forked from phoenix/litellm-mirror
Merge branch 'main' into litellm_claude_3_bedrock_access
This commit is contained in:
Krish Dholakia
GitHub
commit
5b3459d759
26 changed files with 529 additions and 70 deletions
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@ -1,3 +1,6 @@
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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# Anthropic
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LiteLLM supports
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@ -45,7 +48,97 @@ for chunk in response:
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print(chunk["choices"][0]["delta"]["content"]) # same as openai format
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```
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## OpenAI Proxy Usage
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Here's how to call Anthropic with the LiteLLM Proxy Server
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### 1. Save key in your environment
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```bash
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export ANTHROPIC_API_KEY="your-api-key"
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```
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### 2. Start the proxy
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```bash
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$ litellm --model claude-3-opus-20240229
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# Server running on http://0.0.0.0:8000
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```
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### 3. Test it
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<Tabs>
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<TabItem value="Curl" label="Curl Request">
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```shell
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curl --location 'http://0.0.0.0:8000/chat/completions' \
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--header 'Content-Type: application/json' \
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--data ' {
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"model": "gpt-3.5-turbo",
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"messages": [
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{
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"role": "user",
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"content": "what llm are you"
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}
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]
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}
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'
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```
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</TabItem>
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<TabItem value="openai" label="OpenAI v1.0.0+">
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```python
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import openai
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client = openai.OpenAI(
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api_key="anything",
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base_url="http://0.0.0.0:8000"
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)
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# request sent to model set on litellm proxy, `litellm --model`
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response = client.chat.completions.create(model="gpt-3.5-turbo", messages = [
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{
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"role": "user",
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"content": "this is a test request, write a short poem"
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}
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])
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print(response)
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```
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</TabItem>
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<TabItem value="langchain" label="Langchain">
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```python
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from langchain.chat_models import ChatOpenAI
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from langchain.prompts.chat import (
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ChatPromptTemplate,
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HumanMessagePromptTemplate,
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SystemMessagePromptTemplate,
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)
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from langchain.schema import HumanMessage, SystemMessage
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chat = ChatOpenAI(
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openai_api_base="http://0.0.0.0:8000", # set openai_api_base to the LiteLLM Proxy
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model = "gpt-3.5-turbo",
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temperature=0.1
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)
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messages = [
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SystemMessage(
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content="You are a helpful assistant that im using to make a test request to."
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),
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HumanMessage(
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content="test from litellm. tell me why it's amazing in 1 sentence"
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),
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]
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response = chat(messages)
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print(response)
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```
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</TabItem>
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</Tabs>
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## Supported Models
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@ -56,6 +149,7 @@ for chunk in response:
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| claude-2.1 | `completion('claude-2.1', messages)` | `os.environ['ANTHROPIC_API_KEY']` |
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| claude-2 | `completion('claude-2', messages)` | `os.environ['ANTHROPIC_API_KEY']` |
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| claude-instant-1.2 | `completion('claude-instant-1.2', messages)` | `os.environ['ANTHROPIC_API_KEY']` |
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| claude-instant-1 | `completion('claude-instant-1', messages)` | `os.environ['ANTHROPIC_API_KEY']` |
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## Advanced
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@ -574,6 +574,7 @@ from .utils import (
