Sync ling-space changes from GitHub commit b5051bd

smart_writer_kit/agent_for_streaming_completion.py

@@ -1,40 +1,46 @@
 from model_handler import ModelHandler
 from config import LING_FLASH_2_0
 
-def fetch_flow_suggestion_agent(editor_content: str):
+def fetch_flow_suggestion_agent(editor_content: str, style: str = "", kb=None, short_outline=None, long_outline=None):
     """
     Agent for fetching a short, real-time continuation.
     This agent calls a real LLM.
     """
 
-    if not editor_content or len(editor_content.strip()) < 5:
+    if not editor_content or len(editor_content.strip()) < 4:
         return "（请输入更多内容以获取建议...）"
 
     try:
         model_handler = ModelHandler()
-        
+
         # For a simple continuation, we can use a concise system prompt.
-        system_prompt = "你是一个写作助手，请根据用户输入的内容，紧接着写一句简短、流畅的续写。不要重复用户已输入的内容，直接开始写你续写的部分即可。**尤其关注用户输入的最后几个字**。"
-        
+        system_prompt = f"""你是一个写作助手，根据用户输入的内容，紧接着写一句 **简短、流畅** 的续写。
+- 不要重复用户已输入的内容，直接开始写你续写的部分。
+- 遵循 **整体章程** 中的风格和指导原则。
+
+整体章程:
+{style}"""
+
 
-        
         # We use editor_content as the user prompt.
-        # Let's take the last N characters to be more efficient.
-        user_prompt = editor_content[-1000:]
-        
+        # 我们的上下文编排方式，根据当前光标所在位置，来决定续写的位置。
+        # ---
+        # <之前的内容>...</之前的内容>{续写这里}
+        # <之后的内容>...</之后的内容>
+        # 写出 {续写这里} 部分的内容。
+        # ---
+        user_prompt = f"""===之前的内容===\n{editor_content[-80:]}"""
         # Use generate_code as it's a simple generator for direct content.
         # We need to provide a dummy code_type and a model_choice.
         # The model_choice here is the display name, but we can pass the constant.
         response_generator = model_handler.generate_code(
             system_prompt=system_prompt,
             user_prompt=user_prompt,
-            model_choice=LING_FLASH_2_0 
+            model_choice=LING_FLASH_2_0
         )
-        
+
         # Assemble the streamed response
         full_response = "".join(chunk for chunk in response_generator)
-        print("【收到的完整上下文】")
-        print("full_response:", repr(full_response))
         return full_response.strip()
 
     except Exception as e:
@@ -51,6 +57,4 @@ def accept_flow_suggestion_agent(current_text: str, suggestion: str):
         result = current_text
     else:
         result = current_text + suggestion
-    print("【收到的完整上下文】")
-    print("result:", repr(result))
     return result

tab_smart_writer.py

@@ -51,7 +51,7 @@ def dismiss_inspiration():
 # --- UI Construction ---
 
 def create_smart_writer_tab():
-    debounce_state = gr.State({"last_change": 0, "active": False})
+    debounce_state = gr.State({"last_change": 0, "active": False, "style": "", "kb": [], "short_outline": [], "long_outline": []})
     debounce_timer = gr.Timer(0.5, active=False)
 
     with gr.Row(equal_height=False, elem_id="indicator-writing-tab"):
@@ -188,25 +188,25 @@ def create_smart_writer_tab():
     cancel_insp_btn.click(fn=dismiss_inspiration, outputs=inspiration_modal, show_progress="hidden")
 
     # 3. Flow Suggestion with Debounce
-    def start_debounce(editor_content):
-        return {"last_change": time.time(), "active": True}, gr.update(active=True), gr.update(visible=True, value="<progress value='0' max='100'></progress> 补全中... 3.0s")
+    def start_debounce(editor_content, style, kb, short_outline, long_outline):
+        return {"last_change": time.time(), "active": True, "style": style, "kb": kb, "short_outline": short_outline, "long_outline": long_outline}, gr.update(active=True), gr.update(visible=True, value="<progress value='0' max='100'></progress> 补全中... 3.0s")
 
     def update_debounce(debounce_state, editor_content):
         if not debounce_state["active"]:
             return gr.update(), gr.update(), debounce_state, gr.update()
         elapsed = time.time() - debounce_state["last_change"]
         if elapsed >= 3:
-            suggestion = fetch_flow_suggestion_agent(editor_content)
-            return gr.update(visible=False), suggestion, {"last_change": 0, "active": False}, gr.update(active=False)
+            suggestion = fetch_flow_suggestion_agent(editor_content, debounce_state["style"], debounce_state["kb"], debounce_state["short_outline"], debounce_state["long_outline"])
+            return gr.update(visible=False), suggestion, {"last_change": 0, "active": False, "style": "", "kb": [], "short_outline": [], "long_outline": []}, gr.update(active=False)
         else:
             progress = int((elapsed / 3) * 100)
             remaining = 3 - elapsed
             progress_html = f"<progress value='{progress}' max='100'></progress> 补全中... {remaining:.1f}s"
             return gr.update(value=progress_html), gr.update(), debounce_state, gr.update()
 
-    editor.change(fn=start_debounce, inputs=editor, outputs=[debounce_state, debounce_timer, debounce_progress])
+    editor.change(fn=start_debounce, inputs=[editor, style_input, kb_input, short_outline_input, long_outline_input], outputs=[debounce_state, debounce_timer, debounce_progress])
     debounce_timer.tick(fn=update_debounce, inputs=[debounce_state, editor], outputs=[debounce_progress, flow_suggestion_display, debounce_state, debounce_timer])
-    refresh_flow_btn.click(fn=fetch_flow_suggestion_agent, inputs=editor, outputs=flow_suggestion_display)
+    refresh_flow_btn.click(fn=fetch_flow_suggestion_agent, inputs=[editor, style_input, kb_input, short_outline_input, long_outline_input], outputs=flow_suggestion_display)
 
     # Accept Flow (Triggered by visible Button or hidden Tab Key trigger)
     accept_flow_fn_inputs = [editor, flow_suggestion_display]