CHAT WEB API SERVICE FOR ASSISTANT BASED RAG TRAINING
Descrição da oferta de emprego
One of the 3 methods.
1.
Method with priority, then 2nd method, the latest preferred method 3.
Method.
Project time expectation is between 2 weeks and 4 weeks.
1st method.
Deepseek-Coder API connection and progression with Ragflow Docker installation.
With this method, basic training documents are uploaded to Knowledge Base.
Create a chat assistant (Create Chat Assistant).
Session is created for the chat assistant.
The document is uploaded in particular.
If there is a change in the document, the document is deleted and loaded.
The documents on the person are chunk and the prompt entrances are provided only with selected dataset ids.
[login to view URL] [login to view URL] Codes are run as python on the dedicated linux server.
Server requirement.
CPU ≥ 4 Cores; Ram ≥ 16 GB; Disk ≥ 50 GB; Docker ≥ & Docker Compose ≥ V.
Information.
Ragflow does not work on ARM and AVX2, FMA, BMI1, BMI2, LZCNT, MOVBE CPU features.
2nd Method.
Open AI API connection.
With this method, basic training documents are uploaded to Chroma vector DB.
Vecor DB is created for the person.
Vectorstore, retrievalqa and Langchain provide prompt inputs for the person.
Vectorstore, Python language codes and the following services are run on MODAL.
OM.
3rd Method.
Open AI API connection.
With this method, basic training documents are uploaded to Knowledge Base.
Create Create Assistant (Create Assistant).
File Search structure is created for the chat assistant.
The document is uploaded in particular.
If there is a change in the document, the document is deleted and loaded.
For the person, the prompt entrances are provided only with selected datasets.
[login to view URL] [login to view URL] Codes are run as python on the linux server.
Outputs to be delivered.
1.
Services.
Installing Basic Training Documents, Deleting Selected Document and Updating Web Service Creation and deletion service for the new user Delete, update, or add for files, if there are files for files, web service for Prompt Request service that returns in JSON format (3 methods supports JSON Response.) 2.
Installation Script that will need to run on Linux server 3.
All codes Phases.
1.
Operating the method selected as a demo in a way that does not cover web services 2.
Completion of all services and codes LangChain Linux OpenAI Python ID do Projeto.
# Sobre o projeto 45 propostas Aberto para ofertas Projeto remoto Ativo em 24 minutos atrás
Detalhes da oferta
- Indeterminado
- Em todo Portugal
- Indeterminado - Indeterminado
- 02/12/2024
- 02/03/2025
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