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Readme fixes #593

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41 changes: 26 additions & 15 deletions README.md
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
<h4 align="center">
<a href="https://www.uptrain.ai">
<a href="https://uptrain.ai">
<img alt="Logo of UpTrain - an open-source platform to evaluate and improve LLM applications" src="https://github.com/uptrain-ai/uptrain/assets/108270398/b6a4905f-63fd-47ab-a894-1026a6669c86"/>
</a>
</h4>
Expand All @@ -21,7 +21,7 @@
<img src="https://github.com/uptrain-ai/uptrain/assets/108270398/10d0faeb-c4f8-422f-a01e-49a891fa7ada" alt="Demo of UpTrain's LLM evaluations with scores for hallucinations, retrieved-context quality, response tonality for a customer support chatbot"/>
</h4>

**[UpTrain](https://www.uptrain.ai)** is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.
**[UpTrain](https://uptrain.ai)** is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

<br />

Expand Down Expand Up @@ -55,14 +55,17 @@ UpTrain provides tons of ways to **customize evaluations**. You can customize ev

Support for **40+ operators** such as BLEU, ROUGE, Embeddings Similarity, Exact match, etc.

<img width="1088" alt="Interactive Dashboards" src="https://github.com/uptrain-ai/uptrain/assets/36454110/eb1c8239-dd99-4e66-ba8a-cbaee2beec10">

UpTrain Dashboard is a web-based interface that runs on your **local machine**. You can use the dashboard to evaluate your LLM applications, view the results, and perform root cause analysis.


### Coming Soon:

1. Experiment Dashboards
2. Collaborate with your team
3. Embedding visualization via UMAP and Clustering
4. Pattern recognition among failure cases
5. Prompt improvement suggestions
1. Collaborate with your team
2. Embedding visualization via UMAP and Clustering
3. Pattern recognition among failure cases
4. Prompt improvement suggestions

<br />

Expand All @@ -71,18 +74,19 @@ Support for **40+ operators** such as BLEU, ROUGE, Embeddings Similarity, Exact

| Eval | Description |
| ---- | ----------- |
|[Reponse Completeness](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-completeness) | Grades whether the response has answered all the aspects of the question specified. |
|[Reponse Conciseness](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-conciseness) | Grades how concise the generated response is or if it has any additional irrelevant information for the question asked. |
|[Reponse Relevance](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-relevance)| Grades how relevant the generated context was to the question specified.|
|[Reponse Validity](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-validity)| Grades if the response generated is valid or not. A response is considered to be valid if it contains any information.|
|[Reponse Consistency](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-consistency)| Grades how consistent the response is with the question asked as well as with the context provided.|
|[Response Completeness](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-completeness) | Grades whether the response has answered all the aspects of the question specified. |
|[Response Conciseness](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-conciseness) | Grades how concise the generated response is or if it has any additional irrelevant information for the question asked. |
|[Response Relevance](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-relevance)| Grades how relevant the generated context was to the question specified.|
|[Response Validity](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-validity)| Grades if the response generated is valid or not. A response is considered to be valid if it contains any information.|
|[Response Consistency](https://docs.uptrain.ai/predefined-evaluations/response-quality/response-consistency)| Grades how consistent the response is with the question asked as well as with the context provided.|

<img width="1088" alt="quality of retrieved context and response groundedness" src="https://github.com/uptrain-ai/uptrain/assets/43818888/a7e384a3-c857-4a71-a938-7a2a70f8db1e">


| Eval | Description |
| ---- | ----------- |
|[Context Relevance](https://docs.uptrain.ai/predefined-evaluations/context-awareness/context-relevance) | Grades how relevant the context was to the question specified. |
|[Context Utilization](https://docs.uptrain.ai/predefined-evaluations/context-awareness/context-utilization) | Grades how complete the generated response was for the question specified given the information provided in the context. |
|[Context Utilization](https://docs.uptrain.ai/predefined-evaluations/context-awareness/context-utilization) | Grades how complete the generated response was for the question specified, given the information provided in the context. |
|[Factual Accuracy](https://docs.uptrain.ai/predefined-evaluations/context-awareness/factual-accuracy)| Grades whether the response generated is factually correct and grounded by the provided context.|
|[Context Conciseness](https://docs.uptrain.ai/predefined-evaluations/context-awareness/context-conciseness)| Evaluates the concise context cited from an original context for irrelevant information.
|[Context Reranking](https://docs.uptrain.ai/predefined-evaluations/context-awareness/context-reranking)| Evaluates how efficient the reranked context is compared to the original context.|
Expand All @@ -91,7 +95,7 @@ Support for **40+ operators** such as BLEU, ROUGE, Embeddings Similarity, Exact

| Eval | Description |
| ---- | ----------- |
|[Language Features](https://docs.uptrain.ai/predefined-evaluations/language-quality/fluency-and-coherence) | Grades whether the response has answered all the aspects of the question specified. |
|[Language Features](https://docs.uptrain.ai/predefined-evaluations/language-quality/fluency-and-coherence) | Grades the quality and effectiveness of language in a response, focusing on factors such as clarity, coherence, conciseness, and overall communication. |
|[Tonality](https://docs.uptrain.ai/predefined-evaluations/code-evals/code-hallucination) | Grades whether the generated response matches the required persona's tone |

