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ALLOUNE
commited on
Commit
·
be240c1
1
Parent(s):
a7372e0
add visual prior art
Browse files- app.py +152 -224
- src/core.py +3 -3
- src/services/processor.py +13 -7
app.py
CHANGED
@@ -4,7 +4,10 @@ from typing import Dict, List
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import gradio as gr
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import pandas as pd
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import json
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from src.core import *
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app = FastAPI(
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title="Insight Finder",
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@@ -58,13 +61,13 @@ async def process_constraints(constraints: InputConstraints):
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@app.post("/prior-art-constraints", response_model=OutputPriorArt)
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async def prior_art_constraints(data: InputPriorArtConstraints):
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prior_art = process_prior_art(data.technologies, data.constraints, "constraints")
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print(prior_art)
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return prior_art
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@app.post("/prior-art-problems", response_model=OutputPriorArt)
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async def prior_art_problems(data: InputPriorArtProblem):
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prior_art = process_prior_art(data.technologies, data.problems, "problem")
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return prior_art
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def make_json_serializable(data):
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@@ -135,7 +138,120 @@ def format_final_technologies_html(technologies_list: list) -> str:
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"""
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html_content += "</div>"
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return "<h1>The best technologies combinations </h1>" + html_content
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def process_input_gradio(problem_description: str):
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"""
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Processes the input problem description step-by-step for Gradio.
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@@ -169,12 +285,6 @@ def process_input_gradio(problem_description: str):
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# Step 8: Get Technologies by ID
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best_technologies = get_technologies_by_id(best_technologies_id, global_tech)
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print(constraints)
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print(best_combinations)
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print(best_technologies)
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# Format outputs for Gradio
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# For Constraints:
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@@ -186,17 +296,20 @@ def process_input_gradio(problem_description: str):
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# For Final Technologies:
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final_technologies_html = format_final_technologies_html(best_technologies)
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prior_art = process_prior_art(best_technologies, constraints, "constraints")
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print(prior_art)
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return (
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prompt,
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constraints_html, # Output HTML for constraints
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best_combinations_html, # Output HTML for best combinations
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", ".join(map(str, best_technologies_id)), # Still a simple text list
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final_technologies_html # Output HTML for final technologies
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)
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# --- Gradio Interface Setup ---
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input_problem = gr.Textbox(
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@@ -209,212 +322,11 @@ output_constraints = gr.HTML(label="2. Retrieved Constraints") # Changed to HTML
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output_best_combinations = gr.HTML(label="7. Best Technology Combinations Found") # Changed to HTML
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output_selected_ids = gr.Textbox(label="8. Selected Technology IDs", interactive=False)
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output_final_technologies = gr.HTML(label="9. Final Best Technologies") # Changed to HTML
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# Custom CSS for a professional look and specific output styling
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custom_css = """
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/* General Body and Font Styling */
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body {
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font-family: 'Segoe UI', 'Roboto', 'Helvetica Neue', Arial, sans-serif;
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color: #333;
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background-color: #f0f2f5;
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}
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/* Header Styling */
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.gradio-container h1 {
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color: #0056b3; /* A deep blue for the main title */
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text-align: center;
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margin-bottom: 10px;
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font-weight: 600;
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font-size: 2.5em;
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text-shadow: 1px 1px 2px rgba(0,0,0,0.1);
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}
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.gradio-container h2 {
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color: #007bff; /* A slightly lighter blue for subtitles */
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text-align: center;
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margin-top: 0;
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margin-bottom: 30px;
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font-weight: 400;
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font-size: 1.2em;
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}
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/* Card-like styling for individual components */
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.gradio-container .gr-box {
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background-color: #ffffff;
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border-radius: 12px;
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box-shadow: 0 4px 12px rgba(0, 0, 0, 0.08);
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padding: 20px;
