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logs and fix merge request

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Brandon Hancock
2024-10-11 10:36:39 -04:00
parent 8c83379cb9
commit 774bc9ea75
3 changed files with 26 additions and 20 deletions
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41
docs/concepts/collaboration.mdx
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@@ -4,7 +4,7 @@ description: Exploring the dynamics of agent collaboration within the CrewAI fra
icon: screen-users
---
## Collaboration Fundamentals
## Collaboration Fundamentals
Collaboration in CrewAI is fundamental, enabling agents to combine their skills, share information, and assist each other in task execution, embodying a truly cooperative ecosystem.
@@ -16,24 +16,25 @@ Collaboration in CrewAI is fundamental, enabling agents to combine their skills,
The `Crew` class has been enriched with several attributes to support advanced functionalities:
| Feature | Description |
|:-------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **Language Model Management** (`manager_llm`, `function_calling_llm`) | Manages language models for executing tasks and tools. `manager_llm` is required for hierarchical processes, while `function_calling_llm` is optional with a default value for streamlined interactions. |
| **Custom Manager Agent** (`manager_agent`) | Specifies a custom agent as the manager, replacing the default CrewAI manager. |
| **Process Flow** (`process`) | Defines execution logic (e.g., sequential, hierarchical) for task distribution. |
| **Verbose Logging** (`verbose`) | Provides detailed logging for monitoring and debugging. Accepts integer and boolean values to control verbosity level. |
| **Rate Limiting** (`max_rpm`) | Limits requests per minute to optimize resource usage. Setting guidelines depend on task complexity and load. |
| **Internationalization / Customization** (`language`, `prompt_file`) | Supports prompt customization for global usability. [Example of file](https://github.com/joaomdmoura/crewAI/blob/main/src/crewai/translations/en.json) |
| **Execution and Output Handling** (`full_output`) | Controls output granularity, distinguishing between full and final outputs. |
| **Callback and Telemetry** (`step_callback`, `task_callback`) | Enables step-wise and task-level execution monitoring and telemetry for performance analytics. |
| **Crew Sharing** (`share_crew`) | Allows sharing crew data with CrewAI for model improvement. Privacy implications and benefits should be considered. |
| **Usage Metrics** (`usage_metrics`) | Logs all LLM usage metrics during task execution for performance insights. |
| **Memory Usage** (`memory`) | Enables memory for storing execution history, aiding in agent learning and task efficiency. |
| **Embedder Configuration** (`embedder`) | Configures the embedder for language understanding and generation, with support for provider customization. |
| **Cache Management** (`cache`) | Specifies whether to cache tool execution results, enhancing performance. |
| **Output Logging** (`output_log_file`) | Defines the file path for logging crew execution output. |
| **Planning Mode** (`planning`) | Enables action planning before task execution. Set `planning=True` to activate. |
| **Replay Feature** (`replay`) | Provides CLI for listing tasks from the last run and replaying from specific tasks, aiding in task management and troubleshooting. |
| Feature | Description |
| :-------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Language Model Management** (`manager_llm`, `function_calling_llm`) | Manages language models for executing tasks and tools. `manager_llm` is required for hierarchical processes, while `function_calling_llm` is optional with a default value for streamlined interactions. |
| **Custom Manager Agent** (`manager_agent`) | Specifies a custom agent as the manager, replacing the default CrewAI manager. |
| **Process Flow** (`process`) | Defines execution logic (e.g., sequential, hierarchical) for task distribution. |
| **Verbose Logging** (`verbose`) | Provides detailed logging for monitoring and debugging. Accepts integer and boolean values to control verbosity level. |
| **Rate Limiting** (`max_rpm`) | Limits requests per minute to optimize resource usage. Setting guidelines depend on task complexity and load. |
| **Internationalization / Customization** (`language`, `prompt_file`) | Supports prompt customization for global usability. [Example of file](https://github.com/joaomdmoura/crewAI/blob/main/src/crewai/translations/en.json) |
| **Execution and Output Handling** (`full_output`) | Controls output granularity, distinguishing between full and final outputs. |
| **Callback and Telemetry** (`step_callback`, `task_callback`) | Enables step-wise and task-level execution monitoring and telemetry for performance analytics. |
| **Crew Sharing** (`share_crew`) | Allows sharing crew data with CrewAI for model improvement. Privacy implications and benefits should be considered. |
| **Usage Metrics** (`usage_metrics`) | Logs all LLM usage metrics during task execution for performance insights. |
| **Memory Usage** (`memory`) | Enables memory for storing execution history, aiding in agent learning and task efficiency. |
| **Memory Provider** (`memory_provider`) | Specifies the memory provider to be used by the crew for storing memories. |
| **Embedder Configuration** (`embedder`) | Configures the embedder for language understanding and generation, with support for provider customization. |
| **Cache Management** (`cache`) | Specifies whether to cache tool execution results, enhancing performance. |
| **Output Logging** (`output_log_file`) | Defines the file path for logging crew execution output. |
| **Planning Mode** (`planning`) | Enables action planning before task execution. Set `planning=True` to activate. |
| **Replay Feature** (`replay`) | Provides CLI for listing tasks from the last run and replaying from specific tasks, aiding in task management and troubleshooting. |
## Delegation (Dividing to Conquer)
@@ -49,4 +50,4 @@ Consider a crew with a researcher agent tasked with data gathering and a writer
## Conclusion
The integration of advanced attributes and functionalities into the CrewAI framework significantly enriches the agent collaboration ecosystem. These enhancements not only simplify interactions but also offer unprecedented flexibility and control, paving the way for sophisticated AI-driven solutions capable of tackling complex tasks through intelligent collaboration and delegation.
The integration of advanced attributes and functionalities into the CrewAI framework significantly enriches the agent collaboration ecosystem. These enhancements not only simplify interactions but also offer unprecedented flexibility and control, paving the way for sophisticated AI-driven solutions capable of tackling complex tasks through intelligent collaboration and delegation.

2
src/crewai/agent.py
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@@ -201,6 +201,8 @@ class Agent(BaseAgent):
task_prompt = task.prompt()
print("context for task", context)
if context:
task_prompt = self.i18n.slice("task_with_context").format(
task=task_prompt, context=context

3
src/crewai/memory/contextual/contextual_memory.py
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@@ -82,8 +82,11 @@ class ContextualMemory:
"""
Fetches relevant user memory information from User Memory related to the task's description and expected_output,
"""
print("query", query)
um_results = self.um.search(query)
print("um_results", um_results)
formatted_results = "\n".join(
[f"- {result['memory']}" for result in um_results]
)
print(f"User memories/preferences:\n{formatted_results}")
return f"User memories/preferences:\n{formatted_results}" if um_results else ""