<img width="1088" alt="language quality of the response" src="https://github.com/uptrain-ai/uptrain/assets/36454110/2fba9f0b-71b3-4d90-90f8-16ef38cef3ab">
Expand Down Expand Up @@ -123,9 +127,15 @@ Support for **40+ operators** such as BLEU, ROUGE, Embeddings Similarity, Exact

| Eval | Description |
| ---- | ----------- |
|[Prompt Injection](https://docs.uptrain.ai/predefined-evaluations/safeguarding/prompt-injection) | Grades whether the generated response is leaking any system prompt. |
|[Prompt Injection](https://docs.uptrain.ai/predefined-evaluations/safeguarding/prompt-injection) | Grades whether the user's prompt is an attempt to make the LLM reveal its system prompts. |
|[Jailbreak Detection](https://docs.uptrain.ai/predefined-evaluations/safeguarding/jailbreak) | Grades whether the user's prompt is an attempt to jailbreak (i.e. generate illegal or harmful responses). |

<img width="1088" alt="evaluate the clarity of user queries" src="https://github.com/uptrain-ai/uptrain/assets/36454110/50ed622f-0b92-468c-af48-2391ff6ab8e0">

| Eval | Description |
| ---- | ----------- |
|[Sub-Query Completeness](https://docs.uptrain.ai/predefined-evaluations/query-quality/sub-query-completeness) | Evaluate whether all of the sub-questions generated from a user's query, taken together, cover all aspects of the user's query or not |

<br />

# Get started 🙌
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Expand All @@ -147,6 +157,7 @@ cd uptrain
# Run UpTrain
bash run_uptrain.sh
```
> **_NOTE:_** UpTrain Dashboard is currently in **Beta version**. We would love your feedback to improve it.

## Using the UpTrain package

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2 changes: 2 additions & 0 deletions docs/dashboard/evaluations.mdx
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Expand Up @@ -55,6 +55,8 @@ You can look at the complete list of UpTrain's supported metrics [here](/predefi
</Step>
</Steps>

<Note>UpTrain Dashboard is currently in Beta version. We would love your feedback to improve it.</Note>

<CardGroup cols={1}>
<Card
title="Have Questions?"
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3 changes: 3 additions & 0 deletions docs/dashboard/getting_started.mdx
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Expand Up @@ -12,6 +12,7 @@ You can use the dashboard to evaluate your LLM applications, view the results, m

<Note>Before you start, ensure you have docker installed on your machine. If not, you can install it from [here](https://docs.docker.com/get-docker/). </Note>


### How to install?

The following commands will download the UpTrain dashboard and start it on your local machine:
Expand All @@ -24,6 +25,8 @@ cd uptrain
bash run_uptrain.sh
```

<Note>UpTrain Dashboard is currently in Beta version. We would love your feedback to improve it.</Note>

<CardGroup cols={1}>
<Card
title="Have Questions?"
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2 changes: 2 additions & 0 deletions docs/dashboard/project.mdx
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Expand Up @@ -38,6 +38,8 @@ There are 2 types of projects we support:

Now that you have created a project, you can run evaluations or experiment with prompts

<Note>UpTrain Dashboard is currently in Beta version. We would love your feedback to improve it.</Note>

<CardGroup cols={1}>
<Card
title="Have Questions?"
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2 changes: 2 additions & 0 deletions docs/dashboard/prompts.mdx
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Expand Up @@ -55,6 +55,8 @@ You can look at the complete list of UpTrain's supported metrics [here](/predefi
</Step>
</Steps>

<Note>UpTrain Dashboard is currently in Beta version. We would love your feedback to improve it.</Note>

<CardGroup cols={1}>
<Card
title="Have Questions?"
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@@ -1,11 +1,9 @@
---
title: Response Matching
description: Grades how relevant the generated context was to the question specified.
description: Grades how well the response generated by the LLM aligns with the provided ground truth.
---

Response relevance is the measure of how relevant the generated response is to the question asked.

It helps evaluate how well the response addresses the question asked and if it contains any additional information that is not relevant to the question asked.
Response Matching compares the LLM-generated text with the gold (ideal) response using the defined score metric.

Columns required:
- `question`: The question asked by the user
Expand Down
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