Updated CSS and app
Browse files
app.py
CHANGED
@@ -2,6 +2,7 @@ import gradio as gr
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from haystack.document_stores import FAISSDocumentStore
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from haystack.nodes import EmbeddingRetriever
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import openai
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import os
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from utils import (
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make_pairs,
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@@ -13,15 +14,21 @@ import numpy as np
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from datetime import datetime
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from azure.storage.fileshare import ShareServiceClient
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theme = gr.themes.Soft(
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primary_hue="sky",
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font=[gr.themes.GoogleFont("
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)
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init_prompt = (
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"You are ClimateQA, an AI Assistant by Ekimetrics. "
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"You are given a question and extracted parts of IPCC reports.
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"Provide a clear and structured answer based on the context provided. "
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"When relevant, use bullet points and lists to structure your answers."
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)
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@@ -35,7 +42,7 @@ sources_prompt = (
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def get_reformulation_prompt(query: str) -> str:
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return f"""Reformulate the following user message to be a short standalone question in English, in the context of an
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---
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query: La technologie nous sauvera-t-elle ?
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standalone question: Can technology help humanity mitigate the effects of climate change?
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@@ -45,6 +52,10 @@ query: what are our reserves in fossil fuel?
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standalone question: What are the current reserves of fossil fuels and how long will they last?
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language: English
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---
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query: {query}
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standalone question:"""
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@@ -59,24 +70,24 @@ openai.api_key = os.environ["api_key"]
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openai.api_base = os.environ["ressource_endpoint"]
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openai.api_version = "2022-12-01"
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document_store=FAISSDocumentStore.load(
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index_path="./
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config_path="./
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),
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embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
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model_format="sentence_transformers",
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progress_bar=False,
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)
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retrieve_giec = EmbeddingRetriever(
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)
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credential = {
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"account_key": os.environ["account_key"],
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@@ -90,11 +101,76 @@ share_client = service.get_share_client(file_share_name)
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user_id = create_user_id(10)
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def chat(
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user_id: str,
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query: str,
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history: list = [system_template],
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report_type: str = "IPCC
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threshold: float = 0.555,
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) -> tuple:
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"""retrieve relevant documents in the document store then query gpt-turbo
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@@ -109,12 +185,14 @@ def chat(
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tuple: chat gradio format, chat openai format, sources used.
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"""
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if report_type
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reformulated_query = openai.Completion.create(
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engine="climateGPT",
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@@ -126,16 +204,29 @@ def chat(
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reformulated_query = reformulated_query["choices"][0]["text"]
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reformulated_query, language = reformulated_query.split("\n")
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language = language.split(":")[1].strip()
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messages = history + [{"role": "user", "content": query}]
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if
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docs_string = []
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docs_string.append(f"📃
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response = openai.Completion.create(
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engine="climateGPT",
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@@ -167,14 +258,14 @@ def chat(
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complete_response += chunk_message
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messages[-1]["content"] = complete_response
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gradio_format = make_pairs([a["content"] for a in messages[1:]])
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yield gradio_format, messages,
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else:
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complete_response = "**⚠️ No relevant passages found in the climate science reports, you may want to ask a more specific question (specifying your question on climate issues).**"
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messages.append({"role": "assistant", "content": complete_response})
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gradio_format = make_pairs([a["content"] for a in messages[1:]])
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yield gradio_format, messages,
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def save_feedback(feed: str, user_id):
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@@ -205,35 +296,11 @@ with gr.Blocks(title="🌍 Climate Q&A", css="style.css", theme=theme) as demo:
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# Gradio
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gr.Markdown("<h1><center>Climate Q&A 🌍</center></h1>")
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gr.Markdown("<h4><center>Ask climate-related questions to the IPCC reports</center></h4>")
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with gr.Row():
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with gr.Column(scale=1):
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gr.Markdown(
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"""
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<p><b>Climate change and environmental disruptions have become some of the most pressing challenges facing our planet today</b>. As global temperatures rise and ecosystems suffer, it is essential for individuals to understand the gravity of the situation in order to make informed decisions and advocate for appropriate policy changes.</p>
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<p>However, comprehending the vast and complex scientific information can be daunting, as the scientific consensus references, such as <b>the Intergovernmental Panel on Climate Change (IPCC) reports, span thousands of pages</b>. To bridge this gap and make climate science more accessible, we introduce <b>ClimateQ&A as a tool to distill expert-level knowledge into easily digestible insights about climate science.</b></p>
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<div class="tip-box">
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<div class="tip-box-title">
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<span class="light-bulb" role="img" aria-label="Light Bulb">💡</span>
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How does ClimateQ&A work?
