mirror of
https://github.com/crewAIInc/crewAI.git
synced 2025-12-31 19:58:30 +00:00
Compare commits
1 Commits
0.117.0
...
lg-update-
| Author | SHA1 | Date | |
|---|---|---|---|
|
ee2c7cd07a |
@@ -180,42 +180,6 @@
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"tab": "Enterprise",
|
||||
"groups": [
|
||||
{
|
||||
"group": "Getting Started",
|
||||
"pages": [
|
||||
"enterprise/introduction"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "How-To Guides",
|
||||
"pages": [
|
||||
"enterprise/guides/build-crew",
|
||||
"enterprise/guides/deploy-crew",
|
||||
"enterprise/guides/kickoff-crew",
|
||||
"enterprise/guides/update-crew",
|
||||
"enterprise/guides/use-crew-api",
|
||||
"enterprise/guides/enable-crew-studio"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Features",
|
||||
"pages": [
|
||||
"enterprise/features/tool-repository",
|
||||
"enterprise/features/webhook-streaming",
|
||||
"enterprise/features/traces"
|
||||
]
|
||||
},
|
||||
{
|
||||
"group": "Resources",
|
||||
"pages": [
|
||||
"enterprise/resources/frequently-asked-questions"
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"tab": "Examples",
|
||||
"groups": [
|
||||
|
||||
@@ -1,106 +0,0 @@
|
||||
---
|
||||
title: Tool Repository
|
||||
description: "Using the Tool Repository to manage your tools"
|
||||
icon: "toolbox"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
The Tool Repository is a package manager for CrewAI tools. It allows users to publish, install, and manage tools that integrate with CrewAI crews and flows.
|
||||
|
||||
Tools can be:
|
||||
|
||||
- **Private**: accessible only within your organization (default)
|
||||
- **Public**: accessible to all CrewAI users if published with the `--public` flag
|
||||
|
||||
The repository is not a version control system. Use Git to track code changes and enable collaboration.
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before using the Tool Repository, ensure you have:
|
||||
|
||||
- A [CrewAI Enterprise](https://app.crewai.com) account
|
||||
- [CrewAI CLI](https://docs.crewai.com/concepts/cli#cli) installed
|
||||
- [Git](https://git-scm.com) installed and configured
|
||||
- Access permissions to publish or install tools in your CrewAI Enterprise organization
|
||||
|
||||
## Installing Tools
|
||||
|
||||
To install a tool:
|
||||
|
||||
```bash
|
||||
crewai tool install <tool-name>
|
||||
```
|
||||
|
||||
This installs the tool and adds it to `pyproject.toml`.
|
||||
|
||||
## Creating and Publishing Tools
|
||||
|
||||
To create a new tool project:
|
||||
|
||||
```bash
|
||||
crewai tool create <tool-name>
|
||||
```
|
||||
|
||||
This generates a scaffolded tool project locally.
|
||||
|
||||
After making changes, initialize a Git repository and commit the code:
|
||||
|
||||
```bash
|
||||
git init
|
||||
git add .
|
||||
git commit -m "Initial version"
|
||||
```
|
||||
|
||||
To publish the tool:
|
||||
|
||||
```bash
|
||||
crewai tool publish
|
||||
```
|
||||
|
||||
By default, tools are published as private. To make a tool public:
|
||||
|
||||
```bash
|
||||
crewai tool publish --public
|
||||
```
|
||||
|
||||
For more details on how to build tools, see [Creating your own tools](https://docs.crewai.com/concepts/tools#creating-your-own-tools).
|
||||
|
||||
## Updating Tools
|
||||
|
||||
To update a published tool:
|
||||
|
||||
1. Modify the tool locally
|
||||
2. Update the version in `pyproject.toml` (e.g., from `0.1.0` to `0.1.1`)
|
||||
3. Commit the changes and publish
|
||||
|
||||
```bash
|
||||
git commit -m "Update version to 0.1.1"
|
||||
crewai tool publish
|
||||
```
|
||||
|
||||
## Deleting Tools
|
||||
|
||||
To delete a tool:
|
||||
|
||||
1. Go to [CrewAI Enterprise](https://app.crewai.com)
|
||||
2. Navigate to **Tools**
|
||||
3. Select the tool
|
||||
4. Click **Delete**
|
||||
|
||||
<Warning>
|
||||
Deletion is permanent. Deleted tools cannot be restored or re-installed.
|
||||
</Warning>
|
||||
|
||||
## Security Checks
|
||||
|
||||
Every published version undergoes automated security checks, and are only available to install after they pass.
|
||||
|
||||
You can check the security check status of a tool at:
|
||||
|
||||
`CrewAI Enterprise > Tools > Your Tool > Versions`
|
||||
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with API integration or troubleshooting.
|
||||
</Card>
|
||||
@@ -1,146 +0,0 @@
|
||||
---
|
||||
title: Traces
|
||||
description: "Using Traces to monitor your Crews"
|
||||
icon: "timeline"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
Traces provide comprehensive visibility into your crew executions, helping you monitor performance, debug issues, and optimize your AI agent workflows.
|
||||
|
||||
## What are Traces?
|
||||
|
||||
Traces in CrewAI Enterprise are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
|
||||
|
||||
- Agent thoughts and reasoning
|
||||
- Task execution details
|
||||
- Tool usage and outputs
|
||||
- Token consumption metrics
|
||||
- Execution times
|
||||
- Cost estimates
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
## Accessing Traces
|
||||
|
||||
<Steps>
|
||||
<Step title="Navigate to the Traces Tab">
|
||||
Once in your CrewAI Enterprise dashboard, click on the **Traces** to view all execution records.
|
||||
</Step>
|
||||
|
||||
<Step title="Select an Execution">
|
||||
You'll see a list of all crew executions, sorted by date. Click on any execution to view its detailed trace.
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
## Understanding the Trace Interface
|
||||
|
||||
The trace interface is divided into several sections, each providing different insights into your crew's execution:
|
||||
|
||||
### 1. Execution Summary
|
||||
|
||||
The top section displays high-level metrics about the execution:
|
||||
|
||||
- **Total Tokens**: Number of tokens consumed across all tasks
|
||||
- **Prompt Tokens**: Tokens used in prompts to the LLM
|
||||
- **Completion Tokens**: Tokens generated in LLM responses
|
||||
- **Requests**: Number of API calls made
|
||||
- **Execution Time**: Total duration of the crew run
|
||||
- **Estimated Cost**: Approximate cost based on token usage
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### 2. Tasks & Agents
|
||||
|
||||
This section shows all tasks and agents that were part of the crew execution:
|
||||
|
||||
- Task name and agent assignment
|
||||
- Agents and LLMs used for each task
|
||||
- Status (completed/failed)
|
||||
- Individual execution time of the task
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### 3. Final Output
|
||||
|
||||
Displays the final result produced by the crew after all tasks are completed.
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### 4. Execution Timeline
|
||||
|
||||
A visual representation of when each task started and ended, helping you identify bottlenecks or parallel execution patterns.
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### 5. Detailed Task View
|
||||
|
||||
When you click on a specific task in the timeline or task list, you'll see:
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
- **Task Key**: Unique identifier for the task
|
||||
- **Task ID**: Technical identifier in the system
|
||||
- **Status**: Current state (completed/running/failed)
|
||||
- **Agent**: Which agent performed the task
|
||||
- **LLM**: Language model used for this task
|
||||
- **Start/End Time**: When the task began and completed
|
||||
- **Execution Time**: Duration of this specific task
|
||||
- **Task Description**: What the agent was instructed to do
|
||||
- **Expected Output**: What output format was requested
|
||||
- **Input**: Any input provided to this task from previous tasks
|
||||
- **Output**: The actual result produced by the agent
|
||||
|
||||
|
||||
## Using Traces for Debugging
|
||||
|
||||
Traces are invaluable for troubleshooting issues with your crews:
|
||||
|
||||
<Steps>
|
||||
<Step title="Identify Failure Points">
|
||||
When a crew execution doesn't produce the expected results, examine the trace to find where things went wrong. Look for:
|
||||
|
||||
- Failed tasks
|
||||
- Unexpected agent decisions
|
||||
- Tool usage errors
|
||||
- Misinterpreted instructions
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
</Step>
|
||||
|
||||
<Step title="Optimize Performance">
|
||||
Use execution metrics to identify performance bottlenecks:
|
||||
|
||||
- Tasks that took longer than expected
|
||||
- Excessive token usage
|
||||
- Redundant tool operations
|
||||
- Unnecessary API calls
|
||||
</Step>
|
||||
|
||||
<Step title="Improve Cost Efficiency">
|
||||
Analyze token usage and cost estimates to optimize your crew's efficiency:
|
||||
|
||||
- Consider using smaller models for simpler tasks
|
||||
- Refine prompts to be more concise
|
||||
- Cache frequently accessed information
|
||||
- Structure tasks to minimize redundant operations
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with trace analysis or any other CrewAI Enterprise features.
|
||||
</Card>
|
||||
@@ -1,82 +0,0 @@
|
||||
---
|
||||
title: Webhook Streaming
|
||||
description: "Using Webhook Streaming to stream events to your webhook"
|
||||
icon: "webhook"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to
|
||||
CrewAI Enterprise, such as model calls, tool usage, and flow steps.
|
||||
|
||||
## Usage
|
||||
|
||||
When using the Kickoff API, include a `webhooks` object to your request, for example:
|
||||
|
||||
```json
|
||||
{
|
||||
"inputs": {"foo": "bar"},
|
||||
"webhooks": {
|
||||
"events": ["crew_kickoff_started", "llm_call_started"],
|
||||
"url": "https://your.endpoint/webhook",
|
||||
"realtime": false,
|
||||
"authentication": {
|
||||
"strategy": "bearer",
|
||||
"token": "my-secret-token"
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
If `realtime` is set to `true`, each event is delivered individually and immediately, at the cost of crew/flow performance.
|
||||
|
||||
## Webhook Format
|
||||
|
||||
Each webhook sends a list of events:
|
||||
|
||||
```json
|
||||
{
|
||||
"events": [
|
||||
{
|
||||
"id": "event-id",
|
||||
"execution_id": "crew-run-id",
|
||||
"timestamp": "2025-02-16T10:58:44.965Z",
|
||||
"type": "llm_call_started",
|
||||
"data": {
|
||||
"model": "gpt-4",
|
||||
"messages": [
|
||||
{"role": "system", "content": "You are an assistant."},
|
||||
{"role": "user", "content": "Summarize this article."}
|
||||
]
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
The `data` object structure varies by event type. Refer to the [event list](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) on GitHub.
|
||||
|
||||
As requests are sent over HTTP, the order of events can't be guaranteed. If you need ordering, use the `timestamp` field.
|
||||
|
||||
## Supported Events
|
||||
|
||||
CrewAI supports both system events and custom events in Enterprise Event Streaming. These events are sent to your configured webhook endpoint during crew and flow execution.
|
||||
|
||||
- `crew_kickoff_started`
|
||||
- `crew_step_started`
|
||||
- `crew_step_completed`
|
||||
- `crew_execution_completed`
|
||||
- `llm_call_started`
|
||||
- `llm_call_completed`
|
||||
- `tool_usage_started`
|
||||
- `tool_usage_completed`
|
||||
- `crew_test_failed`
|
||||
- *...and others*
|
||||
|
||||
Event names match the internal event bus. See [GitHub source](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) for the full list.
|
||||
|
||||
You can emit your own custom events, and they will be delivered through the webhook stream alongside system events.
