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Updated pips. Updated README.
Browse files- .github/workflows/docker-image.yml +1 -1
- README.md +65 -0
- requirements.txt +3 -3
.github/workflows/docker-image.yml
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@@ -37,5 +37,5 @@ jobs:
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push: true
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tags: |
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yaleh/meta-prompt:${{ github.sha }}
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yaleh/meta-prompt:latest
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push: true
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tags: |
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yaleh/meta-prompt:${{ github.sha }}
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${{ github.ref == 'refs/heads/main' && 'yaleh/meta-prompt:latest' || '' }}
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README.md
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@@ -8,6 +8,8 @@ This project is a demonstration of the concept of Meta Prompt, which involves ge
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The demo utilizes OpenAI's language models and provides a user interface for interacting with the chatbot. It allows users to input prompts, execute model calls, compare outputs, and optimize prompts based on desired criteria.
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## Try it out!
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[](https://colab.research.google.com/github/yaleh/meta-prompt/blob/main/meta_prompt.ipynb)
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2019-2018,-2.56%,-2.59%,0.01%,-4.11%,0.30%
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```
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## License
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This project is licensed under the MIT License. Please see the [LICENSE](LICENSE) file for more information.
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The demo utilizes OpenAI's language models and provides a user interface for interacting with the chatbot. It allows users to input prompts, execute model calls, compare outputs, and optimize prompts based on desired criteria.
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**New Update (2023/10/15):** A new working mode called `Other User Prompts` has been added. In the prompt optimization process, similar compatible prompts to the original user prompt are referenced to significantly reduce iteration cycles.
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## Try it out!
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[](https://colab.research.google.com/github/yaleh/meta-prompt/blob/main/meta_prompt.ipynb)
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2019-2018,-2.56%,-2.59%,0.01%,-4.11%,0.30%
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```
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#### Other User Prompts
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```
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Here is the GDP data in billions of US dollars (USD) for these years:
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1. China:
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- 2010: $6,101.18 billion
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- 2011: $7,572.80 billion
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- 2012: $8,560.59 billion
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- 2013: $9,607.23 billion
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- 2014: $10,482.65 billion
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2. India:
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- 2010: $1,675.62 billion
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- 2011: $1,823.05 billion
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- 2012: $1,827.64 billion
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- 2013: $1,856.72 billion
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- 2014: $2,046.88 billion
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3. Japan:
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- 2010: $5,700.35 billion
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- 2011: $6,157.47 billion
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- 2012: $6,203.21 billion
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- 2013: $5,155.72 billion
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- 2014: $4,616.52 billion
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4. South Korea:
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- 2010: $1,464.26 billion
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- 2011: $1,622.03 billion
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- 2012: $1,624.76 billion
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- 2013: $1,305.76 billion
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- 2014: $1,411.25 billion
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5. Indonesia:
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- 2010: $706.39 billion
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- 2011: $846.48 billion
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- 2012: $878.47 billion
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- 2013: $868.36 billion
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- 2014: $891.77 billion
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```
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#### Prompt After 1 Interation
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```
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ROLE
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You are an economic analyst.
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TASK
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Your task is to calculate the annual percentage change in GDP for each country based on the provided data.
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REQUIREMENTS_AND_RESTRICTIONS
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- The data will be provided in the format: "Year: $GDP in billions"
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- Calculate the percentage change from year to year for each country.
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- Present the results in a table format, with each row representing the change from one year to the next, and each column representing a different country.
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- The table should be formatted as "Year-Year,Country1,Country2,..."
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- The percentage change should be calculated as ((GDP Year 2 - GDP Year 1) / GDP Year 1) * 100
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- The percentage change should be rounded to two decimal places and followed by a "%" symbol.
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- If data for a year is missing for a country, leave that cell blank in the table.
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```
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## License
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This project is licensed under the MIT License. Please see the [LICENSE](LICENSE) file for more information.
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requirements.txt
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jsonschema==4.19.1
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jsonschema-specifications==2023.7.1
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kiwisolver==1.4.5
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langchain==0.0.
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langsmith==0.0.
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MarkupSafe==2.1.3
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marshmallow==3.20.1
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matplotlib==3.8.0
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typing-inspect==0.9.0
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typing_extensions==4.8.0
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tzdata==2023.3
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urllib3==2.0.
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uvicorn==0.23.2
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websockets==11.0.3
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yarl==1.9.2
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jsonschema==4.19.1
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jsonschema-specifications==2023.7.1
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kiwisolver==1.4.5
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langchain==0.0.312
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langsmith==0.0.43
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MarkupSafe==2.1.3
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marshmallow==3.20.1
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matplotlib==3.8.0
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typing-inspect==0.9.0
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typing_extensions==4.8.0
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tzdata==2023.3
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urllib3==2.0.6
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uvicorn==0.23.2
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websockets==11.0.3
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yarl==1.9.2
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