create compatible class structure
This commit is contained in:
AI Christianson
parent
377a670ac8
commit
c704117444
|
|
@ -1,8 +1,11 @@
|
|||
import os
|
||||
import uuid
|
||||
from dotenv import load_dotenv
|
||||
from ra_aid.agent_utils import run_agent_with_retry
|
||||
from typing import Dict, Any, Generator, List, Optional
|
||||
from langchain_core.messages import AIMessage, HumanMessage
|
||||
from langchain_openai import ChatOpenAI
|
||||
from langchain_core.tools import tool
|
||||
from langchain_core.messages import HumanMessage, SystemMessage
|
||||
from ra_aid.tools.list_directory import list_directory_tree
|
||||
from ra_aid.tool_configs import get_read_only_tools
|
||||
import inspect
|
||||
|
|
@ -15,44 +18,14 @@ console = Console()
|
|||
# Load environment variables
|
||||
load_dotenv()
|
||||
|
||||
|
||||
def get_function_info(func):
|
||||
"""
|
||||
Returns a well-formatted string containing the function signature and docstring,
|
||||
designed to be easily readable by both humans and LLMs.
|
||||
"""
|
||||
# Get signature
|
||||
signature = inspect.signature(func)
|
||||
|
||||
# Get docstring - use getdoc to clean up indentation
|
||||
docstring = inspect.getdoc(func)
|
||||
if docstring is None:
|
||||
docstring = "No docstring provided"
|
||||
|
||||
# Format full signature including return type
|
||||
full_signature = f"{func.__name__}{signature}"
|
||||
|
||||
# Build the complete string
|
||||
info = f"""{full_signature}
|
||||
\"\"\"
|
||||
{docstring}
|
||||
\"\"\" """
|
||||
|
||||
return info
|
||||
|
||||
@tool
|
||||
def check_weather(location: str) -> str:
|
||||
"""
|
||||
Gets the weather at the given location.
|
||||
"""
|
||||
"""Gets the weather at the given location."""
|
||||
return f"The weather in {location} is sunny!"
|
||||
|
||||
@tool
|
||||
def output_message(message: str, prompt_user_input: bool = False) -> str:
|
||||
"""
|
||||
Outputs a message to the user, optionally prompting for input.
|
||||
"""
|
||||
print()
|
||||
"""Outputs a message to the user, optionally prompting for input."""
|
||||
console.print(Panel(Markdown(message.strip())))
|
||||
if prompt_user_input:
|
||||
user_input = input("\n> ").strip()
|
||||
|
|
@ -60,78 +33,42 @@ def output_message(message: str, prompt_user_input: bool = False) -> str:
|
|||
return user_input
|
||||
return ""
|
||||
|
||||
def evaluate_response(code: str, tools: list) -> any:
|
||||
class CiaynAgent:
|
||||
def get_function_info(self, func):
|
||||
"""
|
||||
Evaluates a single function call and returns its result
|
||||
|
||||
Args:
|
||||
code (str): The code to evaluate
|
||||
tools (list): List of tool objects that have a .func property
|
||||
|
||||
Returns:
|
||||
any: Result of the code evaluation
|
||||
Returns a well-formatted string containing the function signature and docstring,
|
||||
designed to be easily readable by both humans and LLMs.