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)
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from .llms.huggingface_restapi import HuggingfaceConfig
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from .llms.anthropic import AnthropicConfig
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from .llms.anthropic_text import AnthropicTextConfig
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from .llms.replicate import ReplicateConfig
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from .llms.cohere import CohereConfig
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from .llms.ai21 import AI21Config
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@ -227,7 +227,7 @@ def completion(
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else:
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text_content = completion_response["content"][0].get("text", None)
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## TOOL CALLING - OUTPUT PARSE
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if _is_function_call == True:
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if text_content is not None and "invoke" in text_content:
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function_name = extract_between_tags("tool_name", text_content)[0]
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function_arguments_str = extract_between_tags("invoke", text_content)[
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0
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222
litellm/llms/anthropic_text.py
Normal file
222
litellm/llms/anthropic_text.py
Normal file
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@ -0,0 +1,222 @@
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import os, types
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import json
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from enum import Enum
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import requests
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import time
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from typing import Callable, Optional
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from litellm.utils import ModelResponse, Usage
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import litellm
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from .prompt_templates.factory import prompt_factory, custom_prompt
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import httpx
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class AnthropicConstants(Enum):
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HUMAN_PROMPT = "\n\nHuman: "
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AI_PROMPT = "\n\nAssistant: "
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class AnthropicError(Exception):
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def __init__(self, status_code, message):
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self.status_code = status_code
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self.message = message
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self.request = httpx.Request(
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method="POST", url="https://api.anthropic.com/v1/complete"
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)
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self.response = httpx.Response(status_code=status_code, request=self.request)
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super().__init__(
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self.message
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) # Call the base class constructor with the parameters it needs
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class AnthropicTextConfig:
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"""
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Reference: https://docs.anthropic.com/claude/reference/complete_post
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to pass metadata to anthropic, it's {"user_id": "any-relevant-information"}
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"""
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max_tokens_to_sample: Optional[int] = (
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litellm.max_tokens
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) # anthropic requires a default
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stop_sequences: Optional[list] = None
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temperature: Optional[int] = None
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top_p: Optional[int] = None
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top_k: Optional[int] = None
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metadata: Optional[dict] = None
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def __init__(
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self,
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max_tokens_to_sample: Optional[int] = 256, # anthropic requires a default
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stop_sequences: Optional[list] = None,
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temperature: Optional[int] = None,
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top_p: Optional[int] = None,
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top_k: Optional[int] = None,
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metadata: Optional[dict] = None,
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) -> None:
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locals_ = locals()
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for key, value in locals_.items():
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if key != "self" and value is not None:
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setattr(self.__class__, key, value)
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@classmethod
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def get_config(cls):
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return {
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k: v
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for k, v in cls.__dict__.items()
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if not k.startswith("__")
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and not isinstance(
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v,
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(
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types.FunctionType,
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types.BuiltinFunctionType,
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classmethod,
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staticmethod,
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),
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)
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and v is not None
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}
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# makes headers for API call
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def validate_environment(api_key, user_headers):
