Spaces:
Running
Running
File size: 11,688 Bytes
352a4b6 |
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 |
# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
from flask import Blueprint, render_template, request, jsonify, send_from_directory
from pathlib import Path
import shutil # For zipping the cache directory
import json # For parsing streamed JSON data
import os
import config
import utils
from llm_client import make_chat_completion_request, is_initialized as llm_is_initialized
from cache_store import cache
from cache_store import cache_directory
import requests
logger = logging.getLogger(__name__)
main_bp = Blueprint('main', __name__)
# LLM client is initialized in app.py create_app()
# --- Serve the cache directory as a zip file ---
@main_bp.route('/download_cache')
def download_cache_zip():
"""Zips the cache directory and serves it for download."""
zip_filename = "radexplain-cache.zip"
# Create the zip file in a temporary directory
# Using /tmp is common in containerized environments
temp_dir = "/tmp"
zip_base_path = os.path.join(temp_dir, "radexplain-cache") # shutil adds .zip
zip_filepath = zip_base_path + ".zip"
# Ensure the cache directory exists before trying to zip it
if not os.path.isdir(cache_directory):
logger.error(f"Cache directory not found at {cache_directory}")
return jsonify({"error": f"Cache directory not found on server: {cache_directory}"}), 500
try:
logger.info(f"Creating zip archive of cache directory: {cache_directory} to {zip_filepath}")
shutil.make_archive(
zip_base_path, # This is the base name, shutil adds the .zip extension
"zip",
cache_directory, # This is the root directory to archive
)
logger.info("Zip archive created successfully.")
# Send the file and then clean it up
return send_from_directory(temp_dir, zip_filename, as_attachment=True)
except Exception as e:
logger.error(f"Error creating or sending zip archive of cache directory: {e}", exc_info=True)
return jsonify({"error": f"Error creating or sending zip archive: {e}"}), 500
@main_bp.route('/')
def index():
"""Serves the main HTML page."""
# The backend now only provides the list of available reports.
# The frontend will be responsible for selecting a report,
# fetching its details (text, image path), and managing the current state.
if not config.AVAILABLE_REPORTS:
logger.warning("No reports found in config. AVAILABLE_REPORTS is empty.")
return render_template(
'index.html',
available_reports=config.AVAILABLE_REPORTS
)
@main_bp.route('/get_report_details/<report_name>')
def get_report_details(report_name):
"""Fetches the text content and image path for a given report name."""
selected_report_info = next((item for item in config.AVAILABLE_REPORTS if item['name'] == report_name), None)
if not selected_report_info:
logger.error(f"Report '{report_name}' not found when fetching details.")
return jsonify({"error": f"Report '{report_name}' not found."}), 404
report_file = selected_report_info.get('report_file')
image_file = selected_report_info.get('image_file')
report_text_content = "" # Default to empty if no report file is configured.
if report_file:
actual_server_report_path = config.BASE_DIR / report_file
try:
report_text_content = actual_server_report_path.read_text(encoding='utf-8').strip()
except Exception as e:
logger.error(f"Error reading report file {actual_server_report_path} for report '{report_name}': {e}", exc_info=True)
return jsonify({"error": "Error reading report file."}), 500
# If report_file was empty, report_text_content remains "".
image_type_from_config = selected_report_info.get('image_type')
display_image_type = 'Chest X-Ray' if image_type_from_config == 'CXR' else ('CT' if image_type_from_config == 'CT' else 'Medical Image')
return jsonify({"text": report_text_content, "image_file": image_file, "image_type": display_image_type})
@main_bp.route('/explain', methods=['POST'])
def explain_sentence():
"""Handles the explanation request using LLM API with base64 encoded image."""
if not llm_is_initialized():
logger.error("LLM client (REST API) not initialized. Cannot process request.")
return jsonify({"error": "LLM client (REST API) not initialized. Check API key and base URL."}), 500
data = request.get_json()
if not data or 'sentence' not in data or 'report_name' not in data:
logger.warning("Missing 'sentence' or 'report_name' in request payload.")
return jsonify({"error": "Missing 'sentence' or 'report_name' in request"}), 400
selected_sentence = data['sentence']
report_name = data['report_name']
logger.info(f"Received request to explain: '{selected_sentence}' for report: '{report_name}'")
# --- Find the selected report info ---
selected_report_info = next((item for item in config.AVAILABLE_REPORTS if item['name'] == report_name), None)
if not selected_report_info:
logger.error(f"Report '{report_name}' not found in available reports.")
