litellm-mirror/litellm/proxy/db/create_views.py
Krish Dholakia bd17424c4b
LiteLLM Minor Fixes & Improvements (09/26/2024) (#5925) (#5937)
* LiteLLM Minor Fixes & Improvements (09/26/2024)  (#5925)

* fix(litellm_logging.py): don't initialize prometheus_logger if non premium user

Prevents bad error messages in logs

Fixes https://github.com/BerriAI/litellm/issues/5897

* Add Support for Custom Providers in Vision and Function Call Utils (#5688)

* Add Support for Custom Providers in Vision and Function Call Utils Lookup

* Remove parallel function call due to missing model info param

* Add Unit Tests for Vision and Function Call Changes

* fix-#5920: set header value to string to fix "'int' object has no att… (#5922)

* LiteLLM Minor Fixes & Improvements (09/24/2024) (#5880)

* LiteLLM Minor Fixes & Improvements (09/23/2024)  (#5842)

* feat(auth_utils.py): enable admin to allow client-side credentials to be passed

Makes it easier for devs to experiment with finetuned fireworks ai models

* feat(router.py): allow setting configurable_clientside_auth_params for a model

Closes https://github.com/BerriAI/litellm/issues/5843

* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit

Fixes https://github.com/BerriAI/litellm/issues/5850

* fix(azure_ai/): support content list for azure ai

Fixes https://github.com/BerriAI/litellm/issues/4237

* fix(litellm_logging.py): always set saved_cache_cost

Set to 0 by default

* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing

handles calling 405b+ size models

* fix(slack_alerting.py): fix error alerting for failed spend tracking

Fixes regression with slack alerting error monitoring

* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error

* docs(bedrock.md): add llama3-1 models

* test: fix tests

* fix(azure_ai/chat): fix transformation for azure ai calls

* feat(azure_ai/embed): Add azure ai embeddings support

Closes https://github.com/BerriAI/litellm/issues/5861

* fix(azure_ai/embed): enable async embedding

* feat(azure_ai/embed): support azure ai multimodal embeddings

* fix(azure_ai/embed): support async multi modal embeddings

* feat(together_ai/embed): support together ai embedding calls

* feat(rerank/main.py): log source documents for rerank endpoints to langfuse

improves rerank endpoint logging

* fix(langfuse.py): support logging `/audio/speech` input to langfuse

* test(test_embedding.py): fix test

* test(test_completion_cost.py): fix helper util

* fix-#5920: set header value to string to fix "'int' object has no attribute 'encode'"

---------

Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>

* Revert "fix-#5920: set header value to string to fix "'int' object has no att…" (#5926)

This reverts commit a554ae2695.

* build(model_prices_and_context_window.json): add azure ai cohere rerank model pricing

Enables cost tracking for azure ai cohere rerank models

* fix(litellm_logging.py): fix debug log to be clearer

Closes https://github.com/BerriAI/litellm/issues/5909

* test(test_utils.py): fix test name

* fix(azure_ai/cost_calculator.py): support cost tracking for azure ai rerank models

* fix(azure_ai): fix azure ai base model cost tracking for rerank endpoints

* fix(converse_handler.py): support new llama 3-2 models

Fixes https://github.com/BerriAI/litellm/issues/5901

* fix(litellm_logging.py): ensure response is redacted for standard message logging

Fixes https://github.com/BerriAI/litellm/issues/5890#issuecomment-2378242360

* fix(cost_calculator.py): use 'get_model_info' for cohere rerank cost calculation

allows user to set custom cost for model

* fix(config.yml): fix docker hub auht

* build(config.yml): add docker auth to all tests

* fix(db/create_views.py): fix linting error

* fix(main.py): fix circular import

* fix(azure_ai/__init__.py): fix circular import

* fix(main.py): fix import

* fix: fix linting errors

* test: fix test

* fix(proxy_server.py): pass premium user value on startup

used for prometheus init

---------

Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>

* handle streaming for azure ai studio error

* [Perf Proxy] parallel request limiter - use one cache update call (#5932)

