mirror of
https://github.com/arc53/DocsGPT.git
synced 2025-11-29 08:33:20 +00:00
a4507008c1
* (feat:pause-stream) generator exit * (feat:pause-stream) close request * (feat:pause-stream) finally close; google anthropic --------- Co-authored-by: GH Action - Upstream Sync <action@github.com>
55 lines
2.0 KiB
Python
55 lines
2.0 KiB
Python
from application.llm.base import BaseLLM
|
|
from application.core.settings import settings
|
|
|
|
|
|
class AnthropicLLM(BaseLLM):
|
|
|
|
def __init__(self, api_key=None, user_api_key=None, *args, **kwargs):
|
|
from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT
|
|
|
|
super().__init__(*args, **kwargs)
|
|
self.api_key = (
|
|
api_key or settings.ANTHROPIC_API_KEY
|
|
) # If not provided, use a default from settings
|
|
self.user_api_key = user_api_key
|
|
self.anthropic = Anthropic(api_key=self.api_key)
|
|
self.HUMAN_PROMPT = HUMAN_PROMPT
|
|
self.AI_PROMPT = AI_PROMPT
|
|
|
|
def _raw_gen(
|
|
self, baseself, model, messages, stream=False, tools=None, max_tokens=300, **kwargs
|
|
):
|
|
context = messages[0]["content"]
|
|
user_question = messages[-1]["content"]
|
|
prompt = f"### Context \n {context} \n ### Question \n {user_question}"
|
|
if stream:
|
|
return self.gen_stream(model, prompt, stream, max_tokens, **kwargs)
|
|
|
|
completion = self.anthropic.completions.create(
|
|
model=model,
|
|
max_tokens_to_sample=max_tokens,
|
|
stream=stream,
|
|
prompt=f"{self.HUMAN_PROMPT} {prompt}{self.AI_PROMPT}",
|
|
)
|
|
return completion.completion
|
|
|
|
def _raw_gen_stream(
|
|
self, baseself, model, messages, stream=True, tools=None, max_tokens=300, **kwargs
|
|
):
|
|
context = messages[0]["content"]
|
|
user_question = messages[-1]["content"]
|
|
prompt = f"### Context \n {context} \n ### Question \n {user_question}"
|
|
stream_response = self.anthropic.completions.create(
|
|
model=model,
|
|
prompt=f"{self.HUMAN_PROMPT} {prompt}{self.AI_PROMPT}",
|
|
max_tokens_to_sample=max_tokens,
|
|
stream=True,
|
|
)
|
|
|
|
try:
|
|
for completion in stream_response:
|
|
yield completion.completion
|
|
finally:
|
|
if hasattr(stream_response, 'close'):
|
|
stream_response.close()
|