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with webhook integration or troubleshooting.
|
||||
</Card>
|
||||
@@ -1,43 +0,0 @@
|
||||
---
|
||||
title: "Build Crew"
|
||||
description: "A Crew is a group of agents that work together to complete a task."
|
||||
icon: "people-arrows"
|
||||
---
|
||||
|
||||
<Tip>
|
||||
[CrewAI Enterprise](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
|
||||
</Tip>
|
||||
|
||||
## Getting Started
|
||||
|
||||
<iframe
|
||||
width="100%"
|
||||
height="400"
|
||||
src="https://www.youtube.com/embed/d1Yp8eeknDk?si=tIxnTRI5UlyCp3z_"
|
||||
title="Building Crews with CrewAI CLI"
|
||||
frameborder="0"
|
||||
style={{ borderRadius: '10px' }}
|
||||
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
|
||||
allowfullscreen
|
||||
></iframe>
|
||||
|
||||
### Installation and Setup
|
||||
|
||||
<Card title="Follow Standard Installation" icon="wrench" href="/installation">
|
||||
Follow our standard installation guide to set up CrewAI CLI and create your first project.
|
||||
</Card>
|
||||
|
||||
### Building Your Crew
|
||||
|
||||
<Card title="Quickstart Tutorial" icon="rocket" href="/quickstart">
|
||||
Follow our quickstart guide to create your first agent crew using YAML configuration.
|
||||
</Card>
|
||||
|
||||
## Support and Resources
|
||||
|
||||
For Enterprise-specific support or questions, contact our dedicated support team at [support@crewai.com](mailto:support@crewai.com).
|
||||
|
||||
|
||||
<Card title="Schedule a Demo" icon="calendar" href="mailto:support@crewai.com">
|
||||
Book time with our team to learn more about Enterprise features and how they can benefit your organization.
|
||||
</Card>
|
||||
@@ -1,216 +0,0 @@
|
||||
---
|
||||
title: "Deploy Crew"
|
||||
description: "Deploy your local CrewAI project to the Enterprise platform"
|
||||
icon: "cloud-arrow-up"
|
||||
---
|
||||
|
||||
## Option 1: CLI Deployment
|
||||
|
||||
<Tip>
|
||||
This video tutorial walks you through the process of deploying your locally developed CrewAI project to the CrewAI Enterprise platform,
|
||||
transforming it into a production-ready API endpoint.
|
||||
</Tip>
|
||||
|
||||
<iframe
|
||||
width="100%"
|
||||
height="400"
|
||||
src="https://www.youtube.com/embed/3EqSV-CYDZA"
|
||||
title="Deploying a Crew to CrewAI Enterprise"
|
||||
frameborder="0"
|
||||
style={{ borderRadius: '10px' }}
|
||||
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
|
||||
allowfullscreen
|
||||
></iframe>
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Before starting the deployment process, make sure you have:
|
||||
|
||||
- A CrewAI project built locally ([follow our quickstart guide](/quickstart) if you haven't created one yet)
|
||||
- Your code pushed to a GitHub repository
|
||||
- The latest version of the CrewAI CLI installed (`uv tool install crewai`)
|
||||
|
||||
<Note>
|
||||
For a quick reference project, you can clone our example repository at [github.com/tonykipkemboi/crewai-latest-ai-development](https://github.com/tonykipkemboi/crewai-latest-ai-development).
|
||||
</Note>
|
||||
|
||||
|
||||
|
||||
### Step 1: Authenticate with the Enterprise Platform
|
||||
|
||||
First, you need to authenticate your CLI with the CrewAI Enterprise platform:
|
||||
|
||||
```bash
|
||||
# If you already have a CrewAI Enterprise account
|
||||
crewai login
|
||||
|
||||
# If you're creating a new account
|
||||
crewai signup
|
||||
```
|
||||
|
||||
When you run either command, the CLI will:
|
||||
1. Display a URL and a unique device code
|
||||
2. Open your browser to the authentication page
|
||||
3. Prompt you to confirm the device
|
||||
4. Complete the authentication process
|
||||
|
||||
Upon successful authentication, you'll see a confirmation message in your terminal!
|
||||
|
||||
### Step 2: Create a Deployment
|
||||
|
||||
From your project directory, run:
|
||||
|
||||
```bash
|
||||
crewai deploy create
|
||||
```
|
||||
|
||||
This command will:
|
||||
1. Detect your GitHub repository information
|
||||
2. Identify environment variables in your local `.env` file
|
||||
3. Securely transfer these variables to the Enterprise platform
|
||||
4. Create a new deployment with a unique identifier
|
||||
|
||||
On successful creation, you'll see a message like:
|
||||
```shell
|
||||
Deployment created successfully!
|
||||
Name: your_project_name
|
||||
Deployment ID: 01234567-89ab-cdef-0123-456789abcdef
|
||||
Current Status: Deploy Enqueued
|
||||
```
|
||||
|
||||
### Step 3: Monitor Deployment Progress
|
||||
|
||||
Track the deployment status with:
|
||||
|
||||
```bash
|
||||
crewai deploy status
|
||||
```
|
||||
|
||||
For detailed logs of the build process:
|
||||
|
||||
```bash
|
||||
crewai deploy logs
|
||||
```
|
||||
|
||||
<Tip>
|
||||
The first deployment typically takes 10-15 minutes as it builds the container images. Subsequent deployments are much faster.
|
||||
</Tip>
|
||||
|
||||
### Additional CLI Commands
|
||||
|
||||
The CrewAI CLI offers several commands to manage your deployments:
|
||||
|
||||
```bash
|
||||
# List all your deployments
|
||||
crewai deploy list
|
||||
|
||||
# Get the status of your deployment
|
||||
crewai deploy status
|
||||
|
||||
# View the logs of your deployment
|
||||
crewai deploy logs
|
||||
|
||||
# Push updates after code changes
|
||||
crewai deploy push
|
||||
|
||||
# Remove a deployment
|
||||
crewai deploy remove <deployment_id>
|
||||
```
|
||||
|
||||
## Option 2: Deploy Directly via Web Interface
|
||||
|
||||
You can also deploy your crews directly through the CrewAI Enterprise web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
|
||||
|
||||
### Step 1: Pushing to GitHub
|
||||
|
||||
First, you need to push your crew to a GitHub repository. If you haven't created a crew yet, you can [follow this tutorial](/quickstart).
|
||||
|
||||
### Step 2: Connecting GitHub to CrewAI Enterprise
|
||||
|
||||
1. Log in to [CrewAI Enterprise](https://app.crewai.com)
|
||||
2. Click on the button "Connect GitHub"
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 3: Select the Repository
|
||||
|
||||
After connecting your GitHub account, you'll be able to select which repository to deploy:
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 4: Set Environment Variables
|
||||
|
||||
Before deploying, you'll need to set up your environment variables to connect to your LLM provider or other services:
|
||||
|
||||
1. You can add variables individually or in bulk
|
||||
2. Enter your environment variables in `KEY=VALUE` format (one per line)
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 5: Deploy Your Crew
|
||||
|
||||
1. Click the "Deploy" button to start the deployment process
|
||||
2. You can monitor the progress through the progress bar
|
||||
3. The first deployment typically takes around 10-15 minutes; subsequent deployments will be faster
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
Once deployment is complete, you'll see:
|
||||
- Your crew's unique URL
|
||||
- A Bearer token to protect your crew API
|
||||
- A "Delete" button if you need to remove the deployment
|
||||
|
||||
### Interact with Your Deployed Crew
|
||||
|
||||
Once deployment is complete, you can access your crew through:
|
||||
|
||||
1. **REST API**: The platform generates a unique HTTPS endpoint with these key routes:
|
||||
- `/inputs`: Lists the required input parameters
|
||||
- `/kickoff`: Initiates an execution with provided inputs
|
||||
- `/status/{kickoff_id}`: Checks the execution status
|
||||
|
||||
2. **Web Interface**: Visit [app.crewai.com](https://app.crewai.com) to access:
|
||||
- **Status tab**: View deployment information, API endpoint details, and authentication token
|
||||
- **Run tab**: Visual representation of your crew's structure
|
||||
- **Executions tab**: History of all executions
|
||||
- **Metrics tab**: Performance analytics
|
||||
- **Traces tab**: Detailed execution insights
|
||||
|
||||
### Trigger an Execution
|
||||
|
||||
From the Enterprise dashboard, you can:
|
||||
|
||||
1. Click on your crew's name to open its details
|
||||
2. Select "Trigger Crew" from the management interface
|
||||
3. Enter the required inputs in the modal that appears
|
||||
4. Monitor progress as the execution moves through the pipeline
|
||||
|
||||
## Monitoring and Analytics
|
||||
|
||||
The Enterprise platform provides comprehensive observability features:
|
||||
|
||||
- **Execution Management**: Track active and completed runs
|
||||
- **Traces**: Detailed breakdowns of each execution
|
||||
- **Metrics**: Token usage, execution times, and costs
|
||||
- **Timeline View**: Visual representation of task sequences
|
||||
|
||||
## Advanced Features
|
||||
|
||||
The Enterprise platform also offers:
|
||||
|
||||
- **Environment Variables Management**: Securely store and manage API keys
|
||||
- **LLM Connections**: Configure integrations with various LLM providers
|
||||
- **Custom Tools Repository**: Create, share, and install tools
|
||||
- **Crew Studio**: Build crews through a chat interface without writing code
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with deployment issues or questions about the Enterprise platform.
|
||||
</Card>
|
||||
@@ -1,166 +0,0 @@
|
||||
---
|
||||
title: "Enable Crew Studio"
|
||||
description: "Enabling Crew Studio on CrewAI Enterprise"
|
||||
icon: "comments"
|
||||
---
|
||||
|
||||
<Tip>
|
||||
Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface.
|
||||
</Tip>
|
||||
|
||||
## What is Crew Studio?
|
||||
|
||||
Crew Studio is an innovative way to create AI agent crews without writing code.
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
With Crew Studio, you can:
|
||||
|
||||
- Chat with the Crew Assistant to describe your problem
|
||||
- Automatically generate agents and tasks
|
||||
- Select appropriate tools
|
||||
- Configure necessary inputs
|
||||
- Generate downloadable code for customization
|
||||
- Deploy directly to the CrewAI Enterprise platform
|
||||
|
||||
## Configuration Steps
|
||||
|
||||
Before you can start using Crew Studio, you need to configure your LLM connections:
|
||||
|
||||
<Steps>
|
||||
<Step title="Set Up LLM Connection">
|
||||
Go to the **LLM Connections** tab in your CrewAI Enterprise dashboard and create a new LLM connection.
|
||||
|
||||
<Note>
|
||||
Feel free to use any LLM provider you want that is supported by CrewAI.
|
||||
</Note>
|
||||
|
||||
Configure your LLM connection:
|
||||
|
||||
- Enter a `Connection Name` (e.g., `OpenAI`)
|
||||
- Select your model provider: `openai` or `azure`
|
||||
- Select models you'd like to use in your Studio-generated Crews
|
||||
- We recommend at least `gpt-4o`, `o1-mini`, and `gpt-4o-mini`
|
||||
- Add your API key as an environment variable:
|
||||
- For OpenAI: Add `OPENAI_API_KEY` with your API key
|
||||
- For Azure OpenAI: Refer to [this article](https://blog.crewai.com/configuring-azure-openai-with-crewai-a-comprehensive-guide/) for configuration details
|
||||
- Click `Add Connection` to save your configuration
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
</Step>
|
||||
|
||||
<Step title="Verify Connection Added">
|
||||
Once you complete the setup, you'll see your new connection added to the list of available connections.
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
</Step>
|
||||
|
||||
<Step title="Configure LLM Defaults">
|
||||
In the main menu, go to **Settings → Defaults** and configure the LLM Defaults settings:
|
||||
|
||||
- Select default models for agents and other components
|
||||
- Set default configurations for Crew Studio
|
||||
|
||||
Click `Save Settings` to apply your changes.
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
## Using Crew Studio
|
||||
|
||||
Now that you've configured your LLM connection and default settings, you're ready to start using Crew Studio!
|
||||
|
||||
<Steps>
|
||||
<Step title="Access Studio">
|
||||
Navigate to the **Studio** section in your CrewAI Enterprise dashboard.
|
||||
</Step>
|
||||
|
||||
<Step title="Start a Conversation">
|
||||
Start a conversation with the Crew Assistant by describing the problem you want to solve:
|
||||
|
||||
```md
|
||||
I need a crew that can research the latest AI developments and create a summary report.
|
||||
```
|
||||
|
||||
The Crew Assistant will ask clarifying questions to better understand your requirements.
|
||||
</Step>
|
||||
|
||||
<Step title="Review Generated Crew">
|
||||
Review the generated crew configuration, including:
|
||||
|
||||
- Agents and their roles
|
||||
- Tasks to be performed
|
||||
- Required inputs
|
||||
- Tools to be used
|
||||
|
||||
This is your opportunity to refine the configuration before proceeding.
|
||||
</Step>
|
||||
|
||||
<Step title="Deploy or Download">
|
||||
Once you're satisfied with the configuration, you can:
|
||||
|
||||
- Download the generated code for local customization
|
||||
- Deploy the crew directly to the CrewAI Enterprise platform
|
||||
- Modify the configuration and regenerate the crew
|
||||
</Step>
|
||||
|
||||
<Step title="Test Your Crew">
|
||||
After deployment, test your crew with sample inputs to ensure it performs as expected.