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margin-bottom: 20px;
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border: 1px solid #e0e0e0;
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}
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/* Input Textbox Styling */
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.gradio-container input[type="text"],
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.gradio-container textarea {
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border: 1px solid #ced4da;
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border-radius: 8px;
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padding: 12px 15px;
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font-size: 1em;
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color: #495057;
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transition: border-color 0.2s ease-in-out, box-shadow 0.2s ease-in-out;
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}
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.gradio-container input[type="text"]:focus,
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.gradio-container textarea:focus {
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border-color: #007bff;
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box-shadow: 0 0 0 0.2rem rgba(0, 123, 255, 0.25);
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outline: none;
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}
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/* Button Styling */
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.gradio-container button {
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background-color: #28a745; /* A vibrant green for action */
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color: white;
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border: none;
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border-radius: 8px;
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padding: 12px 25px;
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font-size: 1.1em;
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font-weight: 500;
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cursor: pointer;
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transition: background-color 0.2s ease-in-out, transform 0.1s ease-in-out;
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
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}
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.gradio-container button:hover {
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background-color: #218838; /* Darker green on hover */
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transform: translateY(-2px);
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}
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.gradio-container button:active {
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transform: translateY(0);
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}
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/* Labels for outputs */
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.gradio-container label {
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font-weight: 600;
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color: #495057;
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margin-bottom: 8px;
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display: block; /* Ensure labels are on their own line */
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font-size: 1.1em;
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}
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/* --- Specific Styling for Outputs --- */
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/* 2. Retrieved Constraints Styling */
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.constraints-container {
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padding: 15px;
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background-color: #f8f9fa;
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border-radius: 8px;
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border: 1px solid #e9ecef;
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font-family: 'Trebuchet MS', 'Lucida Grande', 'Lucida Sans Unicode', 'Lucida Sans', Tahoma, sans-serif; /* Different font */
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line-height: 1.6;
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max-height: 300px;
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overflow-y: auto;
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}
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.constraint-item {
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margin-bottom: 10px;
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padding-bottom: 10px;
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border-bottom: 1px dashed #e0e0e0;
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}
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.constraint-item:last-child {
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border-bottom: none;
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margin-bottom: 0;
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padding-bottom: 0;
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}
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.constraint-title {
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font-weight: bold;
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color: #004085; /* Darker blue for constraint titles */
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font-size: 1.1em;
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}
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.constraint-description {
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color: #333;
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font-size: 1em;
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}
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/* 7. Best Technology Combinations Found & 9. Final Best Technologies Styling */
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.combinations-outer-container, .final-tech-container {
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padding: 15px;
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background-color: #f8f9fa;
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border-radius: 8px;
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border: 1px solid #e9ecef;
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max-height: 500px; /* Adjust as needed */
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overflow-y: auto;
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font-family: 'Trebuchet MS', 'Lucida Grande', 'Lucida Sans Unicode', 'Lucida Sans', Tahoma, sans-serif; /* Different font */
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}
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.problem-card {
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background-color: #ffffff;
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border: 1px solid #cfe2ff; /* Light blue border for problem card */
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border-radius: 10px;
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padding: 20px;
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margin-bottom: 20px;
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box-shadow: 0 4px 10px rgba(0, 0, 0, 0.05);
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}
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.problem-card-title {