return jsonify({"error": f"Report '{report_name}' not found."}), 404
image_file = selected_report_info.get('image_file')
report_file = selected_report_info.get('report_file')
image_type = selected_report_info.get('image_type')
if not image_file:
logger.error(f"Image or report file path (relative to static) missing in config for report '{report_name}'.")
return jsonify({"error": f"File configuration missing for report '{report_name}'."}), 500
# Construct absolute server paths using BASE_DIR as image_file and report_file include "static/"
server_image_path = config.BASE_DIR / image_file
# --- Prepare Base64 Image for API ---
if not server_image_path.is_file():
logger.error(f"Image file not found at {server_image_path}")
return jsonify({"error": f"Image file for report '{report_name}' not found on server."}), 500
base64_image_data_url = utils.image_to_base64_data_url(str(server_image_path))
if not base64_image_data_url:
logger.error("Failed to encode image to base64.")
return jsonify({"error": "Could not encode image for API request"}), 500
logger.info("Image successfully encoded to base64 data URL for API.")
full_report_text = ""
if report_file: # Only attempt to read if a report file is configured
server_report_path = config.BASE_DIR / report_file
try:
full_report_text = server_report_path.read_text(encoding='utf-8')
except FileNotFoundError:
logger.error(f"Report file not found at {server_report_path}")
return jsonify({"error": f"Report file for '{report_name}' not found on server."}), 500
except Exception as e:
logger.error(f"Error reading report file {server_report_path}: {e}", exc_info=True)
return jsonify({"error": "Error reading report file."}), 500
else: # If report_file is not configured (e.g. empty string from selected_report_info)
logger.info(f"No report file configured for report '{report_name}'. Proceeding without full report text for system prompt.")
system_prompt = (
"You are a public-facing clinician. "
f"A learning user has provided a sentence from a radiology report and is viewing the accompanying {image_type} image. "
"Your task is to explain the meaning of ONLY the provided sentence in simple, clear terms. Explain terminology and abbriviations. Keep it concise. "
"Directly address the meaning of the sentence. Do not use introductory phrases like 'Okay' or refer to the sentence itself or the report itself (e.g., 'This sentence means...'). " # noqa: E501
f"{f'Crucially, since the user is looking at their {image_type} image, provide guidance on where to look on the image to understand your explanation, if applicable. ' if image_type != 'CT' else ''}"
"Do not discuss any other part of the report or any sentences not explicitly provided by the user. Stick to facts in the text. Do not infer anything. \n"
"===\n"
f"For context, the full REPORT is:\n{full_report_text}"
)
user_prompt_text = f"Explain this sentence from the radiology report: '{selected_sentence}'"
messages_for_api = [
{"role": "system", "content": system_prompt},
{
"role": "user",
"content": [
{"type": "text", "text": user_prompt_text}
]
}
]
cache_key = f"explain::{report_name}::{selected_sentence}"
cached_result = cache.get(cache_key)
if cached_result:
logger.info("Returning cached explanation.")
return jsonify({"explanation": cached_result})
try:
logger.info("Sending request to LLM API (REST) with base64 image...")
response = make_chat_completion_request(
model="tgi",
messages=messages_for_api,
top_p=None,
temperature=0,
max_tokens=250,
stream=True,
seed=None,
stop=None,
frequency_penalty=None,
presence_penalty=None
)
logger.info("Received response stream from LLM API (REST).")
explanation_parts = []
for line in response.iter_lines():
if line:
decoded_line = line.decode('utf-8')
if decoded_line.startswith('data: '):
json_data_str = decoded_line[len('data: '):].strip()
if json_data_str == "[DONE]":
break
try:
chunk = json.loads(json_data_str)
if chunk.get("choices") and chunk["choices"][0].get("delta") and chunk["choices"][0]["delta"].get("content"):
explanation_parts.append(chunk["choices"][0]["delta"]["content"])
except json.JSONDecodeError:
logger.warning(f"Could not decode JSON from stream chunk: {json_data_str}")
# Depending on API, might need to handle partial JSON or other errors
elif decoded_line.strip() == "[DONE]": # Some APIs might send [DONE] without "data: "
break
explanation = "".join(explanation_parts).strip()
if explanation:
cache.set(cache_key, explanation, expire=None)
logger.info("Explanation generated successfully." if explanation else "Empty explanation from API.")
return jsonify({"explanation": explanation or "No explanation content received from the API."})
except requests.exceptions.RequestException as e:
logger.error(f"Error during LLM API (REST) call: {e}", exc_info=True)
user_error_message = ("Failed to generate explanation. The service might be temporarily unavailable "
"and is now likely starting up. Please try again in a few moments.")
return jsonify({"error": user_error_message}), 500
|