Adding support for translations (crewAIInc#120)

Add translations support

src/crewai/agent.py

@@ -23,6 +23,7 @@
  CrewAgentOutputParser,
  ToolsHandler,
 )
+from crewai.i18n import I18N
 from crewai.prompts import Prompts
 
 
@@ -54,13 +55,6 @@ class Agent(BaseModel):
  role: str = Field(description="Role of the agent")
  goal: str = Field(description="Objective of the agent")
  backstory: str = Field(description="Backstory of the agent")
- llm: Optional[Any] = Field(
- default_factory=lambda: ChatOpenAI(
- temperature=0.7,
- model_name="gpt-4",
- ),
- description="Language model that will run the agent.",
- )
  memory: bool = Field(
  default=True, description="Whether the agent should have memory or not"
  )
@@ -85,6 +79,16 @@ class Agent(BaseModel):
  cache_handler: Optional[InstanceOf[CacheHandler]] = Field(
  default=CacheHandler(), description="An instance of the CacheHandler class."
  )
+ i18n: Optional[I18N] = Field(
+ default=I18N(), description="Internationalization settings."
+ )
+ llm: Optional[Any] = Field(
+ default_factory=lambda: ChatOpenAI(
+ temperature=0.7,
+ model_name="gpt-4",
+ ),
+ description="Language model that will run the agent.",
+ )
 
  @field_validator("id", mode="before")
  @classmethod
@@ -114,8 +118,8 @@ def execute_task(
  Output of the agent
  """
  if context:
- task = "\n".join(
- [task, "\nThis is the context you are working with:", context]
+ task = self.i18n.slice("task_with_context").format(
+ task=task, context=context
  )
 
  tools = tools or self.tools
@@ -148,6 +152,7 @@ def __create_agent_executor(self) -> CrewAgentExecutor:
  "agent_scratchpad": lambda x: format_log_to_str(x["intermediate_steps"]),
  }
  executor_args = {
+ "i18n": self.i18n,
  "tools": self.tools,
  "verbose": self.verbose,
  "handle_parsing_errors": True,
@@ -160,23 +165,25 @@ def __create_agent_executor(self) -> CrewAgentExecutor:
  )
  executor_args["memory"] = summary_memory
  agent_args["chat_history"] = lambda x: x["chat_history"]
- prompt = Prompts().task_execution_with_memory()
+ prompt = Prompts(i18n=self.i18n).task_execution_with_memory()
  else:
- prompt = Prompts().task_execution()
+ prompt = Prompts(i18n=self.i18n).task_execution()
 
  execution_prompt = prompt.partial(
  goal=self.goal,
  role=self.role,
  backstory=self.backstory,
  )
 
- bind = self.llm.bind(stop=["\nObservation"])
+ bind = self.llm.bind(stop=[self.i18n.slice("observation")])
  inner_agent = (
  agent_args
  | execution_prompt
  | bind
  | CrewAgentOutputParser(
- tools_handler=self.tools_handler, cache=self.cache_handler
+ tools_handler=self.tools_handler,
+ cache=self.cache_handler,
+ i18n=self.i18n,
  )
  )
  self.agent_executor = CrewAgentExecutor(agent=inner_agent, **executor_args)

src/crewai/agents/exceptions.py

@@ -1,17 +1,23 @@
 from langchain_core.exceptions import OutputParserException
 
+from crewai.i18n import I18N
+
 
 class TaskRepeatedUsageException(OutputParserException):
  """Exception raised when a task is used twice in a roll."""
 
+ i18n: I18N = I18N()
  error: str = "TaskRepeatedUsageException"
- message: str = "I just used the {tool} tool with input {tool_input}. So I already know the result of that and don't need to use it now.\n"
+ message: str
 
- def __init__(self, tool: str, tool_input: str, text: str):
+ def __init__(self, i18n: I18N, tool: str, tool_input: str, text: str):
+ self.i18n = i18n
  self.text = text
  self.tool = tool
  self.tool_input = tool_input
- self.message = self.message.format(tool=tool, tool_input=tool_input)
+ self.message = self.i18n.errors("task_repeated_usage").format(
+ tool=tool, tool_input=tool_input
+ )
 
  super().__init__(
  error=self.error,

src/crewai/agents/executor.py

@@ -1,5 +1,4 @@
 import time
-from textwrap import dedent
 from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
 
 from langchain.agents import AgentExecutor
@@ -12,11 +11,13 @@
 from langchain_core.tools import BaseTool
 from langchain_core.utils.input import get_color_mapping
 
-from ..tools.cache_tools import CacheTools
-from .cache.cache_hit import CacheHit
+from crewai.agents.cache.cache_hit import CacheHit
+from crewai.i18n import I18N
+from crewai.tools.cache_tools import CacheTools
 
 
 class CrewAgentExecutor(AgentExecutor):
+ i18n: I18N = I18N()
  iterations: int = 0
  max_iterations: Optional[int] = 15
  force_answer_max_iterations: Optional[int] = None
@@ -31,13 +32,7 @@ def _should_force_answer(self) -> bool:
 
  def _force_answer(self, output: AgentAction):
  return AgentStep(
- action=output,
- observation=dedent(
- """\
- I've used too many tools for this task.
- I'm going to give you my absolute BEST Final answer now and
- not use any more tools."""
- ),
+ action=output, observation=self.i18n.errors("used_too_many_tools")
  )
 
  def _call(

src/crewai/agents/output_parser.py

@@ -4,9 +4,10 @@
 from langchain.agents.output_parsers import ReActSingleInputOutputParser
 from langchain_core.agents import AgentAction, AgentFinish
 
