Save Agent Output

from praisonaiagents import Agent

agent = Agent(
    instructions="You are a helpful writer",
    output="poem.txt",
)
agent.start("Write a poem about nature")

from praisonaiagents import Agent

agent = Agent(
    instructions="You are a helpful writer",
    output="output/response.txt"
)

agent.start("Write a poem about nature")
# ✅ Output saved to output/response.txt

from praisonaiagents import Agent

agent = Agent(
    instructions="You are a researcher",
    output="reports/summary.md"
)

agent.start("Summarize AI trends")
# ✅ Creates reports/ directory if needed
# ✅ Output saved to reports/summary.md

from praisonaiagents import Agent, OutputConfig

agent = Agent(
    instructions="You are a blog writer",
    output=OutputConfig(
        output_file="blog_post.md",
        template="""# {{title}}

{{content}}

---
*Generated by AI*
"""
    )
)

agent.start("Write about Python programming")

agent = Agent(
    instructions="You are a researcher",
    output=OutputConfig(
        verbose=True,              # Show rich terminal output
        output_file="research.md", # Also save to file
        template="## Summary\n\n{{content}}"
    )
)

from praisonaiagents import Agent
from praisonaiagents.tools import write_file

agent = Agent(
    name="ReportWriter",
    role="Technical Writer",
    goal="Create and save technical documentation",
    tools=[write_file]
)

# Agent will use write_file tool to save the report
agent.start("Write a technical report about Python and save it to report.md")

from praisonaiagents import Agent
from praisonaiagents.tools import read_file, write_file, list_files

agent = Agent(
    name="FileManager",
    instructions="Manage files: read, write, and organize",
    tools=[read_file, write_file, list_files]
)

agent.start("Read config.json, update the version to 2.0, and save as config_new.json")

from praisonaiagents import Agent, Task, AgentTeam

# Create agent
writer = Agent(
    name="ContentWriter",
    role="Writer",
    goal="Create engaging content"
)

# Task with output_file
task = Task(
    description="Write a blog post about machine learning",
    expected_output="A well-structured blog post in markdown",
    agent=writer,
    output_file="blog_post.md",
    create_directory=True  # Creates parent directories if needed
)

# Run
agents = AgentTeam(agents=[writer], tasks=[task])
result = agents.start()
# File automatically saved to blog_post.md

from praisonaiagents import Agent, Task, AgentTeam

researcher = Agent(name="Researcher", role="Research Analyst")
writer = Agent(name="Writer", role="Content Writer")

research_task = Task(
    description="Research AI trends for 2024",
    agent=researcher,
    output_file="research/ai_trends.txt"
)

writing_task = Task(
    description="Write a summary based on the research",
    agent=writer,
    output_file="output/summary.md",
    create_directory=True
)

agents = AgentTeam(
    agents=[researcher, writer],
    tasks=[research_task, writing_task],
    process="sequential"
)
agents.start()
# Creates: research/ai_trends.txt and output/summary.md

metadata:
  name: content-generator
  version: "1.0"

variables:
  output_dir: "generated"
  topic: "artificial intelligence"

agents:
  writer:
    role: Content Writer
    goal: Create engaging content about {{topic}}
    llm: gpt-4o-mini

steps:
  - agent: writer
    action: "Write a comprehensive article about {{topic}}"
    expected_output: "A well-structured article in markdown format"
    output_file: "{{output_dir}}/article.md"

import os
from praisonaiagents import Agent, Task, AgentTeam

# Default root is the current working directory. Override when needed:
os.environ["PRAISONAI_PROJECT_ROOT"] = "/home/user/myproject"

writer = Agent(name="Writer", role="Writer", goal="Write content")
task = Task(
    description="Write a summary",
    agent=writer,
    output_file="reports/summary.md",   # ✅ saved to /home/user/myproject/reports/summary.md
    # output_file="../summary.md"       # ❌ escapes root → skipped
    create_directory=True,
)
AgentTeam(agents=[writer], tasks=[task]).start()

from praisonaiagents import Agent
import json

agent = Agent(name="DataProcessor")
response = agent.start("Generate a list of 5 programming languages with descriptions")

# Save as text
with open("languages.txt", "w") as f:
    f.write(response)

# Or save as JSON (if response is structured)
with open("languages.json", "w") as f:
    json.dump({"content": response}, f, indent=2)

from praisonaiagents import Agent
from pathlib import Path

agent = Agent(name="Writer")
response = agent.start("Write a short story")

output_path = Path("stories/short_story.txt")
output_path.parent.mkdir(parents=True, exist_ok=True)

try:
    output_path.write_text(response)
    print(f"✅ Saved to {output_path}")
except IOError as e:
    print(f"❌ Failed to save: {e}")