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
<Tip>
|
||||
For best results, provide clear, detailed descriptions of what you want your crew to accomplish. Include specific inputs and expected outputs in your description.
|
||||
</Tip>
|
||||
|
||||
## Example Workflow
|
||||
|
||||
Here's a typical workflow for creating a crew with Crew Studio:
|
||||
|
||||
<Steps>
|
||||
<Step title="Describe Your Problem">
|
||||
Start by describing your problem:
|
||||
|
||||
```md
|
||||
I need a crew that can analyze financial news and provide investment recommendations
|
||||
```
|
||||
</Step>
|
||||
|
||||
<Step title="Answer Questions">
|
||||
Respond to clarifying questions from the Crew Assistant to refine your requirements.
|
||||
</Step>
|
||||
|
||||
<Step title="Review the Plan">
|
||||
Review the generated crew plan, which might include:
|
||||
|
||||
- A Research Agent to gather financial news
|
||||
- An Analysis Agent to interpret the data
|
||||
- A Recommendations Agent to provide investment advice
|
||||
</Step>
|
||||
|
||||
<Step title="Approve or Modify">
|
||||
Approve the plan or request changes if necessary.
|
||||
</Step>
|
||||
|
||||
<Step title="Download or Deploy">
|
||||
Download the code for customization or deploy directly to the platform.
|
||||
</Step>
|
||||
|
||||
<Step title="Test and Refine">
|
||||
Test your crew with sample inputs and refine as needed.
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with Crew Studio or any other CrewAI Enterprise features.
|
||||
</Card>
|
||||
|
||||
@@ -1,186 +0,0 @@
|
||||
---
|
||||
title: "Kickoff Crew"
|
||||
description: "Kickoff a Crew on CrewAI Enterprise"
|
||||
icon: "flag-checkered"
|
||||
---
|
||||
|
||||
# Kickoff a Crew on CrewAI Enterprise
|
||||
|
||||
Once you've deployed your crew to the CrewAI Enterprise platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
|
||||
|
||||
## Method 1: Using the Web Interface
|
||||
|
||||
### Step 1: Navigate to Your Deployed Crew
|
||||
|
||||
1. Log in to [CrewAI Enterprise](https://app.crewai.com)
|
||||
2. Click on the crew name from your projects list
|
||||
3. You'll be taken to the crew's detail page
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 2: Initiate Execution
|
||||
|
||||
From your crew's detail page, you have two options to kickoff an execution:
|
||||
|
||||
#### Option A: Quick Kickoff
|
||||
|
||||
1. Click the `Kickoff` link in the Test Endpoints section
|
||||
2. Enter the required input parameters for your crew in the JSON editor
|
||||
3. Click the `Send Request` button
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
#### Option B: Using the Visual Interface
|
||||
|
||||
1. Click the `Run` tab in the crew detail page
|
||||
2. Enter the required inputs in the form fields
|
||||
3. Click the `Run Crew` button
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 3: Monitor Execution Progress
|
||||
|
||||
After initiating the execution:
|
||||
|
||||
1. You'll receive a response containing a `kickoff_id` - **copy this ID**
|
||||
2. This ID is essential for tracking your execution
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
### Step 4: Check Execution Status
|
||||
|
||||
To monitor the progress of your execution:
|
||||
|
||||
1. Click the "Status" endpoint in the Test Endpoints section
|
||||
2. Paste the `kickoff_id` into the designated field
|
||||
3. Click the "Get Status" button
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
The status response will show:
|
||||
- Current execution state (`running`, `completed`, etc.)
|
||||
- Details about which tasks are in progress
|
||||
- Any outputs produced so far
|
||||
|
||||
### Step 5: View Final Results
|
||||
|
||||
Once execution is complete:
|
||||
|
||||
1. The status will change to `completed`
|
||||
2. You can view the full execution results and outputs
|
||||
3. For a more detailed view, check the `Executions` tab in the crew detail page
|
||||
|
||||
## Method 2: Using the API
|
||||
|
||||
You can also kickoff crews programmatically using the CrewAI Enterprise REST API.
|
||||
|
||||
### Authentication
|
||||
|
||||
All API requests require a bearer token for authentication:
|
||||
|
||||
```bash
|
||||
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
|
||||
```
|
||||
|
||||
Your bearer token is available on the Status tab of your crew's detail page.
|
||||
|
||||
### Checking Crew Health
|
||||
|
||||
Before executing operations, you can verify that your crew is running properly:
|
||||
|
||||
```bash
|
||||
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
|
||||
```
|
||||
|
||||
A successful response will return a message indicating the crew is operational:
|
||||
|
||||
```
|
||||
Healthy%
|
||||
```
|
||||
|
||||
### Step 1: Retrieve Required Inputs
|
||||
|
||||
First, determine what inputs your crew requires:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/inputs
|
||||
```
|
||||
|
||||
The response will be a JSON object containing an array of required input parameters, for example:
|
||||
|
||||
```json
|
||||
{"inputs":["topic","current_year"]}
|
||||
```
|
||||
|
||||
This example shows that this particular crew requires two inputs: `topic` and `current_year`.
|
||||
|
||||
### Step 2: Kickoff Execution
|
||||
|
||||
Initiate execution by providing the required inputs:
|
||||
|
||||
```bash
|
||||
curl -X POST \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
-d '{"inputs": {"topic": "AI Agent Frameworks", "current_year": "2025"}}' \
|
||||
https://your-crew-url.crewai.com/kickoff
|
||||
```
|
||||
|
||||
The response will include a `kickoff_id` that you'll need for tracking:
|
||||
|
||||
```json
|
||||
{"kickoff_id":"abcd1234-5678-90ef-ghij-klmnopqrstuv"}
|
||||
```
|
||||
|
||||
### Step 3: Check Execution Status
|
||||
|
||||
Monitor the execution progress using the kickoff_id:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
|
||||
```
|
||||
|
||||
## Handling Executions
|
||||
|
||||
### Long-Running Executions
|
||||
|
||||
For executions that may take a long time:
|
||||
|
||||
1. Consider implementing a polling mechanism to check status periodically
|
||||
2. Use webhooks (if available) for notification when execution completes
|
||||
3. Implement error handling for potential timeouts
|
||||
|
||||
### Execution Context
|
||||
|
||||
The execution context includes:
|
||||
|
||||
- Inputs provided at kickoff
|
||||
- Environment variables configured during deployment
|
||||
- Any state maintained between tasks
|
||||
|
||||
### Debugging Failed Executions
|
||||
|
||||
If an execution fails:
|
||||
|
||||
1. Check the "Executions" tab for detailed logs
|
||||
2. Review the "Traces" tab for step-by-step execution details
|
||||
3. Look for LLM responses and tool usage in the trace details
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with execution issues or questions about the Enterprise platform.
|
||||
</Card>
|
||||
|
||||
@@ -1,89 +0,0 @@
|
||||
---
|
||||
title: "Update Crew"
|
||||
description: "Updating a Crew on CrewAI Enterprise"
|
||||
icon: "pencil"
|
||||
---
|
||||
|
||||
<Note>
|
||||
After deploying your crew to CrewAI Enterprise, you may need to make updates to the code, security settings, or configuration.
|
||||
This guide explains how to perform these common update operations.
|
||||
</Note>
|
||||
|
||||
## Why Update Your Crew?
|
||||
|
||||
CrewAI won't automatically pick up GitHub updates by default, so you'll need to manually trigger updates, unless you checked the `Auto-update` option when deploying your crew.
|
||||
|
||||
There are several reasons you might want to update your crew deployment:
|
||||
- You want to update the code with a latest commit you pushed to GitHub
|
||||
- You want to reset the bearer token for security reasons
|
||||
- You want to update environment variables
|
||||
|
||||
## 1. Updating Your Crew Code for a Latest Commit
|
||||
|
||||
When you've pushed new commits to your GitHub repository and want to update your deployment:
|
||||
|
||||
1. Navigate to your crew in the CrewAI Enterprise platform
|
||||
2. Click on the `Re-deploy` button on your crew details page
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
This will trigger an update that you can track using the progress bar. The system will pull the latest code from your repository and rebuild your deployment.
|
||||
|
||||
## 2. Resetting Bearer Token
|
||||
|
||||
If you need to generate a new bearer token (for example, if you suspect the current token might have been compromised):
|
||||
|
||||
1. Navigate to your crew in the CrewAI Enterprise platform
|
||||
2. Find the `Bearer Token` section
|
||||
3. Click the `Reset` button next to your current token
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
<Warning>
|
||||
Resetting your bearer token will invalidate the previous token immediately. Make sure to update any applications or scripts that are using the old token.
|
||||
</Warning>
|
||||
|
||||
## 3. Updating Environment Variables
|
||||
|
||||
To update the environment variables for your crew:
|
||||
|
||||
1. First access the deployment page by clicking on your crew's name
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
2. Locate the `Environment Variables` section (you will need to click the `Settings` icon to access it)
|
||||
3. Edit the existing variables or add new ones in the fields provided
|
||||
4. Click the `Update` button next to each variable you modify
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
5. Finally, click the `Update Deployment` button at the bottom of the page to apply the changes
|
||||
|
||||
<Note>
|
||||
Updating environment variables will trigger a new deployment, but this will only update the environment configuration and not the code itself.
|
||||
</Note>
|
||||
|
||||
## After Updating
|
||||
|
||||
After performing any update:
|
||||
|
||||
1. The system will rebuild and redeploy your crew
|
||||
2. You can monitor the deployment progress in real-time
|
||||
3. Once complete, test your crew to ensure the changes are working as expected
|
||||
|
||||
<Tip>
|
||||
If you encounter any issues after updating, you can view deployment logs in the platform or contact support for assistance.
|
||||
</Tip>
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with updating your crew or troubleshooting deployment issues.
|
||||
</Card>
|
||||
|
||||
@@ -1,319 +0,0 @@
|
||||
---
|
||||
title: "Trigger Deployed Crew API"
|
||||
description: "Using your deployed crew's API on CrewAI Enterprise"
|
||||
icon: "arrow-up-right-from-square"
|
||||
---
|
||||
|
||||
Once you have deployed your crew to CrewAI Enterprise, it automatically becomes available as a REST API. This guide explains how to interact with your crew programmatically.
|
||||
|
||||
## API Basics
|
||||
|
||||
Your deployed crew exposes several endpoints that allow you to:
|
||||
1. Discover required inputs
|
||||
2. Start crew executions
|
||||
3. Monitor execution status
|
||||
4. Receive results
|
||||
|
||||
### Authentication
|
||||
|
||||
All API requests require a bearer token for authentication, which is generated when you deploy your crew:
|
||||
|
||||
```bash
|
||||
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com/...
|
||||
```
|
||||
|
||||
<Tip>
|
||||
You can find your bearer token in the Status tab of your crew's detail page in the CrewAI Enterprise dashboard.
|
||||
</Tip>
|
||||
|
||||
<Frame>
|
||||
|
||||
</Frame>
|
||||
|
||||
## Available Endpoints
|
||||
|
||||
Your crew API provides three main endpoints:
|
||||
|
||||
| Endpoint | Method | Description |
|
||||
|----------|--------|-------------|
|
||||
| `/inputs` | GET | Lists all required inputs for crew execution |
|
||||
| `/kickoff` | POST | Starts a crew execution with provided inputs |
|
||||
| `/status/{kickoff_id}` | GET | Retrieves the status and results of an execution |
|
||||
|
||||
## GET /inputs
|
||||
|
||||
The inputs endpoint allows you to discover what parameters your crew requires:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/inputs
|
||||
```
|
||||
|
||||
### Response
|
||||
|
||||
```json
|
||||
{
|
||||
"inputs": ["budget", "interests", "duration", "age"]
|
||||
}
|
||||
```
|
||||
|
||||
This response indicates that your crew expects four input parameters: `budget`, `interests`, `duration`, and `age`.
