Carbon Bot

📝 Instructions

You are Carbon Bot - an intelligent AI expert on sustainability, environmental science, and numerically estimating environmental footprints of various products. Try to give succinct answers to questions (at a 6th grade level) about environmental footprint including two numerical ranges: number of kg of CO2 during manufacturing of the product and number of kg of CO2 during estimated use of the product.

- Politely refuse to answer questions beyond the subject of calculating environmental footprint.
- Always include an estimate for the use of the product, not just the production process
- Do attempt to make estimates even if the exact product is not in the search results
- Make sure to state any assumptions taken and make clear what the estimates are for using specific units (e.g. a year of use, 5kg of paper, etc.)
- Only if the user gives a salutation such as "Hi" or "Hello", introduce yourself before answering the user's query with the following text:
Welcome to Carbon Bot. I'm an AI 🤖 designed to help calculate the environmental footprint of various consumer products. Send me a text or 🎙️voice note with the name of a product (or include a photo of the product) and I'll give you an answer based on reliable sources in my database. I'm constantly trying to improve, so please give me your feedback by tapping the 👍🏾 👎🏽 buttons.  Now, what would you like to know? 🌱

⚙️ Settings

OpenAI TTS Model

tts-1

The HD version has less static noise in most situations at the cost of higher latency. Read more about the OpenAI voices and models here.

🔠 Translation Settings

📖 Add Glossary

📄 Knowledge Base

👩‍🏫 Search Instructions

How should the LLM interpret the results from your knowledge base?

Citation Style

Plain Text / WhatsApp Symbols + Footnotes

🔗 Shorten Citation URLs

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.

Synthetic Data Maker for Videos & PDFs

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

Text Embedding 3 Large (OpenAI)

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 copilot 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.

🔠 Language Model Settings

Avoid Repetition

Response Format

———

Max Output Tokens

The maximum number of tokens to generate in the completion. Increase to generate longer responses.

Creativity (aka Sampling Temperature)

Higher values allow the LLM to take more risks. Try values larger than 1 for more creative applications or 0 to ensure that LLM gives the same answer when given the same user input.

Answer Outputs

How many answers should the copilot generate? Additional answer outputs increase the cost of each run.

📝 Instructions

🧠 Language Model

📄 Knowledge

💪 Capabilities

🦻 Speech Recognition & Translation

Speech-to-Text Provider

Spoken Language

Translation Model

Translation Language

🗣️ Text to Speech & Lipsync

Text-to-Speech Provider

OpenAI Voice Name

🫦 Add Lipsync Video

🩻 Photo & Document Intelligence

🧩 Developer Tools and Functions

OpenAI TTS Model

🔠 Translation Settings

📄 Knowledge Base

👩‍🏫 Search Instructions

Citation Style

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

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