add graphs in a separate pannel
Browse files- app.py +65 -31
- front/utils.py +50 -2
- sandbox/20240310 - CQA - Semantic Routing 1.ipynb +0 -0
- style.css +6 -1
app.py
CHANGED
@@ -32,7 +32,7 @@ from utils import create_user_id
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# ClimateQ&A imports
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from climateqa.engine.llm import get_llm
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from climateqa.engine.vectorstore import get_pinecone_vectorstore
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-
from climateqa.knowledge.retriever import ClimateQARetriever
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from climateqa.engine.reranker import get_reranker
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from climateqa.engine.embeddings import get_embeddings_function
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from climateqa.engine.chains.prompts import audience_prompts
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@@ -43,7 +43,7 @@ from climateqa.engine.keywords import make_keywords_chain
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# from climateqa.engine.chains.answer_rag import make_rag_papers_chain
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from climateqa.engine.graph import make_graph_agent,display_graph
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-
from front.utils import make_html_source,parse_output_llm_with_sources,serialize_docs,make_toolbox
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# Load environment variables in local mode
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try:
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@@ -133,6 +133,7 @@ async def chat(query,history,audience,sources,reports):
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output_keywords = ""
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gallery = []
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start_streaming = False
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steps_display = {
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"categorize_intent":("ποΈ Analyzing user message",True),
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@@ -151,10 +152,12 @@ async def chat(query,history,audience,sources,reports):
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try:
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docs = event["data"]["output"]["documents"]
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docs_html = []
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-
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-
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-
used_documents = used_documents + [d.metadata[
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history[-1].content = "Adding sources :\n\n - " + "\n - ".join(np.unique(used_documents))
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docs_html = "".join(docs_html)
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@@ -184,7 +187,7 @@ async def chat(query,history,audience,sources,reports):
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if event["name"] == "categorize_intent" and event["event"] == "on_chain_start":
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print("X")
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-
yield history,docs_html,output_query,output_language,gallery #,output_query,output_keywords
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except Exception as e:
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print(event, "has failed")
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@@ -212,12 +215,49 @@ async def chat(query,history,audience,sources,reports):
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print(f"Error logging on Azure Blob Storage: {e}")
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raise gr.Error(f"ClimateQ&A Error: {str(e)[:100]} - The error has been noted, try another question and if the error remains, you can contact us :)")
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if doc.metadata["chunk_type"] == "image":
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try:
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key = f"Image {i+1}"
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image_path = doc.metadata["image_path"].split("documents/")[1]
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img = get_image_from_azure_blob_storage(image_path)
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@@ -225,31 +265,18 @@ async def chat(query,history,audience,sources,reports):
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buffered = BytesIO()
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img.save(buffered, format="PNG")
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img_str = base64.b64encode(buffered.getvalue()).decode()
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# Embedding the base64 string in Markdown
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markdown_image = f"![Alt text](data:image/png;base64,{img_str})"
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image_dict[key] = {"img":img,"md":markdown_image,"caption":doc.page_content,"key":key,"figure_code":doc.metadata["figure_code"]}
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except Exception as e:
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print(f"Skipped adding image {i} because of {e}")
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-
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gallery = [x["img"] for x in list(image_dict.values())]
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img = list(image_dict.values())[0]
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img_md = img["md"]
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img_caption = img["caption"]
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-
img_code = img["figure_code"]
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if img_code != "N/A":
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img_name = f"{img['key']} - {img['figure_code']}"
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-
else:
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-
img_name = f"{img['key']}"
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-
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history.append(ChatMessage(role="assistant", content = f"\n\n{img_md}\n<p class='chatbot-caption'><b>{img_name}</b> - {img_caption}</p>"))
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-
# answer_yet = history[-1][1] + f"\n\n{img_md}\n<p class='chatbot-caption'><b>{img_name}</b> - {img_caption}</p>"
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# history[-1] = (history[-1][0],answer_yet)
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# history = [tuple(x) for x in history]
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-
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yield history,docs_html,output_query,output_language,gallery#,output_query,output_keywords
