac56
commit d19370083d
2 changed files with 58 additions and 26 deletions
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53
docs/my-website/docs/proxy/metrics.md
View file

@ -3,30 +3,37 @@
## Response format
```json
[
{
"daily_spend": 7.9261938052047e+16,
"day": "2024-02-01T00:00:00",
"spend_per_model": {"azure/gpt-4": 7.9261938052047e+16},
"spend_per_api_key": {
"76": 914495704992000.0,
"12": 905726697912000.0,
"71": 866312628003000.0,
"28": 865461799332000.0,
"13": 859151538396000.0
daily_spend = [
{
"daily_spend": 7.9261938052047e+16,
"day": "2024-02-01T00:00:00",
"spend_per_model": {"azure/gpt-4": 7.9261938052047e+16},
"spend_per_api_key": {
"76": 914495704992000.0,
"12": 905726697912000.0,
"71": 866312628003000.0,
"28": 865461799332000.0,
"13": 859151538396000.0
}
},
{
"daily_spend": 7.938489251309491e+16,
"day": "2024-02-02T00:00:00",
"spend_per_model": {"gpt-3.5": 7.938489251309491e+16},
"spend_per_api_key": {
"91": 896805036036000.0,
"78": 889692646082000.0,
"49": 885386687861000.0,
"28": 873869890984000.0,
"56": 867398637692000.0
}
}
},
{
"daily_spend": 7.938489251309491e+16,
"day": "2024-02-02T00:00:00",
"spend_per_model": {"gpt-3.5": 7.938489251309491e+16},
"spend_per_api_key": {
"91": 896805036036000.0,
"78": 889692646082000.0,
"49": 885386687861000.0,
"28": 873869890984000.0,
"56": 867398637692000.0
}
}
],
total_spend = 200,
top_models = {"gpt4": 0.2, "vertexai/gemini-pro":10},
top_api_keys = {"899922": 0.9, "838hcjd999seerr88": 20}
]
```

31
litellm/integrations/clickhouse.py
View file

@ -62,7 +62,6 @@ def build_daily_metrics():
)
# get daily spend per model
daily_spend_per_model = click_house_client.query_df(
"""
SELECT sumMerge(DailySpend) as daily_spend, day, model FROM daily_aggregated_spend_per_model GROUP BY day, model
@ -82,6 +81,7 @@ def build_daily_metrics():
# Display the resulting dictionary
# get daily spend per API key
daily_spend_per_api_key = click_house_client.query_df(
"""
SELECT
@ -122,6 +122,23 @@ def build_daily_metrics():
# Display the resulting dictionary
# Calculate total spend across all days
total_spend = daily_spend["daily_spend"].sum()
# Identify top models and top API keys with the highest spend across all days
top_models = {}
top_api_keys = {}
for day, spend_per_model in result_dict.items():
for model, model_spend in spend_per_model.items():
if model not in top_models or model_spend > top_models[model]:
top_models[model] = model_spend
for day, spend_per_api_key in api_key_result_dict.items():
for api_key, api_key_spend in spend_per_api_key.items():
if api_key not in top_api_keys or api_key_spend > top_api_keys[api_key]:
top_api_keys[api_key] = api_key_spend
# for each day in daily spend, look up the day in result_dict and api_key_result_dict
# Assuming daily_spend DataFrame has 'day' column
result = []
@ -143,8 +160,16 @@ def build_daily_metrics():
result.append(data_day)
# print("FINAL daily metric", result)
return result
data_to_return = {}
data_to_return["daily_spend"] = result
data_to_return["total_spend"] = total_spend
data_to_return["top_models"] = top_models
data_to_return["top_api_keys"] = top_api_keys
return data_to_return
# build_daily_metrics()
def _create_clickhouse_material_views(client=None, table_names=[]):