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color: #0056b3; /* Deep blue for problem title */
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font-size: 1.4em;
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margin-top: 0;
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margin-bottom: 15px;
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border-bottom: 2px solid #cfe2ff;
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padding-bottom: 10px;
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}
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.technologies-inner-container {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(280px, 1fr)); /* Responsive grid for technologies */
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gap: 15px;
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}
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.technology-card, .final-tech-card {
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background-color: #f0faff; /* Very light blue for technology cards */
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border: 1px solid #b0d9ff; /* Slightly darker blue border */
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border-radius: 8px;
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padding: 15px;
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box-shadow: 0 2px 5px rgba(0, 0, 0, 0.05);
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transition: transform 0.2s ease-in-out;
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}
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.technology-card:hover, .final-tech-card:hover {
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transform: translateY(-3px);
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}
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.tech-card-title, .final-tech-title {
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color: #007bff; /* Gradio's primary blue */
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font-size: 1.2em;
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margin-top: 0;
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margin-bottom: 10px;
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font-weight: 600;
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}
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.technology-card p, .final-tech-card p {
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font-size: 0.95em;
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line-height: 1.5;
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margin-bottom: 5px;
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color: #555;
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}
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.technology-card p strong, .final-tech-card p strong {
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color: #004085; /* Darker blue for bold labels */
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}
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/* Responsive adjustments */
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@media (max-width: 768px) {
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.gradio-container {
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padding: 15px;
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}
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.gradio-container h1 {
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font-size: 2em;
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}
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.gradio-container button {
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width: 100%;
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padding: 15px;
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}
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.technologies-inner-container {
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grid-template-columns: 1fr; /* Stack columns on smaller screens */
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}
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}
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"""
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# Create the Gradio Blocks demo with custom theme and CSS
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with gr.Blocks(
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theme=gr.themes.Soft(),
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css=custom_css
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with gr.Row():
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with gr.Column():
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output_prompt.render()
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output_constraints.render()
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with gr.Column():
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output_selected_ids.render()
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output_best_combinations.render()
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output_final_technologies.render()
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process_button.click(
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fn=process_input_gradio,
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inputs=input_problem,
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output_constraints,
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output_best_combinations,
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output_selected_ids,
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output_final_technologies
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]
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)
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gr.mount_gradio_app(app, gradio_app_blocks, path="/gradio")
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#if __name__ == "__main__":
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# gradio_app_blocks.launch()
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import gradio as gr
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import pandas as pd
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import json
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import re
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from src.core import *
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from src.ressources.main_css import *
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app = FastAPI(
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title="Insight Finder",
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@app.post("/prior-art-constraints", response_model=OutputPriorArt)
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async def prior_art_constraints(data: InputPriorArtConstraints):
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prior_art = process_prior_art(data.technologies, data.constraints, "constraints", "pydantic")
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print(prior_art)
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return prior_art
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@app.post("/prior-art-problems", response_model=OutputPriorArt)
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async def prior_art_problems(data: InputPriorArtProblem):
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prior_art = process_prior_art(data.technologies, data.problems, "problem", "pydantic")
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return prior_art
