Health: Nursing advice from a 4000 page PDF

⚙️ Settings

Microsoft Server Speech Text to Speech Voice (en-IN, AnanyaNeural):

Name: Ananya
Gender: Female
Locale: English (India)
Locale Code: en-IN
Sample Rate: 48000 Hz
Voice Type: Neural
Words Per Minute: None

See all the supported languages and voices here.

📄 Knowledge Base

👩‍🏫 Search Instructions

Make sure to use only the following search results to guide your response. Do not quote the sources and search results in your responses.

[Guidelines]
- Use an unbiased, succinct, and friendly tone. Think step-by-step and ask questions one at a time. 
- If the user gives a salutation such as "Hi" or "Hello", introduce yourself before answering the user's query with the text below between the triple backticks:
```
Welcome to Noora Health. I'm an AI 🤖 designed to help caregivers and patients. Send me a text or 🎙️voice note with any health concern or question and I'll give you an answer based on recommendations and best practices. Now how can i help you?. 
```
- Please ask the user once for their location, gender, whether they are a caregiver or a patient improve your answer to their questions.
- Make sure to use only the Search Results to produce a coherent answer
- If the Search Results provide insufficient information, refuse to answer the question and redirect the user to https://noorahealth.org/ for more help. 
- If the Search Result's Title or Snippet is unrelated or irrelevant to the question, don't respond and just say you don't know.
- Never give advice to search the Internet. 
- Politely refuse to answer questions beyond the subject of medical care, health care.
- Respond in the same language as the last question or statement uttered by the user. Do not quote the sources and search results in your responses. 
- Organize the response based on the most critical issue to least
- Highlight actions and recommendations as separate itemized lists in your responses. 
- Please complete the last sentence even if it does not fit into maximum number of token. 
- Use the tone provided in the [SAMPLE QUESTION AND ANSWER] section

Citation Style

🔗 Shorten citation links

Cache

By default we embed your knowledge files & links and cache their contents for fast responses.

Always Check for Updates

Create Synthetic Data

To improve answer quality, pick a synthetic data maker workflow to scan & OCR any images in your documents or transcribe & translate any videos. It also can synthesize a helpful FAQ. Adds ~2 minutes of one-time processing per file.

Advanced Settings

In general, you should not need to adjust these.

👁‍🗨 Conversation Summarization

These instructions run before the knowledge base is search and should reduce the conversation into a search query most relevant to the user's last message.

🔑 Keyword Extraction

Instructions to create a query for keyword/hybrid BM25 search. Runs after the Conversations Summarization above and can use its result via {{ final_search_query }}.

✏ Embeddings Model

Dense Embeddings Weightage

Weightage for dense vs sparse embeddings. 0 for sparse, 1 for dense, 0.5 for equal weight.
Generally speaking, dense embeddings excel at understanding the context of the query, whereas sparse vectors excel at keyword matches.

Max Citations

The maximum number of document search citations.

Max Snippet Words

After a document search, relevant snippets of your documents are returned as results.
This setting adjusts the maximum number of words in each snippet (tokens = words * 2).
A high snippet size allows the LLM to access more information from your document results, at the cost of being verbose and potentially exhausting input tokens (which can cause a failure of the agent to respond).

Snippet Overlap Ratio

Your knowledge base documents are split into overlapping snippets.
This settings adjusts how much those snippets overlap (overlap tokens = snippet tokens / overlap ratio).
In general you shouldn't need to adjust this.

Instructions

Language Model

Knowledge Base

💪 Capabilities

🦻 Speech Recognition & Translation

🗣️ Text to Speech & Lipsync

Text-to-Speech Provider

Azure TTS Voice name

🩻 Photo & Document Intelligence

📊 Analytics & Evaluation

🛠️ Developer Tools and Functions

Microsoft Server Speech Text to Speech Voice (en-IN, AnanyaNeural):

📄 Knowledge Base

👩‍🏫 Search Instructions

Citation Style

Cache

Create Synthetic Data

Advanced Settings

👁‍🗨 Conversation Summarization

🔑 Keyword Extraction

✏ Embeddings Model

Dense Embeddings Weightage

Max Citations

Max Snippet Words

Snippet Overlap Ratio

🔠 Language Model Settings

Response Format

Max Output Tokens

Creativity (aka Sampling Temperature)

Answer Outputs

How to Use This Recipe

Related Workflows

Lipsync with Text-to-Speech

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