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if api_key is None:
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raise ValueError(
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"Missing Anthropic API Key - A call is being made to anthropic but no key is set either in the environment variables or via params"
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)
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headers = {
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"accept": "application/json",
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"anthropic-version": "2023-06-01",
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"content-type": "application/json",
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"x-api-key": api_key,
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}
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if user_headers is not None and isinstance(user_headers, dict):
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headers = {**headers, **user_headers}
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return headers
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def completion(
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model: str,
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messages: list,
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api_base: str,
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custom_prompt_dict: dict,
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model_response: ModelResponse,
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print_verbose: Callable,
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encoding,
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api_key,
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logging_obj,
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optional_params=None,
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litellm_params=None,
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logger_fn=None,
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headers={},
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):
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headers = validate_environment(api_key, headers)
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if model in custom_prompt_dict:
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# check if the model has a registered custom prompt
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model_prompt_details = custom_prompt_dict[model]
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prompt = custom_prompt(
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role_dict=model_prompt_details["roles"],
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initial_prompt_value=model_prompt_details["initial_prompt_value"],
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final_prompt_value=model_prompt_details["final_prompt_value"],
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messages=messages,
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)
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else:
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prompt = prompt_factory(
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model=model, messages=messages, custom_llm_provider="anthropic"
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)
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## Load Config
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config = litellm.AnthropicTextConfig.get_config()
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for k, v in config.items():
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if (
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k not in optional_params
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): # completion(top_k=3) > anthropic_config(top_k=3) <- allows for dynamic variables to be passed in
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optional_params[k] = v
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data = {
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"model": model,
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"prompt": prompt,
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**optional_params,
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}
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## LOGGING
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logging_obj.pre_call(
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input=prompt,
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api_key=api_key,
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additional_args={
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"complete_input_dict": data,
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"api_base": api_base,
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"headers": headers,
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},
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)
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## COMPLETION CALL
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if "stream" in optional_params and optional_params["stream"] == True:
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response = requests.post(
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api_base,
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headers=headers,
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data=json.dumps(data),
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stream=optional_params["stream"],
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)
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if response.status_code != 200:
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raise AnthropicError(
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status_code=response.status_code, message=response.text
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)
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return response.iter_lines()
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else:
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response = requests.post(api_base, headers=headers, data=json.dumps(data))
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if response.status_code != 200:
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raise AnthropicError(
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status_code=response.status_code, message=response.text
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)
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## LOGGING
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logging_obj.post_call(
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input=prompt,
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api_key=api_key,
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original_response=response.text,
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additional_args={"complete_input_dict": data},
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)
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print_verbose(f"raw model_response: {response.text}")
