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72 lines
1.8 KiB
Python
72 lines
1.8 KiB
Python
import clickhouse_connect
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import datetime as datetime
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import os
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client = clickhouse_connect.get_client(
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host=os.getenv("CLICKHOUSE_HOST"),
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port=int(os.getenv("CLICKHOUSE_PORT")),
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username=os.getenv("CLICKHOUSE_USERNAME"),
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password=os.getenv("CLICKHOUSE_PASSWORD"),
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)
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import clickhouse_connect
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row1 = [
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"ishaan", # request_id
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"GET", # call_type
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"api_key_123", # api_key
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50.00, # spend
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1000, # total_tokens
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800, # prompt_tokens
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200, # completion_tokens
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datetime.datetime.now(), # startTime (replace with the actual timestamp)
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datetime.datetime.now(), # endTime (replace with the actual timestamp)
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"gpt-3.5", # model
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"user123", # user
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'{"key": "value"}', # metadata (replace with valid JSON)
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"True", # cache_hit
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"cache_key_123", # cache_key
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"tag1,tag2", # request_tags
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]
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row2 = [
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"jaffer", # request_id
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"POST", # call_type
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"api_key_456", # api_key
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30.50, # spend
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800, # total_tokens
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600, # prompt_tokens
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200, # completion_tokens
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datetime.datetime.now(), # startTime (replace with the actual timestamp)
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datetime.datetime.now(), # endTime (replace with the actual timestamp)
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"gpt-4.0", # model
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"user456", # user
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'{"key": "value"}', # metadata (replace with valid JSON)
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"False", # cache_hit
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"cache_key_789", # cache_key
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"tag3,tag4", # request_tags
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]
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data = [row1, row2]
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resp = client.insert(
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"spend_logs",
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data,
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column_names=[
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"request_id",
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"call_type",
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"api_key",
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"spend",
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"total_tokens",
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"prompt_tokens",
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"completion_tokens",
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"startTime",
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"endTime",
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"model",
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"user",
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"metadata",
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"cache_hit",
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"cache_key",
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"request_tags",
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],
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)
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print(resp)
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