Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -1,100 +1,19 @@
|
|
1 |
import gradio as gr
|
2 |
-
|
3 |
-
from
|
4 |
-
|
5 |
-
|
6 |
# ---------------------------- Configuration ----------------------------
|
7 |
-
ENTREZ_EMAIL = os.environ.get("ENTREZ_EMAIL", "
|
8 |
-
|
9 |
-
HUGGINGFACE_API_TOKEN = os.environ.get("HUGGINGFACE_API_TOKEN", "HUGGINGFACE_API_TOKEN") # Use environment variable, default fallback
|
10 |
-
SUMMARIZATION_MODEL = "facebook/bart-large-cnn"
|
11 |
|
12 |
# ---------------------------- Global Variables ----------------------------
|
13 |
-
summarizer = None
|
14 |
-
initialization_status = "Initializing..." # Track initialization state
|
15 |
-
|
16 |
-
# ---------------------------- Helper Functions ----------------------------
|
17 |
-
|
18 |
-
def log_error(message: str):
|
19 |
-
"""Logs an error message to the console and a file (if possible)."""
|
20 |
-
print(f"ERROR: {message}")
|
21 |
-
try:
|
22 |
-
with open("error_log.txt", "a") as f:
|
23 |
-
f.write(f"{message}\n")
|
24 |
-
except:
|
25 |
-
print("Couldn't write to error log file.") #If logging fails, still print to console
|
26 |
-
|
27 |
-
# ---------------------------- Tool Functions ----------------------------
|
28 |
-
|
29 |
-
def search_pubmed(query: str) -> list:
|
30 |
-
"""Searches PubMed and returns a list of article IDs."""
|
31 |
-
try:
|
32 |
-
Entrez.email = ENTREZ_EMAIL
|
33 |
-
handle = Entrez.esearch(db="pubmed", term=query, retmax="5")
|
34 |
-
record = Entrez.read(handle)
|
35 |
-
handle.close()
|
36 |
-
return record["IdList"]
|
37 |
-
except Exception as e:
|
38 |
-
log_error(f"PubMed search error: {e}")
|
39 |
-
return [f"Error during PubMed search: {e}"]
|
40 |
-
|
41 |
-
def fetch_abstract(article_id: str) -> str:
|
42 |
-
"""Fetches the abstract for a given PubMed article ID."""
|
43 |
-
try:
|
44 |
-
Entrez.email = ENTREZ_EMAIL
|
45 |
-
handle = Entrez.efetch(db="pubmed", id=article_id, rettype="abstract", retmode="text")
|
46 |
-
abstract = handle.read()
|
47 |
-
handle.close()
|
48 |
-
return abstract
|
49 |
-
except Exception as e:
|
50 |
-
log_error(f"Error fetching abstract for {article_id}: {e}")
|
51 |
-
return f"Error fetching abstract for {article_id}: {e}"
|
52 |
-
|
53 |
-
# ---------------------------- Agent Function ----------------------------
|
54 |
-
|
55 |
-
def medai_agent(query: str) -> str:
|
56 |
-
"""Orchestrates the medical literature review and summarization."""
|
57 |
-
article_ids = search_pubmed(query)
|
58 |
-
|
59 |
-
if isinstance(article_ids, list) and article_ids:
|
60 |
-
results = []
|
61 |
-
for article_id in article_ids:
|
62 |
-
abstract = fetch_abstract(article_id)
|
63 |
-
if "Error" not in abstract:
|
64 |
-
results.append(f"<div class='article'>\n"
|
65 |
-
f" <h3 class='article-id'>Article ID: {article_id}</h3>\n"
|
66 |
-
f" <p class='abstract'><strong>Abstract:</strong> {abstract}</p>\n"
|
67 |
-
f"</div>\n")
|
68 |
-
else:
|
69 |
-
results.append(f"<div class='article error'>\n"
|
70 |
-
f" <h3 class='article-id'>Article ID: {article_id}</h3>\n"
|
71 |
-
f" <p class='error-message'>Error processing article: {abstract}</p>\n"
|
72 |
-
f"</div>\n")
|
73 |
-
return "\n".join(results)
|
74 |
-
else:
|
75 |
-
return f"No articles found or error occurred: {article_ids}"
|
76 |
-
|
77 |
-
# ---------------------------- Initialization and Setup ----------------------------
|
78 |
-
|
79 |
-
def setup():
|
80 |
-
"""Initializes the summarization model."""
