Merge branch 'main' of github.com:crewAIInc/crewAI into knowledge

README.md

@@ -100,7 +100,7 @@ You can now start developing your crew by editing the files in the `src/my_proje
 
 #### Example of a simple crew with a sequential process:
 
-Instantiate your crew:
+Instatiate your crew:
 
 ```shell
 crewai create crew latest-ai-development
@@ -399,7 +399,7 @@ Data collected includes:
 - Roles of agents in a crew
   - Understand high level use cases so we can build better tools, integrations and examples about it
 - Tools names available
-  - Understand out of the publicly available tools, which ones are being used the most so we can improve them
+  - Understand out of the publically available tools, which ones are being used the most so we can improve them
 
 Users can opt-in to Further Telemetry, sharing the complete telemetry data by setting the `share_crew` attribute to `True` on their Crews. Enabling `share_crew` results in the collection of detailed crew and task execution data, including `goal`, `backstory`, `context`, and `output` of tasks. This enables a deeper insight into usage patterns while respecting the user's choice to share.
 

docs/concepts/llms.mdx

@@ -310,8 +310,8 @@ These are examples of how to configure LLMs for your agent.
     from crewai import LLM
 
     llm = LLM(
-        model="llama-3.1-sonar-large-128k-online",
-        base_url="https://api.perplexity.ai/",
+        model="perplexity/mistral-7b-instruct",
+        base_url="https://api.perplexity.ai/v1",
         api_key="your-api-key-here"
     )
     agent = Agent(llm=llm, ...)
@@ -400,4 +400,4 @@ This is particularly useful when working with OpenAI-compatible APIs or when you
 - **API Errors**: Check your API key, network connection, and rate limits.
 - **Unexpected Outputs**: Refine your prompts and adjust temperature or top_p.
 - **Performance Issues**: Consider using a more powerful model or optimizing your queries.
-- **Timeout Errors**: Increase the `timeout` parameter or optimize your input.
+- **Timeout Errors**: Increase the `timeout` parameter or optimize your input.

src/crewai/llm.py

@@ -1,6 +1,6 @@
+import io
 import logging
 import sys
-import threading
 import warnings
 from contextlib import contextmanager
 from typing import Any, Dict, List, Optional, Union
@@ -13,25 +13,16 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
 )
 
 
-class FilteredStream:
-    def __init__(self, original_stream):
-        self._original_stream = original_stream
-        self._lock = threading.Lock()
-
-    def write(self, s) -> int:
-        with self._lock:
-            if (
-                "Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new"
-                in s
-                or "LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True`"
-                in s
-            ):
-                return 0
-            return self._original_stream.write(s)
-
-    def flush(self):
-        with self._lock:
-            return self._original_stream.flush()
+class FilteredStream(io.StringIO):
+    def write(self, s):
+        if (
+            "Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new"
+            in s
+            or "LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True`"
+            in s
+        ):
+            return
+        super().write(s)
 
 
 LLM_CONTEXT_WINDOW_SIZES = {
@@ -69,8 +60,8 @@ def suppress_warnings():
         # Redirect stdout and stderr
         old_stdout = sys.stdout
         old_stderr = sys.stderr
-        sys.stdout = FilteredStream(old_stdout)
-        sys.stderr = FilteredStream(old_stderr)
+        sys.stdout = FilteredStream()
+        sys.stderr = FilteredStream()
 
         try:
             yield

src/crewai/task.py

@@ -20,10 +20,10 @@ from pydantic import (
 from pydantic_core import PydanticCustomError
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.tools.base_tool import BaseTool
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry.telemetry import Telemetry
-from crewai.tools.base_tool import BaseTool
 from crewai.utilities.config import process_config
 from crewai.utilities.converter import Converter, convert_to_model
 from crewai.utilities.i18n import I18N
@@ -208,9 +208,7 @@ class Task(BaseModel):
         """Execute the task asynchronously."""
         future: Future[TaskOutput] = Future()
         threading.Thread(
-            daemon=True,
-            target=self._execute_task_async,
-            args=(agent, context, tools, future),
+            target=self._execute_task_async, args=(agent, context, tools, future)
         ).start()
         return future
 
@@ -279,9 +277,7 @@ class Task(BaseModel):
             content = (
                 json_output
                 if json_output
-                else pydantic_output.model_dump_json()
-                if pydantic_output
-                else result
+                else pydantic_output.model_dump_json() if pydantic_output else result
             )
             self._save_file(content)