Kye Gomez
2 months ago
parent
2e6b2df013
commit
0a39f2d48a
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from swarms import Agent
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from swarms.prompts.finance_agent_sys_prompt import (
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FINANCIAL_AGENT_SYS_PROMPT,
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)
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from swarms.structs.majority_voting import MajorityVoting
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from dotenv import load_dotenv
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load_dotenv()
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# Initialize the agent
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agent = Agent(
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agent_name="Financial-Analysis-Agent",
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agent_description="Personal finance advisor agent",
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system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
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max_loops=1,
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model_name="gpt-4o",
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dynamic_temperature_enabled=True,
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user_name="swarms_corp",
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retry_attempts=3,
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context_length=8192,
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return_step_meta=False,
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output_type="str", # "json", "dict", "csv" OR "string" "yaml" and
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auto_generate_prompt=False, # Auto generate prompt for the agent based on name, description, and system prompt, task
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max_tokens=4000, # max output tokens
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saved_state_path="agent_00.json",
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interactive=False,
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)
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swarm = MajorityVoting(agents=[agent, agent, agent])
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swarm.run(
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"Create a table of super high growth opportunities for AI. I have $40k to invest in ETFs, index funds, and more. Please create a table in markdown.",
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)
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@ -1,417 +0,0 @@
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import json
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import logging
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import time
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import uuid
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from datetime import datetime
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from typing import Any, Dict, List, Optional
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import yaml
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from pydantic import BaseModel
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from swarms.utils.litellm_tokenizer import count_tokens
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logger = logging.getLogger(__name__)
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class MemoryMetadata(BaseModel):
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"""Metadata for memory entries"""
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timestamp: Optional[float] = time.time()
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role: Optional[str] = None
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agent_name: Optional[str] = None
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session_id: Optional[str] = None
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memory_type: Optional[str] = None # 'short_term' or 'long_term'
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token_count: Optional[int] = None
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message_id: Optional[str] = str(uuid.uuid4())
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class MemoryEntry(BaseModel):
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"""Single memory entry with content and metadata"""
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content: Optional[str] = None
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metadata: Optional[MemoryMetadata] = None
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class MemoryConfig(BaseModel):
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"""Configuration for memory manager"""
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max_short_term_tokens: Optional[int] = 4096
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max_entries: Optional[int] = None
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system_messages_token_buffer: Optional[int] = 1000
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enable_long_term_memory: Optional[bool] = False
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auto_archive: Optional[bool] = True
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archive_threshold: Optional[float] = 0.8 # Archive when 80% full
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class MemoryManager:
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"""
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Manages both short-term and long-term memory for an agent, handling token limits,
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archival, and context retrieval.
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Args:
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config (MemoryConfig): Configuration for memory management
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tokenizer (Optional[Any]): Tokenizer to use for token counting
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long_term_memory (Optional[Any]): Vector store or database for long-term storage
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"""
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def __init__(
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self,
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config: MemoryConfig,
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tokenizer: Optional[Any] = None,
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long_term_memory: Optional[Any] = None,
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):
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self.config = config
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self.tokenizer = tokenizer
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self.long_term_memory = long_term_memory
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# Initialize memories
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self.short_term_memory: List[MemoryEntry] = []
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self.system_messages: List[MemoryEntry] = []
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# Memory statistics
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self.total_tokens_processed: int = 0
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self.archived_entries_count: int = 0
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def create_memory_entry(
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self,
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content: str,
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role: str,
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agent_name: str,
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session_id: str,
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memory_type: str = "short_term",
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) -> MemoryEntry:
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"""Create a new memory entry with metadata"""
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metadata = MemoryMetadata(
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timestamp=time.time(),
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role=role,
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agent_name=agent_name,
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session_id=session_id,
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memory_type=memory_type,
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token_count=count_tokens(content),
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)
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return MemoryEntry(content=content, metadata=metadata)
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def add_memory(
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self,
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content: str,
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role: str,
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agent_name: str,
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session_id: str,
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is_system: bool = False,
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) -> None:
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"""Add a new memory entry to appropriate storage"""
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entry = self.create_memory_entry(
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content=content,
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role=role,
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agent_name=agent_name,
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session_id=session_id,
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memory_type="system" if is_system else "short_term",
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)
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if is_system:
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self.system_messages.append(entry)
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else:
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self.short_term_memory.append(entry)
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# Check if archiving is needed
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if self.should_archive():
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self.archive_old_memories()
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self.total_tokens_processed += entry.metadata.token_count
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def get_current_token_count(self) -> int:
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"""Get total tokens in short-term memory"""
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return sum(
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entry.metadata.token_count
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for entry in self.short_term_memory
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)
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def get_system_messages_token_count(self) -> int:
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"""Get total tokens in system messages"""
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return sum(
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entry.metadata.token_count
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for entry in self.system_messages
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)
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def should_archive(self) -> bool:
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"""Check if archiving is needed based on configuration"""
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if not self.config.auto_archive:
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return False
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current_usage = (
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self.get_current_token_count()
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/ self.config.max_short_term_tokens
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)
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return current_usage >= self.config.archive_threshold
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def archive_old_memories(self) -> None:
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"""Move older memories to long-term storage"""
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if not self.long_term_memory:
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logger.warning(
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"No long-term memory storage configured for archiving"
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)
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return
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while self.should_archive():
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# Get oldest non-system message
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if not self.short_term_memory:
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break
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oldest_entry = self.short_term_memory.pop(0)
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# Store in long-term memory
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self.store_in_long_term_memory(oldest_entry)
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self.archived_entries_count += 1
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def store_in_long_term_memory(self, entry: MemoryEntry) -> None:
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"""Store a memory entry in long-term memory"""
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if self.long_term_memory is None:
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logger.warning(
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"Attempted to store in non-existent long-term memory"
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)
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return
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try:
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self.long_term_memory.add(str(entry.model_dump()))
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except Exception as e:
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logger.error(f"Error storing in long-term memory: {e}")
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# Re-add to short-term if storage fails
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self.short_term_memory.insert(0, entry)
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def get_relevant_context(
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self, query: str, max_tokens: Optional[int] = None
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) -> str:
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"""
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Get relevant context from both memory types
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Args:
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query (str): Query to match against memories
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max_tokens (Optional[int]): Maximum tokens to return
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Returns:
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str: Combined relevant context
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"""
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contexts = []
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# Add system messages first
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for entry in self.system_messages:
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contexts.append(entry.content)
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# Add short-term memory
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for entry in reversed(self.short_term_memory):
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contexts.append(entry.content)
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# Query long-term memory if available
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if self.long_term_memory is not None:
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long_term_context = self.long_term_memory.query(query)
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if long_term_context:
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contexts.append(str(long_term_context))
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# Combine and truncate if needed
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combined = "\n".join(contexts)
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if max_tokens:
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combined = self.truncate_to_token_limit(
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combined, max_tokens
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)
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return combined
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def truncate_to_token_limit(
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self, text: str, max_tokens: int
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) -> str:
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"""Truncate text to fit within token limit"""
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current_tokens = count_tokens(text)
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if current_tokens <= max_tokens:
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return text
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# Truncate by splitting into sentences and rebuilding
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sentences = text.split(". ")
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result = []
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current_count = 0
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for sentence in sentences:
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sentence_tokens = count_tokens(sentence)
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if current_count + sentence_tokens <= max_tokens:
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result.append(sentence)
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current_count += sentence_tokens
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else:
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break
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return ". ".join(result)
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def clear_short_term_memory(
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self, preserve_system: bool = True
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) -> None:
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"""Clear short-term memory with option to preserve system messages"""
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if not preserve_system:
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self.system_messages.clear()
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self.short_term_memory.clear()
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logger.info(
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"Cleared short-term memory"
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+ " (preserved system messages)"
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if preserve_system
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else ""
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)
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def get_memory_stats(self) -> Dict[str, Any]:
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"""Get detailed memory statistics"""
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return {
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"short_term_messages": len(self.short_term_memory),
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"system_messages": len(self.system_messages),
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"current_tokens": self.get_current_token_count(),
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"system_tokens": self.get_system_messages_token_count(),
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"max_tokens": self.config.max_short_term_tokens,
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"token_usage_percent": round(
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(
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self.get_current_token_count()
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/ self.config.max_short_term_tokens
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)
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* 100,
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2,
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),
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"has_long_term_memory": self.long_term_memory is not None,
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"archived_entries": self.archived_entries_count,
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"total_tokens_processed": self.total_tokens_processed,
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}
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def save_memory_snapshot(self, file_path: str) -> None:
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"""Save current memory state to file"""
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try:
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data = {
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"timestamp": datetime.now().isoformat(),
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"config": self.config.model_dump(),
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"system_messages": [
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entry.model_dump()
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for entry in self.system_messages
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],
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"short_term_memory": [
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entry.model_dump()
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for entry in self.short_term_memory
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],
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"stats": self.get_memory_stats(),
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}
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with open(file_path, "w") as f:
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if file_path.endswith(".yaml"):
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yaml.dump(data, f)
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else:
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json.dump(data, f, indent=2)
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logger.info(f"Saved memory snapshot to {file_path}")
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except Exception as e:
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logger.error(f"Error saving memory snapshot: {e}")
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raise
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def load_memory_snapshot(self, file_path: str) -> None:
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"""Load memory state from file"""
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try:
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with open(file_path, "r") as f:
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if file_path.endswith(".yaml"):
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data = yaml.safe_load(f)
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else:
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data = json.load(f)
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self.config = MemoryConfig(**data["config"])
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self.system_messages = [
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MemoryEntry(**entry)
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for entry in data["system_messages"]
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]
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self.short_term_memory = [
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MemoryEntry(**entry)
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for entry in data["short_term_memory"]
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]
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logger.info(f"Loaded memory snapshot from {file_path}")
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except Exception as e:
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logger.error(f"Error loading memory snapshot: {e}")
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raise
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def search_memories(
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self, query: str, memory_type: str = "all"
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) -> List[MemoryEntry]:
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"""
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Search through memories of specified type
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Args:
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query (str): Search query
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memory_type (str): Type of memories to search ("short_term", "system", "long_term", or "all")
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Returns:
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List[MemoryEntry]: Matching memory entries
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"""
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results = []
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if memory_type in ["short_term", "all"]:
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results.extend(
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[
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entry
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for entry in self.short_term_memory
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if query.lower() in entry.content.lower()
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]
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)
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if memory_type in ["system", "all"]:
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results.extend(
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[
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entry
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for entry in self.system_messages
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if query.lower() in entry.content.lower()
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]
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)
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if (
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memory_type in ["long_term", "all"]
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and self.long_term_memory is not None
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):
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long_term_results = self.long_term_memory.query(query)
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if long_term_results:
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# Convert long-term results to MemoryEntry format
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for result in long_term_results:
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content = str(result)
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metadata = MemoryMetadata(
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timestamp=time.time(),
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role="long_term",
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agent_name="system",
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session_id="long_term",
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memory_type="long_term",
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token_count=count_tokens(content),
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)
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results.append(
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MemoryEntry(
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content=content, metadata=metadata
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)
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)
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||||||
|
|
||||||
return results
|
|
||||||
|
|
||||||
def get_memory_by_timeframe(
|
|
||||||
self, start_time: float, end_time: float
|
|
||||||
) -> List[MemoryEntry]:
|
|
||||||
"""Get memories within a specific timeframe"""
|
|
||||||
return [
|
|
||||||
entry
|
|
||||||
for entry in self.short_term_memory
|
|
||||||
if start_time <= entry.metadata.timestamp <= end_time
|
|
||||||
]
|
|
||||||
|
|
||||||
def export_memories(
|
|
||||||
self, file_path: str, format: str = "json"
|
|
||||||
) -> None:
|
|
||||||
"""Export memories to file in specified format"""
|
|
||||||
data = {
|
|
||||||
"system_messages": [
|
|
||||||
entry.model_dump() for entry in self.system_messages
|
|
||||||
],
|
|
||||||
"short_term_memory": [
|
|
||||||
entry.model_dump() for entry in self.short_term_memory
|
|
||||||
],
|
|
||||||
"stats": self.get_memory_stats(),
|
|
||||||
}
|
|
||||||
|
|
||||||
with open(file_path, "w") as f:
|
|
||||||
if format == "yaml":
|
|
||||||
yaml.dump(data, f)
|
|
||||||
else:
|
|
||||||
json.dump(data, f, indent=2)
|
|
||||||
@ -1,177 +0,0 @@
|
|||||||
from dataclasses import dataclass, field
|
|
||||||
from typing import Dict, List, Optional, Union
|
|
||||||
|
|
||||||
from swarms.structs.agent import Agent
|
|
||||||
from swarms.structs.base_swarm import BaseSwarm
|
|
||||||
from swarms.utils.loguru_logger import initialize_logger
|
|
||||||
|
|
||||||
|
|
||||||
logger = initialize_logger("company-swarm")
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Company(BaseSwarm):
|
|
||||||
"""
|
|
||||||
Represents a company with a hierarchical organizational structure.
