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https://github.com/BerriAI/litellm.git
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Litellm ruff linting enforcement (#5992)
* ci(config.yml): add a 'check_code_quality' step Addresses https://github.com/BerriAI/litellm/issues/5991 * ci(config.yml): check why circle ci doesn't pick up this test * ci(config.yml): fix to run 'check_code_quality' tests * fix(__init__.py): fix unprotected import * fix(__init__.py): don't remove unused imports * build(ruff.toml): update ruff.toml to ignore unused imports * fix: fix: ruff + pyright - fix linting + type-checking errors * fix: fix linting errors * fix(lago.py): fix module init error * fix: fix linting errors * ci(config.yml): cd into correct dir for checks * fix(proxy_server.py): fix linting error * fix(utils.py): fix bare except causes ruff linting errors * fix: ruff - fix remaining linting errors * fix(clickhouse.py): use standard logging object * fix(__init__.py): fix unprotected import * fix: ruff - fix linting errors * fix: fix linting errors * ci(config.yml): cleanup code qa step (formatting handled in local_testing) * fix(_health_endpoints.py): fix ruff linting errors * ci(config.yml): just use ruff in check_code_quality pipeline for now * build(custom_guardrail.py): include missing file * style(embedding_handler.py): fix ruff check
This commit is contained in:
Krish Dholakia
GitHub
parent
3fc4ae0d65
commit
d57be47b0f
263 changed files with 1687 additions and 3320 deletions
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@ -1,6 +1,10 @@
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import requests, traceback, json, os
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import json
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import os
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import traceback
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import types
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import requests
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class LiteDebugger:
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user_email = None
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@ -17,23 +21,17 @@ class LiteDebugger:
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email or os.getenv("LITELLM_TOKEN") or os.getenv("LITELLM_EMAIL")
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)
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if (
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self.user_email == None
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self.user_email is None
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): # if users are trying to use_client=True but token not set
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raise ValueError(
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"litellm.use_client = True but no token or email passed. Please set it in litellm.token"
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)
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self.dashboard_url = "https://admin.litellm.ai/" + self.user_email
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try:
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print(
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f"\033[92mHere's your LiteLLM Dashboard 👉 \033[94m\033[4m{self.dashboard_url}\033[0m"
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)
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except:
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print(f"Here's your LiteLLM Dashboard 👉 {self.dashboard_url}")
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if self.user_email == None:
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if self.user_email is None:
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raise ValueError(
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"[Non-Blocking Error] LiteLLMDebugger: Missing LITELLM_TOKEN. Set it in your environment. Eg.: os.environ['LITELLM_TOKEN']= <your_email>"
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)
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except Exception as e:
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except Exception:
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raise ValueError(
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"[Non-Blocking Error] LiteLLMDebugger: Missing LITELLM_TOKEN. Set it in your environment. Eg.: os.environ['LITELLM_TOKEN']= <your_email>"
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)
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@ -49,123 +47,18 @@ class LiteDebugger:
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litellm_params,
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optional_params,
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):
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print_verbose(
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f"LiteDebugger: Pre-API Call Logging for call id {litellm_call_id}"
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)
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try:
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print_verbose(
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f"LiteLLMDebugger: Logging - Enters input logging function for model {model}"
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)
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def remove_key_value(dictionary, key):
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new_dict = dictionary.copy() # Create a copy of the original dictionary
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new_dict.pop(key) # Remove the specified key-value pair from the copy
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return new_dict
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updated_litellm_params = remove_key_value(litellm_params, "logger_fn")
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if call_type == "embedding":
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for (
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message
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) in (
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messages
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): # assuming the input is a list as required by the embedding function
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litellm_data_obj = {
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"model": model,
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"messages": [{"role": "user", "content": message}],
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"end_user": end_user,
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"status": "initiated",
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"litellm_call_id": litellm_call_id,
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"user_email": self.user_email,
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"litellm_params": updated_litellm_params,
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"optional_params": optional_params,
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}
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print_verbose(
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f"LiteLLMDebugger: Logging - logged data obj {litellm_data_obj}"
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)
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response = requests.post(
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url=self.api_url,
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headers={"content-type": "application/json"},
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data=json.dumps(litellm_data_obj),
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)
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print_verbose(f"LiteDebugger: embedding api response - {response.text}")
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elif call_type == "completion":
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litellm_data_obj = {
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"model": model,
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"messages": messages
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if isinstance(messages, list)
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else [{"role": "user", "content": messages}],
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"end_user": end_user,
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"status": "initiated",
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"litellm_call_id": litellm_call_id,
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"user_email": self.user_email,
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"litellm_params": updated_litellm_params,
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"optional_params": optional_params,
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}
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print_verbose(
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f"LiteLLMDebugger: Logging - logged data obj {litellm_data_obj}"
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)
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response = requests.post(
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url=self.api_url,
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headers={"content-type": "application/json"},
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data=json.dumps(litellm_data_obj),
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)
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print_verbose(
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f"LiteDebugger: completion api response - {response.text}"
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)
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except:
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print_verbose(
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f"[Non-Blocking Error] LiteDebugger: Logging Error - {traceback.format_exc()}"
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)
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pass
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"""
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This integration is not implemented yet.