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</div>
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ClimateQ&A harnesses modern OCR techniques to parse and preprocess IPCC reports. By leveraging state-of-the-art question-answering algorithms, <i>ClimateQ&A is able to sift through the extensive collection of climate scientific reports and identify relevant passages in response to user inquiries</i>. Furthermore, the integration of the ChatGPT API allows ClimateQ&A to present complex data in a user-friendly manner, summarizing key points and facilitating communication of climate science to a wider audience.
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</div>
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<div class="warning-box">
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Version 0.2-beta - This tool is under active development
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</div>
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"""
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)
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with gr.Column(scale=1):
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gr.Markdown("![](https://i.postimg.cc/fLvsvMzM/Untitled-design-5.png)")
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gr.Markdown("*Source : IPCC AR6 - Synthesis Report of the IPCC 6th assessment report (AR6)*")
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with gr.Row():
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with gr.Column(scale=2):
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chatbot = gr.Chatbot(elem_id="chatbot", label="ClimateQ&A chatbot")
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state = gr.State([system_template])
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with gr.Row():
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examples_questions = gr.Examples(
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[
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"
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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
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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 caused by humans?",
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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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with gr.Column(scale=1, variant="panel"):
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gr.Markdown("### Sources")
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sources_textbox = gr.
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ask.submit(
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fn=chat,
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inputs=[
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user_id_state,
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ask,
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state,
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default="IPCC only",
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label="Select reports",
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),
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],
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outputs=[chatbot, state, sources_textbox],
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)
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user_id_state,
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ask_examples_hidden,
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state,
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],
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outputs=[chatbot, state, sources_textbox],
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)
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gr.Markdown("## How to use ClimateQ&A")
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with gr.Row():
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with gr.Column(scale=1):
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- ClimateQ&A retrieves specific passages from the IPCC reports to help answer your question accurately.
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- Source information, including page numbers and passages, is displayed on the right side of the screen for easy verification.
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- Feel free to ask follow-up questions within the chatbot for a more in-depth understanding.
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- ClimateQ&A integrates multiple sources (IPCC
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"""
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)
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with gr.Column(scale=1):
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"""
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### Beta test
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- ClimateQ&A welcomes community contributions. To participate, head over to the Community Tab and create a "New Discussion" to ask questions and share your insights.
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- Provide feedback through
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- Only a few sources (see below) are integrated (all IPCC, IPBES
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"""
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)
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with gr.Row():
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# with gr.Column(scale=1):
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# gr.Markdown("### OpenAI API")
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demo.queue(concurrency_count=16)
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demo.launch()
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from haystack.document_stores import FAISSDocumentStore
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from haystack.nodes import EmbeddingRetriever
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import openai
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import pandas as pd
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import os
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from utils import (
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make_pairs,
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from datetime import datetime
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from azure.storage.fileshare import ShareServiceClient
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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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theme = gr.themes.Soft(
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primary_hue="sky",
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font=[gr.themes.GoogleFont("Poppins"), "ui-sans-serif", "system-ui", "sans-serif"],
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)
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init_prompt = (
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"You are ClimateQA, an AI Assistant by Ekimetrics. "
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"You are given a question and extracted parts of the IPCC and IPBES reports."
