kopia lustrzana https://github.com/dgtlmoon/changedetection.io
65 wiersze
2.4 KiB
Python
65 wiersze
2.4 KiB
Python
|
import importlib
|
||
|
|
from langchain_core.messages import SystemMessage, HumanMessage
|
||
|
|
|
||
|
|
SYSTEM_MESSAGE = (
|
||
|
|
"You are a text analyser who will attempt to give the most concise information "
|
||
|
|
"to the request, the information should be returned in a way that if I ask you again "
|
||
|
|
"I should get the same answer if the outcome is the same. The goal is to cut down "
|
||
|
|
"or reduce the text changes from you when i ask the same question about similar content "
|
||
|
|
"Always list items in exactly the same order and wording as found in the source text. "
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
class LLM_integrate:
|
||
|
|
PROVIDER_MAP = {
|
||
|
|
"openai": ("langchain_openai", "ChatOpenAI"),
|
||
|
|
"azure": ("langchain_community.chat_models", "AzureChatOpenAI"),
|
||
|
|
"gemini": ("langchain_google_genai", "ChatGoogleGenerativeAI")
|
||
|
|
}
|
||
|
|
|
||
|
|
def __init__(self, api_keys: dict):
|
||
|
|
"""
|
||
|
|
api_keys = {
|
||
|
|
"openai": "sk-xxx",
|
||
|
|
"azure": "AZURE_KEY",
|
||
|
|
"gemini": "GEMINI_KEY"
|
||
|
|
}
|
||
|
|
"""
|
||
|
|
self.api_keys = api_keys
|
||
|
|
|
||
|
|
def run(self, provider: str, model: str, message: str):
|
||
|
|
module_name, class_name = self.PROVIDER_MAP[provider]
|
||
|
|
|
||
|
|
# Import the class dynamically
|
||
|
|
module = importlib.import_module(module_name)
|
||
|
|
LLMClass = getattr(module, class_name)
|
||
|
|
|
||
|
|
# Create the LLM object
|
||
|
|
llm_kwargs = {}
|
||
|
|
if provider == "openai":
|
||
|
|
llm_kwargs = dict(api_key=self.api_keys.get("openai", ''),
|
||
|
|
model=model,
|
||
|
|
# https://api.python.langchain.com/en/latest/chat_models/langchain_openai.chat_models.base.ChatOpenAI.html#langchain_openai.chat_models.base.ChatOpenAI.temperature
|
||
|
|
temperature=0 # most deterministic,
|
||
|
|
)
|
||
|
|
elif provider == "azure":
|
||
|
|
llm_kwargs = dict(
|
||
|
|
api_key=self.api_keys["azure"],
|
||
|
|
azure_endpoint="https://<your-endpoint>.openai.azure.com",
|
||
|
|
deployment_name=model
|
||
|
|
)
|
||
|
|
elif provider == "gemini":
|
||
|
|
llm_kwargs = dict(api_key=self.api_keys.get("gemini"), model=model)
|
||
|
|
|
||
|
|
llm = LLMClass(**llm_kwargs)
|
||
|
|
|
||
|
|
# Build your messages
|
||
|
|
messages = [
|
||
|
|
SystemMessage(content=SYSTEM_MESSAGE),
|
||
|
|
HumanMessage(content=message)
|
||
|
|
]
|
||
|
|
|
||
|
|
# Run the model asynchronously
|
||
|
|
result = llm.invoke(messages)
|
||
|
|
return result.content
|