|
||||
"""
|
||||
# Create globals dictionary from tool functions
|
||||
globals_dict = {
|
||||
tool.func.__name__: tool.func
|
||||
for tool in tools
|
||||
}
|
||||
|
||||
try:
|
||||
# Using eval() instead of exec() since we're evaluating a single expression
|
||||
result = eval(code, globals_dict)
|
||||
return result
|
||||
except Exception as e:
|
||||
print(f"Code:\n\n{code}\n\n")
|
||||
print(f"Error executing code: {str(e)}")
|
||||
return f"Error executing code: {str(e)}"
|
||||
|
||||
def create_chat_interface():
|
||||
# Initialize the chat model
|
||||
chat = ChatOpenAI(
|
||||
# api_key=os.getenv("OPENROUTER_API_KEY"),
|
||||
api_key=os.getenv("DEEPSEEK_API_KEY"),
|
||||
temperature=0.7 ,
|
||||
# base_url="https://openrouter.ai/api/v1",
|
||||
base_url="https://api.deepseek.com/v1",
|
||||
# model="deepseek/deepseek-chat"
|
||||
model="deepseek-chat"
|
||||
# model="openai/gpt-4o-mini"
|
||||
# model="qwen/qwen-2.5-coder-32b-instruct"
|
||||
# model="qwen/qwen-2.5-72b-instruct"
|
||||
)
|
||||
|
||||
# Chat loop
|
||||
print("Welcome to the Chat Interface! (Type 'quit' to exit)")
|
||||
|
||||
chat_history = []
|
||||
last_result = None
|
||||
first_iteration = True
|
||||
|
||||
tools = get_read_only_tools(True, True)
|
||||
|
||||
tools.extend([output_message])
|
||||
|
||||
available_functions = []
|
||||
signature = inspect.signature(func)
|
||||
docstring = inspect.getdoc(func)
|
||||
if docstring is None:
|
||||
docstring = "No docstring provided"
|
||||
full_signature = f"{func.__name__}{signature}"
|
||||
info = f"""{full_signature}
|
||||
\"\"\"
|
||||
{docstring}
|
||||
\"\"\" """
|
||||
return info
|
||||
|
||||
def __init__(self, model, tools: list):
|
||||
"""Initialize the agent with a model and list of tools."""
|
||||
self.model = model
|
||||
self.tools = tools
|
||||
self.available_functions = []
|
||||
for t in tools:
|
||||
available_functions.append(get_function_info(t.func))
|
||||
self.available_functions.append(self.get_function_info(t.func))
|
||||
|
||||
while True:
|
||||
def _build_prompt(self, last_result: Optional[str] = None) -> str:
|
||||
"""Build the prompt for the agent including available tools and context."""
|
||||
base_prompt = ""
|
||||
|
||||
# Add the last result to the prompt if it's not the first iteration
|
||||
if not first_iteration and last_result is not None:
|
||||
if last_result is not None:
|
||||
base_prompt += f"\n<last result>{last_result}</last result>"
|
||||
|
||||
# Construct the tool documentation and context
|
||||
base_prompt += f"""
|
||||
<available functions>
|
||||
{"\n\n".join(available_functions)}
|
||||
{"\n\n".join(self.available_functions)}
|
||||
</available functions>
|
||||
"""
|
||||
|
||||
base_prompt += """
|
||||
<agent instructions>
|
||||
You are a ReAct agent. You run in a loop and use ONE of the available functions per iteration.
|
||||
If the current query does not require a function call, just use output_message to say what you would normally say.
|
||||
|
|
@ -148,49 +85,90 @@ def create_chat_interface():
|
|||
</example response>
|
||||
|
||||
<example response>
|
||||
output_message(\"\"\"
|
||||
How can I help you today?
|
||||
\"\"\", True)
|
||||
output_message(\"\"\"How can I help you today?\"\"\", True)
|
||||
</example response>
|
||||
"""
|
||||
|
||||
base_prompt += "\nOutput **ONLY THE CODE** and **NO MARKDOWN BACKTICKS**"
|
||||
Output **ONLY THE CODE** and **NO MARKDOWN BACKTICKS**"""
|
||||
return base_prompt
|
||||
|
||||
# Add user message to history
|
||||
# Remove the previous messages if they exist
|
||||
# if len(chat_history) > 1:
|
||||
# chat_history.pop() # Remove the last assistant message
|
||||
# chat_history.pop() # Remove the last human message
|
||||
def _execute_tool(self, code: str) -> str:
|
||||
"""Execute a tool call and return its result."""
