File size: 10,000 Bytes
d7a7846
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
import re
import gradio as gr
from pathlib import Path
import time
import shutil
from typing import AsyncGenerator, List, Optional, Tuple
from gradio import ChatMessage


class ChatInterface:
    """
    A chat interface for interacting with a medical AI agent through Gradio.

    Handles file uploads, message processing, and chat history management.
    Supports both regular image files and DICOM medical imaging files.
    """

    def __init__(self, agent, tools_dict):
        """
        Initialize the chat interface.

        Args:
            agent: The medical AI agent to handle requests
            tools_dict (dict): Dictionary of available tools for image processing
        """
        self.agent = agent
        self.tools_dict = tools_dict
        self.upload_dir = Path("temp")
        self.upload_dir.mkdir(exist_ok=True)
        self.current_thread_id = None
        # Separate storage for original and display paths
        self.original_file_path = None  # For LLM (.dcm or other)
        self.display_file_path = None  # For UI (always viewable format)

    def handle_upload(self, file_path: str) -> str:
        """
        Handle new file upload and set appropriate paths.

        Args:
            file_path (str): Path to the uploaded file

        Returns:
            str: Display path for UI, or None if no file uploaded
        """
        if not file_path:
            return None

        source = Path(file_path)
        timestamp = int(time.time())

        # Save original file with proper suffix
        suffix = source.suffix.lower()
        saved_path = self.upload_dir / f"upload_{timestamp}{suffix}"
        shutil.copy2(file_path, saved_path)  # Use file_path directly instead of source
        self.original_file_path = str(saved_path)

        # Handle DICOM conversion for display only
        if suffix == ".dcm":
            output, _ = self.tools_dict["DicomProcessorTool"]._run(str(saved_path))
            self.display_file_path = output["image_path"]
        else:
            self.display_file_path = str(saved_path)

        return self.display_file_path

    def add_message(
        self, message: str, display_image: str, history: List[dict]
    ) -> Tuple[List[dict], gr.Textbox]:
        """
        Add a new message to the chat history.

        Args:
            message (str): Text message to add
            display_image (str): Path to image being displayed
            history (List[dict]): Current chat history

        Returns:
            Tuple[List[dict], gr.Textbox]: Updated history and textbox component
        """
        image_path = self.original_file_path or display_image
        if image_path is not None:
            history.append({"role": "user", "content": {"path": image_path}})
        if message is not None:
            history.append({"role": "user", "content": message})
        return history, gr.Textbox(value=message, interactive=False)

    async def process_message(
        self, message: str, display_image: Optional[str], chat_history: List[ChatMessage]
    ) -> AsyncGenerator[Tuple[List[ChatMessage], Optional[str], str], None]:
        """
        Process a message and generate responses.

        Args:
            message (str): User message to process
            display_image (Optional[str]): Path to currently displayed image
            chat_history (List[ChatMessage]): Current chat history

        Yields:
            Tuple[List[ChatMessage], Optional[str], str]: Updated chat history, display path, and empty string
        """
        chat_history = chat_history or []

        # Initialize thread if needed
        if not self.current_thread_id:
            self.current_thread_id = str(time.time())

        messages = []
        image_path = self.original_file_path or display_image
        if image_path is not None:
            messages.append({"role": "user", "content": f"path: {image_path}"})
        if message is not None:
            messages.append({"role": "user", "content": message})

        try:
            for event in self.agent.workflow.stream(
                {"messages": messages}, {"configurable": {"thread_id": self.current_thread_id}}
            ):
                if isinstance(event, dict):
                    if "process" in event:
                        content = event["process"]["messages"][-1].content
                        if content:
                            content = re.sub(r"temp/[^\s]*", "", content)
                            chat_history.append(ChatMessage(role="assistant", content=content))
                            yield chat_history, self.display_file_path, ""

                    elif "execute" in event:
                        for message in event["execute"]["messages"]:
                            tool_name = message.name
                            tool_result = eval(message.content)[0]

                            if tool_result:
                                metadata = {"title": f"πŸ–ΌοΈ Image from tool: {tool_name}"}
                                formatted_result = " ".join(
                                    line.strip() for line in str(tool_result).splitlines()
                                ).strip()
                                metadata["description"] = formatted_result
                                chat_history.append(
                                    ChatMessage(
                                        role="assistant",
                                        content=formatted_result,
                                        metadata=metadata,
                                    )
                                )

                            # For image_visualizer, use display path
                            if tool_name == "image_visualizer":
                                self.display_file_path = tool_result["image_path"]
                                chat_history.append(
                                    ChatMessage(
                                        role="assistant",
                                        # content=gr.Image(value=self.display_file_path),
                                        content={"path": self.display_file_path},
                                    )
                                )

                            yield chat_history, self.display_file_path, ""

        except Exception as e:
            chat_history.append(
                ChatMessage(
                    role="assistant", content=f"❌ Error: {str(e)}", metadata={"title": "Error"}
                )
            )
            yield chat_history, self.display_file_path


def create_demo(agent, tools_dict):
    """
    Create a Gradio demo interface for the medical AI agent.

    Args:
        agent: The medical AI agent to handle requests
        tools_dict (dict): Dictionary of available tools for image processing

    Returns:
        gr.Blocks: Gradio Blocks interface
    """
    interface = ChatInterface(agent, tools_dict)

    with gr.Blocks(theme=gr.themes.Soft()) as demo:
        with gr.Column():
            gr.Markdown(
                """
            # πŸ₯ MedRAX
            Medical Reasoning Agent for Chest X-ray
            """
            )

            with gr.Row():
                with gr.Column(scale=3):
                    chatbot = gr.Chatbot(
                        [],
                        height=800,
                        container=True,
                        show_label=True,
                        elem_classes="chat-box",
                        type="messages",
                        label="Agent",
                        avatar_images=(
                            None,
                            "assets/medrax_logo.jpg",
                        ),
                    )
                    with gr.Row():
                        with gr.Column(scale=3):
                            txt = gr.Textbox(
                                show_label=False,
                                placeholder="Ask about the X-ray...",
                                container=False,
                            )

                with gr.Column(scale=3):
                    image_display = gr.Image(
                        label="Image", type="filepath", height=700, container=True
                    )
                    with gr.Row():
                        upload_button = gr.UploadButton(
                            "πŸ“Ž Upload X-Ray",
                            file_types=["image"],
                        )
                        dicom_upload = gr.UploadButton(
                            "πŸ“„ Upload DICOM",
                            file_types=["file"],
                        )
                    with gr.Row():
                        clear_btn = gr.Button("Clear Chat")
                        new_thread_btn = gr.Button("New Thread")

        # Event handlers
        def clear_chat():
            interface.original_file_path = None
            interface.display_file_path = None
            return [], None

        def new_thread():
            interface.current_thread_id = str(time.time())
            return [], interface.display_file_path

        def handle_file_upload(file):
            return interface.handle_upload(file.name)

        chat_msg = txt.submit(
            interface.add_message, inputs=[txt, image_display, chatbot], outputs=[chatbot, txt]
        )
        bot_msg = chat_msg.then(
            interface.process_message,
            inputs=[txt, image_display, chatbot],
            outputs=[chatbot, image_display, txt],
        )
        bot_msg.then(lambda: gr.Textbox(interactive=True), None, [txt])

        upload_button.upload(handle_file_upload, inputs=upload_button, outputs=image_display)

        dicom_upload.upload(handle_file_upload, inputs=dicom_upload, outputs=image_display)

        clear_btn.click(clear_chat, outputs=[chatbot, image_display])
        new_thread_btn.click(new_thread, outputs=[chatbot, image_display])

    return demo