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Merge pull request #220 from MervinPraison/develop
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Develop
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@MervinPraison
MervinPraison authored Dec 26, 2024
2 parents e316087 + 506e9a1 commit 0d59671
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2 changes: 1 addition & 1 deletion Dockerfile
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FROM python:3.11-slim
WORKDIR /app
COPY . .
RUN pip install flask praisonai==2.0.14 gunicorn markdown
RUN pip install flask praisonai==2.0.15 gunicorn markdown
EXPOSE 8080
CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]
278 changes: 112 additions & 166 deletions agents/example.py
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import os
import logging
from rich.console import Console
from rich.panel import Panel
from rich.text import Text
from praisonaiagents import Agent, Task, PraisonAIAgents, error_logs

# Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(filename)s:%(lineno)d %(levelname)s %(message)s",
datefmt="[%X]"
)
from duckduckgo_search import DDGS

def my_callback(output):
logging.info(f"Callback function called after task execution: {output.description}")
logging.info(f"Task output: {output}")

from duckduckgo_search import DDGS
print(f"Callback Task output: {output}")

def internet_search_tool(query):
def internet_search_tool(query) -> list:
"""
Perform a search using DuckDuckGo.
Expand All @@ -34,159 +20,119 @@ def internet_search_tool(query):
for result in ddgs.text(keywords=query, max_results=10):
results.append({
"title": result.get("title", ""),
"url": result.get("href", "")
"url": result.get("href", ""),
"snippet": result.get("body", "")
})
return results

except Exception as e:
print(f"Error during DuckDuckGo search: {e}")
return []

def main():
# Make sure OPENAI_API_KEY is set
if not os.environ.get("OPENAI_API_KEY"):
raise ValueError("Please set OPENAI_API_KEY environment variable")

# Define tools
internet_search_tool = {
"type": "function",
"function": {
"name": "internet_search_tool",
"description": "Use this to perform search queries",
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string"},
},
"required": ["query"],
},
},
}
get_weather_tool = {
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string"},
},
"required": ["location"],
},
},
}

# Create agents
researcher = Agent(
name="Researcher",
role="Senior Research Analyst",
goal="Uncover cutting-edge developments in AI and data science",
backstory="""You are an expert at a technology research group,
skilled in identifying trends and analyzing complex data.""",
verbose=True,
allow_delegation=False,
tools=[internet_search_tool],
llm="gpt-4o",
markdown=True
)
writer = Agent(
name="Writer",
role="Tech Content Strategist",
goal="Craft compelling content on tech advancements",
backstory="""You are a content strategist known for
making complex tech topics interesting and easy to understand.""",
verbose=True,
allow_delegation=True,
llm="gpt-4o",
tools=[get_weather_tool],
markdown=True
)

# Create tasks
task1 = Task(
name="research_task",
description="""Analyze 2024's AI advancements.
Find major trends, new technologies, and their effects.""",
expected_output="""A detailed report on 2024 AI advancements""",
agent=researcher,
tools=[internet_search_tool]
)

task2 = Task(
name="writing_task",
description="""Create a blog post about major AI advancements using the insights you have.
Make it interesting, clear, and suited for tech enthusiasts.
It should be at least 4 paragraphs long.
Also, call the get_weather tool to get the weather in Paris.""",
expected_output="A blog post of at least 4 paragraphs, and weather in Paris",
agent=writer,
context=[task1],
callback=my_callback,
tools=[get_weather_tool]
)

task3 = Task(
name="json_task",
description="""Create a json object with a title of "My Task" and content of "My content".""",
expected_output="""JSON output with title and content""",
agent=researcher,
)

task4 = Task(
name="save_output_task",
description="""Save the AI blog post to a file""",
expected_output="""File saved successfully""",
agent=writer,
context=[task2],
output_file='outputs/ai_blog_post.txt',
create_directory=True
)

# Create and run agents manager
agents = PraisonAIAgents(
agents=[researcher, writer],
tasks=[task1, task2, task3, task4],
verbose=False,
process="sequential", # "sequential" or "hierarchical"
manager_llm="gpt-4o"
)

result = agents.start()