* fix parallel request limiter - use one cache update call

* ci/cd run again

* run ci/cd again

* use docker username password

* fix config.yml

* fix config

* fix config

* fix config.yml

* ci/cd run again

* use correct typing for batch set cache

* fix async_set_cache_pipeline

* fix only check user id tpm / rpm limits when limits set

* fix test_openai_azure_embedding_with_oidc_and_cf

* test: fix test

* test(test_rerank.py): fix test

---------

Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
2024-09-27 17:54:13 -07:00

227 lines
7.1 KiB
Python

from typing import Any
from litellm import verbose_logger
_db = Any
async def create_missing_views(db: _db):
"""
--------------------------------------------------
NOTE: Copy of `litellm/db_scripts/create_views.py`.
--------------------------------------------------
Checks if the LiteLLM_VerificationTokenView and MonthlyGlobalSpend exists in the user's db.
LiteLLM_VerificationTokenView: This view is used for getting the token + team data in user_api_key_auth
MonthlyGlobalSpend: This view is used for the admin view to see global spend for this month
If the view doesn't exist, one will be created.
"""
try:
# Try to select one row from the view
await db.query_raw("""SELECT 1 FROM "LiteLLM_VerificationTokenView" LIMIT 1""")
print("LiteLLM_VerificationTokenView Exists!") # noqa
except Exception as e:
# If an error occurs, the view does not exist, so create it
await db.execute_raw(
"""
CREATE VIEW "LiteLLM_VerificationTokenView" AS
SELECT
v.*,
t.spend AS team_spend,
t.max_budget AS team_max_budget,
t.tpm_limit AS team_tpm_limit,
t.rpm_limit AS team_rpm_limit
FROM "LiteLLM_VerificationToken" v
LEFT JOIN "LiteLLM_TeamTable" t ON v.team_id = t.team_id;
"""
)
print("LiteLLM_VerificationTokenView Created!") # noqa
try:
await db.query_raw("""SELECT 1 FROM "MonthlyGlobalSpend" LIMIT 1""")
print("MonthlyGlobalSpend Exists!") # noqa
except Exception as e:
sql_query = """
CREATE OR REPLACE VIEW "MonthlyGlobalSpend" AS
SELECT
DATE("startTime") AS date,
SUM("spend") AS spend
FROM
"LiteLLM_SpendLogs"
WHERE
"startTime" >= (CURRENT_DATE - INTERVAL '30 days')
GROUP BY
DATE("startTime");
"""
await db.execute_raw(query=sql_query)
print("MonthlyGlobalSpend Created!") # noqa
try:
await db.query_raw("""SELECT 1 FROM "Last30dKeysBySpend" LIMIT 1""")
print("Last30dKeysBySpend Exists!") # noqa
except Exception as e:
sql_query = """
CREATE OR REPLACE VIEW "Last30dKeysBySpend" AS
SELECT
L."api_key",
V."key_alias",
V."key_name",
SUM(L."spend") AS total_spend
FROM
"LiteLLM_SpendLogs" L
LEFT JOIN
"LiteLLM_VerificationToken" V
ON
L."api_key" = V."token"
WHERE
L."startTime" >= (CURRENT_DATE - INTERVAL '30 days')
GROUP BY
L."api_key", V."key_alias", V."key_name"
ORDER BY
total_spend DESC;
"""
await db.execute_raw(query=sql_query)
print("Last30dKeysBySpend Created!") # noqa
try:
await db.query_raw("""SELECT 1 FROM "Last30dModelsBySpend" LIMIT 1""")
print("Last30dModelsBySpend Exists!") # noqa
except Exception as e:
sql_query = """
CREATE OR REPLACE VIEW "Last30dModelsBySpend" AS
SELECT
"model",
