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https://github.com/crewAIInc/crewAI.git
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ae59abb052
- Add google-generativeai dependency to pyproject.toml - Extend LLM class with batch mode parameters (batch_mode, batch_size, batch_timeout) - Implement batch request management methods for Gemini models - Add batch-specific event types (BatchJobStartedEvent, BatchJobCompletedEvent, BatchJobFailedEvent) - Create comprehensive test suite for batch mode functionality - Add example demonstrating batch mode usage with cost savings - Support inline batch requests for up to 50% cost reduction on Gemini models Resolves issue #3116 Co-Authored-By: João <joao@crewai.com>
64 lines
1.7 KiB
Python
64 lines
1.7 KiB
Python
"""
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Example demonstrating Google Batch Mode support in CrewAI.
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This example shows how to use batch mode with Gemini models to reduce costs
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by up to 50% for non-urgent LLM calls.
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"""
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import os
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from crewai import Agent, Task, Crew
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from crewai.llm import LLM
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os.environ["GOOGLE_API_KEY"] = "your-google-api-key-here"
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def main():
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batch_llm = LLM(
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model="gemini/gemini-1.5-pro",
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batch_mode=True,
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batch_size=5, # Process 5 requests at once
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batch_timeout=300, # Wait up to 5 minutes for batch completion
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temperature=0.7
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)
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research_agent = Agent(
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role="Research Analyst",
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goal="Analyze market trends and provide insights",
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backstory="You are an expert market analyst with years of experience.",
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llm=batch_llm,
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verbose=True
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)
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tasks = []
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topics = [
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"artificial intelligence market trends",
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"renewable energy investment opportunities",
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"cryptocurrency regulatory landscape",
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"e-commerce growth projections",
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"healthcare technology innovations"
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]
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for topic in topics:
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task = Task(
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description=f"Research and analyze {topic}. Provide a brief summary of key trends and insights.",
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agent=research_agent,
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expected_output="A concise analysis with key findings and trends"
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)
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tasks.append(task)
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crew = Crew(
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agents=[research_agent],
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tasks=tasks,
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verbose=True
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)
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print("Starting batch processing...")
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print("Note: Batch requests will be queued until batch_size is reached")
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result = crew.kickoff()
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print("Batch processing completed!")
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print("Results:", result)
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if __name__ == "__main__":
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main()
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