Update app.py

app.py

@@ -39,6 +39,9 @@ def process_repo_input(text):
 last_repo_ids = []
 current_repo_idx = 0
 
+# Store extracted keywords for the chatbot flow
+generated_keywords = []
+
 def process_repo_input_and_store(text):
     global last_repo_ids, current_repo_idx
     if not text:
@@ -124,16 +127,19 @@ def show_combined_repo_and_llm():
     return combined_content, summary, df
 
 def go_to_analysis():
-    return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
+    return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
 
 def go_to_input():
-    return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+    return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
 
 def go_to_chatbot():
-    return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
+    return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
 
 def go_to_start():
-    return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+    return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+
+def go_to_results():
+    return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
 
 repo_id_input = gr.Textbox(label="Enter repo IDs (comma or newline separated)", lines=5, placeholder="repo1, repo2\nrepo3")
 df_output = gr.Dataframe(headers=["repo id", "strength", "weaknesses", "speciality", "relevance rating", "Usecase"],
@@ -164,12 +170,29 @@ def extract_keywords_from_conversation(history):
     conversation = "\n".join([f"User: {msg[0]}\nAssistant: {msg[1]}" for msg in history if msg[1]])
     prompt = (
         "Given the following conversation between a user and an assistant about finding an ideal open-source repo, "
-        "extract about 5 keywords that best represent what the user is looking for. "
+        "extract about 5 keywords that would be most useful for searching Hugging Face repos to find the most relevant results for the user. "
         "Return only the keywords as a comma-separated list.\n\nConversation:\n" + conversation
     )
     keywords = analyze_code(prompt)
     return keywords
 
+def use_keywords_to_search_and_update_csv(keywords):
+    global last_repo_ids, current_repo_idx
+    if not keywords:
+        return pd.DataFrame(columns=["repo id", "strength", "weaknesses", "speciality", "relevance rating"])
+    # Use the keywords to search for repos
+    repo_ids = search_top_spaces(keywords, limit=5)
+    last_repo_ids = repo_ids
+    current_repo_idx = 0
+    csv_filename = "repo_ids.csv"
+    with open(csv_filename, mode="w", newline='', encoding="utf-8") as csvfile:
+        writer = csv.writer(csvfile)
+        writer.writerow(["repo id", "strength", "weaknesses", "speciality", "relevance rating"])
+        for repo_id in repo_ids:
+            writer.writerow([repo_id, "", "", "", ""])
+    df = read_csv_as_text(csv_filename)
+    return df
+
 with gr.Blocks() as demo:
     page_state = gr.State(0)
 
@@ -212,16 +235,27 @@ with gr.Blocks() as demo:
         send_btn = gr.Button("Send")
         end_btn = gr.Button("End Chat and Extract Keywords")
         keywords_output = gr.Textbox(label="Extracted Keywords for Repo Search", interactive=False)
+        go_to_results_btn = gr.Button("Find Repos with These Keywords")
         back_to_start_btn3 = gr.Button("Back to Start")
 
+    # --- Page 4: Results after Chatbot ---
+    with gr.Column(visible=False) as results_page:
+        gr.Markdown("## Repo Results Based on Your Conversation")
+        results_df = gr.Dataframe(
+            headers=["repo id", "strength", "weaknesses", "speciality", "relevance rating", "Usecase"],
+            datatype=["str", "str", "str", "str", "str", "str"]
+        )
+        back_to_start_btn4 = gr.Button("Back to Start")
+
     # Navigation logic
-    option_a_btn.click(go_to_input, inputs=None, outputs=[start_page, input_page, chatbot_page])
-    option_b_btn.click(go_to_chatbot, inputs=None, outputs=[start_page, input_page, chatbot_page])
-    next_btn.click(go_to_analysis, inputs=None, outputs=[input_page, analysis_page, chatbot_page])
-    back_btn.click(go_to_input, inputs=None, outputs=[input_page, analysis_page, chatbot_page])
-    back_to_start_btn.click(go_to_start, inputs=None, outputs=[start_page, input_page, chatbot_page])
-    back_to_start_btn2.click(go_to_start, inputs=None, outputs=[start_page, input_page, chatbot_page])
-    back_to_start_btn3.click(go_to_start, inputs=None, outputs=[start_page, input_page, chatbot_page])
+    option_a_btn.click(go_to_input, inputs=None, outputs=[start_page, input_page, chatbot_page, results_page])
+    option_b_btn.click(go_to_chatbot, inputs=None, outputs=[start_page, input_page, chatbot_page, results_page])
+    next_btn.click(go_to_analysis, inputs=None, outputs=[input_page, analysis_page, chatbot_page, results_page])
+    back_btn.click(go_to_input, inputs=None, outputs=[input_page, analysis_page, chatbot_page, results_page])
+    back_to_start_btn.click(go_to_start, inputs=None, outputs=[start_page, input_page, chatbot_page, results_page])
+    back_to_start_btn2.click(go_to_start, inputs=None, outputs=[start_page, input_page, chatbot_page, results_page])
+    back_to_start_btn3.click(go_to_start, inputs=None, outputs=[start_page, input_page, chatbot_page, results_page])
+    back_to_start_btn4.click(go_to_start, inputs=None, outputs=[start_page, input_page, chatbot_page, results_page])
 
     # Keyword and repo input logic
     keyword_btn.click(keyword_search_and_update, inputs=keyword_input, outputs=df_box)
@@ -238,9 +272,18 @@ with gr.Blocks() as demo:
 
     def end_chat(history):
         keywords = extract_keywords_from_conversation(history)
+        global generated_keywords
+        generated_keywords.clear()
+        generated_keywords.extend([k.strip() for k in keywords.split(",") if k.strip()])
         return keywords
 
+    def go_to_results_from_chatbot(keywords):
+        # Use the keywords to search and update the CSV, then display the DataFrame
+        df = use_keywords_to_search_and_update_csv(keywords)
+        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), df
+
     send_btn.click(user_send, inputs=[user_input, state], outputs=[chatbot, state, user_input])
     end_btn.click(end_chat, inputs=state, outputs=keywords_output)
+    go_to_results_btn.click(go_to_results_from_chatbot, inputs=keywords_output, outputs=[chatbot_page, input_page, analysis_page, results_page, results_df])
 
 demo.launch()