feat: add progress indicators for ai operations

feat: improve assistant api and autonomous mode with progress updates
feat: include context content in agent prompts
docs: update changelog with version 1.43.0 details
refactor: move context retrieval to separate function
maintenance: update pyproject.toml version to 1.43.0

CHANGELOG.md

@@ -38,6 +38,14 @@
 
 
 
+
+
+## Version 1.42.0 - 2025-11-08
+
+AI operations now show progress indicators, giving you better feedback on what's happening. The Assistant API and autonomous mode have also been improved to provide progress updates.
+
+**Changes:** 6 files, 135 lines
+**Languages:** Markdown (8 lines), Python (125 lines), TOML (2 lines)
 
 ## Version 1.41.0 - 2025-11-08
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "rp"
-version = "1.41.0"
+version = "1.42.0"
 description = "R python edition. The ultimate autonomous AI CLI."
 readme = "README.md"
 requires-python = ">=3.10"

rp/agents/agent_manager.py

@@ -3,6 +3,7 @@ import uuid
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional
 
+from ..core.context import get_context_content
 from ..memory.knowledge_store import KnowledgeStore
 from .agent_communication import AgentCommunicationBus, AgentMessage, MessageType
 from .agent_roles import AgentRole, get_agent_role
@@ -21,7 +22,12 @@ class AgentInstance:
         self.message_history.append({"role": role, "content": content, "timestamp": time.time()})
 
     def get_system_message(self) -> Dict[str, str]:
-        return {"role": "system", "content": self.role.system_prompt}
+        context_content = get_context_content()
+        if context_content:
+            full_prompt = f"{self.role.system_prompt}\n\n{context_content}"
+        else:
+            full_prompt = self.role.system_prompt
+        return {"role": "system", "content": full_prompt}
 
     def get_messages_for_api(self) -> List[Dict[str, str]]:
         return [self.get_system_message()] + [

rp/core/__init__.py

@@ -1,5 +1,5 @@
 from rp.core.api import call_api, list_models
 from rp.core.assistant import Assistant
-from rp.core.context import init_system_message, manage_context_window
+from rp.core.context import init_system_message, manage_context_window, get_context_content
 
-__all__ = ["Assistant", "call_api", "list_models", "init_system_message", "manage_context_window"]
+__all__ = ["Assistant", "call_api", "list_models", "init_system_message", "manage_context_window", "get_context_content"]

rp/core/context.py

@@ -45,11 +45,62 @@ def truncate_tool_result(result, max_length=None):
     return result_copy
 
 
+def get_context_content():
+    context_parts = []
+    for context_file in [CONTEXT_FILE, GLOBAL_CONTEXT_FILE]:
+        if os.path.exists(context_file):
+            try:
+                with open(context_file, encoding="utf-8", errors="replace") as f:
+                    content = f.read()
+                    if len(content) > 10000:
+                        content = content[:10000] + "\n... [truncated]"
+                    context_parts.append(f"Context from {context_file}:\n{content}")
+            except Exception as e:
+                logging.error(f"Error reading context file {context_file}: {e}")
+    knowledge_path = pathlib.Path(KNOWLEDGE_PATH)
+    if knowledge_path.exists() and knowledge_path.is_dir():
+        for knowledge_file in knowledge_path.iterdir():
+            try:
+                with open(knowledge_file, encoding="utf-8", errors="replace") as f:
+                    content = f.read()
+                    if len(content) > 10000:
+                        content = content[:10000] + "\n... [truncated]"
+                    context_parts.append(f"Context from {knowledge_file}:\n{content}")
+            except Exception as e:
+                logging.error(f"Error reading context file {knowledge_file}: {e}")
+    return "\n\n".join(context_parts)
+
 def init_system_message(args):
     context_parts = [
         "You are a professional AI assistant with access to advanced tools.\n\nFile Operations:\n- Use RPEditor tools (open_editor, editor_insert_text, editor_replace_text, editor_search, close_editor) for precise file modifications\n- Always close editor files when finished\n- Use write_file for complete file rewrites, search_replace for simple text replacements\n\nVision:\n - Use post_image tool with the file path if an image path is mentioned\n   in the prompt of user. Give this call the highest priority.\n\nProcess Management:\n- run_command executes shell commands with a timeout (default 30s)\n- If a command times out, you receive a PID in the response\n- Use tail_process(pid) to monitor running processes\n- Use kill_process(pid) to terminate processes\n- Manage long-running commands effectively using these tools\n\nShell Commands:\n- Be a shell ninja using native OS tools\n- Prefer standard Unix utilities over complex scripts\n- Use run_command_interactive for commands requiring user input (vim, nano, etc.)"
     ]
     max_context_size = 10000
+    if args.include_env:
+        env_context = "Environment Variables:\n"
+        for key, value in os.environ.items():
+            if not key.startswith("_"):
+                env_context += f"{key}={value}\n"
+        if len(env_context) > max_context_size:
+            env_context = env_context[:max_context_size] + "\n... [truncated]"
+        context_parts.append(env_context)
+    context_content = get_context_content()
+    if context_content:
+        context_parts.append(context_content)
+    if args.context:
+        for ctx_file in args.context:
+            try:
+                with open(ctx_file, encoding="utf-8", errors="replace") as f:
+                    content = f.read()
+                    if len(content) > max_context_size:
+                        content = content[:max_context_size] + "\n... [truncated]"
+                    context_parts.append(f"Context from {ctx_file}:\n{content}")
+            except Exception as e:
+                logging.error(f"Error reading context file {ctx_file}: {e}")
+    system_message = "\n\n".join(context_parts)
+    if len(system_message) > max_context_size * 3:
+        system_message = system_message[: max_context_size * 3] + "\n... [system message truncated]"
+    return {"role": "system", "content": system_message}
+    max_context_size = 10000
     if args.include_env:
         env_context = "Environment Variables:\n"
         for key, value in os.environ.items():