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"Provide a clear and structured answer based on the context provided. "
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"When relevant, use bullet points and lists to structure your answers."
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)
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def get_reformulation_prompt(query: str) -> str:
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return f"""Reformulate the following user message to be a short standalone question in English, in the context of an educational discussion about climate change.
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---
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query: La technologie nous sauvera-t-elle ?
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standalone question: Can technology help humanity mitigate the effects of climate change?
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standalone question: What are the current reserves of fossil fuels and how long will they last?
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language: English
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---
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query: what are the main causes of climate change?
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standalone question: What are the main causes of climate change in the last century?
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language: English
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---
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query: {query}
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standalone question:"""
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openai.api_base = os.environ["ressource_endpoint"]
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openai.api_version = "2022-12-01"
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retriever = EmbeddingRetriever(
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document_store=FAISSDocumentStore.load(
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index_path="./climateqa_v3.faiss",
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config_path="./climateqa_v3.json",
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),
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embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
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model_format="sentence_transformers",
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progress_bar=False,
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)
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# retrieve_giec = EmbeddingRetriever(
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# document_store=FAISSDocumentStore.load(
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# index_path="./documents/climate_gpt_v2_only_giec.faiss",
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# config_path="./documents/climate_gpt_v2_only_giec.json",
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# ),
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# embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
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# model_format="sentence_transformers",
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# )
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credential = {
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"account_key": os.environ["account_key"],
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user_id = create_user_id(10)
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def filter_sources(df,k_summary = 3,k_total = 10,source = "ipcc"):
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assert source in ["ipcc","ipbes","all"]
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# Filter by source
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if source == "ipcc":
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df = df.loc[df["source"]=="IPCC"]
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elif source == "ipbes":
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df = df.loc[df["source"]=="IPBES"]
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else:
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pass
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# Separate summaries and full reports
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df_summaries = df.loc[df["report_type"].isin(["SPM","TS"])]
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df_full = df.loc[~df["report_type"].isin(["SPM","TS"])]
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# Find passages from summaries dataset
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passages_summaries = df_summaries.head(k_summary)
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# Find passages from full reports dataset
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passages_fullreports = df_full.head(k_total - len(passages_summaries))
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# Concatenate passages
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passages = pd.concat([passages_summaries,passages_fullreports],axis = 0,ignore_index = True)
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return passages
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def retrieve_with_summaries(query,retriever,k_summary = 3,k_total = 10,source = "ipcc",max_k = 100,threshold = 0.555,as_dict = True):
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assert max_k > k_total
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docs = retriever.retrieve(query,top_k = max_k)
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docs = [{**x.meta,"score":x.score,"content":x.content} for x in docs if x.score > threshold]
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if len(docs) == 0:
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return []
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res = pd.DataFrame(docs)
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passages_df = filter_sources(res,k_summary,k_total,source)
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if as_dict:
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contents = passages_df["content"].tolist()
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meta = passages_df.drop(columns = ["content"]).to_dict(orient = "records")
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passages = []
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for i in range(len(contents)):
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passages.append({"content":contents[i],"meta":meta[i]})
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return passages
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else:
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return passages_df
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def make_html_source(source,i):
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meta = source['meta']
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return f"""
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<div class="card">
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<div class="card-content">
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<h2>Doc {i} - {meta['short_name']} - Page {meta['page_number']}</h2>
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<p>{source['content']}</p>
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</div>
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<div class="card-footer">
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<span>{meta['name']}</span>
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<a href="{meta['url']}#page={meta['page_number']}" target="_blank" class="pdf-link">
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<span role="img" aria-label="Open PDF">🔗</span>
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</a>
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</div>
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</div>
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"""
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def chat(
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user_id: str,
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query: str,
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history: list = [system_template],
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report_type: str = "IPCC",
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threshold: float = 0.555,
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) -> tuple:
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"""retrieve relevant documents in the document store then query gpt-turbo
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tuple: chat gradio format, chat openai format, sources used.