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def save_feedback(feed: str, user_id):
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@@ -382,6 +409,9 @@ with gr.Blocks(title="Climate Q&A", css_paths=os.getcwd()+ "/style.css", theme=t
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with gr.Tab("Sources",elem_id = "tab-citations",id = 1):
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sources_textbox = gr.HTML(show_label=False, elem_id="sources-textbox")
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docs_textbox = gr.State("")
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# with Modal(visible = False) as config_modal:
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with gr.Tab("Configuration",elem_id = "tab-config",id = 2):
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@@ -415,6 +445,10 @@ with gr.Blocks(title="Climate Q&A", css_paths=os.getcwd()+ "/style.css", theme=t
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output_language = gr.Textbox(label="Language",show_label = True,elem_id = "language",lines = 1,interactive = False)
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#---------------------------------------------------------------------------------------
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# OTHER TABS
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@@ -463,13 +497,13 @@ with gr.Blocks(title="Climate Q&A", css_paths=os.getcwd()+ "/style.css", theme=t
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(textbox
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.submit(start_chat, [textbox,chatbot], [textbox,tabs,chatbot],queue = False,api_name = "start_chat_textbox")
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-
.then(chat, [textbox,chatbot,dropdown_audience, dropdown_sources,dropdown_reports], [chatbot,sources_textbox,output_query,output_language,gallery_component],concurrency_limit = 8,api_name = "chat_textbox")
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.then(finish_chat, None, [textbox],api_name = "finish_chat_textbox")
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)
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(examples_hidden
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.change(start_chat, [examples_hidden,chatbot], [textbox,tabs,chatbot],queue = False,api_name = "start_chat_examples")
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.then(chat, [examples_hidden,chatbot,dropdown_audience, dropdown_sources,dropdown_reports], [chatbot,sources_textbox,output_query,output_language,gallery_component],concurrency_limit = 8,api_name = "chat_examples")
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.then(finish_chat, None, [textbox],api_name = "finish_chat_examples")
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)
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# ClimateQ&A imports
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from climateqa.engine.llm import get_llm
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from climateqa.engine.vectorstore import get_pinecone_vectorstore
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+
# from climateqa.knowledge.retriever import ClimateQARetriever
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from climateqa.engine.reranker import get_reranker
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from climateqa.engine.embeddings import get_embeddings_function
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from climateqa.engine.chains.prompts import audience_prompts
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# from climateqa.engine.chains.answer_rag import make_rag_papers_chain
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from climateqa.engine.graph import make_graph_agent,display_graph
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+
from front.utils import make_html_source, make_html_figure_sources,parse_output_llm_with_sources,serialize_docs,make_toolbox
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# Load environment variables in local mode
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try:
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output_keywords = ""
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gallery = []
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start_streaming = False
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+
figures = '<div class="figures-container"> <p> Go to the "Figures" tab at the top of the page to see full size images </p> </div>'
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steps_display = {
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"categorize_intent":("ποΈ Analyzing user message",True),
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try:
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docs = event["data"]["output"]["documents"]
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docs_html = []
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textual_docs = [d for d in docs if d.metadata["chunk_type"] == "text"]
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for i, d in enumerate(textual_docs, 1):
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if d.metadata["chunk_type"] == "text":
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docs_html.append(make_html_source(d, i))
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used_documents = used_documents + [f"{d.metadata['short_name']} - {d.metadata['name']}" for d in docs]
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history[-1].content = "Adding sources :\n\n - " + "\n - ".join(np.unique(used_documents))
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docs_html = "".join(docs_html)
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if event["name"] == "categorize_intent" and event["event"] == "on_chain_start":
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print("X")
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+
yield history,docs_html,output_query,output_language,gallery, figures #,output_query,output_keywords
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except Exception as e:
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print(event, "has failed")
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print(f"Error logging on Azure Blob Storage: {e}")
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raise gr.Error(f"ClimateQ&A Error: {str(e)[:100]} - The error has been noted, try another question and if the error remains, you can contact us :)")
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+
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# image_dict = {}
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# for i,doc in enumerate(docs):
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# if doc.metadata["chunk_type"] == "image":
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# try:
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# key = f"Image {i+1}"
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# image_path = doc.metadata["image_path"].split("documents/")[1]
