add in 2 small improvements based on joao feedback

Added missing quotes around os.environ

Co-authored-by: Eduardo Chiarotti <dudumelgaco@hotmail.com>

docs/core-concepts/Pipeline.md

@@ -32,8 +32,8 @@ Each input creates its own run, flowing through all stages of the pipeline. Mult
 
 ## Pipeline Attributes
 
-| Attribute  | Parameters | Description                                                                           |
-| :--------- | :--------- | :------------------------------------------------------------------------------------ |
+| Attribute  | Parameters | Description                                                                                     |
+| :--------- | :--------- | :---------------------------------------------------------------------------------------------- |
 | **Stages** | `stages`   | A list of crews, lists of crews, or routers representing the stages to be executed in sequence. |
 
 ## Creating a Pipeline
@@ -239,7 +239,7 @@ email_router = Router(
             pipeline=normal_pipeline
         )
     },
-    default=Pipeline(stages=[normal_pipeline])  # Default to just classification if no urgency score
+    default=Pipeline(stages=[normal_pipeline])  # Default to just normal if no urgency score
 )
 
 # Use the router in a main pipeline

docs/how-to/LLM-Connections.md

@@ -112,30 +112,30 @@ Switch between APIs and models seamlessly using environment variables, supportin
 ### Configuration Examples
 #### FastChat
 ```sh
-os.environ[OPENAI_API_BASE]="http://localhost:8001/v1"
-os.environ[OPENAI_MODEL_NAME]='oh-2.5m7b-q51'
-os.environ[OPENAI_API_KEY]=NA
+os.environ["OPENAI_API_BASE"]='http://localhost:8001/v1'
+os.environ["OPENAI_MODEL_NAME"]='oh-2.5m7b-q51'
+os.environ[OPENAI_API_KEY]='NA'
 ```
 
 #### LM Studio
 Launch [LM Studio](https://lmstudio.ai) and go to the Server tab. Then select a model from the dropdown menu and wait for it to load. Once it's loaded, click the green Start Server button and use the URL, port, and API key that's shown (you can modify them). Below is an example of the default settings as of LM Studio 0.2.19:
 ```sh
-os.environ[OPENAI_API_BASE]="http://localhost:1234/v1"
-os.environ[OPENAI_API_KEY]="lm-studio"
+os.environ["OPENAI_API_BASE"]='http://localhost:1234/v1'
+os.environ["OPENAI_API_KEY"]='lm-studio'
 ```
 
 #### Groq API
 ```sh
-os.environ[OPENAI_API_KEY]=your-groq-api-key
-os.environ[OPENAI_MODEL_NAME]='llama3-8b-8192'
-os.environ[OPENAI_API_BASE]=https://api.groq.com/openai/v1
+os.environ["OPENAI_API_KEY"]='your-groq-api-key'
+os.environ["OPENAI_MODEL_NAME"]='llama3-8b-8192'
+os.environ["OPENAI_API_BASE"]='https://api.groq.com/openai/v1'
 ```
 
 #### Mistral API
 ```sh
-os.environ[OPENAI_API_KEY]=your-mistral-api-key
-os.environ[OPENAI_API_BASE]=https://api.mistral.ai/v1
-os.environ[OPENAI_MODEL_NAME]="mistral-small"
+os.environ["OPENAI_API_KEY"]='your-mistral-api-key'
+os.environ["OPENAI_API_BASE"]='https://api.mistral.ai/v1'
+os.environ["OPENAI_MODEL_NAME"]='mistral-small'
 ```
 
 ### Solar
@@ -143,8 +143,8 @@ os.environ[OPENAI_MODEL_NAME]="mistral-small"
 from langchain_community.chat_models.solar import SolarChat
 ```
 ```sh
-os.environ[SOLAR_API_BASE]="https://api.upstage.ai/v1/solar"
-os.environ[SOLAR_API_KEY]="your-solar-api-key"
+os.environ["SOLAR_API_BASE"]='https://api.upstage.ai/v1/solar'
+os.environ["SOLAR_API_KEY"]='your-solar-api-key'
 ```
 
 # Free developer API key available here: https://console.upstage.ai/services/solar
@@ -155,7 +155,7 @@ os.environ[SOLAR_API_KEY]="your-solar-api-key"
 ```python
 from langchain_cohere import ChatCohere
 # Initialize language model
-os.environ["COHERE_API_KEY"] = "your-cohere-api-key"
+os.environ["COHERE_API_KEY"]='your-cohere-api-key'
 llm = ChatCohere()
 
 # Free developer API key available here: https://cohere.com/
@@ -166,10 +166,10 @@ llm = ChatCohere()
 For Azure OpenAI API integration, set the following environment variables:
 ```sh
 
-os.environ[AZURE_OPENAI_DEPLOYMENT] = "Your deployment"
-os.environ["OPENAI_API_VERSION"] = "2023-12-01-preview"
-os.environ["AZURE_OPENAI_ENDPOINT"] = "Your Endpoint"
-os.environ["AZURE_OPENAI_API_KEY"] = "<Your API Key>"
+os.environ["AZURE_OPENAI_DEPLOYMENT"]='Your deployment'
+os.environ["OPENAI_API_VERSION"]='2023-12-01-preview'
+os.environ["AZURE_OPENAI_ENDPOINT"]='Your Endpoint'
+os.environ["AZURE_OPENAI_API_KEY"]='Your API Key'
 ```
 