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"""
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if report_type not in ["IPCC","IPBES"]: report_type = "all"
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print("Searching in ",report_type," reports")
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# if report_type == "All available":
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# retriever = retrieve_all
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# elif report_type == "IPCC only":
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# retriever = retrieve_giec
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# else:
|
195 |
+
# raise Exception("report_type arg should be in (All available, IPCC only)")
|
196 |
|
197 |
reformulated_query = openai.Completion.create(
|
198 |
engine="climateGPT",
|
|
|
204 |
reformulated_query = reformulated_query["choices"][0]["text"]
|
205 |
reformulated_query, language = reformulated_query.split("\n")
|
206 |
language = language.split(":")[1].strip()
|
207 |
+
|
208 |
+
|
209 |
+
sources = retrieve_with_summaries(reformulated_query,retriever,k_total = 10,k_summary = 3,as_dict = True,source = report_type.lower(),threshold = threshold)
|
210 |
+
response_retriever = {
|
211 |
+
"language":language,
|
212 |
+
"reformulated_query":reformulated_query,
|
213 |
+
"query":query,
|
214 |
+
"sources":sources,
|
215 |
+
}
|
216 |
+
|
217 |
+
# docs = [d for d in retriever.retrieve(query=reformulated_query, top_k=10) if d.score > threshold]
|
218 |
messages = history + [{"role": "user", "content": query}]
|
219 |
|
220 |
+
if len(sources) > 0:
|
221 |
docs_string = []
|
222 |
+
docs_html = []
|
223 |
+
for i, d in enumerate(sources, 1):
|
224 |
+
docs_string.append(f"📃 Doc {i}: {d['meta']['short_name']} page {d['meta']['page_number']}\n{d['content']}")
|
225 |
+
docs_html.append(make_html_source(d,i))
|
226 |
+
docs_string = "\n\n".join([f"Query used for retrieval:\n{reformulated_query}"] + docs_string)
|
227 |
+
docs_html = "\n\n".join([f"Query used for retrieval:\n{reformulated_query}"] + docs_html)
|
228 |
+
messages.append({"role": "system", "content": f"{sources_prompt}\n\n{docs_string}\n\nAnswer in {language}:"})
|
229 |
+
|
230 |
|
231 |
response = openai.Completion.create(
|
232 |
engine="climateGPT",
|
|
|
258 |
complete_response += chunk_message
|
259 |
messages[-1]["content"] = complete_response
|
260 |
gradio_format = make_pairs([a["content"] for a in messages[1:]])
|
261 |
+
yield gradio_format, messages, docs_html
|
262 |
|
263 |
else:
|
264 |
+
docs_string = "⚠️ No relevant passages found in the climate science reports (IPCC and IPBES)"
|
265 |
+
complete_response = "**⚠️ No relevant passages found in the climate science reports (IPCC and IPBES), you may want to ask a more specific question (specifying your question on climate issues).**"
|
266 |
messages.append({"role": "assistant", "content": complete_response})
|
267 |
gradio_format = make_pairs([a["content"] for a in messages[1:]])
|
268 |
+
yield gradio_format, messages, docs_string
|
269 |
|
270 |
|
271 |
def save_feedback(feed: str, user_id):
|
|
|
296 |
# Gradio
|
297 |
gr.Markdown("<h1><center>Climate Q&A 🌍</center></h1>")
|
298 |
gr.Markdown("<h4><center>Ask climate-related questions to the IPCC reports</center></h4>")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
299 |
|
|
|
|
|
|
|
300 |
|
301 |