-from .cache import CacheHandler, CacheHit
-from .exceptions import TaskRepeatedUsageException
-from .tools_handler import ToolsHandler
+from crewai.agents.cache import CacheHandler, CacheHit
+from crewai.agents.exceptions import TaskRepeatedUsageException
+from crewai.agents.tools_handler import ToolsHandler
+from crewai.i18n import I18N
 
 FINAL_ANSWER_ACTION = "Final Answer:"
 FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE = (
@@ -46,6 +47,7 @@ class Config:
 
  tools_handler: ToolsHandler
  cache: CacheHandler
+ i18n: I18N
 
  def parse(self, text: str) -> Union[AgentAction, AgentFinish, CacheHit]:
  FINAL_ANSWER_ACTION in text
@@ -65,10 +67,13 @@ def parse(self, text: str) -> Union[AgentAction, AgentFinish, CacheHit]:
  }
  if usage == last_tool_usage:
  raise TaskRepeatedUsageException(
- tool=action, tool_input=tool_input, text=text
+ text=text,
+ tool=action,
+ tool_input=tool_input,
+ i18n=self.i18n,
  )
 
- if result := self.cache.read(action, tool_input):
+ if self.cache.read(action, tool_input):
  action = AgentAction(action, tool_input, text)
  return CacheHit(action=action, cache=self.cache)
 

src/crewai/crew.py

@@ -16,6 +16,7 @@
 
 from crewai.agent import Agent
 from crewai.agents.cache import CacheHandler
+from crewai.i18n import I18N
 from crewai.process import Process
 from crewai.task import Task
 from crewai.tools.agent_tools import AgentTools
@@ -44,6 +45,10 @@ class Crew(BaseModel):
  config: Optional[Union[Json, Dict[str, Any]]] = Field(default=None)
  cache_handler: Optional[InstanceOf[CacheHandler]] = Field(default=CacheHandler())
  id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
+ language: str = Field(
+ default="en",
+ description="Language used for the crew, defaults to English.",
+ )
 
  @field_validator("id", mode="before")
  @classmethod
@@ -99,6 +104,7 @@ def kickoff(self) -> str:
  """Starts the crew to work on its assigned tasks."""
  for agent in self.agents:
  agent.cache_handler = self.cache_handler
+ agent.i18n = I18N(language=self.language)
 
  if self.process == Process.sequential:
  return self._sequential_loop()

src/crewai/i18n.py

@@ -0,0 +1,45 @@
+import json
+import os
+from typing import Dict, Optional
+
+from pydantic import BaseModel, Field, PrivateAttr, ValidationError, model_validator
+
+
+class I18N(BaseModel):
+ _translations: Optional[Dict[str, str]] = PrivateAttr()
+ language: Optional[str] = Field(
+ default="en",
+ description="Language used to load translations",
+ )
+
+ @model_validator(mode="after")
+ def load_translation(self) -> "I18N":
+ """Load translations from a JSON file based on the specified language."""
+ try:
+ dir_path = os.path.dirname(os.path.realpath(__file__))
+ prompts_path = os.path.join(dir_path, f"translations/{self.language}.json")
+
+ with open(prompts_path, "r") as f:
+ self._translations = json.load(f)
+ except FileNotFoundError:
+ raise ValidationError(
+ f"Trasnlation file for language '{self.language}' not found."
+ )
+ except json.JSONDecodeError:
+ raise ValidationError(f"Error decoding JSON from the prompts file.")
+ return self
+
+ def slice(self, slice: str) -> str:
+ return self.retrieve("slices", slice)
+
+ def errors(self, error: str) -> str:
+ return self.retrieve("errors", error)
+
+ def tools(self, error: str) -> str:
+ return self.retrieve("tools", error)
+
+ def retrieve(self, kind, key):
+ try:
+ return self._translations[kind].get(key)
+ except:
+ raise ValidationError(f"Translation for '{kind}':'{key}' not found.")

src/crewai/prompts.py

@@ -1,36 +1,15 @@
-import json
-import os
-from typing import ClassVar, Dict, Optional
+from typing import ClassVar
 
 from langchain.prompts import PromptTemplate
-from pydantic import BaseModel, Field, PrivateAttr, ValidationError, model_validator
+from pydantic import BaseModel, Field
+
+from .i18n import I18N
 
 
 class Prompts(BaseModel):
  """Manages and generates prompts for a generic agent with support for different languages."""
 
- _prompts: Optional[Dict[str, str]] = PrivateAttr()
- language: Optional[str] = Field(
- default="en",
- description="Language of the prompts.",
- )
-
- @model_validator(mode="after")
- def load_prompts(self) -> "Prompts":
- """Load prompts from a JSON file based on the specified language."""
- try:
- dir_path = os.path.dirname(os.path.realpath(__file__))
- prompts_path = os.path.join(dir_path, f"prompts/{self.language}.json")
-
- with open(prompts_path, "r") as f:
- self._prompts = json.load(f)["slices"]
- except FileNotFoundError:
- raise ValidationError(
- f"Prompt file for language '{self.language}' not found."
- )
- except json.JSONDecodeError:
- raise ValidationError(f"Error decoding JSON from the prompts file.")
- return self
+ i18n: I18N = Field(default=I18N())
 
  SCRATCHPAD_SLICE: ClassVar[str] = "\n{agent_scratchpad}"
 
@@ -48,10 +27,6 @@ def task_execution(self) -> str:
 
  def _build_prompt(self, components: [str]) -> str:
  """Constructs a prompt string from specified components."""
- prompt_parts = [
- self._prompts[component]
- for component in components
- if component in self._prompts
- ]
+ prompt_parts = [self.i18n.slice(component) for component in components]
  prompt_parts.append(self.SCRATCHPAD_SLICE)
  return PromptTemplate.from_template("".join(prompt_parts))