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# img = get_image_from_azure_blob_storage(image_path)
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# # Convert the image to a byte buffer
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# buffered = BytesIO()
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# img.save(buffered, format="PNG")
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# img_str = base64.b64encode(buffered.getvalue()).decode()
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# # Embedding the base64 string in Markdown
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# markdown_image = f"![Alt text](data:image/png;base64,{img_str})"
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# image_dict[key] = {"img":img,"md":markdown_image,"short_name": doc.metadata["short_name"],"figure_code":doc.metadata["figure_code"],"caption":doc.page_content,"key":key,"figure_code":doc.metadata["figure_code"], "img_str" : img_str}
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# except Exception as e:
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# print(f"Skipped adding image {i} because of {e}")
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# if len(image_dict) > 0:
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# gallery = [x["img"] for x in list(image_dict.values())]
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# img = list(image_dict.values())[0]
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# img_md = img["md"]
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# img_caption = img["caption"]
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# img_code = img["figure_code"]
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# if img_code != "N/A":
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# img_name = f"{img['key']} - {img['figure_code']}"
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# else:
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# img_name = f"{img['key']}"
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# history.append(ChatMessage(role="assistant", content = f"\n\n{img_md}\n<p class='chatbot-caption'><b>{img_name}</b> - {img_caption}</p>"))
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docs_figures = [d for d in docs if d.metadata["chunk_type"] == "image"]
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for i, doc in enumerate(docs_figures):
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if doc.metadata["chunk_type"] == "image":
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try:
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key = f"Image {i+1}"
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+
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image_path = doc.metadata["image_path"].split("documents/")[1]
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img = get_image_from_azure_blob_storage(image_path)
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buffered = BytesIO()
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img.save(buffered, format="PNG")
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img_str = base64.b64encode(buffered.getvalue()).decode()
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+
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figures = figures + make_html_figure_sources(doc, i, img_str)
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+
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gallery.append(img)
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except Exception as e:
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print(f"Skipped adding image {i} because of {e}")
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yield history,docs_html,output_query,output_language,gallery, figures#,output_query,output_keywords
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def save_feedback(feed: str, user_id):
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with gr.Tab("Sources",elem_id = "tab-citations",id = 1):
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sources_textbox = gr.HTML(show_label=False, elem_id="sources-textbox")
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docs_textbox = gr.State("")
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+
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+
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+
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# with Modal(visible = False) as config_modal:
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with gr.Tab("Configuration",elem_id = "tab-config",id = 2):
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output_language = gr.Textbox(label="Language",show_label = True,elem_id = "language",lines = 1,interactive = False)
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with gr.Tab("Figures",elem_id = "tab-figures",id = 3):
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figures_cards = gr.HTML(show_label=False, elem_id="sources-figures")
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#---------------------------------------------------------------------------------------
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# OTHER TABS
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(textbox
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.submit(start_chat, [textbox,chatbot], [textbox,tabs,chatbot],queue = False,api_name = "start_chat_textbox")
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+
.then(chat, [textbox,chatbot,dropdown_audience, dropdown_sources,dropdown_reports], [chatbot,sources_textbox,output_query,output_language,gallery_component,figures_cards],concurrency_limit = 8,api_name = "chat_textbox")
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.then(finish_chat, None, [textbox],api_name = "finish_chat_textbox")
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)
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(examples_hidden
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.change(start_chat, [examples_hidden,chatbot], [textbox,tabs,chatbot],queue = False,api_name = "start_chat_examples")
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+
.then(chat, [examples_hidden,chatbot,dropdown_audience, dropdown_sources,dropdown_reports], [chatbot,sources_textbox,output_query,output_language,gallery_component, figures_cards],concurrency_limit = 8,api_name = "chat_examples")
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.then(finish_chat, None, [textbox],api_name = "finish_chat_examples")
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)
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front/utils.py
CHANGED
@@ -55,7 +55,7 @@ def make_html_source(source,i):
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score = meta['reranking_score']
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if score > 0.8:
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color = "score-green"
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-
elif score > 0.