with gr.Row():
|
302 |
with gr.Column(scale=2):
|
303 |
+
chatbot = gr.Chatbot(elem_id="chatbot", label="ClimateQ&A chatbot",show_label = False)
|
304 |
state = gr.State([system_template])
|
305 |
|
306 |
with gr.Row():
|
|
|
312 |
|
313 |
examples_questions = gr.Examples(
|
314 |
[
|
315 |
+
"Is climate change caused by humans?",
|
316 |
+
"What evidence do we have of climate change?",
|
317 |
"What are the impacts of climate change?",
|
318 |
"Can climate change be reversed?",
|
319 |
"What is the difference between climate change and global warming?",
|
320 |
+
"What can individuals do to address climate change?",
|
321 |
+
"What are the main causes of climate change?",
|
322 |
"What is the Paris Agreement and why is it important?",
|
323 |
"Which industries have the highest GHG emissions?",
|
|
|
324 |
"Is climate change a hoax created by the government or environmental organizations?",
|
325 |
"What is the relationship between climate change and biodiversity loss?",
|
326 |
"What is the link between gender equality and climate change?",
|
|
|
351 |
|
352 |
with gr.Column(scale=1, variant="panel"):
|
353 |
gr.Markdown("### Sources")
|
354 |
+
sources_textbox = gr.Markdown(show_label=False)
|
355 |
|
356 |
+
dropdown_sources = gr.inputs.Dropdown(
|
357 |
+
["IPCC", "IPBES","IPCC and IPBES"],
|
358 |
+
default="IPCC",
|
359 |
+
label="Select reports",
|
360 |
+
)
|
361 |
ask.submit(
|
362 |
fn=chat,
|
363 |
inputs=[
|
364 |
user_id_state,
|
365 |
ask,
|
366 |
state,
|
367 |
+
dropdown_sources
|
368 |
+
|
|
|
|
|
|
|
369 |
],
|
370 |
outputs=[chatbot, state, sources_textbox],
|
371 |
)
|
|
|
377 |
user_id_state,
|
378 |
ask_examples_hidden,
|
379 |
state,
|
380 |
+
dropdown_sources
|
381 |
],
|
382 |
outputs=[chatbot, state, sources_textbox],
|
383 |
)
|
384 |
|
385 |
+
|
386 |
+
with gr.Row():
|
387 |
+
with gr.Column(scale=1):
|
388 |
+
gr.Markdown(
|
389 |
+
"""
|
390 |
+
<p><b>Climate change and environmental disruptions have become some of the most pressing challenges facing our planet today</b>. As global temperatures rise and ecosystems suffer, it is essential for individuals to understand the gravity of the situation in order to make informed decisions and advocate for appropriate policy changes.</p>
|
391 |
+
<p>However, comprehending the vast and complex scientific information can be daunting, as the scientific consensus references, such as <b>the Intergovernmental Panel on Climate Change (IPCC) reports, span thousands of pages</b>. To bridge this gap and make climate science more accessible, we introduce <b>ClimateQ&A as a tool to distill expert-level knowledge into easily digestible insights about climate science.</b></p>
|
392 |
+
<div class="tip-box">
|
393 |
+
<div class="tip-box-title">
|
394 |
+
<span class="light-bulb" role="img" aria-label="Light Bulb">💡</span>
|
395 |
+
How does ClimateQ&A work?
|
396 |
+
</div>
|
397 |
+
ClimateQ&A harnesses modern OCR techniques to parse and preprocess IPCC reports. By leveraging state-of-the-art question-answering algorithms, <i>ClimateQ&A is able to sift through the extensive collection of climate scientific reports and identify relevant passages in response to user inquiries</i>. Furthermore, the integration of the ChatGPT API allows ClimateQ&A to present complex data in a user-friendly manner, summarizing key points and facilitating communication of climate science to a wider audience.