|
|
||||||
"""
|
|
||||||
|
|
||||||
org_chart: List[List[Agent]]
|
|
||||||
shared_instructions: str = None
|
|
||||||
ceo: Optional[Agent] = None
|
|
||||||
agents: List[Agent] = field(default_factory=list)
|
|
||||||
agent_interactions: Dict[str, List[str]] = field(
|
|
||||||
default_factory=dict
|
|
||||||
)
|
|
||||||
|
|
||||||
def __post_init__(self):
|
|
||||||
self._parse_org_chart(self.org_chart)
|
|
||||||
|
|
||||||
def add(self, agent: Agent) -> None:
|
|
||||||
"""
|
|
||||||
Adds an agent to the company.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
agent (Agent): The agent to be added.
|
|
||||||
|
|
||||||
Raises:
|
|
||||||
ValueError: If an agent with the same ID already exists in the company.
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
if any(
|
|
||||||
existing_agent.id == agent.id
|
|
||||||
for existing_agent in self.agents
|
|
||||||
):
|
|
||||||
raise ValueError(
|
|
||||||
f"Agent with id {agent.id} already exists in the"
|
|
||||||
" company."
|
|
||||||
)
|
|
||||||
self.agents.append(agent)
|
|
||||||
|
|
||||||
except Exception as error:
|
|
||||||
logger.error(
|
|
||||||
f"[ERROR][CLASS: Company][METHOD: add] {error}"
|
|
||||||
)
|
|
||||||
raise error
|
|
||||||
|
|
||||||
def get(self, agent_name: str) -> Agent:
|
|
||||||
"""
|
|
||||||
Retrieves an agent from the company by name.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
agent_name (str): The name of the agent to retrieve.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
Agent: The retrieved agent.
|
|
||||||
|
|
||||||
Raises:
|
|
||||||
ValueError: If an agent with the specified name does not exist in the company.
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
for agent in self.agents:
|
|
||||||
if agent.name == agent_name:
|
|
||||||
return agent
|
|
||||||
raise ValueError(
|
|
||||||
f"Agent with name {agent_name} does not exist in the"
|
|
||||||
" company."
|
|
||||||
)
|
|
||||||
except Exception as error:
|
|
||||||
logger.error(
|
|
||||||
f"[ERROR][CLASS: Company][METHOD: get] {error}"
|
|
||||||
)
|
|
||||||
raise error
|
|
||||||
|
|
||||||
def remove(self, agent: Agent) -> None:
|
|
||||||
"""
|
|
||||||
Removes an agent from the company.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
agent (Agent): The agent to be removed.
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
self.agents.remove(agent)
|
|
||||||
except Exception as error:
|
|
||||||
logger.error(
|
|
||||||
f"[ERROR][CLASS: Company][METHOD: remove] {error}"
|
|
||||||
)
|
|
||||||
raise error
|
|
||||||
|
|
||||||
def _parse_org_chart(
|
|
||||||
self, org_chart: Union[List[Agent], List[List[Agent]]]
|
|
||||||
) -> None:
|
|
||||||
"""
|
|
||||||
Parses the organization chart and adds agents to the company.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
org_chart (Union[List[Agent], List[List[Agent]]]): The organization chart
|
|
||||||
representing the hierarchy of agents.
|
|
||||||
|
|
||||||
Raises:
|
|
||||||
ValueError: If more than one CEO is found in the org chart or if an invalid
|
|
||||||
agent is encountered.
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
for node in org_chart:
|
|
||||||
if isinstance(node, Agent):
|
|
||||||
if self.ceo:
|
|
||||||
raise ValueError("1 CEO is only allowed")
|
|
||||||
self.ceo = node
|
|
||||||
self.add(node)
|
|
||||||
|
|
||||||
elif isinstance(node, list):
|
|
||||||
for agent in node:
|
|
||||||
if not isinstance(agent, Agent):
|
|
||||||
raise ValueError(
|
|
||||||
"Invalid agent in org chart"
|
|
||||||
)
|
|
||||||
self.add(agent)
|
|
||||||
|
|
||||||
for i, agent in enumerate(node):
|
|
||||||
if i == len(node) - 1:
|
|
||||||
continue
|
|
||||||
|
|
||||||
for other_agent in node[i + 1]:
|
|
||||||
self.__init_task(agent, other_agent)
|
|
||||||
except Exception as error:
|
|
||||||
logger.error(
|
|
||||||
"[ERROR][CLASS: Company][METHOD: _parse_org_chart]"
|
|
||||||
f" {error}"
|
|
||||||
)
|
|
||||||
raise error
|
|
||||||
|
|
||||||
def _init_interaction(
|
|
||||||
self,
|
|
||||||
agent1: Agent,
|
|
||||||
agent2: Agent,
|
|
||||||
) -> None:
|
|
||||||
"""
|
|
||||||
Initializes the interaction between two agents.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
agent1 (Agent): The first agent involved in the interaction.
