41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
from cognee.infrastructure.llm.LLMGateway import LLMGateway
|
|
|
|
|
|
async def generate_completion(
|
|
query: str,
|
|
context: str,
|
|
user_prompt_path: str,
|
|
system_prompt_path: str,
|
|
user_prompt: str = None,
|
|
system_prompt: str = None,
|
|
only_context: bool = False,
|
|
) -> str:
|
|
"""Generates a completion using LLM with given context and prompts."""
|
|
args = {"question": query, "context": context}
|
|
user_prompt = LLMGateway.render_prompt(user_prompt if user_prompt else user_prompt_path, args)
|
|
system_prompt = LLMGateway.read_query_prompt(
|
|
system_prompt if system_prompt else system_prompt_path
|
|
)
|
|
|
|
if only_context:
|
|
return context
|
|
else:
|
|
return await LLMGateway.acreate_structured_output(
|
|
text_input=user_prompt,
|
|
system_prompt=system_prompt,
|
|
response_model=str,
|
|
)
|
|
|
|
|
|
async def summarize_text(
|
|
text: str,
|
|
prompt_path: str = "summarize_search_results.txt",
|
|
) -> str:
|
|
"""Summarizes text using LLM with the specified prompt."""
|
|
system_prompt = LLMGateway.read_query_prompt(prompt_path)
|
|
|
|
return await LLMGateway.acreate_structured_output(
|
|
text_input=text,
|
|
system_prompt=system_prompt,
|
|
response_model=str,
|
|
)
|