File size: 8,298 Bytes
86f402d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
"""
Analysis View Component - Main analysis interface with input and results
"""

import gradio as gr
import re
from typing import Optional


def parse_markdown(text: str) -> str:
    """Convert basic markdown to HTML"""
    text = re.sub(r'\*\*(.+?)\*\*', r'<strong>\1</strong>', text)
    text = re.sub(r'__(.+?)__', r'<strong>\1</strong>', text)
    text = re.sub(r'\*(.+?)\*', r'<em>\1</em>', text)

    # Bullet lists
    lines = text.split('\n')
    in_list = False
    result = []
    for line in lines:
        stripped = line.strip()
        if re.match(r'^[\*\-] ', stripped):
            if not in_list:
                result.append('<ul>')
                in_list = True
            item = re.sub(r'^[\*\-] ', '', stripped)
            result.append(f'<li>{item}</li>')
        else:
            if in_list:
                result.append('</ul>')
                in_list = False
            result.append(line)
    if in_list:
        result.append('</ul>')

    return '\n'.join(result)


# Regex patterns for output parsing
_STAGE_RE = re.compile(r'\[STAGE:(\w+)\](.*?)\[/STAGE\]')
_THINKING_RE = re.compile(r'\[THINKING\](.*?)\[/THINKING\]')
_OBSERVATION_RE = re.compile(r'\[OBSERVATION\](.*?)\[/OBSERVATION\]')
_TOOL_OUTPUT_RE = re.compile(r'\[TOOL_OUTPUT:(.*?)\]\n(.*?)\[/TOOL_OUTPUT\]', re.DOTALL)
_RESULT_RE = re.compile(r'\[RESULT\](.*?)\[/RESULT\]')
_ERROR_RE = re.compile(r'\[ERROR\](.*?)\[/ERROR\]')
_GRADCAM_RE = re.compile(r'\[GRADCAM_IMAGE:[^\]]+\]\n?')
_RESPONSE_RE = re.compile(r'\[RESPONSE\]\n(.*?)\n\[/RESPONSE\]', re.DOTALL)
_COMPLETE_RE = re.compile(r'\[COMPLETE\](.*?)\[/COMPLETE\]')
_CONFIRM_RE = re.compile(r'\[CONFIRM:(\w+)\](.*?)\[/CONFIRM\]')
_REFERENCES_RE = re.compile(r'\[REFERENCES\](.*?)\[/REFERENCES\]', re.DOTALL)
_REF_RE = re.compile(r'\[REF:([^:]+):([^:]+):([^:]+):([^:]+):([^\]]+)\]')


def format_output(raw_text: str, gradcam_base64: Optional[str] = None) -> str:
    """Convert tagged output to styled HTML"""
    html = raw_text

    # Stage headers
    html = _STAGE_RE.sub(
        r'<div class="stage"><span class="stage-indicator"></span><span class="stage-text">\2</span></div>',
        html
    )

    # Thinking
    html = _THINKING_RE.sub(r'<div class="thinking">\1</div>', html)

    # Observations
    html = _OBSERVATION_RE.sub(r'<div class="observation">\1</div>', html)

    # Tool outputs
    html = _TOOL_OUTPUT_RE.sub(
        r'<div class="tool-output"><div class="tool-header">\1</div><pre class="tool-content">\2</pre></div>',
        html
    )

    # Results
    html = _RESULT_RE.sub(r'<div class="result">\1</div>', html)

    # Errors
    html = _ERROR_RE.sub(r'<div class="error">\1</div>', html)

    # GradCAM image
    if gradcam_base64:
        img_html = f'<div class="gradcam-inline"><div class="gradcam-header">Attention Map</div><img src="data:image/png;base64,{gradcam_base64}" alt="Grad-CAM"></div>'
        html = _GRADCAM_RE.sub(img_html, html)
    else:
        html = _GRADCAM_RE.sub('', html)

    # Response section
    def format_response(match):
        content = match.group(1)
        parsed = parse_markdown(content)
        parsed = re.sub(r'\n\n+', '</p><p>', parsed)
        parsed = parsed.replace('\n', '<br>')
        return f'<div class="response"><p>{parsed}</p></div>'

    html = _RESPONSE_RE.sub(format_response, html)

