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app.py

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+import os
+import gradio as gr
+from openai import OpenAI
+
+
+def demo(project_TCGA, output_language="Chinese"):
+    name_English, name_Chinese = project_name_TCGA[project_TCGA]
+    output1, output2 = None, None
+
+    if output_language == "Chinese":
+        output1 = f"✍️ 简称：{project_TCGA}\n❤️ 中文全称：{name_Chinese}\n💛 英文全称：{name_English}"
+        system_instruction = f"您是系统生物学、流行病学、癌症研究和精准医学领域的专家，对{name_Chinese}有着深刻的洞察。"
+        prompt_template = f"""
+您的任务是深入分析{name_Chinese}这一复杂疾病，并深入探索其发病和进展中涉及的关键的分子机制与信号通路。让我们一步一步地思考。
+""".strip()
+    else:
+        output1 = f"✍️ Abbreviation: {project_TCGA}\n❤️ Full name in Chinese: {name_Chinese}\n💛 Full Name in English: {name_English}"
+        system_instruction = f"You are an expert in the fields of systems biology, epidemiology, cancer research, and precision medicine, with deep insights into {name_English}."
+        prompt_template = f"""
+Your task is to analyze in depth the complex disease of {name_English} and to explore in depth the key molecular mechanisms and signaling pathways involved in its initiation and progression. Let's think step by step.
+""".strip()
+
+    try:
+        # 要实例化一个 OpenAI 对象，你需要设置 OpenAI API Key、Base URL、最大重试次数以及超时限制时间。
+        client = OpenAI(
+            api_key=os.environ["OPENAI_API_KEY"],
+            base_url=os.environ["API_BASE"],
+            max_retries=3,
+            timeout=60,
+        )
+        # 调用 client.chat.completions.create，设置关键参数。
+        chat_completion = client.chat.completions.create(
+            model="gpt-4o-mini-2024-07-18",
+            messages=[
+                {"role": "system", "content": system_instruction},
+                {"role": "user", "content": prompt_template},
+            ],
+            n=1,
+            temperature=0.30,
+            seed=42,
+            max_tokens=2048,
+            logprobs=True,
+            top_logprobs=3,
+            presence_penalty=0,
+            frequency_penalty=0,
+        )
+        resp_text = chat_completion.choices[0].message.content.strip()
+
+        # 在普通文本框不能用 "**" 渲染加粗，Markdown 才可以。因此，将输入字符串中所有的 "**" 替换为 ""。
+        if "**" in resp_text:
+            output2 = resp_text.replace("**", "")
+
+    except Exception as e:
+        print(str(e), "Response Error")
+        return str(e), "Response Error"
+
+    return output1, output2
+
+
+project_name_TCGA = {
+    "TCGA-ACC": ["adrenocortical carcinoma", "肾上腺皮质癌"],
+    "TCGA-BLCA": ["bladder urothelial carcinoma", "膀胱尿路上皮癌"],
+    "TCGA-BRCA": ["breast invasive carcinoma", "浸润性乳腺癌"],
+    "TCGA-CESC": [
+        "cervical squamous cell carcinoma and endocervical adenocarcinoma",
+        "宫颈鳞状细胞癌与宫颈内膜腺癌",
+    ],
+    "TCGA-CHOL": ["cholangiocarcinoma", "胆管癌"],
+    "TCGA-COAD": ["colon adenocarcinoma", "结肠腺癌"],
+    "TCGA-DLBC": [
+        "lymphoid neoplasm diffuse large B-cell lymphoma",
+        "弥漫性大 B 细胞淋巴瘤",
+    ],
+    "TCGA-ESCA": ["esophageal carcinoma", "食道癌"],
