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LiteLLM Minor Fixes + Improvements (#5474)

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* feat(proxy/_types.py): add lago billing to callbacks ui

Closes https://github.com/BerriAI/litellm/issues/5472

* fix(anthropic.py): return anthropic prompt caching information

Fixes https://github.com/BerriAI/litellm/issues/5364

* feat(bedrock/chat.py): support 'json_schema' for bedrock models

Closes https://github.com/BerriAI/litellm/issues/5434

* fix(bedrock/embed/embeddings.py): support async embeddings for amazon titan models

* fix: linting fixes

* fix: handle key errors

* fix(bedrock/chat.py): fix bedrock ai21 streaming object

* feat(bedrock/embed): support bedrock embedding optional params

* fix(databricks.py): fix usage chunk

* fix(internal_user_endpoints.py): apply internal user defaults, if user role updated

Fixes issue where user update wouldn't apply defaults

* feat(slack_alerting.py): provide multiple slack channels for a given alert type

multiple channels might be interested in receiving an alert for a given type

* docs(alerting.md): add multiple channel alerting to docs
This commit is contained in:
Krish Dholakia 2024-09-02 14:29:57 -07:00 • committed by GitHub
parent 02f288a8a3
commit f9e6507cd1
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22 changed files with 720 additions and 209 deletions
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17
litellm/main.py
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@ -5431,6 +5431,9 @@ def stream_chunk_builder(
# # Update usage information if needed
prompt_tokens = 0
completion_tokens = 0
## anthropic prompt caching information ##
cache_creation_input_tokens: Optional[int] = None
cache_read_input_tokens: Optional[int] = None
for chunk in chunks:
usage_chunk: Optional[Usage] = None
if "usage" in chunk:
@ -5442,6 +5445,13 @@ def stream_chunk_builder(
prompt_tokens = usage_chunk.get("prompt_tokens", 0) or 0
if "completion_tokens" in usage_chunk:
completion_tokens = usage_chunk.get("completion_tokens", 0) or 0
if "cache_creation_input_tokens" in usage_chunk:
cache_creation_input_tokens = usage_chunk.get(
"cache_creation_input_tokens"
)
if "cache_read_input_tokens" in usage_chunk:
cache_read_input_tokens = usage_chunk.get("cache_read_input_tokens")
try:
response["usage"]["prompt_tokens"] = prompt_tokens or token_counter(
model=model, messages=messages
@ -5460,6 +5470,13 @@ def stream_chunk_builder(
response["usage"]["prompt_tokens"] + response["usage"]["completion_tokens"]
)
if cache_creation_input_tokens is not None:
response["usage"][
"cache_creation_input_tokens"
] = cache_creation_input_tokens
if cache_read_input_tokens is not None:
response["usage"]["cache_read_input_tokens"] = cache_read_input_tokens
return convert_to_model_response_object(
response_object=response,
model_response_object=model_response,