add numpyml-display

README.md

@@ -4,7 +4,7 @@ emoji: 🏆
 colorFrom: indigo
 colorTo: purple
 sdk: gradio
-sdk_version: 4.13.0
+sdk_version: 3.35.2
 app_file: app.py
 pinned: false
 license: gpl-3.0

app.py

@@ -0,0 +1,342 @@
+"""
+Usage:
+python3 qa_browser.py --share
+"""
+
+# import argparse
+from collections import defaultdict
+import re
+
+import gradio as gr
+import json
+
+MAX_py_file_paths_depth = 3
+
+
+
+
+py_file_paths = {}
+
+comment = {"title2comment": {}, "path2comment": {}}
+model_judgments_normal = {}
+model_judgments_math = {}
+
+def load_py_file_paths(data_path):
+    global py_file_paths
+    py_file_paths = []
+    with open(data_path, "r") as f:
+        py_file_paths = f.readlines()
+        py_file_paths = [json.loads(line) for line in py_file_paths]
+        py_file_paths = {line["path"]: line['content'] for line in py_file_paths}
+    return py_file_paths
+
+def load_comment(data_path):
+    global comment
+    comment = {"title2comment": {}, "path2comment": {}}
+    title2comment = {}
+    path2comment = {}
+    with open(data_path, "r") as f:
+        data_f = f.readlines()
+        data_f = [json.loads(line) for line in data_f]
+        for line in data_f:
+            title2comment[line["title"]] = line
+            path2comment[line["class_link"]] = line
+    comment["title2comment"] = title2comment
+    comment["path2comment"] = path2comment
+    return comment
+
+def display_question(question_selector,file_path_selector, request: gr.Request):
+    if question_selector == None:
+        return [gr.Dropdown.update(
+        value=file_path_selector
+    )] +  [""] * 4
+
+    choice = comment['title2comment'][question_selector]['class_link'].split("#")[0]
+    lines = comment['title2comment'][question_selector]['class_link'].split("#")[1].replace("L","")
+
+    question = comment['title2comment'][question_selector]['comment']
+    code_path = choice
+    test_path = comment['title2comment'][question_selector]['test_file_path']
+
+    highlight_lines = [int(line) for line in lines.split("-")]
+    class_link = comment['title2comment'][question_selector]['class_link']
+    question_mds,code_mds = to_gradio_chat_mds(question, code_path, highlight_lines, class_link, test_path)
+    return [gr.Dropdown.update(
+        value=choice
+    )] +  question_mds + code_mds
+
+def display_answer(question_selector,file_path_selector, request: gr.Request):
+    choice = comment['title2comment'][question_selector]['class_link'].split("#")[0]
+    lines = comment['title2comment'][question_selector]['class_link'].split("#")[1].replace("L","")
+
+    question = comment['title2comment'][question_selector]['comment']
+    code_path = choice
+    test_path = comment['title2comment'][question_selector]['test_file_path']
+
+    highlight_lines = [int(line) for line in lines.split("-")]
+    class_link = comment['title2comment'][question_selector]['class_link']
+    if comment['title2comment'][question_selector]['class_link'].split("#")[0] != file_path_selector:
+        highlight_lines = None
+        class_link = None
+        test_path = None
+        code_path = file_path_selector
+    question_mds,code_mds = to_gradio_chat_mds(question, code_path, highlight_lines, class_link, test_path)
+    return code_mds
+
+# def display_answer(
+#     file_path_selector, request: gr.Request
+# ):
+#     # if comment['title2comment'][question_selector]['class_link'].split("#")[0] == file_path_selector:
+#     #     choice = question_selector
+#     # else:
+#     #     choice = None
+
+#     code_path = file_path_selector
+#     question = ""
+#     highlight_lines = None
+    
+#     question_mds,code_mds = to_gradio_chat_mds(question, code_path, highlight_lines)
+
+#     return code_mds
+
+
+newline_pattern1 = re.compile("\n\n(\d+\. )")
+newline_pattern2 = re.compile("\n\n(- )")
+
+
+def to_gradio_chat_mds(question, code_path, highlight_lines = None, class_link = None, test_path = None):