|
|
||||||
agent2 (Agent): The second agent involved in the interaction.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
None
|
|
||||||
"""
|
|
||||||
if agent1.ai_name not in self.agents_interactions:
|
|
||||||
self.agents_interactions[agent1.ai_name] = []
|
|
||||||
self.agents_interactions[agent1.ai_name].append(
|
|
||||||
agent2.ai_name
|
|
||||||
)
|
|
||||||
|
|
||||||
def run(self):
|
|
||||||
"""
|
|
||||||
Run the company
|
|
||||||
"""
|
|
||||||
for (
|
|
||||||
agent_name,
|
|
||||||
interaction_agents,
|
|
||||||
) in self.agents_interactions.items():
|
|
||||||
agent = self.get(agent_name)
|
|
||||||
for interaction_agent in interaction_agents:
|
|
||||||
task_description = (
|
|
||||||
f"Task for {agent_name} to interact with"
|
|
||||||
f" {interaction_agent}"
|
|
||||||
)
|
|
||||||
print(f"{task_description} is being executed")
|
|
||||||
agent.run(task_description)
|
|
||||||
@ -1,87 +0,0 @@
|
|||||||
import os
|
|
||||||
import platform
|
|
||||||
import socket
|
|
||||||
import psutil
|
|
||||||
import uuid
|
|
||||||
from typing import Dict
|
|
||||||
import requests
|
|
||||||
|
|
||||||
from swarms.utils.loguru_logger import initialize_logger
|
|
||||||
|
|
||||||
logger = initialize_logger(log_folder="capture_sys_data")
|
|
||||||
|
|
||||||
|
|
||||||
def capture_system_data() -> Dict[str, str]:
|
|
||||||
"""
|
|
||||||
Captures extensive system data including platform information, user ID, IP address, CPU count,
|
|
||||||
memory information, and other system details.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
Dict[str, str]: A dictionary containing system data.
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
system_data = {
|
|
||||||
"platform": platform.system(),
|
|
||||||
"platform_version": platform.version(),
|
|
||||||
"platform_release": platform.release(),
|
|
||||||
"hostname": socket.gethostname(),
|
|
||||||
"ip_address": socket.gethostbyname(socket.gethostname()),
|
|
||||||
"cpu_count": psutil.cpu_count(logical=True),
|
|
||||||
"memory_total": f"{psutil.virtual_memory().total / (1024 ** 3):.2f} GB",
|
|
||||||
"memory_available": f"{psutil.virtual_memory().available / (1024 ** 3):.2f} GB",
|
|
||||||
"user_id": str(uuid.uuid4()), # Unique user identifier
|
|
||||||
"machine_type": platform.machine(),
|
|
||||||
"processor": platform.processor(),
|
|
||||||
"architecture": platform.architecture()[0],
|
|
||||||
}
|
|
||||||
|
|
||||||
# Get external IP address
|
|
||||||
try:
|
|
||||||
system_data["external_ip"] = requests.get(
|
|
||||||
"https://api.ipify.org"
|
|
||||||
).text
|
|
||||||
except Exception:
|
|
||||||
system_data["external_ip"] = "N/A"
|
|
||||||
|
|
||||||
return system_data
|
|
||||||
except Exception as e:
|
|
||||||
logger.error("Failed to capture system data: {}", e)
|
|
||||||
return {}
|
|
||||||
|
|
||||||
|
|
||||||
def log_agent_data(data_dict: dict) -> dict | None:
|
|
||||||
"""
|
|
||||||
Silently logs agent data to the Swarms database with retry logic.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
data_dict (dict): The dictionary containing the agent data to be logged.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
dict | None: The JSON response from the server if successful, otherwise None.
|
|
||||||
"""
|
|
||||||
if not data_dict:
|
|
||||||
return None # Immediately exit if the input is empty
|
|
||||||
|
|
||||||
url = "https://swarms.world/api/get-agents/log-agents"
|
|
||||||
headers = {
|
|
||||||
"Content-Type": "application/json",
|
|
||||||
"Authorization": os.getenv("SWARMS_API_KEY"),
|
|
||||||
}
|
|
||||||
|
|
||||||
try:
|
|
||||||
response = requests.post(
|
|
||||||
url, json=data_dict, headers=headers, timeout=10
|
|
||||||
)
|
|
||||||
if (
|
|
||||||
response.ok and response.text.strip()
|
|
||||||
): # Check if response is valid and non-empty
|
|
||||||
return (
|
|
||||||
response.json()
|
|
||||||
) # Parse and return the JSON response
|
|
||||||
except (
|
|
||||||
requests.exceptions.RequestException,
|
|
||||||
requests.exceptions.JSONDecodeError,
|
|
||||||
):
|
|
||||||
pass # Fail silently without any action
|
|
||||||
|
|
||||||
return None # Return None if anything goes wrong
|
|
||||||
@ -0,0 +1,304 @@
|
|||||||
|
import hashlib
|
||||||
|
import os
|
||||||
|
import platform
|
||||||
|
import socket
|
||||||
|
import subprocess
|
||||||
|
import uuid
|
||||||
|
from typing import Dict
|
||||||
|
|
||||||
|
import pkg_resources
|
||||||
|
import psutil
|
||||||
|
import requests
|
||||||
|
import toml
|
||||||
|
|
||||||
|
from swarms.utils.loguru_logger import initialize_logger
|
||||||
|
|
||||||
|
logger = initialize_logger(log_folder="capture_sys_data")
|
||||||
|
|
||||||
|
|
||||||
|
# Helper functions
|
||||||
|
def generate_user_id():
|
||||||
|
"""Generate user id
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
_type_: _description_
|
||||||
|
"""
|
||||||
|
return str(uuid.uuid4())
|
||||||
|
|
||||||
|
|
||||||
|
def get_machine_id():
|
||||||
|
"""Get machine id
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
_type_: _description_
|
||||||
|
"""
|
||||||
|
raw_id = platform.node()
|
||||||
|
hashed_id = hashlib.sha256(raw_id.encode()).hexdigest()
|
||||||
|
return hashed_id
|
||||||
|
|
||||||
|
|
||||||
|
def get_system_info():
|
||||||
|
"""
|
||||||
|
Gathers basic system information.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
dict: A dictionary containing system-related information.
