Add application file

README.md

@@ -1,41 +1,12 @@
-# auto_evaluator
-
-### Aim
-In this lesson we want to create a app which thake some data and from that data we provide some questions and answer. Then we test that answer through LLM and grade them.
-
-Context
-
-Document Question-Answering is a popular LLM use-case. LangChain makes it easy to assemble LLM components (e.g., models and retrievers) into chains that support question-answering: input documents are split into chunks and stored in a retriever, relevant chunks are retrieved given a user question and passed to an LLM for synthesis into an answer.
-
-Challenge
-
-The quality of QA systems can vary considerably; for example, we have seen cases of hallucination and poor answer quality due specific parameter settings. But, it is not always obvious to (1) evaluate the answer quality in a systematic way and (2) use this evaluation to guide improved QA chain settings (e.g., chunk size) or components (e.g., model or retriever choice).
-
-App overview
-
-This app aims to address the above limitations. Recent work from Anthropic has used model-written evaluation sets. OpenAI and others have shown that model-graded evaluation is an effective way to evaluate models. This app combines both of these ideas into a single workspace, auto-generating a QA test set and auto-grading the result of the specified QA chain.
-
-![image](https://github.com/DeepakJaiz/auto_evaluator/assets/120568685/d9a2aaac-e8c1-4836-b6d8-7121ad797ccf)
-
-### Reference
-https://github.com/langchain-ai/auto-evaluator/blob/main/README.md
-
-### Prerequist
-`You required Phython in your system fyou can follow this (https://www.python.org)`<br/>
-`OpenAi API key required to get you can follow this link (https://platform.openai.com/account/api-keys)`<br/>
-`Create a account on huggingface https://huggingface.co/login`<br/>
-
-### Modules required
-All the requirment are define in requirment.text file.
-### How to run
-1. Open the huggingface after login.
-2. Go to the space button and then create new space.
-3. For creating new space enter the name of space as you want, then select "streamlit" from select the space sdk. Then make your space public or private as you want.
-4. After that click the create space.
-5. Then upload all the above file in your space.
-6. Then you can see your application by clicking the app button.
-
-### How to use app
-1. In left side enter your open API Key.
-2. Upload you source data in pdf and text format.
-3. Upload your test question answer in JSON format just below it.
+---
+title: Test
+emoji: 🐢
+colorFrom: gray
+colorTo: yellow
+sdk: streamlit
+sdk_version: 1.21.0
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference