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docs: update "LLM-Connections" import and "Tasks" formatting (#1345)

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* Update Tasks.md

Current formating of the page Tasks has been broken, fix the markdown formatting.

* Update LLM-Connections.md

LLM class has been moved to llm.py file
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2024-09-24 12:52:41 +08:00
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commit 33695aa2fd
2 changed files with 4 additions and 4 deletions
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docs/core-concepts/Tasks.md
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@@ -1,4 +1,3 @@
```markdown
---
title: crewAI Tasks
description: Detailed guide on managing and creating tasks within the crewAI framework, reflecting the latest codebase updates.
@@ -314,4 +313,4 @@ save_output_task = Task(
## Conclusion
Tasks are the driving force behind the actions of agents in crewAI. By properly defining tasks and their outcomes, you set the stage for your AI agents to work effectively, either independently or as a collaborative unit. Equipping tasks with appropriate tools, understanding the execution process, and following robust validation practices are crucial for maximizing CrewAI's potential, ensuring agents are effectively prepared for their assignments and that tasks are executed as intended.
Tasks are the driving force behind the actions of agents in crewAI. By properly defining tasks and their outcomes, you set the stage for your AI agents to work effectively, either independently or as a collaborative unit. Equipping tasks with appropriate tools, understanding the execution process, and following robust validation practices are crucial for maximizing CrewAI's potential, ensuring agents are effectively prepared for their assignments and that tasks are executed as intended.

5
docs/how-to/LLM-Connections.md
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@@ -66,7 +66,8 @@ claude_agent = Agent(
For more detailed configuration, use the LLM class:
```python
from crewai import Agent, LLM
from crewai import Agent
from crewai.llm import LLM
llm = LLM(
model="gpt-4",
@@ -160,4 +161,4 @@ This is particularly useful when working with OpenAI-compatible APIs or when you
## Conclusion
By leveraging LiteLLM, CrewAI offers seamless integration with a vast array of LLMs. This flexibility allows you to choose the most suitable model for your specific needs, whether you prioritize performance, cost-efficiency, or local deployment. Remember to consult the [LiteLLM documentation](https://docs.litellm.ai/docs/) for the most up-to-date information on supported models and configuration options.
By leveraging LiteLLM, CrewAI offers seamless integration with a vast array of LLMs. This flexibility allows you to choose the most suitable model for your specific needs, whether you prioritize performance, cost-efficiency, or local deployment. Remember to consult the [LiteLLM documentation](https://docs.litellm.ai/docs/) for the most up-to-date information on supported models and configuration options.