|
81 |
-
global summarizer, initialization_status
|
82 |
-
initialization_status = "Initializing..."
|
83 |
-
try:
|
84 |
-
initialization_status = "Model is running. The user is now set to search and obtain abstract articles."
|
85 |
-
return initialization_status
|
86 |
-
except Exception as e:
|
87 |
-
initialization_status = f"Initialization error: {e}"
|
88 |
-
log_error(initialization_status)
|
89 |
-
return initialization_status
|
90 |
|
91 |
# ---------------------------- Gradio Interface ----------------------------
|
92 |
|
93 |
def launch_gradio():
|
94 |
"""Launches the Gradio interface."""
|
95 |
-
global initialization_status
|
96 |
|
97 |
-
# CSS to style the article output
|
98 |
css = """
|
99 |
.article {
|
100 |
border: 1px solid #ddd;
|
@@ -118,14 +37,15 @@ def launch_gradio():
|
|
118 |
"""
|
119 |
|
120 |
with gr.Blocks(css=css) as iface:
|
121 |
-
gr.Markdown("# MedAI: Medical Literature Review
|
122 |
-
|
|
|
123 |
query_input = gr.Textbox(lines=3, placeholder="Enter your medical query (e.g., 'new treatments for diabetes')...")
|
124 |
submit_button = gr.Button("Submit")
|
125 |
output_results = gr.HTML() # Use HTML for formatted output
|
126 |
|
127 |
-
|
128 |
-
|
129 |
|
130 |
iface.launch()
|
131 |
|
|
|
1 |
import gradio as gr
|
2 |
+
import os
|
3 |
+
from components import pubmed_search
|
4 |
+
from components import model_utils
|
5 |
+
import time
|
6 |
# ---------------------------- Configuration ----------------------------
|
7 |
+
ENTREZ_EMAIL = os.environ.get("ENTREZ_EMAIL", "ENTREZ_EMAIL")
|
8 |
+
HUGGINGFACE_API_TOKEN = os.environ.get("HUGGINGFACE_API_TOKEN", "HUGGINGFACE_API_TOKEN")
|
|
|
|
|
9 |
|
10 |
# ---------------------------- Global Variables ----------------------------
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
11 |
|
12 |
# ---------------------------- Gradio Interface ----------------------------
|
13 |
|
14 |
def launch_gradio():
|
15 |
"""Launches the Gradio interface."""
|
|
|
16 |
|
|
|
17 |
css = """
|
18 |
.article {
|
19 |
border: 1px solid #ddd;
|
|
|
37 |
"""
|
38 |
|
39 |
with gr.Blocks(css=css) as iface:
|
40 |
+
gr.Markdown("# MedAI: Medical Literature Review")
|
41 |
+
gr.Markdown("Enter a medical query to retrieve abstracts from PubMed.")
|
42 |
+
|
43 |
query_input = gr.Textbox(lines=3, placeholder="Enter your medical query (e.g., 'new treatments for diabetes')...")
|
44 |
submit_button = gr.Button("Submit")
|
45 |
output_results = gr.HTML() # Use HTML for formatted output
|
46 |
|
47 |
+
# Get data
|
48 |
+
submit_button.click(pubmed_search.medai_agent, inputs=query_input, outputs=output_results)
|
49 |
|
50 |
iface.launch()
|
51 |
|