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def make_json_serializable(data):
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"""
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html_content += "</div>"
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return "<h1>The best technologies combinations </h1>" + html_content
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+
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def format_prior_art_html(prior_art_data: dict) -> str:
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if not prior_art_data or 'content' not in prior_art_data:
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return "<div class='prior-art-container'><p>No prior art data available.</p></div>"
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content = prior_art_data['content']
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uris = prior_art_data.get('uris', [])
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# 1. Convert **text** to <strong>text</strong>
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processed_content = re.sub(r'\*\*(.*?)\*\*', r'<strong>\1</strong>', content)
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# 2. Convert [x](uri) to clickable links
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# This regex handles cases where [x] is followed by (uri)
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# It captures the number (group 1) and the URI (group 2)
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processed_content = re.sub(r'\[(\d+)\]\((https?:\/\/[^\s\)]+)\)', r'<a href="\2" target="_blank" class="prior-art-inline-link">\1</a>', processed_content)
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# Split content into initial summary and then document sections
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sections = processed_content.split("Here are the documents found and the technologies used within them:\n\n")
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summary_html = ""
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documents_html = ""
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# Process summary part (the first part of the split)
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if len(sections) > 0:
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summary_lines = sections[0].strip().split('\n')
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summary_html += " <div class='prior-art-summary'>\n"
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for line in summary_lines:
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if line.strip().startswith('*'):
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# For bullet points, specially format bold text
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# The bolding for **text** is already handled by re.sub
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parts = line.split(':', 1)
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if len(parts) > 1:
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summary_html += f" <p class='summary-bullet'><strong>{parts[0].replace('*', '').strip()}:</strong> {parts[1].strip()}</p>\n"
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else:
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summary_html += f" <p class='summary-bullet'>{line.replace('*', '').strip()}</p>\n"
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elif line.strip():
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summary_html += f" <p>{line.strip()}</p>\n"
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summary_html += " </div>\n"
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# Process documents part (the second part of the split)
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if len(sections) > 1:
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documents_raw = sections[1].strip()
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# Split by "number. **" to get individual document entries reliably
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+
document_entries = re.split(r'(\d+\.\s*\*\*.*?\*\*)', documents_raw)
|
185 |
+
|
186 |
+
parsed_docs = []
|
187 |
+
for i in range(1, len(document_entries), 2):
|
188 |
+
title_line = document_entries[i].strip()
|
189 |
+
content_block = document_entries[i+1].strip() if i+1 < len(document_entries) else ""
|
190 |
+
parsed_docs.append({'title_line': title_line, 'content_block': content_block})
|
191 |
+
|
192 |
+
documents_html += " <div class='prior-art-documents'>\n"
|
193 |
+
for doc in parsed_docs:
|
194 |
+
doc_number_title = doc['title_line']
|
195 |
+
doc_content_lines = [l.strip() for l in doc['content_block'].split('\n') if l.strip()]
|
196 |
+
|
197 |
+
doc_description = ""
|
198 |
+
tech_used_section = []
|
199 |
+
|
200 |
+
desc_start_idx = -1
|
201 |
+
tech_start_idx = -1
|
202 |
+
|
203 |
+
for idx, line in enumerate(doc_content_lines):
|
204 |
+
if line.startswith("Description:"):
|
205 |
+
desc_start_idx = idx
|
206 |
+
elif line.startswith("Technologies Used:"):
|
207 |
+
tech_start_idx = idx
|
208 |
+
|
209 |
+
if desc_start_idx != -1:
|
210 |
+
desc_end_idx = tech_start_idx if tech_start_idx != -1 else len(doc_content_lines)
|
211 |
+
doc_description = " ".join(doc_content_lines[desc_start_idx:desc_end_idx]).replace("Description:", "").strip()
|
212 |
+
|
213 |
+
if tech_start_idx != -1:
|
214 |
+
tech_used_section = [l.replace('*', '').strip() for l in doc_content_lines[tech_start_idx:] if l.strip().startswith('*')]
|
215 |
+
|
216 |
+
|
217 |
+
documents_html += f"""\
|
218 |
+
<div class='prior-art-document-card'>
|
219 |
+
<h4 class='document-title'>{doc_number_title}</h4>
|
220 |
+
<p class='document-description'><strong>Description:</strong> {doc_description}</p>\n"""
|
221 |
+
if tech_used_section:
|
222 |
+
documents_html += " <div class='document-technologies'>\n"
|
223 |
+
documents_html += " <h5>Technologies Used:</h5>\n <ul>\n"
|
224 |
+
for tech_item in tech_used_section:
|
225 |
+
if tech_item.strip():
|
226 |
+
tech_parts = tech_item.split(':', 1)
|
227 |
+
if len(tech_parts) > 1:
|
228 |
+
documents_html += f" <li><strong>{tech_parts[0].strip()}:</strong> {tech_parts[1].strip()}</li>\n"
|
229 |
+
else:
|
230 |
+
documents_html += f" <li>{tech_item.strip()}</li>\n"
|
231 |
+
documents_html += " </ul>\n </div>\n"
|
232 |
+
documents_html += " </div>\n"
|
233 |
+
documents_html += " </div>\n"
|
234 |
+
|
235 |
+
# Grouped URLs at the end
|
236 |
+
grouped_uris_html = ""
|
237 |
+
if uris:
|
238 |
+
grouped_uris_html += " <div class='grouped-uris-section'>\n"
|
239 |
+
grouped_uris_html += " <hr class='disruptive-line'>\n" # Disruptive line
|
240 |
+
grouped_uris_html += " <h3>Referenced Documents (URIs):</h3>\n"
|
241 |
+
grouped_uris_html += " <ul>\n"
|
242 |
+
for idx, uri in enumerate(uris):
|
243 |
+
grouped_uris_html += f" <li>{idx + 1}. <a href='{uri}' target='_blank' class='prior-art-grouped-link'>Document {idx + 1} Link</a></li>\n"
|
244 |
+
grouped_uris_html += " </ul>\n </div>\n"
|
245 |
+
|
246 |
+
return f"<div class='prior-art-container'>\n{summary_html}{documents_html}{grouped_uris_html}</div>"
|
247 |
+
|
248 |
+
|
249 |
+
def gradio_prior_art(best_technologies, constraints):
|
250 |
+
prior_art = process_prior_art(best_technologies, constraints, "constraints", "dict")
|
251 |
+
html_prior_art = format_prior_art_html(prior_art)
|
252 |
+
print(html_prior_art)
|
253 |
+
return html_prior_art
|
254 |
+
|
255 |
def process_input_gradio(problem_description: str):
|
256 |
"""
|
257 |
Processes the input problem description step-by-step for Gradio.