 ### Example Agent with Azure LLM

src/crewai/__init__.py

@@ -2,6 +2,7 @@ from crewai.agent import Agent
 from crewai.crew import Crew
 from crewai.pipeline import Pipeline
 from crewai.process import Process
+from crewai.routers import Router
 from crewai.task import Task
 
-__all__ = ["Agent", "Crew", "Process", "Task", "Pipeline"]
+__all__ = ["Agent", "Crew", "Process", "Task", "Pipeline", "Router"]

src/crewai/agents/__init__.py

@@ -2,3 +2,5 @@ from .cache.cache_handler import CacheHandler
 from .executor import CrewAgentExecutor
 from .parser import CrewAgentParser
 from .tools_handler import ToolsHandler
+
+__all__ = ["CacheHandler", "CrewAgentExecutor", "CrewAgentParser", "ToolsHandler"]

src/crewai/agents/cache/__init__.py

@@ -1 +1,3 @@
 from .cache_handler import CacheHandler
+
+__all__ = ["CacheHandler"]

src/crewai/crews/__init__.py

@@ -1 +1,3 @@
 from .crew_output import CrewOutput
+
+__all__ = ["CrewOutput"]

src/crewai/memory/__init__.py

@@ -1,3 +1,5 @@
 from .entity.entity_memory import EntityMemory
 from .long_term.long_term_memory import LongTermMemory
 from .short_term.short_term_memory import ShortTermMemory
+
+__all__ = ["EntityMemory", "LongTermMemory", "ShortTermMemory"]

src/crewai/memory/storage/rag_storage.py

@@ -5,13 +5,14 @@ import os
 import shutil
 from typing import Any, Dict, List, Optional
 
-from crewai.memory.storage.interface import Storage
-from crewai.utilities.paths import db_storage_path
 from embedchain import App
 from embedchain.llm.base import BaseLlm
 from embedchain.models.data_type import DataType
 from embedchain.vectordb.chroma import InvalidDimensionException
 
+from crewai.memory.storage.interface import Storage
+from crewai.utilities.paths import db_storage_path
+
 
 @contextlib.contextmanager
 def suppress_logging(
@@ -77,12 +78,12 @@ class RAGStorage(Storage):
         self.app.llm = FakeLLM()
         if allow_reset:
             self.app.reset()
-            
+
     def _sanitize_role(self, role: str) -> str:
         """
         Sanitizes agent roles to ensure valid directory names.
         """
-        return role.replace('\n', '').replace(' ', '_').replace('/', '_')
+        return role.replace("\n", "").replace(" ", "_").replace("/", "_")
 
     def save(self, value: Any, metadata: Dict[str, Any]) -> None:
         self._generate_embedding(value, metadata)

src/crewai/pipeline/__init__.py

@@ -1,3 +1,5 @@
 from crewai.pipeline.pipeline import Pipeline
 from crewai.pipeline.pipeline_kickoff_result import PipelineKickoffResult
 from crewai.pipeline.pipeline_output import PipelineOutput
+
+__all__ = ["Pipeline", "PipelineKickoffResult", "PipelineOutput"]

src/crewai/routers/__init__.py

@@ -1 +1,3 @@
 from crewai.routers.router import Router
+
+__all__ = ["Router"]

src/crewai/task.py

@@ -273,7 +273,9 @@ 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)
 

src/crewai/telemetry/__init__.py

@@ -1 +1,3 @@
 from .telemetry import Telemetry
+
+__all__ = ["Telemetry"]

src/crewai/utilities/parser.py

@@ -1,5 +1,6 @@
 import re
 
+
 class YamlParser:
     @staticmethod
     def parse(file):
@@ -16,7 +17,9 @@ class YamlParser:
 
         # Replace single { and } with doubled ones, while leaving already doubled ones intact and the other special characters {# and {%
         modified_content = re.sub(r"(?<!\{){(?!\{)(?!\#)(?!\%)", "{{", content)
-        modified_content = re.sub(r"(?<!\})(?<!\%)(?<!\#)\}(?!})", "}}", modified_content)
+        modified_content = re.sub(
+            r"(?<!\})(?<!\%)(?<!\#)\}(?!})", "}}", modified_content
+        )
 
         # Check for 'context:' not followed by '[' and raise an error
         if re.search(r"context:(?!\s*\[)", modified_content):

tests/pipeline/test_pipeline.py

@@ -113,7 +113,9 @@ def mock_router_factory(mock_crew_factory):
                 (
                     "route1"
                     if x.get("score", 0) > 80
-                    else "route2" if x.get("score", 0) > 50 else "default"
+                    else "route2"
+                    if x.get("score", 0) > 50
+                    else "default"
                 ),
             )
         )