update app.py

README.md

@@ -3,8 +3,8 @@ title: Awesome ChatGPT Repositories Search
 emoji: 🏢
 colorFrom: red
 colorTo: blue
-sdk: streamlit
-sdk_version: 1.35.0
+sdk: gradio
+sdk_version: 4.36.0
 app_file: app.py
 pinned: false
 license: mit

app.py

@@ -1,9 +1,7 @@
-import difflib
 import json
 
-import numpy as np
-import streamlit as st
-from pyserini.search.lucene import LuceneSearcher
+import gradio as gr
+import pandas as pd
 
 
 def read_json(file_name):
@@ -12,146 +10,46 @@ def read_json(file_name):
     return json_data
 
 
-class SearchApplication:
-    def __init__(self):
-        self.title = "Awesome ChatGPT repositories search"
-
-        self.set_page_config()
-        self.searcher = self.set_searcher()
-
-        st.header(self.title)
-        col1, col2 = st.columns(2)
-        with col1:
-            self.query = st.text_input("Search English words", value="")
-
-        with col2:
-            st.write("#")
-            self.search_button = st.button("🔎")
-
-        st.caption(
-            "You can search for open-source software from [1500+ "
-            " repositories](https://github.com/taishi-i/awesome-ChatGPT-repositories)."
-        )
-        st.write("#")
-
-        candidate_words_file = "candidate_words.json"
-        candidate_words_json = read_json(candidate_words_file)
-        self.candidate_words = candidate_words_json["candidate_words"]
-
-        self.show_popular_words()
-        self.show_search_results()
-
-    def set_page_config(self):
-        st.set_page_config(
-            page_title=self.title,
-            page_icon="😎",
-            layout="centered",
-        )
-
-    def set_searcher(self):
-        searcher = LuceneSearcher("indexes/docs")
-        return searcher
-
-    def show_popular_words(self):
-        st.caption("Popular words")
-
-        word1, word2, word3, word4, word5, word6 = st.columns(6)
-        with word1:
-            button1 = st.button("Prompt")
-            if button1:
-                self.query = "prompt"
-
-        with word2:
-            button2 = st.button("Chatbot")
-            if button2:
-                self.query = "chatbot"
-
-        with word3:
-            button3 = st.button("Langchain")
-            if button3:
-                self.query = "langchain"
-
-        with word4:
-            button4 = st.button("Extension")
-            if button4:
-                self.query = "extension"
-
-        with word5:
-            button5 = st.button("LLMs")
-            if button5:
-                self.query = "llms"
-
-        with word6:
-            button6 = st.button("API")
-            if button6:
-                self.query = "api"
-
-    def show_search_results(self):
-        if self.query or self.search_button:
-            st.write("#")
-
-            search_results = self.searcher.search(self.query, k=500)
-            num_search_results = len(search_results)
-            st.write(f"A total of {num_search_results} repositories found.")
-
-            if num_search_results > 0:
-                json_search_results = []
-                for result in search_results:
-                    docid = result.docid
-                    doc = self.searcher.doc(docid)
-                    json_data = json.loads(doc.raw())
-                    json_search_results.append(json_data)
-
-                for json_data in sorted(
-                    json_search_results, key=lambda x: x["freq"], reverse=True
-                ):
-                    description = json_data["description"]
-                    url = json_data["url"]
-                    project_name = json_data["project_name"]
-
-                    st.write("---")
-                    st.subheader(f"[{project_name}]({url})")
-                    st.write(description)
-
-                    info = []
-                    language = json_data["language"]
-                    if language is not None and len(language) > 0:
-                        info.append(language)
-                    else:
-                        info.append("Laugage: Unkwown")
-
-                    license = json_data["license"]
-                    if license is None:
-                        info.append("License: Unkwown")
-                    else:
-                        info.append(license)
-
-                    st.caption(" / ".join(info))
-
-            else:
-                if len(self.query) > 0:
-                    scores = []
-                    for candidate_word in self.candidate_words:
-                        score = difflib.SequenceMatcher(
-                            None, self.query, candidate_word
-                        ).ratio()
-                        scores.append(score)
-
-                    num_candidate_words = 6
-
-                    indexes = np.argsort(scores)[::-1][:num_candidate_words]
-                    suggestions = [self.candidate_words[i] for i in indexes]
-                    suggestions = sorted(
-                        set(suggestions), key=suggestions.index
-                    )
-                    st.caption("Suggestions")
-                    for i, word in enumerate(suggestions, start=1):
-                        st.write(f"{i}: {word}")
-
-
-def main():
-    SearchApplication()
-
-
-if __name__ == "__main__":
-    main()
+data = {"project_name": [], "description": []}
+
+json_file = "awesome-ChatGPT-repositories.json"
+json_data = read_json(json_file)
+for v in json_data["contents"].values():
+    for url, repo in v.items():
+        description = repo["multilingual_descriptions"]["en"]
+        project_name = repo["repository_name"]
+        data["project_name"].append(f"[{project_name}]({url})")
+        data["description"].append(description)
+
+
+data = pd.DataFrame(data)
+
+
+def show_search_results(queries):
+    queries = queries.lower()
+    queries = queries.split()
+
+    df_search = data
+    for query in queries:
+        contained_description = data["description"].str.contains(query)
+        contained_project_name = data["project_name"].str.contains(query)
+        df_search = df_search[contained_description | contained_project_name]
+    return df_search
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    # Awesome ChatGPT repositories search 🔎
+    You can search for open-source software from [1500+ repositories](https://github.com/taishi-i/awesome-ChatGPT-repositories).
+    """
+    )
+
+    query = gr.Textbox(label="Search words", placeholder="prompt")
+    df = gr.DataFrame(
+        value=data, type="pandas", datatype="markdown", height=1000
+    )
+
+    query.change(fn=show_search_results, inputs=query, outputs=df)
+
+demo.launch()

packages.txt

@@ -1 +0,0 @@
-default-jdk

requirements.txt

@@ -1,4 +1 @@
-pyserini
-faiss-cpu
-torch
-altair<5
+pandas