Updated CSS
Browse files- app.py +54 -56
- climateqa/llm.py +7 -5
- climateqa/vectorstore.py +6 -4
- style.css +16 -2
app.py
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@@ -342,66 +342,65 @@ with gr.Blocks(title="π Climate Q&A", css="style.css", theme=theme) as demo:
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# gr.Markdown("<h1><center>Climate Q&A π</center></h1>")
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# gr.Markdown("<h4><center>Ask climate-related questions to the IPCC and IPBES reports using AI</center></h4>")
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with gr.Tab("
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with gr.Row():
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with gr.Column(scale=2):
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# state = gr.State([system_template])
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bot = gr.Chatbot(height=
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with gr.Column(scale=1, variant="panel"):
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with gr.Tab("π Citations"):
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sources_textbox = gr.Markdown(show_label=False, elem_id="sources-textbox")
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with gr.Tab("βοΈ Configuration"):
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gr.Markdown("Reminder: You can talk in any language, ClimateQ&A is multi-lingual!")
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@@ -613,5 +612,4 @@ Or around 2 to 4 times more than a typical Google search.
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demo.queue(concurrency_count=16)
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demo.launch()
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# gr.Markdown("<h1><center>Climate Q&A π</center></h1>")
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# gr.Markdown("<h4><center>Ask climate-related questions to the IPCC and IPBES reports using AI</center></h4>")
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with gr.Tab("π ClimateQ&A"):
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with gr.Row(elem_id="chatbot-row"):
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with gr.Column(scale=2):
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# state = gr.State([system_template])
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bot = gr.Chatbot(height="100%",show_copy_button=True,show_label = False,elem_id="chatbot")
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textbox=gr.Textbox(placeholder="Ask me a question about climate change or biodiversity in any language!",show_label=False)
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submit_button = gr.Button("Submit")
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with gr.Column(scale=1, variant="panel",elem_id = "right-panel"):
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with gr.Tab("π Examples",elem_id = "tab-examples"):
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examples_hidden = gr.Textbox(elem_id="hidden-message")
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examples_questions = gr.Examples(
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[
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"Is climate change caused by humans?",
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"What evidence do we have of climate change?",
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"What are the impacts of climate change?",
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"Can climate change be reversed?",
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"What is the difference between climate change and global warming?",
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"What can individuals do to address climate change?",
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"What are the main causes of climate change?",
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"What is the Paris Agreement and why is it important?",
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"Which industries have the highest GHG emissions?",
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"Is climate change a hoax created by the government or environmental organizations?",
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"What is the relationship between climate change and biodiversity loss?",
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"What is the link between gender equality and climate change?",
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"Is the impact of climate change really as severe as it is claimed to be?",
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"What is the impact of rising sea levels?",
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"What are the different greenhouse gases (GHG)?",
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"What is the warming power of methane?",
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"What is the jet stream?",
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"What is the breakdown of carbon sinks?",
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"How do the GHGs work ? Why does temperature increase ?",
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"What is the impact of global warming on ocean currents?",
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"How much warming is possible in 2050?",
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"What is the impact of climate change in Africa?",
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"Will climate change accelerate diseases and epidemics like COVID?",
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"What are the economic impacts of climate change?",
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"How much is the cost of inaction ?",
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"What is the relationship between climate change and poverty?",
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"What are the most effective strategies and technologies for reducing greenhouse gas (GHG) emissions?",
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"Is economic growth possible? What do you think about degrowth?",
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"Will technology save us?",
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"Is climate change a natural phenomenon ?",
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"Is climate change really happening or is it just a natural fluctuation in Earth's temperature?",
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"Is the scientific consensus on climate change really as strong as it is claimed to be?",
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],
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[examples_hidden],
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examples_per_page=10,
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)
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with gr.Tab("π Citations",elem_id = "tab-citations"):
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sources_textbox = gr.Markdown(show_label=False, elem_id="sources-textbox")
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with gr.Tab("βοΈ Configuration",elem_id = "tab-config"):
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gr.Markdown("Reminder: You can talk in any language, ClimateQ&A is multi-lingual!")
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demo.queue(concurrency_count=16)
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demo.launch()
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climateqa/llm.py
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@@ -1,9 +1,11 @@
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from langchain.chat_models import AzureChatOpenAI
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# LOAD ENVIRONMENT VARIABLES
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from dotenv import load_dotenv
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import os
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def get_llm(max_tokens = 1024,temperature = 0.0,verbose = True,streaming = False, **kwargs):
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streaming = streaming,
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**kwargs,
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)
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return llm
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from langchain.chat_models import AzureChatOpenAI
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import os
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# LOAD ENVIRONMENT VARIABLES
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try:
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from dotenv import load_dotenv
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load_dotenv()
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except:
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pass
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def get_llm(max_tokens = 1024,temperature = 0.0,verbose = True,streaming = False, **kwargs):
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streaming = streaming,
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**kwargs,
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)
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return llm
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climateqa/vectorstore.py
CHANGED
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# Pinecone
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# More info at https://docs.pinecone.io/docs/langchain
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# And https://python.langchain.com/docs/integrations/vectorstores/pinecone
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import pinecone
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from langchain.vectorstores import Pinecone
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# LOAD ENVIRONMENT VARIABLES
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import
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load_dotenv()
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def get_pinecone_vectorstore(embeddings,text_key = "content"):
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# Pinecone
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# More info at https://docs.pinecone.io/docs/langchain
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# And https://python.langchain.com/docs/integrations/vectorstores/pinecone
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import os
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import pinecone
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from langchain.vectorstores import Pinecone
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# LOAD ENVIRONMENT VARIABLES
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try:
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from dotenv import load_dotenv
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load_dotenv()
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except:
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pass
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def get_pinecone_vectorstore(embeddings,text_key = "content"):
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style.css
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background:none !important;
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}
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div#sources-textbox{
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height:100vh;
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overflow-y: auto;
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}
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background:none !important;
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}
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div#tab-examples{
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height:calc(100vh - 190px) !important;
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overflow-y: auto;
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}
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div#sources-textbox{
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height:calc(100vh - 190px) !important;
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overflow-y: auto;
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}
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div#chatbot-row{
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height:calc(100vh - 120px);
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}
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div#chatbot{
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height:calc(100vh - 270px)
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}
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