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Documentation Index

Fetch the complete documentation index at: https://docs.timbal.ai/llms.txt

Use this file to discover all available pages before exploring further.

Agents can analyze EML files to extract key information and provide summaries. First validate your EML file with Timbal’s File type, then pass it alongside text in a list: 
from timbal import Agent
from timbal.types.file import File

agent = Agent(
    name="EmailSummarizer",
    model="openai/gpt-4.1-mini",
    system_prompt="Summarize emails and extract key information like sender, subject, main points, and action items."
)

# Validate EML file and summarize
eml_file = File.validate("path/to/email.eml")
result = await agent(
    prompt=["Summarize this email and extract the key points", eml_file]
).collect()

print(result.output.collect_text())

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Key Features

  • Email Summarization: Extract key information from email content
  • Structured Analysis: Identify sender, subject, main points, and action items
  • File Support: Works with local files, URLs, and base64 data