* feature(intelligent-search): Added API to connect to Llama.cpp in EC2 and filter the response into OR filters * updated sql to filter script and added init.sql for tables * feature(intelligent-search): Changed llama.cpp for llama in GPU now contained in API * Updated Dockerfile to use GPU and download LLM from S3 * Added link to facebook/research/llama * Updated Dockerfile * Updated requirements and Dockerfile base images * fixed minor issues: Not used variables, updated COPY and replace values * fix(intelligent-search): Fixed WHERE statement filter * feature(smart-charts): Added method to create charts using llama. style(intelligent-search): Changed names for attributes to match frontend format. fix(intelligent-search): Fixed vulnerability in requiments and small issues fix * Added some test before deploying the service * Added semaphore to handle concurrency --------- Co-authored-by: EC2 Default User <ec2-user@ip-10-0-2-226.eu-central-1.compute.internal>
8 lines
117 B
Python
8 lines
117 B
Python
from pydantic import BaseModel
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class LLMQuestion(BaseModel):
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question: str
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userId: int
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projectId: int
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