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FEAT add verbose logging

This commit is contained in:
Jose Leon 2024-12-25 23:41:16 +00:00
parent 64fc0f6b99
commit 204f44cda0
6 changed files with 128 additions and 45 deletions
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4
README.md
View File

@ -151,6 +151,9 @@ ra-aid -m "Your task or query here"
# Research-only mode (no implementation)
ra-aid -m "Explain the authentication flow" --research-only
# Enable verbose logging for detailed execution information
ra-aid -m "Add new feature" --verbose
```
### Command Line Options
@ -164,6 +167,7 @@ ra-aid -m "Explain the authentication flow" --research-only
- `--expert-provider`: Specify the provider for the expert tool (defaults to OpenAI)
- `--expert-model`: Specify the model name for the expert tool (defaults to o1-preview for OpenAI)
- `--chat`: Enable chat mode for interactive assistance
- `--verbose`: Enable detailed logging output for debugging and monitoring
### Example Tasks

15
ra_aid/__main__.py
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@ -21,11 +21,13 @@ from ra_aid.prompts import (
WEB_RESEARCH_PROMPT_SECTION_CHAT
)
from ra_aid.llm import initialize_llm
from ra_aid.logging_config import setup_logging, get_logger
from ra_aid.tool_configs import (
get_chat_tools
)
logger = get_logger(__name__)
def parse_arguments():
parser = argparse.ArgumentParser(
description='RA.Aid - AI Agent for executing programming and research tasks',
@ -85,6 +87,11 @@ Examples:
action='store_true',
help='Enable chat mode with direct human interaction (implies --hil)'
)
parser.add_argument(
'--verbose',
action='store_true',
help='Enable verbose logging output'
)
args = parser.parse_args()
@ -126,9 +133,13 @@ def is_stage_requested(stage: str) -> bool:
def main():
"""Main entry point for the ra-aid command line tool."""
args = parse_arguments()
setup_logging(args.verbose)
logger.debug("Starting RA.Aid with arguments: %s", args)
try:
args = parse_arguments()
expert_enabled, expert_missing, web_research_enabled, web_research_missing = validate_environment(args) # Will exit if main env vars missing
logger.debug("Environment validation successful")
if expert_missing:
console.print(Panel(

125
ra_aid/agent_utils.py
View File

@ -10,17 +10,11 @@ import threading
import time
from typing import Optional
class AgentInterrupt(Exception):
"""Exception raised when an agent's execution is interrupted.
This exception is used for internal agent interruption handling,
separate from KeyboardInterrupt which is reserved for top-level handling.
"""
pass
from langgraph.prebuilt import create_react_agent
from ra_aid.console.formatting import print_stage_header, print_error
from ra_aid.console.output import print_agent_output
from ra_aid.logging_config import get_logger
from ra_aid.exceptions import AgentInterrupt
from ra_aid.tool_configs import (
get_implementation_tools,
get_research_tools,
@ -69,6 +63,8 @@ from ra_aid.prompts import (
console = Console()
logger = get_logger(__name__)
def run_research_agent(
base_task_or_query: str,
model,
@ -83,7 +79,7 @@ def run_research_agent(
console_message: Optional[str] = None
) -> Optional[str]:
"""Run a research agent with the given configuration.
Args:
base_task_or_query: The main task or query for research
model: The LLM model to use
@ -95,10 +91,10 @@ def run_research_agent(
config: Optional configuration dictionary
thread_id: Optional thread ID (defaults to new UUID)
console_message: Optional message to display before running
Returns:
Optional[str]: The completion message if task completed successfully
Example:
result = run_research_agent(
"Research Python async patterns",
@ -107,6 +103,11 @@ def run_research_agent(
research_only=True
)
"""
thread_id = thread_id or str(uuid.uuid4())
logger.debug("Starting research agent with thread_id=%s", thread_id)
logger.debug("Research configuration: expert=%s, research_only=%s, hil=%s, web=%s",
expert_enabled, research_only, hil, web_research_enabled)
# Initialize memory if not provided
if memory is None:
memory = MemorySaver()
@ -130,12 +131,12 @@ def run_research_agent(
expert_section = EXPERT_PROMPT_SECTION_RESEARCH if expert_enabled else ""
human_section = HUMAN_PROMPT_SECTION_RESEARCH if hil else ""
web_research_section = WEB_RESEARCH_PROMPT_SECTION_RESEARCH if config.get('web_research') else ""
# Get research context from memory
key_facts = _global_memory.get("key_facts", "")
code_snippets = _global_memory.get("code_snippets", "")
related_files = _global_memory.get("related_files", "")
# Build prompt
prompt = (RESEARCH_ONLY_PROMPT if research_only else RESEARCH_PROMPT).format(
base_task=base_task_or_query,
@ -156,12 +157,17 @@ def run_research_agent(
if config:
run_config.update(config)
# Display console message if provided
if console_message:
console.print(Panel(Markdown(console_message), title="🔬 Looking into it..."))
try:
# Display console message if provided
if console_message:
console.print(Panel(Markdown(console_message), title="🔬 Looking into it..."))