|
||||||
|
"""
|
||||||
|
info = {
|
||||||
|
"platform": platform.system(),
|
||||||
|
"platform_release": platform.release(),
|
||||||
|
"platform_version": platform.version(),
|
||||||
|
"architecture": platform.machine(),
|
||||||
|
"hostname": socket.gethostname(),
|
||||||
|
"ip_address": socket.gethostbyname(socket.gethostname()),
|
||||||
|
"mac_address": ":".join(
|
||||||
|
[
|
||||||
|
f"{(uuid.getnode() >> elements) & 0xFF:02x}"
|
||||||
|
for elements in range(0, 2 * 6, 8)
|
||||||
|
][::-1]
|
||||||
|
),
|
||||||
|
"processor": platform.processor(),
|
||||||
|
"python_version": platform.python_version(),
|
||||||
|
"Misc": system_info(),
|
||||||
|
}
|
||||||
|
return info
|
||||||
|
|
||||||
|
|
||||||
|
def generate_unique_identifier():
|
||||||
|
"""Generate unique identifier
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: unique id
|
||||||
|
|
||||||
|
"""
|
||||||
|
system_info = get_system_info()
|
||||||
|
unique_id = uuid.uuid5(uuid.NAMESPACE_DNS, str(system_info))
|
||||||
|
return str(unique_id)
|
||||||
|
|
||||||
|
|
||||||
|
def get_local_ip():
|
||||||
|
"""Get local ip
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: local ip
|
||||||
|
|
||||||
|
"""
|
||||||
|
return socket.gethostbyname(socket.gethostname())
|
||||||
|
|
||||||
|
|
||||||
|
def get_user_device_data():
|
||||||
|
data = {
|
||||||
|
"ID": generate_user_id(),
|
||||||
|
"Machine ID": get_machine_id(),
|
||||||
|
"System Info": get_system_info(),
|
||||||
|
"UniqueID": generate_unique_identifier(),
|
||||||
|
}
|
||||||
|
return data
|
||||||
|
|
||||||
|
|
||||||
|
def get_python_version():
|
||||||
|
return platform.python_version()
|
||||||
|
|
||||||
|
|
||||||
|
def get_pip_version() -> str:
|
||||||
|
"""Get pip version
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: The version of pip installed
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
pip_version = (
|
||||||
|
subprocess.check_output(["pip", "--version"])
|
||||||
|
.decode()
|
||||||
|
.split()[1]
|
||||||
|
)
|
||||||
|
except Exception as e:
|
||||||
|
pip_version = str(e)
|
||||||
|
return pip_version
|
||||||
|
|
||||||
|
|
||||||
|
def get_swarms_verison() -> tuple[str, str]:
|
||||||
|
"""Get swarms version from both command line and package
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
tuple[str, str]: A tuple containing (command line version, package version)
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
swarms_verison_cmd = (
|
||||||
|
subprocess.check_output(["swarms", "--version"])
|
||||||
|
.decode()
|
||||||
|
.split()[1]
|
||||||
|
)
|
||||||
|
except Exception as e:
|
||||||
|
swarms_verison_cmd = str(e)
|
||||||
|
swarms_verison_pkg = pkg_resources.get_distribution(
|
||||||
|
"swarms"
|
||||||
|
).version
|
||||||
|
swarms_verison = swarms_verison_cmd, swarms_verison_pkg
|
||||||
|
return swarms_verison
|
||||||
|
|
||||||
|
|
||||||
|
def get_os_version() -> str:
|
||||||
|
"""Get operating system version
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: The operating system version and platform details
|
||||||
|
"""
|
||||||
|
return platform.platform()
|
||||||
|
|
||||||
|
|
||||||
|
def get_cpu_info() -> str:
|
||||||
|
"""Get CPU information
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: The processor information
|
||||||
|
"""
|
||||||
|
return platform.processor()
|
||||||
|
|
||||||
|
|
||||||
|
def get_ram_info() -> str:
|
||||||
|
"""Get RAM information
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: A formatted string containing total, used and free RAM in GB
|
||||||
|
"""
|
||||||
|
vm = psutil.virtual_memory()
|
||||||
|
used_ram_gb = vm.used / (1024**3)
|
||||||
|
free_ram_gb = vm.free / (1024**3)
|
||||||
|
total_ram_gb = vm.total / (1024**3)
|
||||||
|
return (
|
||||||
|
f"{total_ram_gb:.2f} GB, used: {used_ram_gb:.2f}, free:"
|
||||||
|
f" {free_ram_gb:.2f}"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def get_package_mismatches(file_path: str = "pyproject.toml") -> str:
|
||||||
|
"""Get package version mismatches between pyproject.toml and installed packages
|
||||||
|
|
||||||
|
Args:
|
||||||
|
file_path (str, optional): Path to pyproject.toml file. Defaults to "pyproject.toml".
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: A formatted string containing package version mismatches
|
||||||
|
"""
|
||||||
|
with open(file_path) as file:
|
||||||
|
pyproject = toml.load(file)
|
||||||
|
dependencies = pyproject["tool"]["poetry"]["dependencies"]
|
||||||
|
dev_dependencies = pyproject["tool"]["poetry"]["group"]["dev"][
|
||||||
|
"dependencies"
|
||||||
|
]
|
||||||
|
dependencies.update(dev_dependencies)
|
||||||
|
|
||||||
|
installed_packages = {
|
||||||
|
pkg.key: pkg.version for pkg in pkg_resources.working_set
|
||||||
|
}
|
||||||
|
|
||||||
|
mismatches = []
|
||||||
|
for package, version_info in dependencies.items():
|
||||||
|
if isinstance(version_info, dict):
|
||||||
|
version_info = version_info["version"]
|
||||||
|
installed_version = installed_packages.get(package)
|
||||||
|
if installed_version and version_info.startswith("^"):
|
||||||
|
expected_version = version_info[1:]
|
||||||
|
if not installed_version.startswith(expected_version):
|
||||||
|
mismatches.append(
|
||||||
|
f"\t {package}: Mismatch,"
|
||||||
|
f" pyproject.toml={expected_version},"
|
||||||
|
f" pip={installed_version}"
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
mismatches.append(f"\t {package}: Not found in pip list")
|
||||||
|
|
||||||
|
return "\n" + "\n".join(mismatches)
|
||||||
|
|
||||||
|
|
||||||
|
def system_info() -> dict[str, str]:
|
||||||
|
"""Get system information including Python, pip, OS, CPU and RAM details
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
dict[str, str]: A dictionary containing system information
|
||||||
|
"""
|
||||||
|
return {
|
||||||
|
"Python Version": get_python_version(),
|
||||||
|
"Pip Version": get_pip_version(),
|
||||||
|
# "Swarms Version": swarms_verison,
|
||||||
|
"OS Version and Architecture": get_os_version(),
|
||||||
|
"CPU Info": get_cpu_info(),
|
||||||
|
"RAM Info": get_ram_info(),
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def capture_system_data() -> Dict[str, str]:
|
||||||
|
"""
|
||||||
|
Captures extensive system data including platform information, user ID, IP address, CPU count,
|
||||||
|
memory information, and other system details.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
Dict[str, str]: A dictionary containing system data.