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"""
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return
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def post_call_log_event(
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self, original_response, litellm_call_id, print_verbose, call_type, stream
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):
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print_verbose(
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f"LiteDebugger: Post-API Call Logging for call id {litellm_call_id}"
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)
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try:
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if call_type == "embedding":
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litellm_data_obj = {
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"status": "received",
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"additional_details": {
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"original_response": str(
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original_response["data"][0]["embedding"][:5]
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)
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}, # don't store the entire vector
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"litellm_call_id": litellm_call_id,
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"user_email": self.user_email,
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}
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elif call_type == "completion" and not stream:
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litellm_data_obj = {
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"status": "received",
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"additional_details": {"original_response": original_response},
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"litellm_call_id": litellm_call_id,
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"user_email": self.user_email,
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}
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elif call_type == "completion" and stream:
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litellm_data_obj = {
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"status": "received",
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"additional_details": {
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"original_response": "Streamed response"
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if isinstance(original_response, types.GeneratorType)
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else original_response
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},
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"litellm_call_id": litellm_call_id,
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"user_email": self.user_email,
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}
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print_verbose(f"litedebugger post-call data object - {litellm_data_obj}")
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response = requests.post(
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url=self.api_url,
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headers={"content-type": "application/json"},
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data=json.dumps(litellm_data_obj),
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)
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print_verbose(f"LiteDebugger: api response - {response.text}")
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except:
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print_verbose(
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f"[Non-Blocking Error] LiteDebugger: Logging Error - {traceback.format_exc()}"
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)
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"""
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This integration is not implemented yet.
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"""
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return
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def log_event(
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self,
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@ -178,85 +71,7 @@ class LiteDebugger:
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call_type,
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stream=False,
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):
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print_verbose(
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f"LiteDebugger: Success/Failure Call Logging for call id {litellm_call_id}"
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)
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try:
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print_verbose(
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f"LiteLLMDebugger: Success/Failure Logging - Enters handler logging function for function {call_type} and stream set to {stream} with response object {response_obj}"
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)
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total_cost = 0 # [TODO] implement cost tracking
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response_time = (end_time - start_time).total_seconds()
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if call_type == "completion" and stream == False:
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litellm_data_obj = {
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"response_time": response_time,
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"total_cost": total_cost,
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"response": response_obj["choices"][0]["message"]["content"],
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"litellm_call_id": litellm_call_id,
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"status": "success",
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}
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print_verbose(
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f"LiteDebugger: Logging - final data object: {litellm_data_obj}"
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)
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response = requests.post(
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url=self.api_url,
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headers={"content-type": "application/json"},
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data=json.dumps(litellm_data_obj),
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)
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elif call_type == "embedding":
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litellm_data_obj = {
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"response_time": response_time,
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"total_cost": total_cost,
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"response": str(response_obj["data"][0]["embedding"][:5]),
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"litellm_call_id": litellm_call_id,
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"status": "success",
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}
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response = requests.post(
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url=self.api_url,
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headers={"content-type": "application/json"},
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data=json.dumps(litellm_data_obj),
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)
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elif call_type == "completion" and stream == True:
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if len(response_obj["content"]) > 0: # don't log the empty strings
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litellm_data_obj = {
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"response_time": response_time,
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"total_cost": total_cost,
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"response": response_obj["content"],
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"litellm_call_id": litellm_call_id,
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"status": "success",
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}
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print_verbose(
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f"LiteDebugger: Logging - final data object: {litellm_data_obj}"
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)
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response = requests.post(
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url=self.api_url,
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headers={"content-type": "application/json"},
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data=json.dumps(litellm_data_obj),
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)
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elif "error" in response_obj:
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if "Unable to map your input to a model." in response_obj["error"]:
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total_cost = 0
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litellm_data_obj = {
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"response_time": response_time,
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"model": response_obj["model"],
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"total_cost": total_cost,
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"error": response_obj["error"],
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"end_user": end_user,
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"litellm_call_id": litellm_call_id,
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"status": "failure",
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"user_email": self.user_email,
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}
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print_verbose(
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f"LiteDebugger: Logging - final data object: {litellm_data_obj}"
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)
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response = requests.post(
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url=self.api_url,
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headers={"content-type": "application/json"},
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data=json.dumps(litellm_data_obj),
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)
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print_verbose(f"LiteDebugger: api response - {response.text}")
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except:
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print_verbose(
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f"[Non-Blocking Error] LiteDebugger: Logging Error - {traceback.format_exc()}"
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)
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pass
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"""
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This integration is not implemented yet.
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"""
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return
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