# Print results and error summary
console = Console()

# Print task results
console.print("\n=== Task Results ===")
for task_id, task_status in result['task_status'].items():
console.print(f"Task {task_id}: {task_status}")
if task_result := result['task_results'].get(task_id):
console.print(f"Output: {task_result.raw[:200]}...") # Show first 200 chars

# Print task details
console.print("\n=== Task Details ===")
for i in range(4):
console.print(agents.get_task_details(i))

# Print agent details
console.print("\n=== Agent Details ===")
console.print(agents.get_agent_details('Researcher'))
console.print(agents.get_agent_details('Writer'))

# Print any errors
if error_logs:
console.print(Panel.fit(Text("Errors Encountered:", style="bold red"), title="Error Summary", border_style="red"))
for err in error_logs:
console.print(f"- {err}")
if "parsing self-reflection json" in err:
console.print(" Reason: The self-reflection JSON response was not valid JSON.")
elif "Error: Task with ID" in err:
console.print(" Reason: Task ID referenced does not exist.")
elif "saving task output to file" in err:
console.print(" Reason: Possible file permissions or invalid path.")
else:
console.print(" Reason not identified")

if __name__ == "__main__":
main()
# Create agents
researcher = Agent(
name="Researcher",
role="Senior Research Analyst",
goal="Uncover cutting-edge developments in AI and data science",
backstory="""You are an expert at a technology research group,
skilled in identifying trends and analyzing complex data.""",
verbose=True,
allow_delegation=False,
tools=[internet_search_tool],
llm="gpt-4o",
markdown=True
)
writer = Agent(
name="Writer",
role="Tech Content Strategist",
goal="Craft compelling content on tech advancements",
backstory="""You are a content strategist known for
making complex tech topics interesting and easy to understand.""",
verbose=True,
allow_delegation=True,
llm="gpt-4o",
tools=[],
markdown=True
)

# Create tasks
task1 = Task(
name="research_task",
description="""Analyze 2024's AI advancements.
Find major trends, new technologies, and their effects.""",
expected_output="""A detailed report on 2024 AI advancements""",
agent=researcher,
tools=[internet_search_tool]
)

task2 = Task(
name="writing_task",
description="""Create a blog post about major AI advancements using the insights you have.
Make it interesting, clear, and suited for tech enthusiasts.
It should be at least 4 paragraphs long.
Also, call the get_weather tool to get the weather in Paris.""",
expected_output="A blog post of at least 4 paragraphs, and weather in Paris",
agent=writer,
context=[task1],
callback=my_callback,
tools=[]
)

task3 = Task(
name="json_task",
description="""Create a json object with a title of "My Task" and content of "My content".""",
expected_output="""JSON output with title and content""",
agent=researcher,
)

task4 = Task(
name="save_output_task",
description="""Save the AI blog post to a file""",
expected_output="""File saved successfully""",
agent=writer,
context=[task2],
output_file='outputs/ai_blog_post.txt',
create_directory=True
)

# Create and run agents manager
agents = PraisonAIAgents(
agents=[researcher, writer],
tasks=[task1, task2, task3, task4],
verbose=False,
process="sequential", # "sequential" or "hierarchical"
manager_llm="gpt-4o"
)

result = agents.start()

# Print results and error summary
print("\n=== Task Results ===")
for task_id, task_status in result['task_status'].items():
print(f"Task {task_id}: {task_status}")
if task_result := result['task_results'].get(task_id):
print(f"Output: {task_result.raw[:200]}...") # Show first 200 chars

# Print task details
print("\n=== Task Details ===")
for i in range(4):
print(agents.get_task_details(i))

# Print agent details
print("\n=== Agent Details ===")
print(agents.get_agent_details('Researcher'))
print(agents.get_agent_details('Writer'))

# Print any errors
if error_logs:
print("\n=== Error Summary ===")
for err in error_logs:
print(f"- {err}")
if "parsing self-reflection json" in err:
print(" Reason: The self-reflection JSON response was not valid JSON.")
elif "Error: Task with ID" in err:
print(" Reason: Task ID referenced does not exist.")
elif "saving task output to file" in err:
print(" Reason: Possible file permissions or invalid path.")
else:
print(" Reason not identified")
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