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Overview
CrewAI supports native multimodal file inputs, allowing you to pass images, PDFs, audio, video, and text files directly to your agents. Files are automatically formatted for each LLM provider's API requirements.
Note
File support requires the optional crewai-files package. Install it with:
uv add 'crewai[file-processing]'Note
The file processing API is currently in early access.
File Types
CrewAI supports five specific file types plus a generic File class that auto-detects the type:
| Type | Class | Use Cases |
|---|---|---|
| Image | ImageFile | Photos, screenshots, diagrams, charts |
PDFFile | Documents, reports, papers | |
| Audio | AudioFile | Voice recordings, podcasts, meetings |
| Video | VideoFile | Screen recordings, presentations |
| Text | TextFile | Code files, logs, data files |
| Generic | File | Auto-detect type from content |
from crewai_files import File, ImageFile, PDFFile, AudioFile, VideoFile, TextFile
image = ImageFile(source="screenshot.png")
pdf = PDFFile(source="report.pdf")
audio = AudioFile(source="meeting.mp3")
video = VideoFile(source="demo.mp4")
text = TextFile(source="data.csv")
file = File(source="document.pdf")File Sources
The source parameter accepts multiple input types and auto-detects the appropriate handler:
From Path
from crewai_files import ImageFile
image = ImageFile(source="./images/chart.png")From URL
from crewai_files import ImageFile
image = ImageFile(source="https://example.com/image.png")From Bytes
from crewai_files import ImageFile, FileBytes
image_bytes = download_image_from_api()
image = ImageFile(source=FileBytes(data=image_bytes, filename="downloaded.png"))
image = ImageFile(source=image_bytes)Using Files
Files can be passed at multiple levels, with more specific levels taking precedence.
With Crews
Pass files when kicking off a crew:
from crewai import Crew
from crewai_files import ImageFile
crew = Crew(agents=[analyst], tasks=[analysis_task])
result = crew.kickoff(
inputs={"topic": "Q4 Sales"},
input_files={
"chart": ImageFile(source="sales_chart.png"),
"report": PDFFile(source="quarterly_report.pdf"),
}
)With Tasks
Attach files to specific tasks:
from crewai import Task
from crewai_files import ImageFile
task = Task(
description="Analyze the sales chart and identify trends in {chart}",
expected_output="A summary of key trends",
input_files={
"chart": ImageFile(source="sales_chart.png"),
}
)With Flows
Pass files to flows, which automatically inherit to crews:
from crewai.flow.flow import Flow, start
from crewai_files import ImageFile
class AnalysisFlow(Flow):
@start()
def analyze(self):
return self.analysis_crew.kickoff()
flow = AnalysisFlow()
result = flow.kickoff(
input_files={"image": ImageFile(source="data.png")}
)With Standalone Agents
Pass files directly to agent kickoff:
from crewai import Agent
from crewai_files import ImageFile
agent = Agent(
role="Image Analyst",
goal="Analyze images",
backstory="Expert at visual analysis",
llm="gpt-4o",
)
result = agent.kickoff(
messages="What's in this image?",
input_files={"photo": ImageFile(source="photo.jpg")},
)File Precedence
When files are passed at multiple levels, more specific levels override broader ones:
Flow input_files < Crew input_files < Task input_files
For example, if both Flow and Task define a file named "chart", the Task's version is used.
Provider Support
Different providers support different file types. CrewAI automatically formats files for each provider's API.
| Provider | Image | Audio | Video | Text | |
|---|---|---|---|---|---|
| OpenAI (completions API) | ✓ | ||||
| OpenAI (responses API) | ✓ | ✓ | ✓ | ||
| Anthropic (claude-3.x) | ✓ | ✓ | |||
| Google Gemini (gemini-1.5, 2.0, 2.5) | ✓ | ✓ | ✓ | ✓ | ✓ |
| AWS Bedrock (claude-3) | ✓ | ✓ | |||
| Azure OpenAI (gpt-4o) | ✓ | ✓ |
Note
Google Gemini models support all file types including video (up to 1 hour, 2GB). Use Gemini when you need to process video content.
Note
If you pass a file type that the provider doesn't support (e.g., video to OpenAI), you'll receive an UnsupportedFileTypeError. Choose your provider based on the file types you need to process.
How Files Are Sent
CrewAI automatically chooses the optimal method to send files to each provider:
| Method | Description | Used When |
|---|---|---|
| Inline Base64 | File embedded directly in the request | Small files (< 5MB typically) |
| File Upload API | File uploaded separately, referenced by ID | Large files that exceed threshold |
| URL Reference | Direct URL passed to the model | File source is already a URL |
Provider Transmission Methods
| Provider | Inline Base64 | File Upload API | URL References |
|---|---|---|---|
| OpenAI | ✓ | ✓ (> 5 MB) | ✓ |
| Anthropic | ✓ | ✓ (> 5 MB) | ✓ |
| Google Gemini | ✓ | ✓ (> 20 MB) | ✓ |
| AWS Bedrock | ✓ | ✓ (S3 URIs) | |
| Azure OpenAI | ✓ | ✓ |
Note
You don't need to manage this yourself. CrewAI automatically uses the most efficient method based on file size and provider capabilities. Providers without file upload APIs use inline base64 for all files.
File Handling Modes
Control how files are processed when they exceed provider limits:
from crewai_files import ImageFile, PDFFile
image = ImageFile(source="large.png", mode="strict")
image = ImageFile(source="large.png", mode="auto")
image = ImageFile(source="large.png", mode="warn")
pdf = PDFFile(source="large.pdf", mode="chunk")Provider Constraints
Each provider has specific limits for file sizes and dimensions:
OpenAI
- Images: Max 20 MB, up to 10 images per request
- PDFs: Max 32 MB, up to 100 pages
- Audio: Max 25 MB, up to 25 minutes
Anthropic
- Images: Max 5 MB, max 8000x8000 pixels, up to 100 images
- PDFs: Max 32 MB, up to 100 pages
Google Gemini
- Images: Max 100 MB
- PDFs: Max 50 MB
- Audio: Max 100 MB, up to 9.5 hours
- Video: Max 2 GB, up to 1 hour
AWS Bedrock
- Images: Max 3.75 MB, max 8000x8000 pixels
- PDFs: Max 4.5 MB, up to 100 pages
Referencing Files in Prompts
Use the file's key name in your task descriptions to reference files:
task = Task(
description="""
Analyze the provided materials:
1. Review the chart in {sales_chart}
2. Cross-reference with data in {quarterly_report}
3. Summarize key findings
""",
expected_output="Analysis summary with key insights",
input_files={
"sales_chart": ImageFile(source="chart.png"),
"quarterly_report": PDFFile(source="report.pdf"),
}
)