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
system_data = {
|
||||||
|
"platform": platform.system(),
|
||||||
|
"platform_version": platform.version(),
|
||||||
|
"platform_release": platform.release(),
|
||||||
|
"hostname": socket.gethostname(),
|
||||||
|
"ip_address": socket.gethostbyname(socket.gethostname()),
|
||||||
|
"cpu_count": psutil.cpu_count(logical=True),
|
||||||
|
"memory_total": f"{psutil.virtual_memory().total / (1024 ** 3):.2f} GB",
|
||||||
|
"memory_available": f"{psutil.virtual_memory().available / (1024 ** 3):.2f} GB",
|
||||||
|
"user_id": str(uuid.uuid4()), # Unique user identifier
|
||||||
|
"machine_type": platform.machine(),
|
||||||
|
"processor": platform.processor(),
|
||||||
|
"architecture": platform.architecture()[0],
|
||||||
|
}
|
||||||
|
|
||||||
|
# Get external IP address
|
||||||
|
try:
|
||||||
|
system_data["external_ip"] = requests.get(
|
||||||
|
"https://api.ipify.org"
|
||||||
|
).text
|
||||||
|
except Exception:
|
||||||
|
system_data["external_ip"] = "N/A"
|
||||||
|
|
||||||
|
return system_data
|
||||||
|
except Exception as e:
|
||||||
|
logger.error("Failed to capture system data: {}", e)
|
||||||
|
return {}
|
||||||
|
|
||||||
|
|
||||||
|
def log_agent_data(data_dict: dict) -> dict | None:
|
||||||
|
"""
|
||||||
|
Silently logs agent data to the Swarms database with retry logic.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
data_dict (dict): The dictionary containing the agent data to be logged.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
dict | None: The JSON response from the server if successful, otherwise None.
|
||||||
|
"""
|
||||||
|
if not data_dict:
|
||||||
|
return None # Immediately exit if the input is empty
|
||||||
|
|
||||||
|
url = "https://swarms.world/api/get-agents/log-agents"
|
||||||
|
headers = {
|
||||||
|
"Content-Type": "application/json",
|
||||||
|
"Authorization": os.getenv("SWARMS_API_KEY"),
|
||||||
|
}
|
||||||
|
|
||||||
|
try:
|
||||||
|
response = requests.post(
|
||||||
|
url, json=data_dict, headers=headers, timeout=10
|
||||||
|
)
|
||||||
|
if (
|
||||||
|
response.ok and response.text.strip()
|
||||||
|
): # Check if response is valid and non-empty
|
||||||
|
return (
|
||||||
|
response.json()
|
||||||
|
) # Parse and return the JSON response
|
||||||
|
except (
|
||||||
|
requests.exceptions.RequestException,
|
||||||
|
requests.exceptions.JSONDecodeError,
|
||||||
|
):
|
||||||
|
pass # Fail silently without any action
|
||||||
|
|
||||||
|
return None # Return None if anything goes wrong
|
||||||
@ -1,138 +0,0 @@
|
|||||||
import platform
|
|
||||||
import subprocess
|
|
||||||
|
|
||||||
import pkg_resources
|
|
||||||
import psutil
|
|
||||||
import toml
|
|
||||||
|
|
||||||
|
|
||||||
def get_python_version():
|
|
||||||
return platform.python_version()
|
|
||||||
|
|
||||||
|
|
||||||
def get_pip_version() -> str:
|
|
||||||
"""Get pip version
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
str: The version of pip installed
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
pip_version = (
|
|
||||||
subprocess.check_output(["pip", "--version"])
|
|
||||||
.decode()
|
|
||||||
.split()[1]
|
|
||||||
)
|
|
||||||
except Exception as e:
|
|
||||||
pip_version = str(e)
|
|
||||||
return pip_version
|
|
||||||
|
|
||||||
|
|
||||||
def get_swarms_verison() -> tuple[str, str]:
|
|
||||||
"""Get swarms version from both command line and package
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
tuple[str, str]: A tuple containing (command line version, package version)
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
swarms_verison_cmd = (
|
|
||||||
subprocess.check_output(["swarms", "--version"])
|
|
||||||
.decode()
|
|
||||||
.split()[1]
|
|
||||||
)
|
|
||||||
except Exception as e:
|
|
||||||
swarms_verison_cmd = str(e)
|
|
||||||
swarms_verison_pkg = pkg_resources.get_distribution(
|
|
||||||
"swarms"
|
|
||||||
).version
|
|
||||||
swarms_verison = swarms_verison_cmd, swarms_verison_pkg
|
|
||||||
return swarms_verison
|
|
||||||
|
|
||||||
|
|
||||||
def get_os_version() -> str:
|
|
||||||
"""Get operating system version
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
str: The operating system version and platform details
|
|
||||||
"""
|
|
||||||
return platform.platform()
|
|
||||||
|
|
||||||
|
|
||||||
def get_cpu_info() -> str:
|
|
||||||
"""Get CPU information
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
str: The processor information
|
|
||||||
"""
|
|
||||||
return platform.processor()
|
|
||||||
|
|
||||||
|
|
||||||
def get_ram_info() -> str:
|
|
||||||
"""Get RAM information
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
str: A formatted string containing total, used and free RAM in GB
|
|
||||||
"""
|
|
||||||
vm = psutil.virtual_memory()
|
|
||||||
used_ram_gb = vm.used / (1024**3)
|
|
||||||
free_ram_gb = vm.free / (1024**3)
|
|
||||||
total_ram_gb = vm.total / (1024**3)
|
|
||||||
return (
|
|
||||||
f"{total_ram_gb:.2f} GB, used: {used_ram_gb:.2f}, free:"
|
|
||||||
f" {free_ram_gb:.2f}"
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def get_package_mismatches(file_path: str = "pyproject.toml") -> str:
|
|
||||||
"""Get package version mismatches between pyproject.toml and installed packages
|
|
||||||
|
|
||||||
Args:
|
|
||||||
file_path (str, optional): Path to pyproject.toml file. Defaults to "pyproject.toml".