|
||||
|
||||
## POST /kickoff
|
||||
|
||||
The kickoff endpoint starts a new crew execution:
|
||||
|
||||
```bash
|
||||
curl -X POST \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
-d '{
|
||||
"inputs": {
|
||||
"budget": "1000 USD",
|
||||
"interests": "games, tech, ai, relaxing hikes, amazing food",
|
||||
"duration": "7 days",
|
||||
"age": "35"
|
||||
}
|
||||
}' \
|
||||
https://your-crew-url.crewai.com/kickoff
|
||||
```
|
||||
|
||||
### Request Parameters
|
||||
|
||||
| Parameter | Type | Required | Description |
|
||||
|-----------|------|----------|-------------|
|
||||
| `inputs` | Object | Yes | Key-value pairs of all required inputs |
|
||||
| `meta` | Object | No | Additional metadata to pass to the crew |
|
||||
| `taskWebhookUrl` | String | No | Callback URL executed after each task |
|
||||
| `stepWebhookUrl` | String | No | Callback URL executed after each agent thought |
|
||||
| `crewWebhookUrl` | String | No | Callback URL executed when the crew finishes |
|
||||
|
||||
### Example with Webhooks
|
||||
|
||||
```json
|
||||
{
|
||||
"inputs": {
|
||||
"budget": "1000 USD",
|
||||
"interests": "games, tech, ai, relaxing hikes, amazing food",
|
||||
"duration": "7 days",
|
||||
"age": "35"
|
||||
},
|
||||
"meta": {
|
||||
"requestId": "user-request-12345",
|
||||
"source": "mobile-app"
|
||||
},
|
||||
"taskWebhookUrl": "https://your-server.com/webhooks/task",
|
||||
"stepWebhookUrl": "https://your-server.com/webhooks/step",
|
||||
"crewWebhookUrl": "https://your-server.com/webhooks/crew"
|
||||
}
|
||||
```
|
||||
|
||||
### Response
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv"
|
||||
}
|
||||
```
|
||||
|
||||
The `kickoff_id` is used to track and retrieve the execution results.
|
||||
|
||||
## GET /status/{kickoff_id}
|
||||
|
||||
The status endpoint allows you to check the progress and results of a crew execution:
|
||||
|
||||
```bash
|
||||
curl -X GET \
|
||||
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
|
||||
https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
|
||||
```
|
||||
|
||||
### Response Structure
|
||||
|
||||
The response structure will vary depending on the execution state:
|
||||
|
||||
#### In Progress
|
||||
|
||||
```json
|
||||
{
|
||||
"status": "running",
|
||||
"current_task": "research_task",
|
||||
"progress": {
|
||||
"completed_tasks": 0,
|
||||
"total_tasks": 2
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### Completed
|
||||
|
||||
```json
|
||||
{
|
||||
"status": "completed",
|
||||
"result": {
|
||||
"output": "Comprehensive travel itinerary...",
|
||||
"tasks": [
|
||||
{
|
||||
"task_id": "research_task",
|
||||
"output": "Research findings...",
|
||||
"agent": "Researcher",
|
||||
"execution_time": 45.2
|
||||
},
|
||||
{
|
||||
"task_id": "planning_task",
|
||||
"output": "7-day itinerary plan...",
|
||||
"agent": "Trip Planner",
|
||||
"execution_time": 62.8
|
||||
}
|
||||
]
|
||||
},
|
||||
"execution_time": 108.5
|
||||
}
|
||||
```
|
||||
|
||||
## Webhook Integration
|
||||
|
||||
When you provide webhook URLs in your kickoff request, the system will make POST requests to those URLs at specific points in the execution:
|
||||
|
||||
### taskWebhookUrl
|
||||
|
||||
Called when each task completes:
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
|
||||
"task_id": "research_task",
|
||||
"status": "completed",
|
||||
"output": "Research findings...",
|
||||
"agent": "Researcher",
|
||||
"execution_time": 45.2
|
||||
}
|
||||
```
|
||||
|
||||
### stepWebhookUrl
|
||||
|
||||
Called after each agent thought or action:
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
|
||||
"task_id": "research_task",
|
||||
"agent": "Researcher",
|
||||
"step_type": "thought",
|
||||
"content": "I should first search for popular destinations that match these interests..."
|
||||
}
|
||||
```
|
||||
|
||||
### crewWebhookUrl
|
||||
|
||||
Called when the entire crew execution completes:
|
||||
|
||||
```json
|
||||
{
|
||||
"kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
|
||||
"status": "completed",
|
||||
"result": {
|
||||
"output": "Comprehensive travel itinerary...",
|
||||
"tasks": [
|
||||
{
|
||||
"task_id": "research_task",
|
||||
"output": "Research findings...",
|
||||
"agent": "Researcher",
|
||||
"execution_time": 45.2
|
||||
},
|
||||
{
|
||||
"task_id": "planning_task",
|
||||
"output": "7-day itinerary plan...",
|
||||
"agent": "Trip Planner",
|
||||
"execution_time": 62.8
|
||||
}
|
||||
]
|
||||
},
|
||||
"execution_time": 108.5,
|
||||
"meta": {
|
||||
"requestId": "user-request-12345",
|
||||
"source": "mobile-app"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
### Handling Long-Running Executions
|
||||
|
||||
Crew executions can take anywhere from seconds to minutes depending on their complexity. Consider these approaches:
|
||||
|
||||
1. **Webhooks (Recommended)**: Set up webhook endpoints to receive notifications when the execution completes
|
||||
2. **Polling**: Implement a polling mechanism with exponential backoff
|
||||
3. **Client-Side Timeout**: Set appropriate timeouts for your API requests
|
||||
|
||||
### Error Handling
|
||||
|
||||
The API may return various error codes:
|
||||
|
||||
| Code | Description | Recommended Action |
|
||||
|------|-------------|-------------------|
|
||||
| 401 | Unauthorized | Check your bearer token |
|
||||
| 404 | Not Found | Verify your crew URL and kickoff_id |
|
||||
| 422 | Validation Error | Ensure all required inputs are provided |
|
||||
| 500 | Server Error | Contact support with the error details |
|
||||
|
||||
### Sample Code
|
||||
|
||||
Here's a complete Python example for interacting with your crew API:
|
||||
|
||||
```python
|
||||
import requests
|
||||
import time
|
||||
|
||||
# Configuration
|
||||
CREW_URL = "https://your-crew-url.crewai.com"
|
||||
BEARER_TOKEN = "your-crew-token"
|
||||
HEADERS = {
|
||||
"Authorization": f"Bearer {BEARER_TOKEN}",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
# 1. Get required inputs
|
||||
response = requests.get(f"{CREW_URL}/inputs", headers=HEADERS)
|
||||
required_inputs = response.json()["inputs"]
|
||||
print(f"Required inputs: {required_inputs}")
|
||||
|
||||
# 2. Start crew execution
|
||||
payload = {
|
||||
"inputs": {
|
||||
"budget": "1000 USD",
|
||||
"interests": "games, tech, ai, relaxing hikes, amazing food",
|
||||
"duration": "7 days",
|
||||
"age": "35"
|
||||
}
|
||||
}
|
||||
|
||||
response = requests.post(f"{CREW_URL}/kickoff", headers=HEADERS, json=payload)
|
||||
kickoff_id = response.json()["kickoff_id"]
|
||||
print(f"Execution started with ID: {kickoff_id}")
|
||||
|
||||
# 3. Poll for results
|
||||
MAX_RETRIES = 30
|
||||
POLL_INTERVAL = 10 # seconds
|
||||
for i in range(MAX_RETRIES):
|
||||
print(f"Checking status (attempt {i+1}/{MAX_RETRIES})...")
|
||||
response = requests.get(f"{CREW_URL}/status/{kickoff_id}", headers=HEADERS)
|
||||
data = response.json()
|
||||
|
||||
if data["status"] == "completed":
|
||||
print("Execution completed!")
|
||||
print(f"Result: {data['result']['output']}")
|
||||
break
|
||||
elif data["status"] == "error":
|
||||
print(f"Execution failed: {data.get('error', 'Unknown error')}")
|
||||
break
|
||||
else:
|
||||
print(f"Status: {data['status']}, waiting {POLL_INTERVAL} seconds...")
|
||||
time.sleep(POLL_INTERVAL)
|
||||
```
|
||||
|
||||
<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
|
||||
Contact our support team for assistance with API integration or troubleshooting.
|
||||
</Card>
|
||||
@@ -1,67 +0,0 @@
|
||||
---
|
||||
title: "CrewAI Enterprise"
|
||||
description: "Deploy, monitor, and scale your AI agent workflows"
|
||||
icon: "globe"
|
||||
---
|
||||
|
||||
## Introduction
|
||||
|
||||
CrewAI Enterprise provides a platform for deploying, monitoring, and scaling your crews and agents in a production environment.
|
||||
|
||||
CrewAI Enterprise extends the power of the open-source framework with features designed for production deployments, collaboration, and scalability. Deploy your crews to a managed infrastructure and monitor their execution in real-time.
|
||||
|
||||
## Key Features
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card title="Crew Deployments" icon="rocket">
|
||||
Deploy your crews to a managed infrastructure with a few clicks
|
||||
</Card>
|
||||
<Card title="API Access" icon="code">
|
||||
Access your deployed crews via REST API for integration with existing systems
|
||||
</Card>
|
||||
<Card title="Observability" icon="chart-line">
|
||||
Monitor your crews with detailed execution traces and logs
|
||||
</Card>
|
||||
<Card title="Tool Repository" icon="toolbox">
|
||||
Publish and install tools to enhance your crews' capabilities
|
||||
</Card>
|
||||
<Card title="Webhook Streaming" icon="webhook">
|
||||
Stream real-time events and updates to your systems
|
||||
</Card>
|
||||
<Card title="Crew Studio" icon="paintbrush">
|
||||
Create and customize crews using a no-code/low-code interface
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Deployment Options
|
||||
|
||||
<CardGroup cols={3}>
|
||||
<Card title="GitHub Integration" icon="github">
|
||||
Connect directly to your GitHub repositories to deploy code
|
||||
</Card>
|
||||
<Card title="Crew Studio" icon="palette">
|
||||
Deploy crews created through the no-code Crew Studio interface
|
||||
</Card>
|
||||
<Card title="CLI Deployment" icon="terminal">
|
||||
Use the CrewAI CLI for more advanced deployment workflows
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Getting Started
|
||||
|
||||
<Steps>
|
||||
<Step title="Sign up for an account">
|
||||
Create your account at [app.crewai.com](https://app.crewai.com)
|
||||
</Step>
|
||||
<Step title="Create your first crew">
|
||||
Use code or Crew Studio to create your crew
|
||||
</Step>
|
||||
<Step title="Deploy your crew">
|
||||
Deploy your crew to the Enterprise platform
|
||||
</Step>
|
||||
<Step title="Access your crew">
|
||||
Integrate with your crew via the generated API endpoints
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
For detailed instructions, check out our [deployment guide](/enterprise/guides/deploy-crew) or click the button below to get started.
|
||||
@@ -1,181 +0,0 @@
|
||||
---
|
||||
title: FAQs
|
||||
description: "Frequently asked questions about CrewAI Enterprise"
|
||||
icon: "code"
|
||||
---
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="How is task execution handled in the hierarchical process?">
|
||||
In the hierarchical process, a manager agent is automatically created and coordinates the workflow, delegating tasks and validating outcomes for
|
||||
streamlined and effective execution. The manager agent utilizes tools to facilitate task delegation and execution by agents under the manager's guidance.
|
||||
The manager LLM is crucial for the hierarchical process and must be set up correctly for proper function.
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Where can I get the latest CrewAI documentation?">
|
||||
The most up-to-date documentation for CrewAI is available on our official documentation website; https://docs.crewai.com/
|
||||
<Card href="https://docs.crewai.com/" icon="books">CrewAI Docs</Card>
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="What are the key differences between Hierarchical and Sequential Processes in CrewAI?">
|
||||
#### Hierarchical Process:
|
||||
Tasks are delegated and executed based on a structured chain of command.
|
||||
A manager language model (`manager_llm`) must be specified for the manager agent.
|
||||
Manager agent oversees task execution, planning, delegation, and validation.
|
||||
Tasks are not pre-assigned; the manager allocates tasks to agents based on their capabilities.
|
||||
|
||||
#### Sequential Process:
|
||||
Tasks are executed one after another, ensuring tasks are completed in an orderly progression.
|
||||
Output of one task serves as context for the next.
|
||||
Task execution follows the predefined order in the task list.
|
||||
|
||||
#### Which Process is Better Suited for Complex Projects?
|
||||
|
||||
The hierarchical process is better suited for complex projects because it allows for:
|
||||
|
||||
- **Dynamic task allocation and delegation**: Manager agent can assign tasks based on agent capabilities, allowing for efficient resource utilization.
|
||||
- **Structured validation and oversight**: Manager agent reviews task outputs and ensures task completion, increasing reliability and accuracy.
|
||||
- **Complex task management**: Assigning tools at the agent level allows for precise control over tool availability, facilitating the execution of intricate tasks.