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## RESPONSE OBJECT
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try:
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completion_response = response.json()
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except:
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raise AnthropicError(
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message=response.text, status_code=response.status_code
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)
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if "error" in completion_response:
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raise AnthropicError(
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message=str(completion_response["error"]),
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status_code=response.status_code,
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)
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else:
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if len(completion_response["completion"]) > 0:
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model_response["choices"][0]["message"]["content"] = (
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completion_response["completion"]
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)
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model_response.choices[0].finish_reason = completion_response["stop_reason"]
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## CALCULATING USAGE
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prompt_tokens = len(
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encoding.encode(prompt)
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) ##[TODO] use the anthropic tokenizer here
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completion_tokens = len(
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encoding.encode(model_response["choices"][0]["message"].get("content", ""))
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) ##[TODO] use the anthropic tokenizer here
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model_response["created"] = int(time.time())
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model_response["model"] = model
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usage = Usage(
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prompt_tokens=prompt_tokens,
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completion_tokens=completion_tokens,
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total_tokens=prompt_tokens + completion_tokens,
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)
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model_response.usage = usage
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return model_response
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def embedding():
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# logic for parsing in - calling - parsing out model embedding calls
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pass
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@ -658,16 +658,6 @@ class Huggingface(BaseLLM):
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message=first_chunk,
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)
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return self.async_streaming_generator(
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first_chunk=first_chunk,
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response_iterator=response_iterator,
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model=model,
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logging_obj=logging_obj,
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)
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async def async_streaming_generator(
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self, first_chunk, response_iterator, model, logging_obj
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):
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# Create a new async generator that begins with the first_chunk and includes the remaining items
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async def custom_stream_with_first_chunk():
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yield first_chunk # Yield back the first chunk
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|
|
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|
@ -39,6 +39,7 @@ from litellm.utils import (
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)
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from .llms import (
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anthropic,
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anthropic_text,
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together_ai,
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ai21,
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sagemaker,
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|
|
@ -1018,13 +1019,40 @@ def completion(
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or litellm.api_key
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or os.environ.get("ANTHROPIC_API_KEY")
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)
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custom_prompt_dict = custom_prompt_dict or litellm.custom_prompt_dict
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if (model == "claude-2") or (model == "claude-instant-1"):
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# call anthropic /completion, only use this route for claude-2, claude-instant-1
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api_base = (
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api_base
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or litellm.api_base
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or get_secret("ANTHROPIC_API_BASE")
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or "https://api.anthropic.com/v1/complete"
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)
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response = anthropic_text.completion(
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model=model,
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messages=messages,
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api_base=api_base,
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custom_prompt_dict=litellm.custom_prompt_dict,
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model_response=model_response,
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print_verbose=print_verbose,
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optional_params=optional_params,
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litellm_params=litellm_params,
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logger_fn=logger_fn,
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encoding=encoding, # for calculating input/output tokens
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api_key=api_key,
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logging_obj=logging,
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headers=headers,