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
str: A formatted string containing package version mismatches
|
|
||||||
"""
|
|
||||||
with open(file_path) as file:
|
|
||||||
pyproject = toml.load(file)
|
|
||||||
dependencies = pyproject["tool"]["poetry"]["dependencies"]
|
|
||||||
dev_dependencies = pyproject["tool"]["poetry"]["group"]["dev"][
|
|
||||||
"dependencies"
|
|
||||||
]
|
|
||||||
dependencies.update(dev_dependencies)
|
|
||||||
|
|
||||||
installed_packages = {
|
|
||||||
pkg.key: pkg.version for pkg in pkg_resources.working_set
|
|
||||||
}
|
|
||||||
|
|
||||||
mismatches = []
|
|
||||||
for package, version_info in dependencies.items():
|
|
||||||
if isinstance(version_info, dict):
|
|
||||||
version_info = version_info["version"]
|
|
||||||
installed_version = installed_packages.get(package)
|
|
||||||
if installed_version and version_info.startswith("^"):
|
|
||||||
expected_version = version_info[1:]
|
|
||||||
if not installed_version.startswith(expected_version):
|
|
||||||
mismatches.append(
|
|
||||||
f"\t {package}: Mismatch,"
|
|
||||||
f" pyproject.toml={expected_version},"
|
|
||||||
f" pip={installed_version}"
|
|
||||||
)
|
|
||||||
else:
|
|
||||||
mismatches.append(f"\t {package}: Not found in pip list")
|
|
||||||
|
|
||||||
return "\n" + "\n".join(mismatches)
|
|
||||||
|
|
||||||
|
|
||||||
def system_info() -> dict[str, str]:
|
|
||||||
"""Get system information including Python, pip, OS, CPU and RAM details
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
dict[str, str]: A dictionary containing system information
|
|
||||||
"""
|
|
||||||
return {
|
|
||||||
"Python Version": get_python_version(),
|
|
||||||
"Pip Version": get_pip_version(),
|
|
||||||
# "Swarms Version": swarms_verison,
|
|
||||||
"OS Version and Architecture": get_os_version(),
|
|
||||||
"CPU Info": get_cpu_info(),
|
|
||||||
"RAM Info": get_ram_info(),
|
|
||||||
}
|
|
||||||
@ -1,86 +0,0 @@
|
|||||||
import hashlib
|
|
||||||
import platform
|
|
||||||
import socket
|
|
||||||
import uuid
|
|
||||||
|
|
||||||
from swarms.telemetry.sys_info import system_info
|
|
||||||
|
|
||||||
|
|
||||||
# Helper functions
|
|
||||||
def generate_user_id():
|
|
||||||
"""Generate user id
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
_type_: _description_
|
|
||||||
"""
|
|
||||||
return str(uuid.uuid4())
|
|
||||||
|
|
||||||
|
|
||||||
def get_machine_id():
|
|
||||||
"""Get machine id
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
_type_: _description_
|
|
||||||
"""
|
|
||||||
raw_id = platform.node()
|
|
||||||
hashed_id = hashlib.sha256(raw_id.encode()).hexdigest()
|
|
||||||
return hashed_id
|
|
||||||
|
|
||||||
|
|
||||||
def get_system_info():
|
|
||||||
"""
|
|
||||||
Gathers basic system information.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
dict: A dictionary containing system-related information.
|
|
||||||
"""
|
|
||||||
info = {
|
|
||||||
"platform": platform.system(),
|
|
||||||
"platform_release": platform.release(),
|
|
||||||
"platform_version": platform.version(),
|
|
||||||
"architecture": platform.machine(),
|
|
||||||
"hostname": socket.gethostname(),
|
|
||||||
"ip_address": socket.gethostbyname(socket.gethostname()),
|
|
||||||
"mac_address": ":".join(
|
|
||||||
[
|
|
||||||
f"{(uuid.getnode() >> elements) & 0xFF:02x}"
|
|
||||||
for elements in range(0, 2 * 6, 8)
|
|
||||||
][::-1]
|
|
||||||
),
|
|
||||||
"processor": platform.processor(),
|
|
||||||
"python_version": platform.python_version(),
|
|
||||||
"Misc": system_info(),
|
|
||||||
}
|
|
||||||
return info
|
|
||||||
|
|
||||||
|
|
||||||
def generate_unique_identifier():
|
|
||||||
"""Generate unique identifier
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
str: unique id
|
|
||||||
|
|
||||||
"""
|
|
||||||
system_info = get_system_info()
|
|
||||||
unique_id = uuid.uuid5(uuid.NAMESPACE_DNS, str(system_info))
|
|
||||||
return str(unique_id)
|
|
||||||
|
|
||||||
|
|
||||||
def get_local_ip():
|
|
||||||
"""Get local ip
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
str: local ip
|
|
||||||
|
|
||||||
"""
|
|
||||||
return socket.gethostbyname(socket.gethostname())
|
|
||||||
|
|
||||||
|
|
||||||
def get_user_device_data():
|
|
||||||
data = {
|
|
||||||
"ID": generate_user_id(),
|
|
||||||
"Machine ID": get_machine_id(),
|
|
||||||
"System Info": get_system_info(),
|
|
||||||
"UniqueID": generate_unique_identifier(),
|
|
||||||
}
|
|
||||||
return data
|
|
||||||
@ -1,106 +0,0 @@
|
|||||||
# In order to accelerate the ops of creating files, we use the async file creation method.
|
|
||||||
import os
|
|
||||||
import asyncio
|
|
||||||
from aiofiles import open as aio_open
|
|
||||||
from typing import List
|
|
||||||
|
|
||||||
|
|
||||||
async def async_create_file(file_path: str, content: str) -> None:
|
|
||||||
"""
|
|
||||||
Asynchronously creates a file at the specified path and writes the given content to it.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
file_path (str): The path where the file will be created.
|
|
||||||
content (str): The content to be written to the file.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
None
|
|
||||||
"""
|
|
||||||
async with aio_open(file_path, "w") as file:
|
|
||||||
await file.write(content)
|
|
||||||
|
|
||||||
|
|
||||||
async def create_multiple_files(
|
|
||||||
file_paths: List[str], contents: List[str]
|
|
||||||
) -> None:
|
|
||||||
"""
|
|
||||||
Asynchronously creates multiple files at the specified paths and writes the corresponding content to each file.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
file_paths (List[str]): A list of paths where the files will be created.