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color = "score-orange"
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else:
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color = "score-red"
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@@ -91,8 +91,9 @@ def make_html_source(source,i):
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<div class="card card-image">
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<div class="card-content">
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<h2>Image {i} - {title} - Page {int(meta['page_number'])}</h2>
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-
<p>{content}</p>
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<p class='ai-generated'>AI-generated description</p>
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{relevancy_score}
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</div>
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<div class="card-footer">
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@@ -107,6 +108,53 @@ def make_html_source(source,i):
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return card
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def make_toolbox(tool_name,description = "",checked = False,elem_id = "toggle"):
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score = meta['reranking_score']
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if score > 0.8:
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color = "score-green"
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+
elif score > 0.5:
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color = "score-orange"
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else:
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color = "score-red"
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<div class="card card-image">
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<div class="card-content">
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<h2>Image {i} - {title} - Page {int(meta['page_number'])}</h2>
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<p class='ai-generated'>AI-generated description</p>
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<p>{content}</p>
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+
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{relevancy_score}
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</div>
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<div class="card-footer">
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return card
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+
def make_html_figure_sources(source,i,img_str):
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meta = source.metadata
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content = source.page_content.strip()
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score = meta['reranking_score']
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if score > 0.8:
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color = "score-green"
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elif score > 0.5:
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color = "score-orange"
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else:
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color = "score-red"
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toc_levels = []
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if len(toc_levels) > 0:
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name = f"<b>{toc_levels}</b><br/>{meta['name']}"
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else:
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name = meta['name']
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+
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relevancy_score = f"<p class=relevancy-score>Relevancy score: <span class='{color}'>{score:.1%}</span></p>"
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+
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if meta["figure_code"] != "N/A":
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title = f"{meta['figure_code']} - {meta['short_name']}"
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else:
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title = f"{meta['short_name']}"
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card = f"""
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<div class="card card-image">
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<div class="card-content">
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<h2>Image {i} - {title} - Page {int(meta['page_number'])}</h2>
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<p class='ai-generated'>AI-generated description</p>
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<img src="data:image/png;base64, { img_str } alt="Alt text" />
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+
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<p>{content}</p>
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+
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{relevancy_score}
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</div>
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<div class="card-footer">
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<span>{name}</span>
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<a href="{meta['url']}#page={int(meta['page_number'])}" target="_blank" class="pdf-link">
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150 |
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<span role="img" aria-label="Open PDF">π</span>
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</a>
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</div>
|
153 |
+
</div>
|
154 |
+
"""
|
155 |
+
return card
|
156 |
+
|
157 |
+
|
158 |
|
159 |
def make_toolbox(tool_name,description = "",checked = False,elem_id = "toggle"):
|
160 |
|
sandbox/20240310 - CQA - Semantic Routing 1.ipynb
CHANGED
The diff for this file is too large to render.
See raw diff
|
|
style.css
CHANGED
@@ -206,6 +206,11 @@ label.selected{
|
|
206 |
overflow-y: auto !important;
|
207 |
}
|
208 |
|
|
|
|
|
|
|
|
|
|
|
209 |
div#tab-config{
|
210 |
height:calc(100vh - 190px) !important;
|
211 |
overflow-y: auto !important;
|
@@ -475,7 +480,7 @@ span.chatbot > p > img{
|
|
475 |
color:orange !important;
|
476 |
}
|
477 |
|
478 |
-
.score-
|
479 |
color:red !important;
|
480 |
}
|
481 |
.message-buttons-left.panel.message-buttons.with-avatar {
|
|
|
206 |
overflow-y: auto !important;
|
207 |
}
|
208 |
|
209 |
+
div#sources-figures{
|
210 |
+
height:calc(100vh - 190px) !important;
|
211 |
+
overflow-y: auto !important;
|
212 |
+
}
|
213 |
+
|
214 |
div#tab-config{
|
215 |
height:calc(100vh - 190px) !important;
|
216 |
overflow-y: auto !important;
|
|
|
480 |
color:orange !important;
|
481 |
}
|
482 |
|
483 |
+
.score-red{
|
484 |
color:red !important;
|
485 |
}
|
486 |
.message-buttons-left.panel.message-buttons.with-avatar {
|