|
398 |
+
</div>
|
399 |
+
|
400 |
+
<div class="warning-box">
|
401 |
+
Version 0.2-beta - This tool is under active development
|
402 |
+
</div>
|
403 |
+
|
404 |
+
|
405 |
+
"""
|
406 |
+
)
|
407 |
+
|
408 |
+
with gr.Column(scale=1):
|
409 |
+
gr.Markdown("![](https://i.postimg.cc/fLvsvMzM/Untitled-design-5.png)")
|
410 |
+
gr.Markdown("*Source : IPCC AR6 - Synthesis Report of the IPCC 6th assessment report (AR6)*")
|
411 |
+
|
412 |
gr.Markdown("## How to use ClimateQ&A")
|
413 |
with gr.Row():
|
414 |
with gr.Column(scale=1):
|
|
|
419 |
- ClimateQ&A retrieves specific passages from the IPCC reports to help answer your question accurately.
|
420 |
- Source information, including page numbers and passages, is displayed on the right side of the screen for easy verification.
|
421 |
- Feel free to ask follow-up questions within the chatbot for a more in-depth understanding.
|
422 |
+
- ClimateQ&A integrates multiple sources (IPCC and IPBES, … ) to cover various aspects of environmental science, such as climate change and biodiversity. See all sources used below.
|
423 |
"""
|
424 |
)
|
425 |
with gr.Column(scale=1):
|
|
|
439 |
"""
|
440 |
### Beta test
|
441 |
- ClimateQ&A welcomes community contributions. To participate, head over to the Community Tab and create a "New Discussion" to ask questions and share your insights.
|
442 |
+
- Provide feedback through email, letting us know which insights you found accurate, useful, or not. Your input will help us improve the platform.
|
443 |
+
- Only a few sources (see below) are integrated (all IPCC, IPBES), if you are a climate science researcher and net to sift through another report, please let us know.
|
444 |
+
|
445 |
+
If you need us to ask another climate science report or ask any question, contact us at <b>[email protected]</b>
|
446 |
"""
|
447 |
)
|
448 |
+
# with gr.Row():
|
449 |
+
# with gr.Column(scale=1):
|
450 |
+
# gr.Markdown("### Feedbacks")
|
451 |
+
# feedback = gr.Textbox(label="Write your feedback here")
|
452 |
+
# feedback_output = gr.Textbox(label="Submit status")
|
453 |
+
# feedback_save = gr.Button(value="submit feedback")
|
454 |
+
# feedback_save.click(
|
455 |
+
# save_feedback,
|
456 |
+
# inputs=[feedback, user_id_state],
|
457 |
+
# outputs=feedback_output,
|
458 |
+
# )
|
459 |
+
# gr.Markdown(
|
460 |
+
# "If you need us to ask another climate science report or ask any question, contact us at <b>[email protected]</b>"
|
461 |
+
# )
|
462 |
|
463 |
# with gr.Column(scale=1):
|
464 |
# gr.Markdown("### OpenAI API")
|
|
|
550 |
|
551 |
demo.queue(concurrency_count=16)
|
552 |
|
553 |
+
demo.launch(server_port = 8080)
|
style.css
CHANGED
@@ -1,3 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
1 |
.warning-box {
|
2 |
background-color: #fff3cd;
|
3 |
border: 1px solid #ffeeba;
|
@@ -42,4 +47,118 @@
|
|
42 |
|
43 |
.message{
|
44 |
font-size:14px !important;
|
45 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
|
2 |
+
:root {
|
3 |
+