|
|
||||||
contents (List[str]): A list of content to be written to each file, corresponding to the file paths.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
None
|
|
||||||
"""
|
|
||||||
tasks = [
|
|
||||||
async_create_file(file_path, content)
|
|
||||||
for file_path, content in zip(file_paths, contents)
|
|
||||||
]
|
|
||||||
await asyncio.gather(*tasks)
|
|
||||||
|
|
||||||
|
|
||||||
async def create_file_with_directory(
|
|
||||||
file_path: str, content: str
|
|
||||||
) -> None:
|
|
||||||
"""
|
|
||||||
Creates a file with the specified directory path and content. If the directory does not exist, it is created.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
file_path (str): The path of the file to be created, including the directory.
|
|
||||||
content (str): The content to be written to the file.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
None
|
|
||||||
"""
|
|
||||||
directory = os.path.dirname(file_path)
|
|
||||||
if not os.path.exists(directory):
|
|
||||||
os.makedirs(directory)
|
|
||||||
|
|
||||||
await async_create_file(file_path, content)
|
|
||||||
|
|
||||||
|
|
||||||
def sync_create_file(file_path: str, content: str) -> None:
|
|
||||||
"""
|
|
||||||
Synchronously creates a file at the specified path and writes the given content to it.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
file_path (str): The path where the file will be created.
|
|
||||||
content (str): The content to be written to the file.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
None
|
|
||||||
"""
|
|
||||||
asyncio.run(async_create_file(file_path, content))
|
|
||||||
|
|
||||||
|
|
||||||
def sync_create_multiple_files(
|
|
||||||
file_paths: List[str], contents: List[str]
|
|
||||||
) -> None:
|
|
||||||
"""
|
|
||||||
Synchronously creates multiple files at the specified paths and writes the corresponding content to each file.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
file_paths (List[str]): A list of paths where the files will be created.
|
|
||||||
contents (List[str]): A list of content to be written to each file, corresponding to the file paths.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
None
|
|
||||||
"""
|
|
||||||
asyncio.run(create_multiple_files(file_paths, contents))
|
|
||||||
|
|
||||||
|
|
||||||
def sync_create_file_with_directory(
|
|
||||||
file_path: str, content: str
|
|
||||||
) -> None:
|
|
||||||
"""
|
|
||||||
Synchronously creates a file with the specified directory path and content. If the directory does not exist, it is created.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
file_path (str): The path of the file to be created, including the directory.
|
|
||||||
content (str): The content to be written to the file.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
None
|
|
||||||
"""
|
|
||||||
asyncio.run(create_file_with_directory(file_path, content))
|
|
||||||
@ -1,36 +0,0 @@
|
|||||||
import inspect
|
|
||||||
|
|
||||||
|
|
||||||
def print_class_parameters(cls, api_format: bool = False):
|
|
||||||
"""
|
|
||||||
Print the parameters of a class constructor.
|
|
||||||
|
|
||||||
Parameters:
|
|
||||||
cls (type): The class to inspect.
|
|
||||||
|
|
||||||
Example:
|
|
||||||
>>> print_class_parameters(Agent)
|
|
||||||
Parameter: x, Type: <class 'int'>
|
|
||||||
Parameter: y, Type: <class 'int'>
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
# Get the parameters of the class constructor
|
|
||||||
sig = inspect.signature(cls.__init__)
|
|
||||||
params = sig.parameters
|
|
||||||
|
|
||||||
if api_format:
|
|
||||||
param_dict = {}
|
|
||||||
for name, param in params.items():
|
|
||||||
if name == "self":
|
|
||||||
continue
|
|
||||||
param_dict[name] = str(param.annotation)
|
|
||||||
return param_dict
|
|
||||||
|
|
||||||
# Print the parameters
|
|
||||||
for name, param in params.items():
|
|
||||||
if name == "self":
|
|
||||||
continue
|
|
||||||
print(f"Parameter: {name}, Type: {param.annotation}")
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
print(f"An error occurred while inspecting the class: {e}")
|
|
||||||
@ -1,53 +0,0 @@
|
|||||||
import concurrent.futures
|
|
||||||
from typing import List, Union
|
|
||||||
from swarms.structs.agent import Agent
|
|
||||||
|
|
||||||
|
|
||||||
def update_system_prompts(
|
|
||||||
agents: List[Union[Agent, str]],
|
|
||||||
prompt: str,
|
|
||||||
) -> List[Agent]:
|
|
||||||
"""
|
|
||||||
Update system prompts for a list of agents concurrently.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
agents: List of Agent objects or strings to update
|
|
||||||
prompt: The prompt text to append to each agent's system prompt
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
List of updated Agent objects
|
|
||||||
"""
|
|
||||||
if not agents:
|
|
||||||
return agents
|
|
||||||
|
|
||||||
def update_agent_prompt(agent: Union[Agent, str]) -> Agent:
|
|
||||||
# Convert string to Agent if needed
|
|
||||||
if isinstance(agent, str):
|
|
||||||
agent = Agent(
|
|
||||||
agent_name=agent,
|
|
||||||
system_prompt=prompt, # Initialize with the provided prompt
|
|
||||||
)
|
|
||||||
else:
|
|
||||||
# Preserve existing prompt and append new one
|
|
||||||
existing_prompt = (
|
|
||||||
agent.system_prompt if agent.system_prompt else ""
|
|
||||||
)
|
|
||||||
agent.system_prompt = existing_prompt + "\n" + prompt
|
|
||||||
return agent
|
|
||||||
|
|
||||||
# Use ThreadPoolExecutor for concurrent execution
|
|
||||||
max_workers = min(len(agents), 4) # Reasonable thread count
|
|
||||||
with concurrent.futures.ThreadPoolExecutor(
|
|
||||||
max_workers=max_workers
|
|
||||||
) as executor:
|
|
||||||
futures = []
|
|
||||||
for agent in agents:
|
|
||||||
future = executor.submit(update_agent_prompt, agent)
|
|
||||||
futures.append(future)
|
|
||||||
|
|
||||||
# Collect results as they complete
|
|
||||||
updated_agents = []
|
|
||||||
for future in concurrent.futures.as_completed(futures):
|
|
||||||
updated_agents.append(future.result())
|
|
||||||
|
|
||||||
return updated_agents
|
|
||||||
Loading…
Reference in new issue