Fixing bug tool calling setelah ada perubahan

scripts/llm_client.py

@@ -104,6 +104,7 @@ class LLMClient:
 
                     # Parse delta dari chunk
                     delta = chunk.get('choices', [{}])[0].get('delta', {})
+                    finish_reason = chunk.get('choices', [{}])[0].get('finish_reason', None)
 
                     # Stream reasoning content jika ada
                     if 'reasoning_content' in delta:
@@ -147,7 +148,32 @@ class LLMClient:
             message = {'content': full_content}
 
             if full_tool_calls:
-                message['tool_calls'] = full_tool_calls
+                # Filter tool_calls yang valid (ada name dan arguments)
+                valid_tool_calls = []
+                for tc in full_tool_calls:
+                    name = tc.get('function', {}).get('name')
+                    args_str = tc.get('function', {}).get('arguments')
+                    tc_id = tc.get('id')
+
+                    # Pastikan name dan arguments ada
+                    if name and args_str and args_str.strip():
+                        # Generate ID jika kosong
+                        if not tc_id:
+                            tc_id = f"call_{len(valid_tool_calls)}"
+                        tc['id'] = tc_id
+
+                        try:
+                            # Validate dan re-encode JSON untuk format yang konsisten
+                            parsed_args = json.loads(args_str)
+                            tc['function']['arguments'] = json.dumps(parsed_args, ensure_ascii=False)
+                            valid_tool_calls.append(tc)
+                        except json.JSONDecodeError:
+                            # Invalid JSON, coba raw string tapi hanya jika tidak kosong
+                            tc['function']['arguments'] = args_str
+                            valid_tool_calls.append(tc)
+
+                if valid_tool_calls:
+                    message['tool_calls'] = valid_tool_calls
 
             response = {'choices': [{'message': message}]}
         except urllib.error.HTTPError as e:

tui/agent.py

@@ -87,18 +87,26 @@ def _agent_loop(app):
         log(app, "system", f"  step {step + 1} \u2014 Thinking...")
         app.scroll = 999999
 
-        # Streaming response - buat placeholder untuk AI response
+        # Streaming response
-        stream_idx = len(app.log)
-        log(app, "ai", "...")  # Placeholder sambil streaming
-
         stream_buffer = []
+        placeholder_marker = None
+
         def on_stream_chunk(chunk):
+            nonlocal placeholder_marker
+            # Buat placeholder di chunk pertama saja
+            if placeholder_marker is None:
+                placeholder_marker = f"_stream_placeholder_{step}"
+                log(app, "ai", placeholder_marker)
             stream_buffer.append(chunk)
             current_text = ''.join(stream_buffer)
             # Update placeholder secara real-time
-            if stream_idx < len(app.log):
+            for i in range(len(app.log) - 1, -1, -1):
-                app.log[stream_idx]['text'] = current_text
+                # Cari placeholder berdasarkan content aslinya (atau apa yang sudah diupdate)
-                app.scroll = 999999
+                # Karena placeholder text berubah seiring streaming, kita harus teliti
+                if app.log[i].get('role') == 'ai' and (app.log[i].get('text') == placeholder_marker or (i > 0 and app.log[i-1].get('role') == 'system' and 'Thinking' in app.log[i-1].get('text', ''))):
+                    app.log[i]['text'] = current_text
+                    break
+            app.scroll = 999999
 
         response = app.llm.chat(app.messages, tools=app.TOOLS, on_stream_chunk=on_stream_chunk)
 
@@ -111,11 +119,23 @@ def _agent_loop(app):
         if response.warning:
             log(app, "system", f"  {response.warning}")
 
-        if response.tool_calls:
+        # Cek apakah ada tool_calls
+        has_tool_calls = bool(response.tool_calls)
+
+        if has_tool_calls:
+            # Hapus placeholder jika ada tool_calls (cari semua AI log yang mungkin placeholder)
+            if placeholder_marker is not None:
+                for i in range(len(app.log) - 1, -1, -1):
+                    # Jika ini adalah log AI yang muncul tepat setelah "Thinking..." atau contains placeholder marker
+                    if app.log[i].get('role') == 'ai':
+                        text = app.log[i].get('text', '')
+                        # Hapus jika text-nya adalah placeholder atau jika itu adalah entry AI yang baru saja kita buat untuk streaming
+                        if placeholder_marker in text or text == "" or text == "...":
+                            app.log.pop(i)
+            
             _add_msg(app, "assistant", response.content, tool_calls=response.tool_calls)
-            # Placeholder sudah terupdate via streaming, jangan log lagi
+
-            if stream_idx < len(app.log) and response.content and response.content.strip():
+            # Log tool_calls dengan label AI
-                app.log[stream_idx]['text'] = response.content
             for tc in response.tool_calls:
                 tname = tc["function"]["name"]
                 targs = tc["function"]["arguments"]
@@ -125,6 +145,10 @@ def _agent_loop(app):
                 }))
                 app.scroll = 999999
                 execute_tool(app, tc)
+
+            # Log content AI setelah tools (jika ada)
+            if response.content and response.content.strip():
+                log(app, "ai", response.content)
         else:
             if response.content:
                 _add_msg(app, "assistant", response.content)