SUM("spend") AS total_spend
FROM
"LiteLLM_SpendLogs"
WHERE
"startTime" >= (CURRENT_DATE - INTERVAL '30 days')
AND "model" != ''
GROUP BY
"model"
ORDER BY
total_spend DESC;
"""
await db.execute_raw(query=sql_query)
print("Last30dModelsBySpend Created!") # noqa
try:
await db.query_raw("""SELECT 1 FROM "MonthlyGlobalSpendPerKey" LIMIT 1""")
print("MonthlyGlobalSpendPerKey Exists!") # noqa
except Exception as e:
sql_query = """
CREATE OR REPLACE VIEW "MonthlyGlobalSpendPerKey" AS
SELECT
DATE("startTime") AS date,
SUM("spend") AS spend,
api_key as api_key
FROM
"LiteLLM_SpendLogs"
WHERE
"startTime" >= (CURRENT_DATE - INTERVAL '30 days')
GROUP BY
DATE("startTime"),
api_key;
"""
await db.execute_raw(query=sql_query)
print("MonthlyGlobalSpendPerKey Created!") # noqa
try:
await db.query_raw(
"""SELECT 1 FROM "MonthlyGlobalSpendPerUserPerKey" LIMIT 1"""
)
print("MonthlyGlobalSpendPerUserPerKey Exists!") # noqa
except Exception as e:
sql_query = """
CREATE OR REPLACE VIEW "MonthlyGlobalSpendPerUserPerKey" AS
SELECT
DATE("startTime") AS date,
SUM("spend") AS spend,
api_key as api_key,
"user" as "user"
FROM
"LiteLLM_SpendLogs"
WHERE
"startTime" >= (CURRENT_DATE - INTERVAL '30 days')
GROUP BY
DATE("startTime"),
"user",
api_key;
"""
await db.execute_raw(query=sql_query)
print("MonthlyGlobalSpendPerUserPerKey Created!") # noqa
try:
await db.query_raw("""SELECT 1 FROM DailyTagSpend LIMIT 1""")
print("DailyTagSpend Exists!") # noqa
except Exception as e:
sql_query = """
CREATE OR REPLACE VIEW DailyTagSpend AS
SELECT
jsonb_array_elements_text(request_tags) AS individual_request_tag,
DATE(s."startTime") AS spend_date,
COUNT(*) AS log_count,
SUM(spend) AS total_spend
FROM "LiteLLM_SpendLogs" s
GROUP BY individual_request_tag, DATE(s."startTime");
"""
await db.execute_raw(query=sql_query)
print("DailyTagSpend Created!") # noqa
try:
await db.query_raw("""SELECT 1 FROM "Last30dTopEndUsersSpend" LIMIT 1""")
print("Last30dTopEndUsersSpend Exists!") # noqa
except Exception as e:
sql_query = """
CREATE VIEW "Last30dTopEndUsersSpend" AS
SELECT end_user, COUNT(*) AS total_events, SUM(spend) AS total_spend
FROM "LiteLLM_SpendLogs"
WHERE end_user <> '' AND end_user <> user
AND "startTime" >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY end_user
ORDER BY total_spend DESC
LIMIT 100;
"""
await db.execute_raw(query=sql_query)
print("Last30dTopEndUsersSpend Created!") # noqa
return
async def should_create_missing_views(db: _db) -> bool:
"""
Run only on first time startup.
If SpendLogs table already has values, then don't create views on startup.
"""
sql_query = """
SELECT reltuples::BIGINT
FROM pg_class
WHERE oid = '"LiteLLM_SpendLogs"'::regclass;
"""
result = await db.query_raw(query=sql_query)
verbose_logger.debug("Estimated Row count of LiteLLM_SpendLogs = {}".format(result))
if (
result
and isinstance(result, list)
and len(result) > 0
and isinstance(result[0], dict)
and "reltuples" in result[0]
and result[0]["reltuples"]
and (result[0]["reltuples"] == 0 or result[0]["reltuples"] == -1)
):
verbose_logger.debug("Should create views")
return True
return False