+    mds = [""] * 1 + [""] * 3
+    mds[0] = question
+    source_code = py_file_paths[code_path]
+    if test_path:
+        test_code = py_file_paths[test_path]
+    else:
+        test_code = [""]
+    # no highlight, highlight, no highlight
+    if not highlight_lines:
+        # mds[1] = "".join(source_code)
+        mds[1] = "#################################################################\n" + "# Please Check the `Full Code in the File` column\n" + "#################################################################\n"
+        # mds[3] = ""
+    else:
+        highlight_lines[0] -= 1
+        mds[1] = "#################################################################\n" + "# From " + class_link + "\n" + f"# From Line {highlight_lines[0]+1} to Line {highlight_lines[1]}\n" + "#################################################################\n"
+        mds[1] += "".join(source_code[highlight_lines[0]:highlight_lines[1]])
+    mds[2] = "".join(source_code)
+    mds[3] = "".join(test_code)
+
+    return mds[:1], mds[1:]
+
+
+def build_pairwise_browser_tab():
+    file_path_list = list(py_file_paths.keys())
+    question_list = list(comment['title2comment'].keys())
+    num_py_file_paths = MAX_py_file_paths_depth
+
+    # Build question selector map
+    with gr.Row():
+        with gr.Column():
+            question_selector = gr.Dropdown(
+                choices=question_list,
+                label="Question",
+                container=False
+            )
+            # locate_button = gr.Button(
+            #     text="Locate",
+            #     label="Locate",
+            #     type="default"
+            #     )
+        with gr.Column():
+            file_path_selector = gr.Dropdown(
+                choices=file_path_list,
+                label="File Path",
+                container=False
+            )
+
+    question_mds = []
+    code_mds = []
+    with gr.Row():
+        with gr.Column():
+            question_mds.append(gr.Code(language="markdown"))
+        with gr.Column():
+            with gr.Tab("Infilling Code"):
+            # add code highlight
+                code_mds.append(gr.Code(language="python",elem_id="locate_code"))
+            with gr.Tab("Full Code in the File"):
+                code_mds.append(gr.Code(language="python"))
+            with gr.Tab("Test Code"):
+                code_mds.append(gr.Code(language="python"))
+
+    # Callbacks
+    question_selector.change(display_question, [question_selector, file_path_selector], [file_path_selector] + question_mds + code_mds)
+    file_path_selector.change(display_answer, [question_selector,file_path_selector], code_mds)
+
+    return (question_selector,)
+
+
+
+
+code_highlight_css = """
+#chatbot .hll { background-color: #ffffcc }
+#chatbot .c { color: #408080; font-style: italic }
+#chatbot .err { border: 1px solid #FF0000 }
+#chatbot .k { color: #008000; font-weight: bold }
+#chatbot .o { color: #666666 }
+#chatbot .ch { color: #408080; font-style: italic }
+#chatbot .cm { color: #408080; font-style: italic }
+#chatbot .cp { color: #BC7A00 }
+#chatbot .cpf { color: #408080; font-style: italic }
+#chatbot .c1 { color: #408080; font-style: italic }
+#chatbot .cs { color: #408080; font-style: italic }
+#chatbot .gd { color: #A00000 }
+#chatbot .ge { font-style: italic }
+#chatbot .gr { color: #FF0000 }
+#chatbot .gh { color: #000080; font-weight: bold }
+#chatbot .gi { color: #00A000 }
+#chatbot .go { color: #888888 }
+#chatbot .gp { color: #000080; font-weight: bold }
+#chatbot .gs { font-weight: bold }
+#chatbot .gu { color: #800080; font-weight: bold }
+#chatbot .gt { color: #0044DD }
+#chatbot .kc { color: #008000; font-weight: bold }
+#chatbot .kd { color: #008000; font-weight: bold }
+#chatbot .kn { color: #008000; font-weight: bold }
+#chatbot .kp { color: #008000 }
+#chatbot .kr { color: #008000; font-weight: bold }
+#chatbot .kt { color: #B00040 }
+#chatbot .m { color: #666666 }