--user-image: url('https://ih1.redbubble.net/image.4776899543.6215/st,small,507x507-pad,600x600,f8f8f8.jpg');
|
4 |
+
}
|
5 |
+
|
6 |
.warning-box {
|
7 |
background-color: #fff3cd;
|
8 |
border: 1px solid #ffeeba;
|
|
|
47 |
|
48 |
.message{
|
49 |
font-size:14px !important;
|
50 |
+
}
|
51 |
+
|
52 |
+
|
53 |
+
a {
|
54 |
+
text-decoration: none;
|
55 |
+
color: inherit;
|
56 |
+
}
|
57 |
+
|
58 |
+
.card {
|
59 |
+
background-color: white;
|
60 |
+
border-radius: 10px;
|
61 |
+
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
|
62 |
+
overflow: hidden;
|
63 |
+
display: flex;
|
64 |
+
flex-direction: column;
|
65 |
+
margin:20px;
|
66 |
+
}
|
67 |
+
|
68 |
+
.card-content {
|
69 |
+
padding: 20px;
|
70 |
+
}
|
71 |
+
|
72 |
+
.card-content h2 {
|
73 |
+
font-size: 14px !important;
|
74 |
+
font-weight: bold;
|
75 |
+
margin-bottom: 10px;
|
76 |
+
margin-top:0px !important;
|
77 |
+
color:#577b9b!important;;
|
78 |
+
}
|
79 |
+
|
80 |
+
.card-content p {
|
81 |
+
font-size: 12px;
|
82 |
+
margin-bottom: 0;
|
83 |
+
}
|
84 |
+
|
85 |
+
.card-footer {
|
86 |
+
background-color: #f4f4f4;
|
87 |
+
font-size: 10px;
|
88 |
+
padding: 10px;
|
89 |
+
display: flex;
|
90 |
+
justify-content: space-between;
|
91 |
+
align-items: center;
|
92 |
+
}
|
93 |
+
|
94 |
+
.card-footer span {
|
95 |
+
flex-grow: 1;
|
96 |
+
text-align: left;
|
97 |
+
color: #999 !important;
|
98 |
+
}
|
99 |
+
|
100 |
+
.pdf-link {
|
101 |
+
display: inline-flex;
|
102 |
+
align-items: center;
|
103 |
+
margin-left: auto;
|
104 |
+
text-decoration: none!important;
|
105 |
+
font-size: 14px;
|
106 |
+
}
|
107 |
+
|
108 |
+
|
109 |
+
|
110 |
+
.message.user{
|
111 |
+
background-color:#7494b0 !important;
|
112 |
+
border:none;
|
113 |
+
color:white!important;
|
114 |
+
}
|
115 |
+
|
116 |
+
.message.bot{
|
117 |
+
background-color:#f2f2f7 !important;
|
118 |
+
border:none;
|
119 |
+
}
|
120 |
+
|
121 |
+
.gallery-item > div:hover{
|
122 |
+
background-color:#7494b0 !important;
|
123 |
+
color:white!important;
|
124 |
+
}
|
125 |
+
|
126 |
+
.gallery-item:hover{
|
127 |
+
border:#7494b0 !important;
|
128 |
+
}
|
129 |
+
|
130 |
+
.gallery-item > div{
|
131 |
+
background-color:white !important;
|
132 |
+
color:#577b9b!important;
|
133 |
+
}
|
134 |
+
|
135 |
+
.label{
|
136 |
+
color:#577b9b!important;
|
137 |
+
}
|
138 |
+
|
139 |
+
.paginate{
|
140 |
+
color:#577b9b!important;
|
141 |
+
}
|
142 |
+
|
143 |
+
|
144 |
+
label > span{
|
145 |
+
background-color:white !important;
|
146 |
+
color:#577b9b!important;
|
147 |
+
}
|
148 |
+
|
149 |
+
/* Pseudo-element for the circularly cropped picture */
|
150 |
+
.message.bot::before {
|
151 |
+
content: '';
|
152 |
+
position: absolute;
|
153 |
+
top: -10px;
|
154 |
+
left: -10px;
|
155 |
+
width: 30px;
|
156 |
+
height: 30px;
|
157 |
+
background-image: var(--user-image);
|
158 |
+
background-size: cover;
|
159 |
+
background-position: center;
|
160 |
+
border-radius: 50%;
|
161 |
+
z-index: 10;
|
162 |
+
}
|
163 |
+
|
164 |
+
|