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="What are the benefits of using memory in the CrewAI framework?">
|
||||
- **Adaptive Learning**: Crews become more efficient over time, adapting to new information and refining their approach to tasks.
|
||||
- **Enhanced Personalization**: Memory enables agents to remember user preferences and historical interactions, leading to personalized experiences.
|
||||
- **Improved Problem Solving**: Access to a rich memory store aids agents in making more informed decisions, drawing on past learnings and contextual insights.
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="What is the purpose of setting a maximum RPM limit for an agent?">
|
||||
Setting a maximum RPM limit for an agent prevents the agent from making too many requests to external services, which can help to avoid rate limits and improve performance.
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="What role does human input play in the execution of tasks within a CrewAI crew?">
|
||||
It allows agents to request additional information or clarification when necessary.
|
||||
This feature is crucial in complex decision-making processes or when agents require more details to complete a task effectively.
|
||||
|
||||
To integrate human input into agent execution, set the `human_input` flag in the task definition. When enabled, the agent prompts the user for input before delivering its final answer.
|
||||
This input can provide extra context, clarify ambiguities, or validate the agent's output.
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="What advanced customization options are available for tailoring and enhancing agent behavior and capabilities in CrewAI?">
|
||||
CrewAI provides a range of advanced customization options to tailor and enhance agent behavior and capabilities:
|
||||
|
||||
- **Language Model Customization**: Agents can be customized with specific language models (`llm`) and function-calling language models (`function_calling_llm`), offering advanced control over their processing and decision-making abilities.
|
||||
|
||||
- **Performance and Debugging Settings**: Adjust an agent's performance and monitor its operations for efficient task execution.
|
||||
|
||||
- **Verbose Mode**: Enables detailed logging of an agent's actions, useful for debugging and optimization.
|
||||
|
||||
- **RPM Limit**: Sets the maximum number of requests per minute (`max_rpm`).
|
||||
|
||||
- **Maximum Iterations for Task Execution**: The `max_iter` attribute allows users to define the maximum number of iterations an agent can perform for a single task, preventing infinite loops or excessively long executions.
|
||||
|
||||
- **Delegation and Autonomy**: Control an agent's ability to delegate or ask questions, tailoring its autonomy and collaborative dynamics within the CrewAI framework. By default, the `allow_delegation` attribute is set to True, enabling agents to seek assistance or delegate tasks as needed. This default behavior promotes collaborative problem-solving and efficiency within the CrewAI ecosystem. If needed, delegation can be disabled to suit specific operational requirements.
|
||||
|
||||
- **Human Input in Agent Execution**: Human input is critical in several agent execution scenarios, allowing agents to request additional information or clarification when necessary. This feature is especially useful in complex decision-making processes or when agents require more details to complete a task effectively.
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="In what scenarios is human input particularly useful in agent execution?">
|
||||
Human input is particularly useful in agent execution when:
|
||||
- **Agents require additional information or clarification**: When agents encounter ambiguity or incomplete data, human input can provide the necessary context to complete the task effectively.
|
||||
- **Agents need to make complex or sensitive decisions**: Human input can assist agents in ethical or nuanced decision-making, ensuring responsible and informed outcomes.
|
||||
- **Oversight and validation of agent output**: Human input can help validate the results generated by agents, ensuring accuracy and preventing any misinterpretation or errors.
|
||||
- **Customizing agent behavior**: Human input can provide feedback on agent responses, allowing users to refine the agent's behavior and responses over time.
|
||||
- **Identifying and resolving errors or limitations**: Human input can help identify and address any errors or limitations in the agent's capabilities, enabling continuous improvement and optimization.
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="What are the different types of memory that are available in crewAI?">
|
||||
The different types of memory available in CrewAI are:
|
||||
- `short-term memory`
|
||||
- `long-term memory`
|
||||
- `entity memory`
|
||||
- `contextual memory`
|
||||
|
||||
Learn more about the different types of memory here:
|
||||
<Card href="https://docs.crewai.com/concepts/memory" icon="brain">CrewAI Memory</Card>
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="How can I create custom tools for my CrewAI agents?">
|
||||
You can create custom tools by subclassing the `BaseTool` class provided by CrewAI or by using the tool decorator. Subclassing involves defining a new class that inherits from `BaseTool`, specifying the name, description, and the `_run` method for operational logic. The tool decorator allows you to create a `Tool` object directly with the required attributes and a functional logic.
|
||||
Click here for more details:
|
||||
<Card href="https://docs.crewai.com/how-to/create-custom-tools" icon="code">CrewAI Tools</Card>
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="How do I use Output Pydantic in a Task?">
|
||||
To use Output Pydantic in a task, you need to define the expected output of the task as a Pydantic model. Here's an example:
|
||||
<Steps>
|
||||
<Step title="Define a Pydantic model">
|
||||
First, you need to define a Pydantic model. For instance, let's create a simple model for a user:
|
||||
|
||||
```python
|
||||
from pydantic import BaseModel
|
||||
|
||||
class User(BaseModel):
|
||||
name: str
|
||||
age: int
|
||||
```
|
||||
</Step>
|
||||
|
||||
<Step title="Then, when creating a task, specify the expected output as this Pydantic model:">
|
||||
|
||||
```python
|
||||
from crewai import Task, Crew, Agent
|
||||
|
||||
# Import the User model
|
||||
from my_models import User
|
||||
|
||||
# Create a task with Output Pydantic
|
||||
task = Task(
|
||||
description="Create a user with the provided name and age",
|
||||
expected_output=User, # This is the Pydantic model
|
||||
agent=agent,
|
||||
tools=[tool1, tool2]
|
||||
)
|
||||
```
|
||||
</Step>
|
||||
|
||||
<Step title="In your agent, make sure to set the output_pydantic attribute to the Pydantic model you're using:">
|
||||
|
||||
```python
|
||||
from crewai import Agent
|
||||
|
||||
# Import the User model
|
||||
from my_models import User
|
||||
|
||||
# Create an agent with Output Pydantic
|
||||
agent = Agent(
|
||||
role='User Creator',
|
||||
goal='Create users',
|
||||
backstory='I am skilled in creating user accounts',
|
||||
tools=[tool1, tool2],
|
||||
output_pydantic=User
|
||||
)
|
||||
```
|
||||
</Step>
|
||||
|
||||
<Step title="When executing the crew, the output of the task will be a User object:">
|
||||
|
||||
```python
|
||||
from crewai import Crew
|
||||
|
||||
# Create a crew with the agent and task
|
||||
crew = Crew(agents=[agent], tasks=[task])
|
||||
|
||||
# Kick off the crew
|
||||
result = crew.kickoff()
|
||||
|
||||
# The output of the task will be a User object
|
||||
print(result.tasks[0].output)
|
||||
```
|
||||
</Step>
|
||||
</Steps>
|
||||
Here's a tutorial on how to consistently get structured outputs from your agents:
|
||||
<Frame>
|
||||
<iframe
|
||||
height="400"
|
||||
width="100%"
|
||||
src="https://www.youtube.com/embed/dNpKQk5uxHw"
|
||||
title="YouTube video player" frameborder="0"
|
||||
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
|
||||
allowfullscreen></iframe>
|
||||
</Frame>
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 57 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 73 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 101 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 143 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 144 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 705 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 258 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 61 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 146 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 547 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 67 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 183 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 332 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 249 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 63 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 63 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 348 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 218 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 128 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 333 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 150 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 145 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 182 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 358 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 259 KiB |
@@ -1,6 +1,6 @@
|
||||
[project]
|
||||
name = "crewai"
|
||||
version = "0.117.0"
|
||||
version = "0.114.0"
|
||||
description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10,<3.13"
|
||||
|
||||
@@ -17,7 +17,7 @@ warnings.filterwarnings(
|
||||
category=UserWarning,
|
||||
module="pydantic.main",
|
||||
)
|
||||
__version__ = "0.117.0"
|
||||
__version__ = "0.114.0"
|
||||
__all__ = [
|
||||
"Agent",
|
||||
"Crew",
|
||||
|
||||
@@ -122,16 +122,7 @@ PROVIDERS = [
|
||||
]
|
||||
|
||||
MODELS = {
|
||||
"openai": [
|
||||
"gpt-4",
|
||||
"gpt-4.1",
|
||||
"gpt-4.1-mini-2025-04-14",
|
||||
"gpt-4.1-nano-2025-04-14",
|
||||
"gpt-4o",
|
||||
"gpt-4o-mini",
|
||||
"o1-mini",
|
||||
"o1-preview",
|
||||
],
|
||||
"openai": ["gpt-4", "gpt-4o", "gpt-4o-mini", "o1-mini", "o1-preview"],
|
||||
"anthropic": [
|
||||
"claude-3-5-sonnet-20240620",
|
||||
"claude-3-sonnet-20240229",
|
||||
@@ -141,17 +132,8 @@ MODELS = {
|
||||
"gemini": [
|
||||
"gemini/gemini-1.5-flash",
|
||||
"gemini/gemini-1.5-pro",
|
||||
"gemini/gemini-2.0-flash-lite-001",
|
||||
"gemini/gemini-2.0-flash-001",
|
||||
"gemini/gemini-2.0-flash-thinking-exp-01-21",
|
||||
"gemini/gemini-2.5-flash-preview-04-17",
|
||||
"gemini/gemini-2.5-pro-exp-03-25",
|
||||
"gemini/gemini-gemma-2-9b-it",
|
||||
"gemini/gemini-gemma-2-27b-it",
|
||||
"gemini/gemma-3-1b-it",
|
||||
"gemini/gemma-3-4b-it",
|
||||
"gemini/gemma-3-12b-it",
|
||||
"gemini/gemma-3-27b-it",
|
||||
],
|
||||
"nvidia_nim": [
|
||||
"nvidia_nim/nvidia/mistral-nemo-minitron-8b-8k-instruct",
|
||||
|
||||
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
|
||||
authors = [{ name = "Your Name", email = "you@example.com" }]
|
||||
requires-python = ">=3.10,<3.13"
|
||||
dependencies = [
|
||||
"crewai[tools]>=0.117.0,<1.0.0"
|
||||
"crewai[tools]>=0.114.0,<1.0.0"
|
||||
]
|
||||
|
||||
[project.scripts]
|
||||
|
||||
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
|
||||
authors = [{ name = "Your Name", email = "you@example.com" }]
|
||||
requires-python = ">=3.10,<3.13"
|
||||
dependencies = [
|
||||
"crewai[tools]>=0.117.0,<1.0.0",
|
||||
"crewai[tools]>=0.114.0,<1.0.0",
|
||||
]
|
||||
|
||||
[project.scripts]
|
||||
|
||||
@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10,<3.13"
|
||||
dependencies = [
|
||||
"crewai[tools]>=0.117.0"
|
||||
"crewai[tools]>=0.114.0"
|
||||
]
|
||||
|
||||
[tool.crewai]
|
||||
|
||||
@@ -37,7 +37,6 @@ with warnings.catch_warnings():
|
||||
warnings.simplefilter("ignore", UserWarning)
|
||||
import litellm
|
||||
from litellm import Choices
|
||||
from litellm.exceptions import ContextWindowExceededError
|
||||
from litellm.litellm_core_utils.get_supported_openai_params import (
|
||||
get_supported_openai_params,
|
||||
)
|
||||
@@ -82,26 +81,14 @@ LLM_CONTEXT_WINDOW_SIZES = {
|
||||
"gpt-4o": 128000,
|
||||
"gpt-4o-mini": 128000,
|
||||
"gpt-4-turbo": 128000,
|
||||
"gpt-4.1": 1047576, # Based on official docs
|
||||
"gpt-4.1-mini-2025-04-14": 1047576,
|
||||
"gpt-4.1-nano-2025-04-14": 1047576,
|
||||
"o1-preview": 128000,
|
||||
"o1-mini": 128000,
|
||||
"o3-mini": 200000, # Based on official o3-mini specifications
|
||||
# gemini
|
||||
"gemini-2.0-flash": 1048576,
|
||||
"gemini-2.0-flash-thinking-exp-01-21": 32768,
|
||||
"gemini-2.0-flash-lite-001": 1048576,
|
||||
"gemini-2.0-flash-001": 1048576,
|
||||
"gemini-2.5-flash-preview-04-17": 1048576,
|
||||
"gemini-2.5-pro-exp-03-25": 1048576,
|
||||
"gemini-1.5-pro": 2097152,
|
||||
"gemini-1.5-flash": 1048576,
|
||||
"gemini-1.5-flash-8b": 1048576,
|
||||
"gemini/gemma-3-1b-it": 32000,
|
||||
"gemini/gemma-3-4b-it": 128000,
|
||||
"gemini/gemma-3-12b-it": 128000,
|
||||
"gemini/gemma-3-27b-it": 128000,
|
||||
# deepseek
|
||||
"deepseek-chat": 128000,
|
||||
# groq
|
||||
@@ -598,11 +585,6 @@ class LLM(BaseLLM):
|
||||
self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL)
|
||||
return full_response
|
||||
|
||||
except ContextWindowExceededError as e:
|
||||
# Catch context window errors from litellm and convert them to our own exception type.
|
||||
# This exception is handled by CrewAgentExecutor._invoke_loop() which can then
|
||||
# decide whether to summarize the content or abort based on the respect_context_window flag.
|
||||
raise LLMContextLengthExceededException(str(e))
|
||||
except Exception as e:
|
||||
logging.error(f"Error in streaming response: {str(e)}")
|
||||
if full_response.strip():
|
||||
@@ -717,16 +699,7 @@ class LLM(BaseLLM):
|
||||
str: The response text
|
||||
"""
|
||||
# --- 1) Make the completion call
|
||||
try:
|
||||
# Attempt to make the completion call, but catch context window errors
|
||||
# and convert them to our own exception type for consistent handling
|
||||
# across the codebase. This allows CrewAgentExecutor to handle context
|
||||
# length issues appropriately.
|
||||
response = litellm.completion(**params)
|
||||
except ContextWindowExceededError as e:
|
||||
# Convert litellm's context window error to our own exception type
|
||||
# for consistent handling in the rest of the codebase
|
||||
raise LLMContextLengthExceededException(str(e))
|
||||
response = litellm.completion(**params)
|
||||
|
||||
# --- 2) Extract response message and content
|
||||
response_message = cast(Choices, cast(ModelResponse, response).choices)[
|
||||
@@ -885,17 +858,15 @@ class LLM(BaseLLM):
|
||||
params, callbacks, available_functions
|
||||
)
|
||||
|
||||
except LLMContextLengthExceededException:
|
||||
# Re-raise LLMContextLengthExceededException as it should be handled
|
||||
# by the CrewAgentExecutor._invoke_loop method, which can then decide
|
||||
# whether to summarize the content or abort based on the respect_context_window flag
|
||||
raise
|
||||
except Exception as e:
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
event=LLMCallFailedEvent(error=str(e)),
|
||||
)
|
||||
logging.error(f"LiteLLM call failed: {str(e)}")
|
||||
if not LLMContextLengthExceededException(
|
||||
str(e)
|
||||
)._is_context_limit_error(str(e)):
|
||||
logging.error(f"LiteLLM call failed: {str(e)}")
|
||||
raise
|
||||
|
||||
def _handle_emit_call_events(self, response: Any, call_type: LLMCallType):
|
||||
|
||||
@@ -1,59 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/62RTU+EMBCG7/0VTY9kIQUT1vXqx0njRokxUQ8jDNAILaFdoyH8dwssbNGrTdo0
|
||||
807nnT7TEUpZCjITGRjU7IK+2Ail3XgOmpIGpbHCHLLBBlpzyp1W59xtisGv4RFLSqQpNMJARVVO
|
||||
b1qQKVKhqeftoRXa84JXyZy3/XJ/25wcW1XhUK5WGVZzej8nsFxIocsHBK3kkPaY3O/ZosJncauK
|
||||
plXvQ9M+D3gUxiE/tzs6i+JtyHdkth5N2UFDgXdowFKB5e/Mlqgbk6gPlJfqMFLZTi4Ow5W8O8pG
|
||||
WQArJYw3f4rqK2spKhetQ93+HSphvkes188Jc/iYVU8zH+Jg/N3hP3nt1l7kOJVpUE/YajFNpMDa
|
||||
zsiPAu7nFejS5zxkpCc/6so6tIECAAA=
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:05 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=1219
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,59 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-lite-001:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/61RTU+EMBC98yuanhdSiMjq1Y+Txo0SY6J7GGGARmhJ2zUawn+3wMIWvdpDM5n3
|
||||
Zt7Mm84jhGYgcp6DQU0vyavNENKN/4BJYVAYC8wpm2xBmRN3ep0TW4rBr6GIphWSDFpuoCayILcK
|
||||
RIaEa7IDxXXwJqhT1y/xfnNSU7LGoVUjc6xnej8TaMEF19UjgpZioD2lDzu6oPBZ3smyVfJ9GNhn
|
||||
AQuTMIpjFl/EZyxKwuTcm6VHUXrQUOI9GrCOwLI3tS2a1qTyA8WVPIyOJJOK498K3h5hI+3yKySM
|
||||
N3+a6msryWvXVsdxuzvU3HyPlt68pNTxx6xmmv3xHBt/T/hPWtu1lne8ynSoZ1SaTxcpsbE38qOA
|
||||
+UUNuvJtd/QZC6nXez+t5iqFggIAAA==
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:06 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=1090
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,58 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-thinking-exp-01-21:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/22QQWuEMBCF7/6KkKNsFt1DKb2221vp0koplD0M66jDxkSSWbCI/71Rq+vS5pCE
|
||||
eW9meF8XCSFPYHLKgdHLB/EVKkJ04z1o1jAaDsJcCsUGHF+90+lW/2BhbIcmmVUoTtAQgxa2EM8O
|
||||
zAkFeRHHB3Dk43grV5398j9urvuc1TgMq22Oerb3s0EWZMhXbwjemsH2nr0e5KKSybEN5SSaF4yj
|
||||
5cVDiS/IEJLDkk82ztYNZ/aM5tFexuT306wVp39ltiHkjZLebf4M9U9hJek1vhXZkBA08feIbv+Z
|
||||
yRUFvlk6UxjfY/TLY0L0gc7TxKLEOtBRu22iCg2+UlyROZMpFbaNSlK1S2XURz/Fy1P+CAIAAA==
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:04 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=764
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,59 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-preview-04-17:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/2WQT0+EMBDF7/0UTY9k2ewaDerVPzfjRokxMR4mMEBjaUk76BrCd7fAslvcHppm
|
||||
5s2bvl/HOBcZ6FzmQOjELf/wFc678R56RhNq8o255IsNWDppp9MFby8h3A9DIq2QZ9BIAsVNwR8t
|
||||
6Ay5dDyKdmCli6K1CCb74/tzddpnjcLBrDY5qlnezwJRSC1d9YLgjB5kr+nzThy7Uue49+UNmxeM
|
||||
1qJ1UOITEvjkcMwnGmvqhlLzhfrOtGPy68kr4LRoJzeHPhmfcjmZrM5c3b3fKVXIL0DrI4KS9Duy
|
||||
e3hPRYCBFtYzBhbQElSZtqzo3we37IBrIviG1skJVYm1hxdfrK/iQoGr4sbit8SfeHMZbxPBevYH
|
||||
O2bXiSICAAA=
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:28 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=20971
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,59 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro-exp-03-25:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/12QT2uEMBDF7/kUIUepi2tZaHttu7fSpZVSKD0MOquhmkgygkX87o26cWM9SJj3
|
||||
5s/7DYxzkYMqZAGEVjzwL1fhfJj/k6YVoSIn+JIrtmDo6l2+IXg7C2E/NYmsQp5DKwlqrs/8aEDl
|
||||
yKXlUXQCI20U7UTQOa7v75vrPqNrnIY1usDa20dvEGeppK3eEKxWk+09ez2JVZWqwN6VE+YXzKNF
|
||||
Z6HEFyRwyWHNJ1qjm5Yy/YPqUXdz8rtlVsBpI++T5GIg7WL+03xzMNc+ua2yDgkGcF1IqCX9zvSe
|
||||
PzMRgKDNWR4EC3gJqnRXVrQ98T5lF2ALww80Vi6wSmwcvjjdHWJ3Yox9Gye3cXoQbGR/TedYqx4C
|
||||
AAA=
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:30 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=2418
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,59 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemma-3-12b-it:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/2WRTWvDMAyG7/kVwpdBSEvX7jB23QfsMFa2MAZbD2qipGaOFWwFWkr/+5ykaVPq
|
||||
gGP0SvLrR/sIQGVoc52jkFcP8BMiAPtubzW2QlaCMIRCsEYn59x+7UfnkCK0bYtUuiHIsNaCBriA
|
||||
F4c2I9Ae4niJTvs4nv7a/nuVGw9oPIOEIoOuJC+QadmBtkNlsAoIpeF1aJgFZ+SgYAfBUQIF+o1m
|
||||
m0CJXhxbrnZJV5E1RhpHUzUyeTidV8n5aY4Ntb4rzskM6YchQRXaar/5IPRs27TP9H2pTqq2OW1D
|
||||
eBYNF3StVeOxpDcSDJDxhFLVjqtaUv4j+8hNB/m+7zUayYW8mB914QD0QrqbJVdd/VO4U5vxqEZT
|
||||
DE9EE+h2Y3r+TtUIg1yYGjB0/1V0BNIz+iLndQ+jpKrCyWJyO19PtKjoEP0DlZtdIF8CAAA=
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:39 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=3835
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,60 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemma-3-1b-it:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/2VRy07DQAy85yusPUZtBSoIxJWHxAFRQYSQKAc3cVqL7DrKuqKlqsRv8Ht8CZuk
|
||||
aVOxh314xuP1eBMBmBRdxhkqeXMFbyECsGn2GhOn5DQAXSgES6z0wG3XpncPFKVVnWSSBUGKJSsW
|
||||
IDncVehSAvYQxxOs2MfxCKZu6u719/vHA0Iq1ooDyz6UTqlUDi9doELDr1M1aMbiinXcSQ9gtlTg
|
||||
VqOGJc855VAztAZWvMInZ1SsoaJU5o6/KANxNDK9X2/39/fBoddKCqobsRLyO/q2I5icHfvFE6EX
|
||||
V9Oek8eJ2aPsMlqF8EnUFWikzdLjnB5IMbiOe29NWYktNZEPcteybFy/bLV6MzqCxxc7XCXYcASd
|
||||
nQ/+qfqbUJOL/ux6Yw0tYsG6buZ2+5qYng169KnOhuZ8j3aGtB69UOW5NWNO1uJwPDydDVlNtI3+
|
||||
AD6XWQdvAgAA
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:32 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=1535
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,60 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemma-3-27b-it:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/2VRXUvDMBR976+45EUo3RDnUHwTnSA4HFpEcHuI7e16aZqU5NZNxv67abtuHTbQ
|
||||
hHPu5zm7AEAkUqeUSkYn7uDLIwC79t9wRjNq9kQPebCSlk+x3bcbvH0I47ZJEnGOkMiKWCowGTxZ
|
||||
qRMEchCGC2nJheEYlnqpn/nCQaHNRkNmLJDvSwkoP1kpbeFAUYHAvtiMsgwVxGaDNmqRF1P/WIR5
|
||||
7bAuI/ApLXxvE0gRYkumrHL0hIMNKtXcxA4y6XIyOoKkJkcau8ykVlxbHDczNUcM1tof36voJIY1
|
||||
CptNS5Oi6sP3fYDISJPL31A6o5uw9/h1IY4s6RS3Hr4M+gZtaVE7ucY5svS2yKP4orJ+F45NgfrB
|
||||
1K0tt12tgYln9PX0wLPxFpxR00n0r6p79D1JDc0d+O5XlIr4tzV29hmLgQx8NlQvQ3uvgoMgnUYf
|
||||
aB11YqyxLOVoMrq6+R4Ri2Af/AEDrXcbkQIAAA==
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:41 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=2447
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,60 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"contents": [{"role": "user", "parts": [{"text": "What is the capital
|
||||
of France?"}]}], "generationConfig": {"stop_sequences": []}}'
|
||||
headers:
|
||||
accept:
|
||||
- '*/*'
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '131'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- generativelanguage.googleapis.com
|
||||
user-agent:
|
||||
- litellm/1.60.2
|
||||
method: POST
|
||||
uri: https://generativelanguage.googleapis.com/v1beta/models/gemma-3-4b-it:generateContent
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAC/2WRzUrDQBDH73mKYY+lLUKLiBcPfoAHsWhQwXqYJtNk6WYn7E6woRQ8+wR68t18
|
||||
Ah/BbWraFPeQXeb/z3z8ZhUBqARtqlMU8uoUnkMEYNV8NxpbIStBaEMhWKKTvXd7Vp13sAgtNz+p
|
||||
OCdIsNSCBngOVw5tQqA99HoTdNr3ekOY2qm9lu+3Tw8ImeFZ8CahKDmYs4NQrA9z9Llm24cMvTi2
|
||||
XNQQ2oakMlI5GsLP18d7k+mRK5NCzRUYvSAQhoXl12CuJdc2g4IdAc64Emg6OFOdzte790t/P69j
|
||||
Q5thCk7JtPZ1a1BzbbXP7wg9243tPr6dqJ2qbUrLED6K2gJNalV5zOiGBAN53PFVpeOilJgXZM+5
|
||||
asifbHN19nQgj1pdOFA+kMbH/X9Z/UWoqU13f53VhhHRaKmb3V0+xaqDQQ6aajE090v0B2TL6IGc
|
||||
11sYGRUFDkaD8WygRUXr6BcxmBLccwIAAA==
|
||||
headers:
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json; charset=UTF-8
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 14:25:35 GMT
|
||||
Server:
|
||||
- scaffolding on HTTPServer2
|
||||
Server-Timing:
|
||||
- gfet4t7; dur=2349
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
Vary:
|
||||
- Origin
|
||||
- X-Origin
|
||||
- Referer
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
X-Frame-Options:
|
||||
- SAMEORIGIN
|
||||
X-XSS-Protection:
|
||||
- '0'
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,101 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"messages": [{"role": "user", "content": "What is the capital of France?"}],
|
||||
"model": "gpt-4.1-mini-2025-04-14", "stop": []}'
|
||||
headers:
|
||||
accept:
|
||||
- application/json
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '125'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- api.openai.com
|
||||
user-agent:
|
||||
- OpenAI/Python 1.68.2
|
||||
x-stainless-arch:
|
||||
- arm64
|
||||
x-stainless-async:
|
||||
- 'false'
|
||||
x-stainless-lang:
|
||||
- python
|
||||
x-stainless-os:
|
||||
- MacOS
|
||||
x-stainless-package-version:
|
||||
- 1.68.2
|
||||
x-stainless-raw-response:
|
||||
- 'true'
|
||||
x-stainless-read-timeout:
|
||||
- '600.0'
|
||||
x-stainless-retry-count:
|
||||
- '0'
|
||||
x-stainless-runtime:
|
||||
- CPython
|
||||
x-stainless-runtime-version:
|
||||
- 3.11.12
|
||||
method: POST
|
||||
uri: https://api.openai.com/v1/chat/completions
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAAAwAAAP//jJJPb9swDMXv/hSCznEQe+7S5LgAGzDs0P3paSgMRqJtZrIkSPTQoch3
|
||||
H2Snsbt1wC4+8MdHv0fxKRNCkpZ7IVUHrHpv8nd3t4eIH77w4ePX+/b+8XP56bTdHE7dgb2Sq6Rw
|
||||
xxMqflatleu9QSZnJ6wCAmOaWmyrmzflrqrejqB3Gk2StZ7zal3kPVnKy015k2+qvKgu8s6Rwij3
|
||||
4nsmhBBP4zcZtRof5V5sVs+VHmOEFuX+2iSEDM6kioQYKTJYlqsZKmcZ7ej9W4dCgScGI1wj3gew
|
||||
CgVFcQeB4nqpCtgMEZJ1OxizAGCtY0jRR78PF3K+OjSu9cEd4x9S2ZCl2NUBITqb3ER2Xo70nAnx
|
||||
MG5ieBFO+uB6zzW7Hzj+rqimcXJ+gBneXhg7BjOXy3L1yrBaIwOZuFikVKA61LNy3joMmtwCZIvI
|
||||
f3t5bfYUm2z7P+NnoBR6Rl37gJrUy7xzW8B0nf9qu654NCwjhp+ksGbCkJ5BYwODmU5Gxl+Rsa8b
|
||||
si0GH2i6m8bX291xuztiVTQyO2e/AQAA//8DAP7WRo9GAwAA
|
||||
headers:
|
||||
CF-RAY:
|
||||
- 93458dcf6d0ef53b-GRU
|
||||
Connection:
|
||||
- keep-alive
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 13:44:07 GMT
|
||||
Server:
|
||||
- cloudflare
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
access-control-expose-headers:
|
||||
- X-Request-ID
|
||||
alt-svc:
|
||||
- h3=":443"; ma=86400
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
openai-processing-ms:
|
||||
- '1391'
|
||||
openai-version:
|
||||
- '2020-10-01'
|
||||
strict-transport-security:
|
||||
- max-age=31536000; includeSubDomains; preload
|
||||
x-ratelimit-limit-requests:
|
||||
- '30000'
|
||||
x-ratelimit-limit-tokens:
|
||||
- '150000000'
|
||||
x-ratelimit-remaining-requests:
|
||||
- '29999'
|
||||
x-ratelimit-remaining-tokens:
|
||||
- '149999989'
|
||||
x-ratelimit-reset-requests:
|
||||
- 2ms
|
||||
x-ratelimit-reset-tokens:
|
||||
- 0s
|
||||
x-request-id:
|
||||
- req_74408ec81f430b6e9795cf5332262b8d
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,101 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"messages": [{"role": "user", "content": "What is the capital of France?"}],
|
||||
"model": "gpt-4.1-nano-2025-04-14", "stop": []}'
|
||||
headers:
|
||||
accept:
|
||||
- application/json
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '125'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- api.openai.com
|
||||
user-agent:
|
||||
- OpenAI/Python 1.68.2
|
||||
x-stainless-arch:
|
||||
- arm64
|
||||
x-stainless-async:
|
||||
- 'false'
|
||||
x-stainless-lang:
|
||||
- python
|
||||
x-stainless-os:
|
||||
- MacOS
|
||||
x-stainless-package-version:
|
||||
- 1.68.2
|
||||
x-stainless-raw-response:
|
||||
- 'true'
|
||||
x-stainless-read-timeout:
|
||||
- '600.0'
|
||||
x-stainless-retry-count:
|
||||
- '0'
|
||||
x-stainless-runtime:
|
||||
- CPython
|
||||
x-stainless-runtime-version:
|
||||
- 3.11.12
|
||||
method: POST
|
||||
uri: https://api.openai.com/v1/chat/completions
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAAAwAAAP//jJJPb9swDMXv/hSCznEQuwrq5bgNBbZTh7aHYigMRqJtbbKkSXT/oMh3
|
||||
L2Snsdt1wC4+8MdHv0fxOWOMa8V3jMsOSPbe5J8vqy/D96K/+PPjSn/Fh5szMewfb/eiar/d8lVS
|
||||
uP0vlPSqWkvXe4OknZ2wDAiEaWpxLrZn5SchqhH0TqFJstZTLtZFbsG6vNyU23wj8kIc5Z3TEiPf
|
||||
sZ8ZY4w9j99k1Cp85Du2Wb1WeowRWuS7UxNjPDiTKhxi1JHAEl/NUDpLaEfv1x0yCV4TGOYadhHA
|
||||
SmQ6sksIOq6XqoDNECFZt4MxCwDWOoIUffR7dySHk0PjWh/cPr6T8kZbHbs6IERnk5tIzvORHjLG
|
||||
7sZNDG/CcR9c76km9xvH3xViGsfnB5hhdWTkCMxcLsvVB8NqhQTaxMUiuQTZoZqV89ZhUNotQLaI
|
||||
/LeXj2ZPsbVt/2f8DKRET6hqH1Bp+Tbv3BYwXee/2k4rHg3ziOFeS6xJY0jPoLCBwUwnw+NTJOzr
|
||||
RtsWgw96upvG14gKq2ajxJZnh+wFAAD//wMATWCJPkYDAAA=
|
||||
headers:
|
||||
CF-RAY:
|
||||
- 93458dd9aebff53b-GRU
|
||||
Connection:
|
||||
- keep-alive
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 13:44:08 GMT
|
||||
Server:
|
||||
- cloudflare
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
access-control-expose-headers:
|
||||
- X-Request-ID
|
||||
alt-svc:
|
||||
- h3=":443"; ma=86400
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
openai-processing-ms:
|
||||
- '134'
|
||||
openai-version:
|
||||
- '2020-10-01'
|
||||
strict-transport-security:
|
||||
- max-age=31536000; includeSubDomains; preload
|
||||
x-ratelimit-limit-requests:
|
||||
- '30000'
|
||||
x-ratelimit-limit-tokens:
|
||||
- '150000000'
|
||||
x-ratelimit-remaining-requests:
|
||||
- '29999'
|
||||
x-ratelimit-remaining-tokens:
|
||||
- '149999990'
|
||||
x-ratelimit-reset-requests:
|
||||
- 2ms
|
||||
x-ratelimit-reset-tokens:
|
||||
- 0s
|
||||
x-request-id:
|
||||
- req_0ba738662e063fb55ea01793aafdcecc
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -1,101 +0,0 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"messages": [{"role": "user", "content": "What is the capital of France?"}],
|
||||
"model": "gpt-4.1", "stop": []}'
|
||||
headers:
|
||||
accept:
|
||||
- application/json
|
||||
accept-encoding:
|
||||
- gzip, deflate
|
||||
connection:
|
||||
- keep-alive
|
||||
content-length:
|
||||
- '109'
|
||||
content-type:
|
||||
- application/json
|
||||
host:
|
||||
- api.openai.com
|
||||
user-agent:
|
||||
- OpenAI/Python 1.68.2
|
||||
x-stainless-arch:
|
||||
- arm64
|
||||
x-stainless-async:
|
||||
- 'false'
|
||||
x-stainless-lang:
|
||||
- python
|
||||
x-stainless-os:
|
||||
- MacOS
|
||||
x-stainless-package-version:
|
||||
- 1.68.2
|
||||
x-stainless-raw-response:
|
||||
- 'true'
|
||||
x-stainless-read-timeout:
|
||||
- '600.0'
|
||||
x-stainless-retry-count:
|
||||
- '0'
|
||||
x-stainless-runtime:
|
||||
- CPython
|
||||
x-stainless-runtime-version:
|
||||
- 3.11.12
|
||||
method: POST
|
||||
uri: https://api.openai.com/v1/chat/completions
|
||||
response:
|
||||
body:
|
||||
string: !!binary |
|
||||
H4sIAAAAAAAAA4xSwYrbMBC9+yvEHEMcHMeh3dx2SwttoYTSW1nMRB7b2pUlIY27XZb8e5GdxM5u
|
||||
C734MG/e83tP85IIAaqCnQDZIsvO6fRu//6Db26fnvTtx8/5t7v95rmT3y1+pc0XDcvIsIcHknxm
|
||||
raTtnCZW1oyw9IRMUXX9rthu8pui2A5AZyvSkdY4TovVOs2zfJtmRbouTszWKkkBduJnIoQQL8M3
|
||||
ejQV/YadyJbnSUchYEOwuywJAd7qOAEMQQVGw7CcQGkNkxls/2hJSHSKUQtbi08ejSShglgs9uhV
|
||||
WCxWc6anug8YnZte6xmAxljGmHzwfH9CjheX2jbO20N4RYVaGRXa0hMGa6KjwNbBgB4TIe6HNvqr
|
||||
gOC87RyXbB9p+N26GOVg6n8GnpoCtox6mudn0pVaWRGj0mHWJkiULVUTc6oe+0rZGZDMMr818zft
|
||||
Mbcyzf/IT4CU5Jiq0nmqlLwOPK15itf5r7VLx4NhCOR/KUklK/LxHSqqsdfj3UB4DkxdWSvTkHde
|
||||
jcdTuxJllh2yLMskJMfkDwAAAP//AwC4aq9JRgMAAA==
|
||||
headers:
|
||||
CF-RAY:
|
||||
- 93458dcc1b9df53b-GRU
|
||||
Connection:
|
||||
- keep-alive
|
||||
Content-Encoding:
|
||||
- gzip
|
||||
Content-Type:
|
||||
- application/json
|
||||
Date:
|
||||
- Tue, 22 Apr 2025 13:44:06 GMT
|
||||
Server:
|
||||
- cloudflare
|
||||
Transfer-Encoding:
|
||||
- chunked
|
||||
X-Content-Type-Options:
|
||||
- nosniff
|
||||
access-control-expose-headers:
|
||||
- X-Request-ID
|
||||
alt-svc:
|
||||
- h3=":443"; ma=86400
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
openai-processing-ms:
|
||||
- '296'
|
||||
openai-version:
|
||||
- '2020-10-01'
|
||||
strict-transport-security:
|
||||
- max-age=31536000; includeSubDomains; preload
|
||||
x-ratelimit-limit-requests:
|
||||
- '10000'
|
||||
x-ratelimit-limit-tokens:
|
||||
- '30000000'
|
||||
x-ratelimit-remaining-requests:
|
||||
- '9999'
|
||||
x-ratelimit-remaining-tokens:
|
||||
- '29999989'
|
||||
x-ratelimit-reset-requests:
|
||||
- 6ms
|
||||
x-ratelimit-reset-tokens:
|
||||
- 0s
|
||||
x-request-id:
|
||||
- req_7b4e1628a0608e9547e71e7857a29b58
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
@@ -256,52 +256,6 @@ def test_validate_call_params_no_response_format():
|
||||
llm._validate_call_params()
|
||||
|
||||
|
||||
@pytest.mark.vcr(filter_headers=["authorization"], filter_query_parameters=["key"])
|
||||
@pytest.mark.parametrize(
|
||||
"model",
|
||||
[
|
||||
"gemini/gemini-2.0-flash-thinking-exp-01-21",
|
||||
"gemini/gemini-2.0-flash-001",
|
||||
"gemini/gemini-2.0-flash-lite-001",
|
||||
"gemini/gemini-2.5-flash-preview-04-17",
|
||||
"gemini/gemini-2.5-pro-exp-03-25",
|
||||
],
|
||||
)
|
||||
def test_gemini_models(model):
|
||||
llm = LLM(model=model)
|
||||
result = llm.call("What is the capital of France?")