+#chatbot .s { color: #BA2121 }
+#chatbot .na { color: #7D9029 }
+#chatbot .nb { color: #008000 }
+#chatbot .nc { color: #0000FF; font-weight: bold }
+#chatbot .no { color: #880000 }
+#chatbot .nd { color: #AA22FF }
+#chatbot .ni { color: #999999; font-weight: bold }
+#chatbot .ne { color: #D2413A; font-weight: bold }
+#chatbot .nf { color: #0000FF }
+#chatbot .nl { color: #A0A000 }
+#chatbot .nn { color: #0000FF; font-weight: bold }
+#chatbot .nt { color: #008000; font-weight: bold }
+#chatbot .nv { color: #19177C }
+#chatbot .ow { color: #AA22FF; font-weight: bold }
+#chatbot .w { color: #bbbbbb }
+#chatbot .mb { color: #666666 }
+#chatbot .mf { color: #666666 }
+#chatbot .mh { color: #666666 }
+#chatbot .mi { color: #666666 }
+#chatbot .mo { color: #666666 }
+#chatbot .sa { color: #BA2121 }
+#chatbot .sb { color: #BA2121 }
+#chatbot .sc { color: #BA2121 }
+#chatbot .dl { color: #BA2121 }
+#chatbot .sd { color: #BA2121; font-style: italic }
+#chatbot .s2 { color: #BA2121 }
+#chatbot .se { color: #BB6622; font-weight: bold }
+#chatbot .sh { color: #BA2121 }
+#chatbot .si { color: #BB6688; font-weight: bold }
+#chatbot .sx { color: #008000 }
+#chatbot .sr { color: #BB6688 }
+#chatbot .s1 { color: #BA2121 }
+#chatbot .ss { color: #19177C }
+#chatbot .bp { color: #008000 }
+#chatbot .fm { color: #0000FF }
+#chatbot .vc { color: #19177C }
+#chatbot .vg { color: #19177C }
+#chatbot .vi { color: #19177C }
+#chatbot .vm { color: #19177C }
+#chatbot .il { color: #666666 }
+"""
+# .highlight  { background: #f8f8f8; }
+
+table_css = """
+table {
+    line-height: 0em
+}
+"""
+old_block_css = (
+    code_highlight_css
+    + """
+pre {
+    white-space: pre-wrap;       /* Since CSS 2.1 */
+    white-space: -moz-pre-wrap;  /* Mozilla, since 1999 */
+    white-space: -pre-wrap;      /* Opera 4-6 */
+    white-space: -o-pre-wrap;    /* Opera 7 */
+    word-wrap: break-word;       /* Internet Explorer 5.5+ */
+}
+#notice_markdown th {
+    display: none;
+}
+#notice_markdown td {
+    padding-top: 8px;
+    padding-bottom: 8px;
+}
+#leaderboard_markdown td {
+    padding-top: 8px;
+    padding-bottom: 8px;
+}
+"""
+)
+block_css = old_block_css + (
+    """
+#locate_code {
+    background-color: #DEEBF7;
+}
+#user_question {
+    background-color: #E2F0D9;
+}
+#reference {
+    background-color: #FFF2CC;
+}
+#model_explanation {
+    background-color: #FBE5D6;
+}
+"""
+)
+
+
+def load_demo():
+    dropdown_update = gr.Dropdown.update(value=list(comment['title2comment'].keys())[0])
+    return dropdown_update
+
+
+def build_demo():
+    with gr.Blocks(
+        title="Class-level Repo Code Generation Benchmark (numpy-ml)",
+        theme=gr.themes.Base(text_size=gr.themes.sizes.text_lg),
+        css=block_css,
+    ) as demo:
+        
+        (question_selector,) = build_pairwise_browser_tab()
+
+        demo.load(load_demo, [], [question_selector])
+
+        thanks_txt = gr.Markdown(
+            """
+            # Acknowledgement
+            This benchmark is based on the [numpy-ml](https://github.com/ddbourgin/numpy-ml) project.
+            """
+        )
+
+    return demo
+
+
+# if __name__ == "__main__":
+#     parser = argparse.ArgumentParser()
+#     parser.add_argument("--host", type=str, default="0.0.0.0")
+#     parser.add_argument("--port", type=int)
+#     parser.add_argument("--share", action="store_true")
+#     parser.add_argument("--bench-name", type=str, default="mt_bench")
+#     args = parser.parse_args()
+#     print(args)
+
+py_file_paths_path = "numpyml-display/all_py_content.jsonl"
+comment_path = "numpyml-display/final_dataset.jsonl"
+
+# Load py_file_paths
+py_file_paths = load_py_file_paths(py_file_paths_path)
+
+# Load answers
+comment = load_comment(comment_path)
+
+demo = build_demo()
+# demo.queue(concurrency_count=10, status_update_rate=10, api_open=False).launch()
+demo.launch()

raw.md

@@ -0,0 +1,2 @@
+- numpy-ml
+> https://github.com/ddbourgin/numpy-ml/tree/master