|
||||
globals_dict = {
|
||||
tool.func.__name__: tool.func
|
||||
for tool in self.tools
|
||||
}
|
||||
|
||||
try:
|
||||
result = eval(code.strip(), globals_dict)
|
||||
return result
|
||||
except Exception as e:
|
||||
error_msg = f"Error executing code: {str(e)}"
|
||||
console.print(f"[red]Error:[/red] {error_msg}")
|
||||
return error_msg
|
||||
|
||||
|
||||
def _create_agent_chunk(self, content: str) -> Dict[str, Any]:
|
||||
"""Create an agent chunk in the format expected by print_agent_output."""
|
||||
return {
|
||||
"agent": {
|
||||
"messages": [AIMessage(content=content)]
|
||||
}
|
||||
}
|
||||
|
||||
def _create_error_chunk(self, content: str) -> Dict[str, Any]:
|
||||
"""Create an error chunk in the format expected by print_agent_output."""
|
||||
return {
|
||||
"tools": {
|
||||
"messages": [{"status": "error", "content": content}]
|
||||
}
|
||||
}
|
||||
|
||||
def stream(self, messages_dict: Dict[str, List[Any]], config: Dict[str, Any] = None) -> Generator[Dict[str, Any], None, None]:
|
||||
"""Stream agent responses in a format compatible with print_agent_output."""
|
||||
initial_messages = messages_dict.get("messages", [])
|
||||
chat_history = []
|
||||
last_result = None
|
||||
first_iteration = True
|
||||
|
||||
while True:
|
||||
base_prompt = self._build_prompt(None if first_iteration else last_result)
|
||||
chat_history.append(HumanMessage(content=base_prompt))
|
||||
|
||||
try:
|
||||
# Get response from model
|
||||
# print("PRECHAT")
|
||||
response = chat.invoke(chat_history)
|
||||
# print("POSTCHAT")
|
||||
full_history = initial_messages + chat_history
|
||||
response = self.model.invoke(full_history)
|
||||
|
||||
# # Print the code response
|
||||
# print("\nAssistant generated code:")
|
||||
# print(response.content)
|
||||
|
||||
# Evaluate the code
|
||||
# print("\nExecuting code:")
|
||||
# print("PREEVAL")
|
||||
last_result = evaluate_response(response.content.strip(), tools)
|
||||
# print("POSTEVAL")
|
||||
# if last_result is not None:
|
||||
# print(f"Result: {last_result}")
|
||||
|
||||
# Add assistant response to history
|
||||
last_result = self._execute_tool(response.content)
|
||||
chat_history.append(response)
|
||||
|
||||
# Set first_iteration to False after the first loop
|
||||
first_iteration = False
|
||||
# print("LOOP")
|
||||
yield {}
|
||||
|
||||
except Exception as e:
|
||||
print(f"\nError: {str(e)}")
|
||||
error_msg = f"Error: {str(e)}"
|
||||
yield self._create_error_chunk(error_msg)
|
||||
break
|
||||
|
||||
if __name__ == "__main__":
|
||||
create_chat_interface()
|
||||
# Initialize the chat model
|
||||
chat = ChatOpenAI(
|
||||
api_key=os.getenv("OPENROUTER_API_KEY"),
|
||||
temperature=0.7,
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
model="qwen/qwen-2.5-coder-32b-instruct"
|
||||
)
|
||||
|
||||
# Get tools
|
||||
tools = get_read_only_tools(True, True)
|
||||
tools.append(output_message)
|
||||
|
||||
# Initialize agent
|
||||
agent = CiaynAgent(chat, tools)
|
||||
|
||||
# Test chat prompt
|
||||
test_prompt = "Find the tests in this codebase."
|
||||
|
||||
# Run the agent using run_agent_with_retry
|
||||
result = run_agent_with_retry(agent, test_prompt, {"configurable": {"thread_id": str(uuid.uuid4())}})
|
||||
|
||||
# Initial greeting
|
||||
print("Welcome to the Chat Interface! (Type 'quit' to exit)")
|
||||
|
|
|
|||
Loading…
Reference in New Issue