    # Complete
    html = _COMPLETE_RE.sub(r'<div class="complete">\1</div>', html)

    # Confirmation
    html = _CONFIRM_RE.sub(
        r'<div class="confirm-box"><div class="confirm-text">\2</div></div>',
        html
    )

    # References
    def format_references(match):
        ref_content = match.group(1)
        refs_html = ['<div class="references"><div class="references-header">References</div><ul>']
        for ref_match in _REF_RE.finditer(ref_content):
            _, source, page, filename, superscript = ref_match.groups()
            refs_html.append(
                f'<li><a href="guidelines/{filename}#page={page}" target="_blank" class="ref-link">'
                f'<sup>{superscript}</sup> {source}, p.{page}</a></li>'
            )
        refs_html.append('</ul></div>')
        return '\n'.join(refs_html)

    html = _REFERENCES_RE.sub(format_references, html)

    # Convert newlines
    html = html.replace('\n', '<br>')

    return f'<div class="analysis-output">{html}</div>'


def create_analysis_view():
    """
    Create the analysis view component.

    Returns:
        Tuple of (container, components dict)
    """
    with gr.Group(visible=False, elem_classes=["analysis-container"]) as container:

        with gr.Row():
            # Main content area
            with gr.Column(elem_classes=["main-content"]):

                # Input greeting (shown when no analysis yet)
                with gr.Group(visible=True, elem_classes=["input-greeting"]) as input_greeting:
                    gr.Markdown("What would you like to analyze?", elem_classes=["greeting-title"])
                    gr.Markdown("Upload an image and describe what you'd like to know", elem_classes=["greeting-subtitle"])

                    with gr.Column(elem_classes=["input-box-container"]):
                        message_input = gr.Textbox(
                            placeholder="Describe the lesion or ask a question...",
                            show_label=False,
                            lines=3,
                            elem_classes=["message-input"]
                        )

                        # Image upload (compact)
                        image_input = gr.Image(
                            label="",
                            type="pil",
                            height=180,
                            elem_classes=["image-preview"],
                            show_label=False
                        )

                        with gr.Row(elem_classes=["input-actions"]):
                            upload_hint = gr.Markdown("*Upload a skin lesion image above*", visible=True)
                            send_btn = gr.Button("Analyze", elem_classes=["send-btn"], interactive=False)

                # Chat/results view (shown after analysis starts)
                with gr.Group(visible=False, elem_classes=["chat-view"]) as chat_view:
                    results_output = gr.HTML(
                        value='<div class="analysis-output">Starting analysis...</div>',
                        elem_classes=["results-area"]
                    )

                    # Confirmation buttons
                    with gr.Group(visible=False, elem_classes=["confirm-buttons"]) as confirm_group:
                        gr.Markdown("**Do you agree with this diagnosis?**")
                        with gr.Row():
                            confirm_yes_btn = gr.Button("Yes, continue", variant="primary", size="sm")
                            confirm_no_btn = gr.Button("No, I disagree", variant="secondary", size="sm")
                        feedback_input = gr.Textbox(
                            label="Your assessment",
                            placeholder="Enter your diagnosis...",
                            visible=False
                        )
                        submit_feedback_btn = gr.Button("Submit", visible=False, size="sm")

                    # Follow-up input
                    with gr.Row(elem_classes=["chat-input-area"]):
                        followup_input = gr.Textbox(
                            placeholder="Ask a follow-up question...",
                            show_label=False,
                            lines=1
                        )
                        followup_btn = gr.Button("Send", size="sm", elem_classes=["send-btn"])

    components = {
        "input_greeting": input_greeting,
        "chat_view": chat_view,
        "message_input": message_input,
        "image_input": image_input,
        "send_btn": send_btn,
        "results_output": results_output,
        "confirm_group": confirm_group,
        "confirm_yes_btn": confirm_yes_btn,
        "confirm_no_btn": confirm_no_btn,
        "feedback_input": feedback_input,
        "submit_feedback_btn": submit_feedback_btn,
        "followup_input": followup_input,
        "followup_btn": followup_btn,
        "upload_hint": upload_hint
    }

    return container, components