|
|
|
285 |
|
286 |
# Step 8: Get Technologies by ID
|
287 |
best_technologies = get_technologies_by_id(best_technologies_id, global_tech)
|
|
|
|
|
|
|
|
|
|
|
|
|
288 |
|
289 |
# Format outputs for Gradio
|
290 |
# For Constraints:
|
|
|
296 |
# For Final Technologies:
|
297 |
final_technologies_html = format_final_technologies_html(best_technologies)
|
298 |
|
|
|
|
|
|
|
299 |
return (
|
300 |
prompt,
|
301 |
constraints_html, # Output HTML for constraints
|
302 |
best_combinations_html, # Output HTML for best combinations
|
303 |
", ".join(map(str, best_technologies_id)), # Still a simple text list
|
304 |
+
final_technologies_html, # Output HTML for final technologies
|
305 |
+
{"technologies": best_technologies}, # `best_technologies` is the actual list of dicts
|
306 |
+
constraints
|
307 |
)
|
308 |
|
309 |
+
|
310 |
+
# Return a gr.update object to change the value and visibility in one step
|
311 |
+
# return gr.update(value=html_prior_art, visible=True)
|
312 |
+
|
313 |
|
314 |
# --- Gradio Interface Setup ---
|
315 |
input_problem = gr.Textbox(
|
|
|
322 |
output_best_combinations = gr.HTML(label="7. Best Technology Combinations Found") # Changed to HTML
|
323 |
output_selected_ids = gr.Textbox(label="8. Selected Technology IDs", interactive=False)
|
324 |
output_final_technologies = gr.HTML(label="9. Final Best Technologies") # Changed to HTML
|
325 |
+
output_prior_art = gr.HTML(label="10. Prior Art Analysis") # Initially hidden
|
326 |
+
|
327 |
+
stock_technologies = gr.JSON(visible=False)
|
328 |
+
stock_constraints = gr.JSON(visible=False)
|
329 |
|
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|
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|
|
|
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|
|
|
|
|
330 |
with gr.Blocks(
|
331 |
theme=gr.themes.Soft(),
|
332 |
css=custom_css
|
|
|
348 |
with gr.Row():
|
349 |
with gr.Column():
|
350 |
output_prompt.render()
|
351 |
+
output_constraints.render()
|
352 |
with gr.Column():
|
353 |
+
output_selected_ids.render()
|
354 |
+
output_best_combinations.render()
|
355 |
+
output_final_technologies.render()
|
356 |
+
|
357 |
+
gr.Markdown("---")
|
358 |
+
gr.Markdown("### Prior Art Analysis")
|
359 |
+
prior_art_button = gr.Button("Find Prior Art", elem_id="prior_art_button")
|
360 |
+
output_prior_art.render()
|
361 |
+
stock_technologies.render()
|
362 |
+
stock_constraints.render()
|
363 |
+
|
364 |
process_button.click(
|
365 |
fn=process_input_gradio,
|
366 |
inputs=input_problem,
|
|
|
369 |
output_constraints,
|
370 |
output_best_combinations,
|
371 |
output_selected_ids,
|
372 |
+
output_final_technologies,
|
373 |
+
stock_technologies,
|
374 |
+
stock_constraints
|
375 |
]
|
376 |
)
|
377 |
|
378 |
+
prior_art_button.click(
|
379 |
+
fn=gradio_prior_art,
|
380 |
+
inputs=[stock_technologies, stock_constraints],
|
381 |
+
outputs=output_prior_art
|
382 |
+
)
|
383 |
+
|
384 |
+
|
385 |
gr.mount_gradio_app(app, gradio_app_blocks, path="/gradio")
|
386 |
#if __name__ == "__main__":
|
387 |
# gradio_app_blocks.launch()
|
src/core.py
CHANGED
@@ -30,13 +30,13 @@ def process_input(data, global_tech, global_tech_embeddings, data_type):
|
|
30 |
|
31 |
return best_technologies
|
32 |
|
33 |
-
def process_prior_art(technologies, data, data_type):
|
34 |
try:
|
35 |
-
prior_art_reponse = search_prior_art(technologies, data, data_type)
|
36 |
prior_art_search = add_citations_and_collect_uris(prior_art_reponse)