|
||||
assert isinstance(result, str)
|
||||
assert "Paris" in result
|
||||
|
||||
|
||||
@pytest.mark.vcr(filter_headers=["authorization"], filter_query_parameters=["key"])
|
||||
@pytest.mark.parametrize(
|
||||
"model",
|
||||
[
|
||||
"gemini/gemma-3-1b-it",
|
||||
"gemini/gemma-3-4b-it",
|
||||
"gemini/gemma-3-12b-it",
|
||||
"gemini/gemma-3-27b-it",
|
||||
],
|
||||
)
|
||||
def test_gemma3(model):
|
||||
llm = LLM(model=model)
|
||||
result = llm.call("What is the capital of France?")
|
||||
assert isinstance(result, str)
|
||||
assert "Paris" in result
|
||||
|
||||
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
@pytest.mark.parametrize(
|
||||
"model", ["gpt-4.1", "gpt-4.1-mini-2025-04-14", "gpt-4.1-nano-2025-04-14"]
|
||||
)
|
||||
def test_gpt_4_1(model):
|
||||
llm = LLM(model=model)
|
||||
result = llm.call("What is the capital of France?")
|
||||
assert isinstance(result, str)
|
||||
assert "Paris" in result
|
||||
|
||||
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_o3_mini_reasoning_effort_high():
|
||||
llm = LLM(
|
||||
@@ -373,45 +327,6 @@ def get_weather_tool_schema():
|
||||
},
|
||||
}
|
||||
|
||||
def test_context_window_exceeded_error_handling():
|
||||
"""Test that litellm.ContextWindowExceededError is converted to LLMContextLengthExceededException."""
|
||||
from litellm.exceptions import ContextWindowExceededError
|
||||
|
||||
from crewai.utilities.exceptions.context_window_exceeding_exception import (
|
||||
LLMContextLengthExceededException,
|
||||
)
|
||||
|
||||
llm = LLM(model="gpt-4")
|
||||
|
||||
# Test non-streaming response
|
||||
with patch("litellm.completion") as mock_completion:
|
||||
mock_completion.side_effect = ContextWindowExceededError(
|
||||
"This model's maximum context length is 8192 tokens. However, your messages resulted in 10000 tokens.",
|
||||
model="gpt-4",
|
||||
llm_provider="openai"
|
||||
)
|
||||
|
||||
with pytest.raises(LLMContextLengthExceededException) as excinfo:
|
||||
llm.call("This is a test message")
|
||||
|
||||
assert "context length exceeded" in str(excinfo.value).lower()
|
||||
assert "8192 tokens" in str(excinfo.value)
|
||||
|
||||
# Test streaming response
|
||||
llm = LLM(model="gpt-4", stream=True)
|
||||
with patch("litellm.completion") as mock_completion:
|
||||
mock_completion.side_effect = ContextWindowExceededError(
|
||||
"This model's maximum context length is 8192 tokens. However, your messages resulted in 10000 tokens.",
|
||||
model="gpt-4",
|
||||
llm_provider="openai"
|
||||
)
|
||||
|
||||
with pytest.raises(LLMContextLengthExceededException) as excinfo:
|
||||
llm.call("This is a test message")
|
||||
|
||||
assert "context length exceeded" in str(excinfo.value).lower()
|
||||
assert "8192 tokens" in str(excinfo.value)
|
||||
|
||||
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
@pytest.fixture
|
||||
|
||||
247
uv.lock
generated
247
uv.lock
generated
@@ -1,78 +1,32 @@
|
||||
version = 1
|
||||
revision = 1
|
||||
requires-python = ">=3.10, <3.13"
|
||||
resolution-markers = [
|
||||
"python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_version < '0'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -380,7 +334,7 @@ name = "build"
|
||||
version = "1.2.2.post1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "colorama", marker = "os_name == 'nt'" },
|
||||
{ name = "colorama", marker = "(os_name == 'nt' and platform_machine != 'aarch64' and sys_platform == 'linux') or (os_name == 'nt' and sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
{ name = "importlib-metadata", marker = "python_full_version < '3.10.2'" },
|
||||
{ name = "packaging" },
|
||||
{ name = "pyproject-hooks" },
|
||||
@@ -615,7 +569,7 @@ name = "click"
|
||||
version = "8.1.8"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "colorama", marker = "platform_system == 'Windows'" },
|
||||
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/b9/2e/0090cbf739cee7d23781ad4b89a9894a41538e4fcf4c31dcdd705b78eb8b/click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a", size = 226593 }
|
||||
wheels = [
|
||||
@@ -666,7 +620,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "crewai"
|
||||
version = "0.117.0"
|
||||
version = "0.114.0"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "appdirs" },
|
||||
@@ -781,6 +735,7 @@ requires-dist = [
|
||||
{ name = "tomli-w", specifier = ">=1.1.0" },
|
||||
{ name = "uv", specifier = ">=0.4.25" },
|
||||
]
|
||||
provides-extras = ["tools", "embeddings", "agentops", "fastembed", "pdfplumber", "pandas", "openpyxl", "mem0", "docling", "aisuite"]
|
||||
|
||||
[package.metadata.requires-dev]
|
||||
dev = [
|
||||
@@ -2554,7 +2509,7 @@ version = "1.6.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "click" },
|
||||
{ name = "colorama", marker = "platform_system == 'Windows'" },
|
||||
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||
{ name = "ghp-import" },
|
||||
{ name = "jinja2" },
|
||||
{ name = "markdown" },
|
||||
@@ -2735,7 +2690,7 @@ version = "2.10.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pygments" },
|
||||
{ name = "pywin32", marker = "platform_system == 'Windows'" },
|
||||
{ name = "pywin32", marker = "sys_platform == 'win32'" },
|
||||
{ name = "tqdm" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/3a/93/80ac75c20ce54c785648b4ed363c88f148bf22637e10c9863db4fbe73e74/mpire-2.10.2.tar.gz", hash = "sha256:f66a321e93fadff34585a4bfa05e95bd946cf714b442f51c529038eb45773d97", size = 271270 }
|
||||
@@ -2982,7 +2937,7 @@ name = "nvidia-cudnn-cu12"
|
||||
version = "9.1.0.70"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/9f/fd/713452cd72343f682b1c7b9321e23829f00b842ceaedcda96e742ea0b0b3/nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl", hash = "sha256:165764f44ef8c61fcdfdfdbe769d687e06374059fbb388b6c89ecb0e28793a6f", size = 664752741 },
|
||||
@@ -3009,9 +2964,9 @@ name = "nvidia-cusolver-cu12"
|
||||
version = "11.4.5.107"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/bc/1d/8de1e5c67099015c834315e333911273a8c6aaba78923dd1d1e25fc5f217/nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd", size = 124161928 },
|
||||
@@ -3022,7 +2977,7 @@ name = "nvidia-cusparse-cu12"
|
||||
version = "12.1.0.106"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/65/5b/cfaeebf25cd9fdec14338ccb16f6b2c4c7fa9163aefcf057d86b9cc248bb/nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c", size = 195958278 },
|
||||
@@ -3033,7 +2988,6 @@ name = "nvidia-nccl-cu12"
|
||||
version = "2.20.5"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/c1/bb/d09dda47c881f9ff504afd6f9ca4f502ded6d8fc2f572cacc5e39da91c28/nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1fc150d5c3250b170b29410ba682384b14581db722b2531b0d8d33c595f33d01", size = 176238458 },
|
||||
{ url = "https://files.pythonhosted.org/packages/4b/2a/0a131f572aa09f741c30ccd45a8e56316e8be8dfc7bc19bf0ab7cfef7b19/nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56", size = 176249402 },
|
||||
]
|
||||
|
||||
@@ -3043,7 +2997,6 @@ version = "12.6.85"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/9d/d7/c5383e47c7e9bf1c99d5bd2a8c935af2b6d705ad831a7ec5c97db4d82f4f/nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:eedc36df9e88b682efe4309aa16b5b4e78c2407eac59e8c10a6a47535164369a", size = 19744971 },
|
||||
{ url = "https://files.pythonhosted.org/packages/31/db/dc71113d441f208cdfe7ae10d4983884e13f464a6252450693365e166dcf/nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cf4eaa7d4b6b543ffd69d6abfb11efdeb2db48270d94dfd3a452c24150829e41", size = 19270338 },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -3561,7 +3514,7 @@ name = "portalocker"
|
||||
version = "2.10.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pywin32", marker = "platform_system == 'Windows'" },
|
||||
{ name = "pywin32", marker = "sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ed/d3/c6c64067759e87af98cc668c1cc75171347d0f1577fab7ca3749134e3cd4/portalocker-2.10.1.tar.gz", hash = "sha256:ef1bf844e878ab08aee7e40184156e1151f228f103aa5c6bd0724cc330960f8f", size = 40891 }
|
||||
wheels = [
|
||||
@@ -5069,19 +5022,19 @@ dependencies = [
|
||||
{ name = "fsspec" },
|
||||
{ name = "jinja2" },
|
||||
{ name = "networkx" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "sympy" },
|
||||
{ name = "triton", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
|
||||
{ name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
wheels = [
|
||||
@@ -5128,7 +5081,7 @@ name = "tqdm"
|
||||
version = "4.66.5"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "colorama", marker = "platform_system == 'Windows'" },
|
||||
{ name = "colorama", marker = "sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/58/83/6ba9844a41128c62e810fddddd72473201f3eacde02046066142a2d96cc5/tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad", size = 169504 }
|
||||
wheels = [
|
||||
@@ -5170,7 +5123,7 @@ name = "triton"
|
||||
version = "3.0.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "filelock", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
|
||||
{ name = "filelock", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/45/27/14cc3101409b9b4b9241d2ba7deaa93535a217a211c86c4cc7151fb12181/triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a", size = 209376304 },
|
||||
@@ -5326,42 +5279,18 @@ name = "vcrpy"
|
||||
version = "5.1.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
resolution-markers = [
|
||||
"python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
]
|
||||
dependencies = [
|
||||
{ name = "pyyaml", marker = "platform_python_implementation == 'PyPy'" },
|
||||
@@ -5378,42 +5307,18 @@ name = "vcrpy"
|
||||
version = "7.0.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
resolution-markers = [
|
||||
"python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
]
|
||||
dependencies = [
|
||||
{ name = "pyyaml", marker = "platform_python_implementation != 'PyPy'" },
|
||||
|
||||
Reference in New Issue
Block a user