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)
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else:
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# call /messages
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# default route for all anthropic models
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api_base = (
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api_base
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or litellm.api_base
|
||||
or get_secret("ANTHROPIC_API_BASE")
|
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or "https://api.anthropic.com/v1/messages"
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)
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custom_prompt_dict = custom_prompt_dict or litellm.custom_prompt_dict
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response = anthropic.completion(
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model=model,
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messages=messages,
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|
|
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File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
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|
@ -1 +1 @@
|
|||
<!DOCTYPE html><html id="__next_error__"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="script" fetchPriority="low" href="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin=""/><script src="/ui/_next/static/chunks/fd9d1056-a85b2c176012d8e5.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/69-e1b183dda365ec86.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/main-app-9b4fb13a7db53edf.js" async="" crossorigin=""></script><title>🚅 LiteLLM</title><meta name="description" content="LiteLLM Proxy Admin UI"/><link rel="icon" href="/ui/favicon.ico" type="image/x-icon" sizes="16x16"/><meta name="next-size-adjust"/><script src="/ui/_next/static/chunks/polyfills-c67a75d1b6f99dc8.js" crossorigin="" noModule=""></script></head><body><script src="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin="" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0]);self.__next_f.push([2,null])</script><script>self.__next_f.push([1,"1:HL[\"/ui/_next/static/media/c9a5bc6a7c948fb0-s.p.woff2\",\"font\",{\"crossOrigin\":\"\",\"type\":\"font/woff2\"}]\n2:HL[\"/ui/_next/static/css/32e93a3d13512de5.css\",\"style\",{\"crossOrigin\":\"\"}]\n0:\"$L3\"\n"])</script><script>self.__next_f.push([1,"4:I[47690,[],\"\"]\n6:I[77831,[],\"\"]\n7:I[56239,[\"730\",\"static/chunks/730-1411b729a1c79695.js\",\"931\",\"static/chunks/app/page-37bd7c3d0bb898a3.js\"],\"\"]\n8:I[5613,[],\"\"]\n9:I[31778,[],\"\"]\nb:I[48955,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"3:[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/32e93a3d13512de5.css\",\"precedence\":\"next\",\"crossOrigin\":\"\"}]],[\"$\",\"$L4\",null,{\"buildId\":\"p1zjZBLDqxGf-NaFvZkeF\",\"assetPrefix\":\"/ui\",\"initialCanonicalUrl\":\"/\",\"initialTree\":[\"\",{\"children\":[\"__PAGE__\",{}]},\"$undefined\",\"$undefined\",true],\"initialSeedData\":[\"\",{\"children\":[\"__PAGE__\",{},[\"$L5\",[\"$\",\"$L6\",null,{\"propsForComponent\":{\"params\":{}},\"Component\":\"$7\",\"isStaticGeneration\":true}],null]]},[null,[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[\"$\",\"body\",null,{\"className\":\"__className_c23dc8\",\"children\":[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\"],\"loading\":\"$undefined\",\"loadingStyles\":\"$undefined\",\"loadingScripts\":\"$undefined\",\"hasLoading\":false,\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 0\",\"fontSize\":24,\"fontWeight\":500,\"verticalAlign\":\"top\",\"lineHeight\":\"49px\"},\"children\":\"404\"}],[\"$\",\"div\",null,{\"style\":{\"display\":\"inline-block\"},\"children\":[\"$\",\"h2\",null,{\"style\":{\"fontSize\":14,\"fontWeight\":400,\"lineHeight\":\"49px\",\"margin\":0},\"children\":\"This page could not be found.\"}]}]]}]}]],\"notFoundStyles\":[],\"styles\":null}]}]}],null]],\"initialHead\":[false,\"$La\"],\"globalErrorComponent\":\"$b\",\"missingSlots\":\"$Wc\"}]]\n"])</script><script>self.__next_f.push([1,"a:[[\"$\",\"meta\",\"0\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}],[\"$\",\"meta\",\"1\",{\"charSet\":\"utf-8\"}],[\"$\",\"title\",\"2\",{\"children\":\"🚅 LiteLLM\"}],[\"$\",\"meta\",\"3\",{\"name\":\"description\",\"content\":\"LiteLLM Proxy Admin UI\"}],[\"$\",\"link\",\"4\",{\"rel\":\"icon\",\"href\":\"/ui/favicon.ico\",\"type\":\"image/x-icon\",\"sizes\":\"16x16\"}],[\"$\",\"meta\",\"5\",{\"name\":\"next-size-adjust\"}]]\n5:null\n"])</script><script>self.__next_f.push([1,""])</script></body></html>
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<!DOCTYPE html><html id="__next_error__"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="script" fetchPriority="low" href="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin=""/><script src="/ui/_next/static/chunks/fd9d1056-a85b2c176012d8e5.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/69-e1b183dda365ec86.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/main-app-9b4fb13a7db53edf.js" async="" crossorigin=""></script><title>🚅 LiteLLM</title><meta name="description" content="LiteLLM Proxy Admin UI"/><link rel="icon" href="/ui/favicon.ico" type="image/x-icon" sizes="16x16"/><meta name="next-size-adjust"/><script src="/ui/_next/static/chunks/polyfills-c67a75d1b6f99dc8.js" crossorigin="" noModule=""></script></head><body><script src="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin="" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0]);self.__next_f.push([2,null])</script><script>self.__next_f.push([1,"1:HL[\"/ui/_next/static/media/c9a5bc6a7c948fb0-s.p.woff2\",\"font\",{\"crossOrigin\":\"\",\"type\":\"font/woff2\"}]\n2:HL[\"/ui/_next/static/css/32e93a3d13512de5.css\",\"style\",{\"crossOrigin\":\"\"}]\n0:\"$L3\"\n"])</script><script>self.__next_f.push([1,"4:I[47690,[],\"\"]\n6:I[77831,[],\"\"]\n7:I[57492,[\"730\",\"static/chunks/730-1411b729a1c79695.js\",\"931\",\"static/chunks/app/page-2ed0bc91ffef505b.js\"],\"\"]\n8:I[5613,[],\"\"]\n9:I[31778,[],\"\"]\nb:I[48955,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"3:[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/32e93a3d13512de5.css\",\"precedence\":\"next\",\"crossOrigin\":\"\"}]],[\"$\",\"$L4\",null,{\"buildId\":\"ZF-EluyKCEJoZptE3dOXT\",\"assetPrefix\":\"/ui\",\"initialCanonicalUrl\":\"/\",\"initialTree\":[\"\",{\"children\":[\"__PAGE__\",{}]},\"$undefined\",\"$undefined\",true],\"initialSeedData\":[\"\",{\"children\":[\"__PAGE__\",{},[\"$L5\",[\"$\",\"$L6\",null,{\"propsForComponent\":{\"params\":{}},\"Component\":\"$7\",\"isStaticGeneration\":true}],null]]},[null,[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[\"$\",\"body\",null,{\"className\":\"__className_c23dc8\",\"children\":[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\"],\"loading\":\"$undefined\",\"loadingStyles\":\"$undefined\",\"loadingScripts\":\"$undefined\",\"hasLoading\":false,\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 0\",\"fontSize\":24,\"fontWeight\":500,\"verticalAlign\":\"top\",\"lineHeight\":\"49px\"},\"children\":\"404\"}],[\"$\",\"div\",null,{\"style\":{\"display\":\"inline-block\"},\"children\":[\"$\",\"h2\",null,{\"style\":{\"fontSize\":14,\"fontWeight\":400,\"lineHeight\":\"49px\",\"margin\":0},\"children\":\"This page could not be found.\"}]}]]}]}]],\"notFoundStyles\":[],\"styles\":null}]}]}],null]],\"initialHead\":[false,\"$La\"],\"globalErrorComponent\":\"$b\",\"missingSlots\":\"$Wc\"}]]\n"])</script><script>self.__next_f.push([1,"a:[[\"$\",\"meta\",\"0\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}],[\"$\",\"meta\",\"1\",{\"charSet\":\"utf-8\"}],[\"$\",\"title\",\"2\",{\"children\":\"🚅 LiteLLM\"}],[\"$\",\"meta\",\"3\",{\"name\":\"description\",\"content\":\"LiteLLM Proxy Admin UI\"}],[\"$\",\"link\",\"4\",{\"rel\":\"icon\",\"href\":\"/ui/favicon.ico\",\"type\":\"image/x-icon\",\"sizes\":\"16x16\"}],[\"$\",\"meta\",\"5\",{\"name\":\"next-size-adjust\"}]]\n5:null\n"])</script><script>self.__next_f.push([1,""])</script></body></html>