+    "TCGA-GBM": ["glioblastoma multiforme", "多形性胶质母细胞瘤"],
+    "TCGA-HNSC": ["head and neck squamous cell carcinoma", "头颈部鳞状细胞癌"],
+    "TCGA-KICH": ["kidney chromophobe", "肾嫌色细胞癌"],
+    "TCGA-KIRC": ["kidney renal clear cell carcinoma", "肾透明细胞癌"],
+    "TCGA-KIRP": ["kidney renal papillary cell carcinoma", "乳头状肾细胞癌"],
+    "TCGA-LAML": ["acute myeloid leukemia", "急性髓系白血病"],
+    "TCGA-LGG": ["brain lower grade glioma", "低级别脑胶质瘤"],
+    "TCGA-LIHC": ["liver hepatocellular carcinoma", "肝细胞癌"],
+    "TCGA-LUAD": ["lung adenocarcinoma", "肺腺癌"],
+    "TCGA-LUSC": ["lung squamous cell carcinoma", "肺鳞状细胞癌"],
+    "TCGA-MESO": ["mesothelioma", "间皮瘤"],
+    "TCGA-OV": ["ovarian serous cystadenocarcinoma", "卵巢浆液性囊腺癌"],
+    "TCGA-PAAD": ["pancreatic adenocarcinoma", "胰腺腺癌"],
+    "TCGA-PCPG": ["pheochromocytoma and paraganglioma", "嗜铬细胞瘤和副神经节瘤"],
+    "TCGA-PRAD": ["prostate adenocarcinoma", "前列腺腺癌"],
+    "TCGA-READ": ["rectum adenocarcinoma", "直肠腺癌"],
+    "TCGA-SARC": ["sarcoma", "肉瘤"],
+    "TCGA-SKCM": ["skin cutaneous melanoma", "皮肤黑色素瘤"],
+    "TCGA-STAD": ["stomach adenocarcinoma", "胃腺癌"],
+    "TCGA-TGCT": ["testicular germ cell tumors", "睾丸生殖细胞肿瘤"],
+    "TCGA-THCA": ["thyroid carcinoma", "甲状腺癌"],
+    "TCGA-THYM": ["thymoma", "胸腺瘤"],
+    "TCGA-UCEC": ["uterine corpus endometrial carcinoma", "子宫体子宫内膜癌"],
+    "TCGA-UCS": ["uterine carcinosarcoma", "子宫癌肉瘤"],
+    "TCGA-UVM": ["uveal melanoma", "眼内（葡萄膜）黑色素瘤"],
+}
+# print(len(project_name_TCGA.keys()))
+# input_query = input("请输入您要查询的 TCGA 项目名称：")
+# print(project_name_TCGA[input_query])
+print([k for k in project_name_TCGA.keys()])
+
+# 支持 Markdown 和 HTML 内容格式：
+# Abbreviations, Full Names and Descriptions of All Cancer Types Covered by TCGA Project.
+desc = """<h1 align="center" style="font-family: Latin Modern Math, sans-serif; font-size: 22px; color: #00FF7F;">🎉 TCGA 项目涵盖的所有癌症类型的缩写、全称和描述 🧬</h1>"""
+outputs = [
+    gr.Textbox(
+        label="🔎 1. 所查询的癌症类型的全称", show_copy_button=True
+    ),  # 1. The Full Name of The Cancer Type Queried.
+    gr.Textbox(
+        label="👩‍⚕️ 2. 深入理解所查询的癌症类型",
+        show_copy_button=True,
+    ),  # 2. Insight Into The Cancer Type Being Queried.
+]
+my_demo = gr.Interface(
+    fn=demo,
+    inputs=[
+        gr.Dropdown(
+            choices=[k for k in project_name_TCGA.keys()],
+            value="TCGA-LUAD",
+            allow_custom_value=False,
+            label="⌨️ 请输入您要查询的 TCGA 项目名称，例如 TCGA-LUAD。",
+        ),  # Please enter the name of the TCGA project you want to query, such as TCGA-LUAD.
+        gr.Dropdown(
+            choices=["Chinese", "English"],
+            value="Chinese",
+            allow_custom_value=False,
+            label="👨‍💻 输出语言",
+        ),
+    ],
+    outputs=outputs,
+    description=desc,
+    theme="JohnSmith9982/small_and_pretty",
+)
+my_demo.launch(show_api=False, show_error=True)

requirements.txt

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+openai==1.52.2
+requests==2.29.0
+urllib3==1.25.11
+gradio==4.19.2
+gradio_client==0.10.1
+tenacity==8.2.3