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from typing import Any, Callable, Coroutine
from anthropic import AI_PROMPT, HUMAN_PROMPT, AsyncAnthropic
from .base import LLM, CompletionOptions
from .prompts.chat import anthropic_template_messages
class AnthropicLLM(LLM):
"""
Import the `AnthropicLLM` class and set it as the default model:
```python title="~/.continue/config.py"
from continuedev.libs.llm.anthropic import AnthropicLLM
config = ContinueConfig(
...
models=Models(
default=AnthropicLLM(api_key="<API_KEY>", model="claude-2")
)
)
```
Claude 2 is not yet publicly released. You can request early access [here](https://www.anthropic.com/earlyaccess).
"""
api_key: str
"Anthropic API key"
model: str = "claude-2"
_async_client: AsyncAnthropic = None
template_messages: Callable = anthropic_template_messages
class Config:
arbitrary_types_allowed = True
async def start(self, **kwargs):
await super().start(**kwargs)
self._async_client = AsyncAnthropic(api_key=self.api_key)
if self.model == "claude-2":
self.context_length = 100_000
def collect_args(self, options: CompletionOptions):
options.stop = None
args = super().collect_args(options)
if "max_tokens" in args:
args["max_tokens_to_sample"] = args["max_tokens"]
del args["max_tokens"]
if "frequency_penalty" in args:
del args["frequency_penalty"]
if "presence_penalty" in args:
del args["presence_penalty"]
return args
async def _stream_complete(self, prompt: str, options):
args = self.collect_args(options)
prompt = f"{HUMAN_PROMPT} {prompt} {AI_PROMPT}"
async for chunk in await self._async_client.completions.create(
prompt=prompt, stream=True, **args
):
yield chunk.completion
async def _complete(self, prompt: str, options) -> Coroutine[Any, Any, str]:
args = self.collect_args(options)
prompt = f"{HUMAN_PROMPT} {prompt} {AI_PROMPT}"
return (
await self._async_client.completions.create(prompt=prompt, **args)
).completion
|