|
||||
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|
@ -1,7 +1,7 @@
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3:I[57492,["730","static/chunks/730-1411b729a1c79695.js","931","static/chunks/app/page-2ed0bc91ffef505b.js"],""]
|
||||
4:I[5613,[],""]
|
||||
5:I[31778,[],""]
|
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|
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|
||||
6:[["$","meta","0",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","1",{"charSet":"utf-8"}],["$","title","2",{"children":"🚅 LiteLLM"}],["$","meta","3",{"name":"description","content":"LiteLLM Proxy Admin UI"}],["$","link","4",{"rel":"icon","href":"/ui/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","meta","5",{"name":"next-size-adjust"}]]
|
||||
1:null
|
||||
|
|
|
|||
|
|
@ -5811,6 +5811,58 @@ async def model_info_v2(
|
|||
return {"data": all_models}
|
||||
|
||||
|
||||
@router.get(
|
||||
"/model/metrics",
|
||||
description="View number of requests & avg latency per model on config.yaml",
|
||||
tags=["model management"],
|
||||
dependencies=[Depends(user_api_key_auth)],
|
||||
)
|
||||
async def model_metrics(
|
||||
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
|
||||
):
|
||||
global prisma_client
|
||||
if prisma_client is None:
|
||||
raise ProxyException(
|
||||
message="Prisma Client is not initialized",
|
||||
type="internal_error",
|
||||
param="None",
|
||||
code=status.HTTP_500_INTERNAL_SERVER_ERROR,
|
||||
)
|
||||
|
||||
sql_query = """
|
||||
SELECT
|
||||
CASE WHEN api_base = '' THEN model ELSE CONCAT(model, '-', api_base) END AS combined_model_api_base,
|
||||
COUNT(*) AS num_requests,
|
||||
AVG(EXTRACT(epoch FROM ("endTime" - "startTime"))) AS avg_latency_seconds
|
||||
FROM
|
||||
"LiteLLM_SpendLogs"
|
||||
WHERE
|
||||
"startTime" >= NOW() - INTERVAL '10000 hours'
|
||||
GROUP BY
|
||||
CASE WHEN api_base = '' THEN model ELSE CONCAT(model, '-', api_base) END
|
||||
ORDER BY
|
||||
num_requests DESC
|
||||
LIMIT 50;
|
||||
"""
|
||||
|
||||
db_response = await prisma_client.db.query_raw(query=sql_query)
|
||||
response: List[dict] = []
|
||||
if response is not None:
|
||||
# loop through all models
|
||||
for model_data in db_response:
|
||||
model = model_data.get("combined_model_api_base", "")
|
||||
num_requests = model_data.get("num_requests", 0)
|
||||
avg_latency_seconds = model_data.get("avg_latency_seconds", 0)
|
||||
response.append(
|
||||
{
|
||||
"model": model,
|
||||
"num_requests": num_requests,
|
||||
"avg_latency_seconds": avg_latency_seconds,
|
||||
}
|
||||
)
|
||||
return response
|
||||
|
||||
|
||||
@router.get(
|
||||
"/model/info",
|
||||
description="Provides more info about each model in /models, including config.yaml descriptions (except api key and api base)",
|
||||
|
|
|
|||
|
|
@ -56,7 +56,7 @@ def test_completion_custom_provider_model_name():
|
|||
def test_completion_claude():
|
||||
litellm.set_verbose = True
|
||||
litellm.cache = None
|
||||
litellm.AnthropicConfig(max_tokens=200, metadata={"user_id": "1224"})
|
||||
litellm.AnthropicTextConfig(max_tokens_to_sample=200, metadata={"user_id": "1224"})
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
|
|
@ -67,10 +67,7 @@ def test_completion_claude():
|
|||
try:
|
||||
# test without max tokens
|
||||
response = completion(
|
||||
model="claude-instant-1.2",
|
||||
messages=messages,
|
||||
request_timeout=10,
|
||||
max_tokens=10,
|
||||
model="claude-instant-1", messages=messages, request_timeout=10
|
||||
)
|
||||
# Add any assertions, here to check response args
|
||||
print(response)
|
||||
|
|
|
|||
|
|
@ -4216,6 +4216,11 @@ def get_optional_params(
|
|||
if top_p is not None:
|
||||
optional_params["top_p"] = top_p
|
||||
if max_tokens is not None:
|
||||
if (model == "claude-2") or (model == "claude-instant-1"):
|
||||
# these models use antropic_text.py which only accepts max_tokens_to_sample
|
||||
optional_params["max_tokens_to_sample"] = max_tokens
|
||||
else:
|
||||
optional_params["max_tokens"] = max_tokens
|
||||
optional_params["max_tokens"] = max_tokens
|
||||
if tools is not None:
|
||||
optional_params["tools"] = tools
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "litellm"
|
||||
version = "1.28.14"
|
||||
version = "1.29.2"
|
||||
description = "Library to easily interface with LLM API providers"
|
||||
authors = ["BerriAI"]
|
||||
license = "MIT"
|
||||
|
|
@ -74,7 +74,7 @@ requires = ["poetry-core", "wheel"]
|
|||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.commitizen]
|
||||
version = "1.28.14"
|
||||
version = "1.29.2"
|
||||
version_files = [
|
||||
"pyproject.toml:^version"
|
||||
]
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -1 +1 @@
|
|||
<!DOCTYPE html><html id="__next_error__"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="script" fetchPriority="low" href="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin=""/><script src="/ui/_next/static/chunks/fd9d1056-a85b2c176012d8e5.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/69-e1b183dda365ec86.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/main-app-9b4fb13a7db53edf.js" async="" crossorigin=""></script><title>🚅 LiteLLM</title><meta name="description" content="LiteLLM Proxy Admin UI"/><link rel="icon" href="/ui/favicon.ico" type="image/x-icon" sizes="16x16"/><meta name="next-size-adjust"/><script src="/ui/_next/static/chunks/polyfills-c67a75d1b6f99dc8.js" crossorigin="" noModule=""></script></head><body><script src="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin="" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0]);self.__next_f.push([2,null])</script><script>self.__next_f.push([1,"1:HL[\"/ui/_next/static/media/c9a5bc6a7c948fb0-s.p.woff2\",\"font\",{\"crossOrigin\":\"\",\"type\":\"font/woff2\"}]\n2:HL[\"/ui/_next/static/css/32e93a3d13512de5.css\",\"style\",{\"crossOrigin\":\"\"}]\n0:\"$L3\"\n"])</script><script>self.