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Description
DeepEval offers an intuitive open-source framework designed for the assessment and testing of large language model systems, similar to what Pytest does but tailored specifically for evaluating LLM outputs. It leverages cutting-edge research to measure various performance metrics, including G-Eval, hallucinations, answer relevancy, and RAGAS, utilizing LLMs and a range of other NLP models that operate directly on your local machine. This tool is versatile enough to support applications developed through methods like RAG, fine-tuning, LangChain, or LlamaIndex. By using DeepEval, you can systematically explore the best hyperparameters to enhance your RAG workflow, mitigate prompt drift, or confidently shift from OpenAI services to self-hosting your Llama2 model. Additionally, the framework features capabilities for synthetic dataset creation using advanced evolutionary techniques and integrates smoothly with well-known frameworks, making it an essential asset for efficient benchmarking and optimization of LLM systems. Its comprehensive nature ensures that developers can maximize the potential of their LLM applications across various contexts.
Description
The documentation of training for new officers is a critical responsibility that can significantly impact liability outcomes. The quality of training provided is often a decisive factor in legal matters. Our software for evaluating field training officers (FTOs), developed by seasoned professionals with over 23 years of experience in FTO management and officer training, is designed to streamline this process. Accessible via the web, this innovative tool enables training officers to meticulously record daily and monthly activities of new recruits. By engaging in an annual contract with your agency, you gain access to round-the-clock support via phone, online, and in-person, ensuring that assistance is always readily available from a knowledgeable software developer. This system allows for the creation of evaluations in a fraction of the time it would normally take, with FTOs maintaining control over the evaluations they generate. Finalization features ensure that once evaluations are completed, they cannot be altered. The software can be utilized from any computer within the department, and daily logs can be effortlessly transformed into monthly reports. Trainees have the capability to log in and electronically sign evaluations without requiring direct input from their FTO. The process of approving evaluations is simplified to a one-button operation, providing a chronological overview that enhances efficiency. Additionally, you can generate statistical reports to assess and monitor the performance of police academies, ultimately supporting continuous improvement in training practices. This ensures that your agency is equipped with the tools necessary for effective officer development and oversight.
API Access
Has API
No
API Access
Has API
No
Integrations
Hugging Face
Yes
KitchenAI
Yes
LangChain
Yes
Llama 2
Yes
LlamaIndex
Yes
OpenAI
Yes
Opik
Yes
Ragas
Yes
Weaviate
Yes
Integrations
Hugging Face
No
KitchenAI
No
LangChain
No
Llama 2
No
LlamaIndex
No
OpenAI
No
Opik
No
Ragas
No
Weaviate
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Confident AI
Country
United States
Website
docs.confident-ai.com
Vendor Details
Company Name
Wayne Enterprises
Founded
1990
Country
United States
Website
revolution911.com/fto.html
