v0 clickhouse

cookbook/misc/clickhouse.py

@@ -0,0 +1,72 @@
+import clickhouse_connect
+
+# client = clickhouse_connect.get_client(
+#     host='hjs1z7j37j.us-east1.gcp.clickhouse.cloud',
+#     port=8443,
+#     username='default',
+#     password='M~PimRs~c3Z6b',
+#     secure=False
+# )
+import clickhouse_connect
+
+client = clickhouse_connect.get_client()
+
+
+row1 = [
+    "123456",  # request_id
+    "GET",  # call_type
+    "api_key_123",  # api_key
+    50.00,  # spend
+    1000,  # total_tokens
+    800,  # prompt_tokens
+    200,  # completion_tokens
+    "2024-02-24 12:00",  # startTime (replace with the actual timestamp)
+    "2024-02-24 13:00",  # endTime (replace with the actual timestamp)
+    "gpt-3.5",  # model
+    "user123",  # user
+    '{"key": "value"}',  # metadata (replace with valid JSON)
+    True,  # cache_hit
+    "cache_key_123",  # cache_key
+    "tag1,tag2",  # request_tags
+]
+
+row2 = [
+    "789012",  # request_id
+    "POST",  # call_type
+    "api_key_456",  # api_key
+    30.50,  # spend
+    800,  # total_tokens
+    600,  # prompt_tokens
+    200,  # completion_tokens
+    "2024-02-24 14:00",  # startTime (replace with the actual timestamp)
+    "2024-02-24 15:00",  # endTime (replace with the actual timestamp)
+    "gpt-4.0",  # model
+    "user456",  # user
+    '{"key": "value"}',  # metadata (replace with valid JSON)
+    False,  # cache_hit
+    "cache_key_789",  # cache_key
+    "tag3,tag4",  # request_tags
+]
+
+data = [row1, row2]
+client.insert(
+    "spend_logs",
+    data,
+    column_names=[
+        "request_id",
+        "call_type",
+        "api_key",
+        "spend",
+        "total_tokens",
+        "prompt_tokens",
+        "completion_tokens",
+        "startTime",
+        "endTime",
+        "model",
+        "user",
+        "metadata",
+        "cache_hit",
+        "cache_key",
+        "request_tags",
+    ],
+)

litellm/integrations/clickhouse.py

@@ -0,0 +1,99 @@
+# callback to make a request to an API endpoint
+
+#### What this does ####
+#    On success, logs events to Promptlayer
+import dotenv, os
+import requests
+
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.caching import DualCache
+
+from typing import Literal, Union
+
+dotenv.load_dotenv()  # Loading env variables using dotenv
+import traceback
+
+
+#### What this does ####
+#    On success + failure, log events to Supabase
+
+import dotenv, os
+import requests
+
+dotenv.load_dotenv()  # Loading env variables using dotenv
+import traceback
+import datetime, subprocess, sys
+import litellm, uuid
+from litellm._logging import print_verbose, verbose_logger
+
+
+class ClickhouseLogger:
+    # Class variables or attributes
+    def __init__(self, endpoint=None, headers=None):
+        import clickhouse_connect
+
+        print_verbose(
+            f"ClickhouseLogger init, host {os.getenv('CLICKHOUSE_HOST')}, port {os.getenv('CLICKHOUSE_PORT')}, username {os.getenv('CLICKHOUSE_USERNAME')}"
+        )
+
+        client = clickhouse_connect.get_client(
+            host=os.getenv("CLICKHOUSE_HOST"),
+            port=os.getenv("CLICKHOUSE_PORT"),
+            username=os.getenv("CLICKHOUSE_USERNAME"),
+            password=os.getenv("CLICKHOUSE_PASSWORD"),
+        )
+        self.client = client
+
+    # This is sync, because we run this in a separate thread. Running in a sepearate thread ensures it will never block an LLM API call
+    # Experience with s3, Langfuse shows that async logging events are complicated and can block LLM calls
+    def log_event(
+        self, kwargs, response_obj, start_time, end_time, user_id, print_verbose
+    ):
+        try:
+            verbose_logger.debug(
+                f"ClickhouseLogger Logging - Enters logging function for model {kwargs}"
+            )
+
+            # construct payload to send custom logger
+            # follows the same params as langfuse.py
+            litellm_params = kwargs.get("litellm_params", {})
+            metadata = (
+                litellm_params.get("metadata", {}) or {}
+            )  # if litellm_params['metadata'] == None
+            messages = kwargs.get("messages")
+            cost = kwargs.get("response_cost", 0.0)
+            optional_params = kwargs.get("optional_params", {})
+            call_type = kwargs.get("call_type", "litellm.completion")
+            cache_hit = kwargs.get("cache_hit", False)
+            usage = response_obj["usage"]
+            id = response_obj.get("id", str(uuid.uuid4()))
+
+            from litellm.proxy.utils import get_logging_payload
+
+            payload = get_logging_payload(
+                kwargs=kwargs,
+                response_obj=response_obj,
+                start_time=start_time,
+                end_time=end_time,
+            )
+            # Build the initial payload
+
+            # Ensure everything in the payload is converted to str
+            for key, value in payload.items():
+                try:
+                    payload[key] = str(value)
+                except:
+                    # non blocking if it can't cast to a str
+                    pass
+
+            print_verbose(f"\nGeneric Logger - Logging payload = {payload}")
+
+            # make request to endpoint with payload
+            # print_verbose(
+            #     f"Generic Logger - final response status = {response_status}, response text = {response_text}"
+            # )
+            # return response
+        except Exception as e:
+            traceback.print_exc()
+            verbose_logger.debug(f"Generic - {str(e)}\n{traceback.format_exc()}")
+            pass