__next_f.push([1,"4:I[47690,[],\"\"]\n6:I[77831,[],\"\"]\n7:I[56239,[\"730\",\"static/chunks/730-1411b729a1c79695.js\",\"931\",\"static/chunks/app/page-37bd7c3d0bb898a3.js\"],\"\"]\n8:I[5613,[],\"\"]\n9:I[31778,[],\"\"]\nb:I[48955,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"3:[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/32e93a3d13512de5.css\",\"precedence\":\"next\",\"crossOrigin\":\"\"}]],[\"$\",\"$L4\",null,{\"buildId\":\"p1zjZBLDqxGf-NaFvZkeF\",\"assetPrefix\":\"/ui\",\"initialCanonicalUrl\":\"/\",\"initialTree\":[\"\",{\"children\":[\"__PAGE__\",{}]},\"$undefined\",\"$undefined\",true],\"initialSeedData\":[\"\",{\"children\":[\"__PAGE__\",{},[\"$L5\",[\"$\",\"$L6\",null,{\"propsForComponent\":{\"params\":{}},\"Component\":\"$7\",\"isStaticGeneration\":true}],null]]},[null,[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[\"$\",\"body\",null,{\"className\":\"__className_c23dc8\",\"children\":[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\"],\"loading\":\"$undefined\",\"loadingStyles\":\"$undefined\",\"loadingScripts\":\"$undefined\",\"hasLoading\":false,\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 0\",\"fontSize\":24,\"fontWeight\":500,\"verticalAlign\":\"top\",\"lineHeight\":\"49px\"},\"children\":\"404\"}],[\"$\",\"div\",null,{\"style\":{\"display\":\"inline-block\"},\"children\":[\"$\",\"h2\",null,{\"style\":{\"fontSize\":14,\"fontWeight\":400,\"lineHeight\":\"49px\",\"margin\":0},\"children\":\"This page could not be found.\"}]}]]}]}]],\"notFoundStyles\":[],\"styles\":null}]}]}],null]],\"initialHead\":[false,\"$La\"],\"globalErrorComponent\":\"$b\",\"missingSlots\":\"$Wc\"}]]\n"])</script><script>self.__next_f.push([1,"a:[[\"$\",\"meta\",\"0\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}],[\"$\",\"meta\",\"1\",{\"charSet\":\"utf-8\"}],[\"$\",\"title\",\"2\",{\"children\":\"🚅 LiteLLM\"}],[\"$\",\"meta\",\"3\",{\"name\":\"description\",\"content\":\"LiteLLM Proxy Admin UI\"}],[\"$\",\"link\",\"4\",{\"rel\":\"icon\",\"href\":\"/ui/favicon.ico\",\"type\":\"image/x-icon\",\"sizes\":\"16x16\"}],[\"$\",\"meta\",\"5\",{\"name\":\"next-size-adjust\"}]]\n5:null\n"])</script><script>self.__next_f.push([1,""])</script></body></html>
|
||||
<!DOCTYPE html><html id="__next_error__"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="script" fetchPriority="low" href="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin=""/><script src="/ui/_next/static/chunks/fd9d1056-a85b2c176012d8e5.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/69-e1b183dda365ec86.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/main-app-9b4fb13a7db53edf.js" async="" crossorigin=""></script><title>🚅 LiteLLM</title><meta name="description" content="LiteLLM Proxy Admin UI"/><link rel="icon" href="/ui/favicon.ico" type="image/x-icon" sizes="16x16"/><meta name="next-size-adjust"/><script src="/ui/_next/static/chunks/polyfills-c67a75d1b6f99dc8.js" crossorigin="" noModule=""></script></head><body><script src="/ui/_next/static/chunks/webpack-59d9232c3e7a8be6.js" crossorigin="" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0]);self.__next_f.push([2,null])</script><script>self.__next_f.push([1,"1:HL[\"/ui/_next/static/media/c9a5bc6a7c948fb0-s.p.woff2\",\"font\",{\"crossOrigin\":\"\",\"type\":\"font/woff2\"}]\n2:HL[\"/ui/_next/static/css/32e93a3d13512de5.css\",\"style\",{\"crossOrigin\":\"\"}]\n0:\"$L3\"\n"])</script><script>self.__next_f.push([1,"4:I[47690,[],\"\"]\n6:I[77831,[],\"\"]\n7:I[57492,[\"730\",\"static/chunks/730-1411b729a1c79695.js\",\"931\",\"static/chunks/app/page-2ed0bc91ffef505b.js\"],\"\"]\n8:I[5613,[],\"\"]\n9:I[31778,[],\"\"]\nb:I[48955,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"3:[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/32e93a3d13512de5.css\",\"precedence\":\"next\",\"crossOrigin\":\"\"}]],[\"$\",\"$L4\",null,{\"buildId\":\"ZF-EluyKCEJoZptE3dOXT\",\"assetPrefix\":\"/ui\",\"initialCanonicalUrl\":\"/\",\"initialTree\":[\"\",{\"children\":[\"__PAGE__\",{}]},\"$undefined\",\"$undefined\",true],\"initialSeedData\":[\"\",{\"children\":[\"__PAGE__\",{},[\"$L5\",[\"$\",\"$L6\",null,{\"propsForComponent\":{\"params\":{}},\"Component\":\"$7\",\"isStaticGeneration\":true}],null]]},[null,[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[\"$\",\"body\",null,{\"className\":\"__className_c23dc8\",\"children\":[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\"],\"loading\":\"$undefined\",\"loadingStyles\":\"$undefined\",\"loadingScripts\":\"$undefined\",\"hasLoading\":false,\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 0\",\"fontSize\":24,\"fontWeight\":500,\"verticalAlign\":\"top\",\"lineHeight\":\"49px\"},\"children\":\"404\"}],[\"$\",\"div\",null,{\"style\":{\"display\":\"inline-block\"},\"children\":[\"$\",\"h2\",null,{\"style\":{\"fontSize\":14,\"fontWeight\":400,\"lineHeight\":\"49px\",\"margin\":0},\"children\":\"This page could not be found.\"}]}]]}]}]],\"notFoundStyles\":[],\"styles\":null}]}]}],null]],\"initialHead\":[false,\"$La\"],\"globalErrorComponent\":\"$b\",\"missingSlots\":\"$Wc\"}]]\n"])</script><script>self.__next_f.push([1,"a:[[\"$\",\"meta\",\"0\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}],[\"$\",\"meta\",\"1\",{\"charSet\":\"utf-8\"}],[\"$\",\"title\",\"2\",{\"children\":\"🚅 LiteLLM\"}],[\"$\",\"meta\",\"3\",{\"name\":\"description\",\"content\":\"LiteLLM Proxy Admin UI\"}],[\"$\",\"link\",\"4\",{\"rel\":\"icon\",\"href\":\"/ui/favicon.ico\",\"type\":\"image/x-icon\",\"sizes\":\"16x16\"}],[\"$\",\"meta\",\"5\",{\"name\":\"next-size-adjust\"}]]\n5:null\n"])</script><script>self.__next_f.push([1,""])</script></body></html>
|
||||
|
|
@ -1,7 +1,7 @@
|
|||
2:I[77831,[],""]
|
||||
3:I[56239,["730","static/chunks/730-1411b729a1c79695.js","931","static/chunks/app/page-37bd7c3d0bb898a3.js"],""]
|
||||
3:I[57492,["730","static/chunks/730-1411b729a1c79695.js","931","static/chunks/app/page-2ed0bc91ffef505b.js"],""]
|
||||
4:I[5613,[],""]
|
||||
5:I[31778,[],""]
|
||||
0:["p1zjZBLDqxGf-NaFvZkeF",[[["",{"children":["__PAGE__",{}]},"$undefined","$undefined",true],["",{"children":["__PAGE__",{},["$L1",["$","$L2",null,{"propsForComponent":{"params":{}},"Component":"$3","isStaticGeneration":true}],null]]},[null,["$","html",null,{"lang":"en","children":["$","body",null,{"className":"__className_c23dc8","children":["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children"],"loading":"$undefined","loadingStyles":"$undefined","loadingScripts":"$undefined","hasLoading":false,"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[["$","title",null,{"children":"404: This page could not be found."}],["$","div",null,{"style":{"fontFamily":"system-ui,\"Segoe UI\",Roboto,Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\"","height":"100vh","textAlign":"center","display":"flex","flexDirection":"column","alignItems":"center","justifyContent":"center"},"children":["$","div",null,{"children":[["$","style",null,{"dangerouslySetInnerHTML":{"__html":"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}"}}],["$","h1",null,{"className":"next-error-h1","style":{"display":"inline-block","margin":"0 20px 0 0","padding":"0 23px 0 0","fontSize":24,"fontWeight":500,"verticalAlign":"top","lineHeight":"49px"},"children":"404"}],["$","div",null,{"style":{"display":"inline-block"},"children":["$","h2",null,{"style":{"fontSize":14,"fontWeight":400,"lineHeight":"49px","margin":0},"children":"This page could not be found."}]}]]}]}]],"notFoundStyles":[],"styles":null}]}]}],null]],[[["$","link","0",{"rel":"stylesheet","href":"/ui/_next/static/css/32e93a3d13512de5.css","precedence":"next","crossOrigin":""}]],"$L6"]]]]