|
37 |
except Exception as e:
|
38 |
print(f"An error occured during the process, trying again : {e}")
|
39 |
-
prior_art_reponse = search_prior_art(technologies, data, data_type)
|
40 |
prior_art_search = add_citations_and_collect_uris(prior_art_reponse)
|
41 |
|
42 |
return prior_art_search
|
|
|
30 |
|
31 |
return best_technologies
|
32 |
|
33 |
+
def process_prior_art(technologies, data, data_type, techno_type):
|
34 |
try:
|
35 |
+
prior_art_reponse = search_prior_art(technologies, data, data_type, techno_type)
|
36 |
prior_art_search = add_citations_and_collect_uris(prior_art_reponse)
|
37 |
except Exception as e:
|
38 |
print(f"An error occured during the process, trying again : {e}")
|
39 |
+
prior_art_reponse = search_prior_art(technologies, data, data_type, techno_type)
|
40 |
prior_art_search = add_citations_and_collect_uris(prior_art_reponse)
|
41 |
|
42 |
return prior_art_search
|
src/services/processor.py
CHANGED
@@ -217,19 +217,26 @@ def select_technologies(problem_technology_list):
|
|
217 |
return set()
|
218 |
return set(best_set)
|
219 |
|
220 |
-
|
221 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
222 |
"""
|
223 |
Searches for prior art patents online that solve a given technical problem
|
224 |
using a set of specified technologies, leveraging the Gemini model's search capabilities.
|
225 |
"""
|
226 |
|
227 |
-
technology_titles =
|
228 |
|
229 |
-
if
|
230 |
prompt = f"Find prior art patents or research paper online that address the technical problem: '{data}'. " \
|
231 |
|
232 |
-
elif
|
233 |
prompt = f"Find prior art patents or research paper online that address those constraints: '{data}'. " \
|
234 |
|
235 |
prompt += f"Using any combination of the following technologies: {', '.join(technology_titles)}. " \
|
@@ -274,5 +281,4 @@ def add_citations_and_collect_uris(response):
|
|
274 |
return {"content": text,"uris": list(uris_added)}
|
275 |
except Exception as e:
|
276 |
print(f"Error : {e}")
|
277 |
-
return {"content": e, "uris": []}
|
278 |
-
|
|
|
217 |
return set()
|
218 |
return set(best_set)
|
219 |
|
220 |
+
def load_titles(techno, data_type):
|
221 |
+
if data_type == "pydantic":
|
222 |
+
technology_titles = [tech.title for tech in techno]
|
223 |
+
else: # data_type == "dict"
|
224 |
+
technologies = techno["technologies"]
|
225 |
+
technology_titles = [tech["title"] for tech in technologies]
|
226 |
+
return technology_titles
|
227 |
+
|
228 |
+
def search_prior_art(technologies_input: list, data: str, data_type: str, techno_type: str) -> json:
|
229 |
"""
|
230 |
Searches for prior art patents online that solve a given technical problem
|
231 |
using a set of specified technologies, leveraging the Gemini model's search capabilities.
|
232 |
"""
|
233 |
|
234 |
+
technology_titles = load_titles(technologies_input, techno_type)
|
235 |
|
236 |
+
if data_type == "problem":
|
237 |
prompt = f"Find prior art patents or research paper online that address the technical problem: '{data}'. " \
|
238 |
|
239 |
+
elif data_type == "constraints":
|
240 |
prompt = f"Find prior art patents or research paper online that address those constraints: '{data}'. " \
|
241 |
|
242 |
prompt += f"Using any combination of the following technologies: {', '.join(technology_titles)}. " \
|
|
|
281 |
return {"content": text,"uris": list(uris_added)}
|
282 |
except Exception as e:
|
283 |
print(f"Error : {e}")
|
284 |
+
return {"content": e, "uris": []}
|
|