# Run agent with retry logic
return run_agent_with_retry(agent, prompt, run_config)
# Run agent with retry logic
logger.debug("Research agent completed successfully")
return run_agent_with_retry(agent, prompt, run_config)
except Exception as e:
logger.error("Research agent failed: %s", str(e), exc_info=True)
raise
def run_web_research_agent(
query: str,
@ -176,7 +182,7 @@ def run_web_research_agent(
console_message: Optional[str] = None
) -> Optional[str]:
"""Run a web research agent with the given configuration.
Args:
query: The mainquery for web research
model: The LLM model to use
@ -187,10 +193,10 @@ def run_web_research_agent(
config: Optional configuration dictionary
thread_id: Optional thread ID (defaults to new UUID)
console_message: Optional message to display before running
Returns:
Optional[str]: The completion message if task completed successfully
Example:
result = run_web_research_agent(
"Research latest Python async patterns",
@ -198,6 +204,11 @@ def run_web_research_agent(
expert_enabled=True
)
"""
thread_id = thread_id or str(uuid.uuid4())
logger.debug("Starting web research agent with thread_id=%s", thread_id)
logger.debug("Web research configuration: expert=%s, hil=%s, web=%s",
expert_enabled, hil, web_research_enabled)
# Initialize memory if not provided
if memory is None:
memory = MemorySaver()
@ -215,12 +226,12 @@ def run_web_research_agent(
# Format prompt sections
expert_section = EXPERT_PROMPT_SECTION_RESEARCH if expert_enabled else ""
human_section = HUMAN_PROMPT_SECTION_RESEARCH if hil else ""
# Get research context from memory
key_facts = _global_memory.get("key_facts", "")
code_snippets = _global_memory.get("code_snippets", "")
related_files = _global_memory.get("related_files", "")
# Build prompt
prompt = WEB_RESEARCH_PROMPT.format(
web_research_query=query,
@ -239,12 +250,17 @@ def run_web_research_agent(
if config:
run_config.update(config)
# Display console message if provided
if console_message:
console.print(Panel(Markdown(console_message), title="🔍 Starting Web Research..."))
try:
# Display console message if provided
if console_message:
console.print(Panel(Markdown(console_message), title="🔍 Starting Web Research..."))
# Run agent with retry logic
return run_agent_with_retry(agent, prompt, run_config)
# Run agent with retry logic
logger.debug("Web research agent completed successfully")
return run_agent_with_retry(agent, prompt, run_config)
except Exception as e:
logger.error("Web research agent failed: %s", str(e), exc_info=True)
raise
def run_planning_agent(
base_task: str,
@ -257,7 +273,7 @@ def run_planning_agent(
thread_id: Optional[str] = None
) -> Optional[str]:
"""Run a planning agent to create implementation plans.
Args:
base_task: The main task to plan implementation for
model: The LLM model to use
@ -266,10 +282,14 @@ def run_planning_agent(
memory: Optional memory instance to use
config: Optional configuration dictionary
thread_id: Optional thread ID (defaults to new UUID)
Returns:
Optional[str]: The completion message if planning completed successfully
"""
thread_id = thread_id or str(uuid.uuid4())
logger.debug("Starting planning agent with thread_id=%s", thread_id)
logger.debug("Planning configuration: expert=%s, hil=%s", expert_enabled, hil)
# Initialize memory if not provided
if memory is None:
memory = MemorySaver()
@ -288,7 +308,7 @@ def run_planning_agent(
expert_section = EXPERT_PROMPT_SECTION_PLANNING if expert_enabled else ""
human_section = HUMAN_PROMPT_SECTION_PLANNING if hil else ""
web_research_section = WEB_RESEARCH_PROMPT_SECTION_PLANNING if config.get('web_research') else ""
# Build prompt
planning_prompt = PLANNING_PROMPT.format(
expert_section=expert_section,
@ -310,9 +330,13 @@ def run_planning_agent(
if config:
run_config.update(config)
# Run agent with retry logic
print_stage_header("Planning Stage")
return run_agent_with_retry(agent, planning_prompt, run_config)
try:
print_stage_header("Planning Stage")
logger.debug("Planning agent completed successfully")
return run_agent_with_retry(agent, planning_prompt, run_config)
except Exception as e:
logger.error("Planning agent failed: %s", str(e), exc_info=True)
raise
def run_task_implementation_agent(
base_task: str,
@ -329,7 +353,7 @@ def run_task_implementation_agent(
thread_id: Optional[str] = None
) -> Optional[str]:
"""Run an implementation agent for a specific task.