|
||||
0:["ZF-EluyKCEJoZptE3dOXT",[[["",{"children":["__PAGE__",{}]},"$undefined","$undefined",true],["",{"children":["__PAGE__",{},["$L1",["$","$L2",null,{"propsForComponent":{"params":{}},"Component":"$3","isStaticGeneration":true}],null]]},[null,["$","html",null,{"lang":"en","children":["$","body",null,{"className":"__className_c23dc8","children":["$","$L4",null,{"parallelRouterKey":"children","segmentPath":["children"],"loading":"$undefined","loadingStyles":"$undefined","loadingScripts":"$undefined","hasLoading":false,"error":"$undefined","errorStyles":"$undefined","errorScripts":"$undefined","template":["$","$L5",null,{}],"templateStyles":"$undefined","templateScripts":"$undefined","notFound":[["$","title",null,{"children":"404: This page could not be found."}],["$","div",null,{"style":{"fontFamily":"system-ui,\"Segoe UI\",Roboto,Helvetica,Arial,sans-serif,\"Apple Color Emoji\",\"Segoe UI Emoji\"","height":"100vh","textAlign":"center","display":"flex","flexDirection":"column","alignItems":"center","justifyContent":"center"},"children":["$","div",null,{"children":[["$","style",null,{"dangerouslySetInnerHTML":{"__html":"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}"}}],["$","h1",null,{"className":"next-error-h1","style":{"display":"inline-block","margin":"0 20px 0 0","padding":"0 23px 0 0","fontSize":24,"fontWeight":500,"verticalAlign":"top","lineHeight":"49px"},"children":"404"}],["$","div",null,{"style":{"display":"inline-block"},"children":["$","h2",null,{"style":{"fontSize":14,"fontWeight":400,"lineHeight":"49px","margin":0},"children":"This page could not be found."}]}]]}]}]],"notFoundStyles":[],"styles":null}]}]}],null]],[[["$","link","0",{"rel":"stylesheet","href":"/ui/_next/static/css/32e93a3d13512de5.css","precedence":"next","crossOrigin":""}]],"$L6"]]]]
|
||||
6:[["$","meta","0",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","1",{"charSet":"utf-8"}],["$","title","2",{"children":"🚅 LiteLLM"}],["$","meta","3",{"name":"description","content":"LiteLLM Proxy Admin UI"}],["$","link","4",{"rel":"icon","href":"/ui/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","meta","5",{"name":"next-size-adjust"}]]
|
||||
1:null
|
||||
|
|
|
|||
|
|
@ -11,7 +11,8 @@ import {
|
|||
Metric,
|
||||
Grid,
|
||||
} from "@tremor/react";
|
||||
import { modelInfoCall, userGetRequesedtModelsCall } from "./networking";
|
||||
import { modelInfoCall, userGetRequesedtModelsCall, modelMetricsCall } from "./networking";
|
||||
import { BarChart } from "@tremor/react";
|
||||
import { Badge, BadgeDelta, Button } from "@tremor/react";
|
||||
import RequestAccess from "./request_model_access";
|
||||
import { Typography } from "antd";
|
||||
|
|
@ -30,6 +31,7 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
userID,
|
||||
}) => {
|
||||
const [modelData, setModelData] = useState<any>({ data: [] });
|
||||
const [modelMetrics, setModelMetrics] = useState<any[]>([]);
|
||||
const [pendingRequests, setPendingRequests] = useState<any[]>([]);
|
||||
|
||||
useEffect(() => {
|
||||
|
|
@ -47,6 +49,15 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
console.log("Model data response:", modelDataResponse.data);
|
||||
setModelData(modelDataResponse);
|
||||
|
||||
const modelMetricsResponse = await modelMetricsCall(
|
||||
accessToken,
|
||||
userID,
|
||||
userRole
|
||||
);
|
||||
|
||||
console.log("Model metrics response:", modelMetricsResponse);
|
||||
setModelMetrics(modelMetricsResponse);
|
||||
|
||||
// if userRole is Admin, show the pending requests
|
||||
if (userRole === "Admin" && accessToken) {
|
||||
const user_requests = await userGetRequesedtModelsCall(accessToken);
|
||||
|
|
@ -75,8 +86,7 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
// loop through model data and edit each row
|
||||
for (let i = 0; i < modelData.data.length; i++) {
|
||||
let curr_model = modelData.data[i];
|
||||
let litellm_model_name = curr_model?.litellm_params?.model;
|
||||
|
||||
let litellm_model_name = curr_model?.litellm_params?.mode
|
||||
let model_info = curr_model?.model_info;
|
||||
|
||||
let defaultProvider = "openai";
|
||||
|
|
@ -109,6 +119,7 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
modelData.data[i].input_cost = input_cost;
|
||||
modelData.data[i].output_cost = output_cost;
|
||||
modelData.data[i].max_tokens = max_tokens;
|
||||
modelData.data[i].api_base = curr_model?.litellm_params?.api_base;
|
||||
|
||||
all_models_on_proxy.push(curr_model.model_name);
|
||||
|
||||
|
|
@ -141,6 +152,14 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
<TableCell>
|
||||
<Title>Provider</Title>
|
||||
</TableCell>
|
||||
{
|
||||
userRole === "Admin" && (
|
||||
<TableCell>
|
||||
<Title>API Base</Title>
|
||||
</TableCell>
|
||||
)
|
||||
}
|
||||
|
||||
<TableCell>
|
||||
<Title>Access</Title>
|
||||
</TableCell>
|
||||
|
|
@ -162,6 +181,11 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
<Title>{model.model_name}</Title>
|
||||
</TableCell>
|
||||
<TableCell>{model.provider}</TableCell>
|
||||
{
|
||||
userRole === "Admin" && (
|
||||
<TableCell>{model.api_base}</TableCell>
|
||||
)
|
||||
}
|
||||
|
||||
<TableCell>
|
||||
{model.user_access ? (
|
||||
|
|
@ -183,7 +207,18 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
</TableBody>
|
||||
</Table>
|
||||
</Card>
|
||||
{userRole === "Admin" &&
|
||||
<Card>
|
||||
<Title>Model Statistics (Number Requests, Latency)</Title>
|
||||
<BarChart
|
||||
data={modelMetrics}
|
||||
index="model"
|
||||
categories={["num_requests", "avg_latency_seconds"]}
|
||||
colors={["blue", "red"]}
|
||||
yAxisWidth={100}
|
||||
tickGap={5}
|
||||
/>
|
||||
</Card>
|
||||
{/* {userRole === "Admin" &&
|
||||
pendingRequests &&
|
||||
pendingRequests.length > 0 ? (
|
||||
<Card>
|
||||
|
|
@ -229,7 +264,7 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
|
|||
</TableBody>
|
||||
</Table>
|
||||
</Card>
|
||||
) : null}
|
||||
) : null} */}
|
||||
</Grid>
|
||||
</div>
|
||||
);
|
||||
|
|
|
|||
|
|
@ -242,6 +242,41 @@ export const modelInfoCall = async (
|
|||
}
|
||||
};
|
||||
|
||||
|
||||
export const modelMetricsCall = async (
|
||||
accessToken: String,
|
||||
userID: String,
|
||||
userRole: String
|
||||
) => {
|
||||
/**
|
||||
* Get all models on proxy
|
||||
*/
|
||||
try {
|
||||
let url = proxyBaseUrl ? `${proxyBaseUrl}/model/metrics` : `/model/metrics`;
|
||||
// message.info("Requesting model data");
|
||||
const response = await fetch(url, {
|
||||
method: "GET",
|
||||
headers: {
|
||||
Authorization: `Bearer ${accessToken}`,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const errorData = await response.text();
|
||||
message.error(errorData);
|
||||
throw new Error("Network response was not ok");
|
||||
}
|
||||
const data = await response.json();
|
||||
// message.info("Received model data");
|
||||
return data;
|
||||
// Handle success - you might want to update some state or UI based on the created key
|
||||
} catch (error) {
|
||||
console.error("Failed to create key:", error);
|
||||
throw error;
|
||||
}
|
||||
};
|
||||
|
||||
export const modelAvailableCall = async (
|
||||
accessToken: String,
|
||||
userID: String,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue