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Code Issues Actions 4 Packages Projects Releases Wiki Activity

Clean up chat

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This commit is contained in:
Brandon Hancock
2025-01-27 12:00:41 -05:00
parent f8f3b10588
commit 45efae8ebb
1 changed files with 84 additions and 70 deletions
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154
src/crewai/cli/crew_chat.py
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@@ -1,6 +1,9 @@
import json
import platform
import re
import sys
import threading
import time
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple
@@ -25,11 +28,11 @@ def check_conversational_crews_version(
Check if the installed crewAI version supports conversational crews.
Args:
crewai_version: The current version of crewAI
pyproject_data: Dictionary containing pyproject.toml data
crewai_version: The current version of crewAI.
pyproject_data: Dictionary containing pyproject.toml data.
Returns:
bool: True if version check passes, False otherwise
bool: True if version check passes, False otherwise.
"""
try:
if version.parse(crewai_version) < version.parse(MIN_REQUIRED_VERSION):
@@ -40,7 +43,7 @@ def check_conversational_crews_version(
)
return False
except version.InvalidVersion:
click.secho("Invalid crewAI version format detected", fg="red")
click.secho("Invalid crewAI version format detected.", fg="red")
return False
return True
@@ -56,6 +59,7 @@ def run_chat():
if not check_conversational_crews_version(crewai_version, pyproject_data):
return
crew, crew_name = load_crew_and_name()
chat_llm = initialize_chat_llm(crew)
if not chat_llm:
@@ -63,26 +67,14 @@ def run_chat():
# Indicate that the crew is being analyzed
click.secho(
"\nAnalyzing crew and required inputs - this may take 3 to 30 seconds depending on the complexity of your crew.",
"\nAnalyzing crew and required inputs - this may take 3 to 30 seconds "
"depending on the complexity of your crew.",
fg="white",
)
# Function to show loading dots
def show_loading():
import sys
import time
while not loading_complete.is_set():
sys.stdout.write(".")
sys.stdout.flush()
time.sleep(1)
print()
# Start loading indicator
import threading
loading_complete = threading.Event()
loading_thread = threading.Thread(target=show_loading)
loading_thread = threading.Thread(target=show_loading, args=(loading_complete,))
loading_thread.start()
try:
@@ -116,6 +108,14 @@ def run_chat():
chat_loop(chat_llm, messages, crew_tool_schema, available_functions)
def show_loading(event: threading.Event):
"""Display animated loading dots while processing."""
while not event.is_set():
print(".", end="", flush=True)
time.sleep(1)
print()
def initialize_chat_llm(crew: Crew) -> Optional[LLM]:
"""Initializes the chat LLM and handles exceptions."""
try:
@@ -149,7 +149,7 @@ def build_system_message(crew_chat_inputs: ChatInputs) -> str:
"Please keep your responses concise and friendly. "
"If a user asks a question outside the crew's scope, provide a brief answer and remind them of the crew's purpose. "
"After calling the tool, be prepared to take user feedback and make adjustments as needed. "
"If you are ever unsure about a user's request or need clarification, ask the user for more information."
"If you are ever unsure about a user's request or need clarification, ask the user for more information. "
"Before doing anything else, introduce yourself with a friendly message like: 'Hey! I'm here to help you with [crew's purpose]. Could you please provide me with [inputs] so we can get started?' "
"For example: 'Hey! I'm here to help you with uncovering and reporting cutting-edge developments through thorough research and detailed analysis. Could you please provide me with a topic you're interested in? This will help us generate a comprehensive research report and detailed analysis.'"
f"\nCrew Name: {crew_chat_inputs.crew_name}"
@@ -168,9 +168,6 @@ def create_tool_function(crew: Crew, messages: List[Dict[str, str]]) -> Any:
def flush_input():
"""Flush any pending input from the user."""
import platform
import sys
if platform.system() == "Windows":
# Windows platform
import msvcrt
@@ -191,44 +188,10 @@ def chat_loop(chat_llm, messages, crew_tool_schema, available_functions):
# Flush any pending input before accepting new input
flush_input()
click.secho(
"\nYou (type your message below. Press 'Enter' twice when you're done):",
fg="blue",
user_input = get_user_input()
handle_user_input(
user_input, chat_llm, messages, crew_tool_schema, available_functions
)
user_input_lines = []
while True:
line = input()
if line.strip().lower() == "exit":
click.echo("Exiting chat. Goodbye!")
return
if line == "":
break
user_input_lines.append(line)
user_input = "\n".join(user_input_lines)
if not user_input.strip():
click.echo(
"Empty message. Please provide input or type 'exit' to quit."
)
continue
messages.append({"role": "user", "content": user_input})
# Indicate that assistant is processing
click.echo()
click.secho(
"Assistant is processing your input. Please wait...", fg="green"
)
# Process assistant's response
final_response = chat_llm.call(
messages=messages,
tools=[crew_tool_schema],
available_functions=available_functions,
)
messages.append({"role": "assistant", "content": final_response})
click.secho(f"\nAssistant: {final_response}\n", fg="green")
except KeyboardInterrupt:
click.echo("\nExiting chat. Goodbye!")
@@ -238,6 +201,55 @@ def chat_loop(chat_llm, messages, crew_tool_schema, available_functions):
break
def get_user_input() -> str:
"""Collect multi-line user input with exit handling."""
click.secho(
"\nYou (type your message below. Press 'Enter' twice when you're done):",
fg="blue",
)
user_input_lines = []
while True:
line = input()
if line.strip().lower() == "exit":
return "exit"
if line == "":
break
user_input_lines.append(line)
return "\n".join(user_input_lines)
def handle_user_input(
user_input: str,
chat_llm: LLM,
messages: List[Dict[str, str]],
crew_tool_schema: Dict[str, Any],
available_functions: Dict[str, Any],
) -> None:
if user_input.strip().lower() == "exit":
click.echo("Exiting chat. Goodbye!")
return
if not user_input.strip():
click.echo("Empty message. Please provide input or type 'exit' to quit.")
return
messages.append({"role": "user", "content": user_input})
# Indicate that assistant is processing
click.echo()
click.secho("Assistant is processing your input. Please wait...", fg="green")
# Process assistant's response
final_response = chat_llm.call(
messages=messages,
tools=[crew_tool_schema],
available_functions=available_functions,
)
messages.append({"role": "assistant", "content": final_response})
click.secho(f"\nAssistant: {final_response}\n", fg="green")
def generate_crew_tool_schema(crew_inputs: ChatInputs) -> dict:
"""
Dynamically build a Littellm 'function' schema for the given crew.
@@ -432,10 +444,10 @@ def generate_input_description_with_ai(input_name: str, crew: Crew, chat_llm) ->
):
# Replace placeholders with input names
task_description = placeholder_pattern.sub(
lambda m: m.group(1), task.description
lambda m: m.group(1), task.description or ""
)
expected_output = placeholder_pattern.sub(
lambda m: m.group(1), task.expected_output
lambda m: m.group(1), task.expected_output or ""
)
context_texts.append(f"Task Description: {task_description}")
context_texts.append(f"Expected Output: {expected_output}")
@@ -446,10 +458,10 @@ def generate_input_description_with_ai(input_name: str, crew: Crew, chat_llm) ->
or f"{{{input_name}}}" in agent.backstory
):
# Replace placeholders with input names
agent_role = placeholder_pattern.sub(lambda m: m.group(1), agent.role)
agent_goal = placeholder_pattern.sub(lambda m: m.group(1), agent.goal)
agent_role = placeholder_pattern.sub(lambda m: m.group(1), agent.role or "")
agent_goal = placeholder_pattern.sub(lambda m: m.group(1), agent.goal or "")
agent_backstory = placeholder_pattern.sub(
lambda m: m.group(1), agent.backstory
lambda m: m.group(1), agent.backstory or ""
)
context_texts.append(f"Agent Role: {agent_role}")
context_texts.append(f"Agent Goal: {agent_goal}")
@@ -490,18 +502,20 @@ def generate_crew_description_with_ai(crew: Crew, chat_llm) -> str:
for task in crew.tasks:
# Replace placeholders with input names
task_description = placeholder_pattern.sub(
lambda m: m.group(1), task.description
lambda m: m.group(1), task.description or ""
)
expected_output = placeholder_pattern.sub(
lambda m: m.group(1), task.expected_output
lambda m: m.group(1), task.expected_output or ""
)
context_texts.append(f"Task Description: {task_description}")
context_texts.append(f"Expected Output: {expected_output}")
for agent in crew.agents:
# Replace placeholders with input names
agent_role = placeholder_pattern.sub(lambda m: m.group(1), agent.role)
agent_goal = placeholder_pattern.sub(lambda m: m.group(1), agent.goal)
agent_backstory = placeholder_pattern.sub(lambda m: m.group(1), agent.backstory)
agent_role = placeholder_pattern.sub(lambda m: m.group(1), agent.role or "")
agent_goal = placeholder_pattern.sub(lambda m: m.group(1), agent.goal or "")
agent_backstory = placeholder_pattern.sub(
lambda m: m.group(1), agent.backstory or ""
)
context_texts.append(f"Agent Role: {agent_role}")
context_texts.append(f"Agent Goal: {agent_goal}")
context_texts.append(f"Agent Backstory: {agent_backstory}")