Args:
base_task: The main task being implemented
tasks: List of tasks to implement
@ -341,10 +365,16 @@ def run_task_implementation_agent(
memory: Optional memory instance to use
config: Optional configuration dictionary
thread_id: Optional thread ID (defaults to new UUID)
Returns:
Optional[str]: The completion message if task completed successfully
"""
thread_id = thread_id or str(uuid.uuid4())
logger.debug("Starting implementation agent with thread_id=%s", thread_id)
logger.debug("Implementation configuration: expert=%s, web=%s", expert_enabled, web_research_enabled)
logger.debug("Task details: base_task=%s, current_task=%s", base_task, task)
logger.debug("Related files: %s", related_files)
# Initialize memory if not provided
if memory is None:
memory = MemorySaver()
@ -382,8 +412,12 @@ def run_task_implementation_agent(
if config:
run_config.update(config)
# Run agent with retry logic
return run_agent_with_retry(agent, prompt, run_config)
try:
logger.debug("Implementation agent completed successfully")
return run_agent_with_retry(agent, prompt, run_config)
except Exception as e:
logger.error("Implementation agent failed: %s", str(e), exc_info=True)
raise
_CONTEXT_STACK = []
_INTERRUPT_CONTEXT = None
@ -393,7 +427,7 @@ def _request_interrupt(signum, frame):
global _INTERRUPT_CONTEXT
if _CONTEXT_STACK:
_INTERRUPT_CONTEXT = _CONTEXT_STACK[-1]
if _FEEDBACK_MODE:
print()
print(" 👋 Bye!")
@ -404,7 +438,7 @@ class InterruptibleSection:
def __enter__(self):
_CONTEXT_STACK.append(self)
return self
def __exit__(self, exc_type, exc_value, traceback):
_CONTEXT_STACK.remove(self)
@ -413,6 +447,8 @@ def check_interrupt():
raise AgentInterrupt("Interrupt requested")
def run_agent_with_retry(agent, prompt: str, config: dict) -> Optional[str]:
"""Run an agent with retry logic for API errors."""
logger.debug("Running agent with prompt length: %d", len(prompt))
original_handler = None
if threading.current_thread() is threading.main_thread():
original_handler = signal.getsignal(signal.SIGINT)
@ -423,22 +459,27 @@ def run_agent_with_retry(agent, prompt: str, config: dict) -> Optional[str]:
with InterruptibleSection():
try:
logger.debug("Attempt %d/%d", attempt + 1, max_retries)
# Track agent execution depth
current_depth = _global_memory.get('agent_depth', 0)
_global_memory['agent_depth'] = current_depth + 1
for attempt in range(max_retries):
check_interrupt()
try:
for chunk in agent.stream({"messages": [HumanMessage(content=prompt)]}, config):
logger.debug("Agent output: %s", chunk)
check_interrupt()
print_agent_output(chunk)
logger.debug("Agent run completed successfully")
return "Agent run completed successfully"
except (KeyboardInterrupt, AgentInterrupt):
raise
except (InternalServerError, APITimeoutError, RateLimitError, APIError) as e:
if attempt == max_retries - 1:
logger.error("Max retries reached, failing: %s", str(e))
raise RuntimeError(f"Max retries ({max_retries}) exceeded. Last error: {e}")
logger.warning("API error (attempt %d/%d): %s", attempt + 1, max_retries, str(e))
delay = base_delay * (2 ** attempt)
print_error(f"Encountered {e.__class__.__name__}: {e}. Retrying in {delay}s... (Attempt {attempt+1}/{max_retries})")
start = time.monotonic()
@ -448,6 +489,6 @@ def run_agent_with_retry(agent, prompt: str, config: dict) -> Optional[str]:
finally:
# Reset depth tracking
_global_memory['agent_depth'] = _global_memory.get('agent_depth', 1) - 1
if original_handler and threading.current_thread() is threading.main_thread():
signal.signal(signal.SIGINT, original_handler)

9
ra_aid/exceptions.py Normal file
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@ -0,0 +1,9 @@
"""Custom exceptions for RA.Aid."""
class AgentInterrupt(Exception):
"""Exception raised when an agent's execution is interrupted.
This exception is used for internal agent interruption handling,
separate from KeyboardInterrupt which is reserved for top-level handling.
"""
pass

18
ra_aid/logging_config.py Normal file
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@ -0,0 +1,18 @@
import logging
import sys
from typing import Optional
def setup_logging(verbose: bool = False) -> None:
logger = logging.getLogger("ra_aid")
logger.setLevel(logging.DEBUG if verbose else logging.INFO)
if not logger.handlers:
handler = logging.StreamHandler(sys.stdout)
formatter = logging.Formatter(
"%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
handler.setFormatter(formatter)
logger.addHandler(handler)
def get_logger(name: Optional[str] = None) -> logging.Logger:
return logging.getLogger(f"ra_aid.{name}" if name else "ra_aid")

2
ra_aid/tools/agent.py
View File

@ -4,7 +4,7 @@ from langchain_core.tools import tool
from typing import Dict, Any, Union, List
from typing_extensions import TypeAlias
from ..agent_utils import AgentInterrupt
from ra_aid.exceptions import AgentInterrupt
ResearchResult = Dict[str, Union[str, bool, Dict[int, Any], List[Any], None]]
from rich.console import Console
from ra_aid.tools.memory import _global_memory