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"""
Brown Agent Tools for LlamaIndex Integration
Wraps existing AgentBrown methods as LlamaIndex FunctionTools for hackathon demo
"""
import json
from typing import Dict, Any, List
from llama_index.core.tools import FunctionTool
from agents.brown import AgentBrown, StoryboardRequest
class BrownTools:
"""Tool wrapper class for Agent Brown's methods"""
def __init__(self, max_iterations: int = 3):
# Use your original AgentBrown class directly
self.brown = AgentBrown(max_iterations)
self._current_request = None
def validate_input_tool(
self,
prompt: str,
style_preference: str = None,
panels: int = 4,
language: str = "english",
extras: str = "[]",
) -> str:
"""Validate user input for comic generation. Returns validation status and feedback."""
try:
extras_list = json.loads(extras) if extras else []
except:
extras_list = []
request = StoryboardRequest(
prompt=prompt,
style_preference=style_preference,
panels=panels,
language=language,
extras=extras_list,
)
# Store for later use
self._current_request = request
result = self.brown.validate_input(request)
return json.dumps(
{
"status": result.status.value,
"is_valid": result.is_valid(),
"issues": result.issues,
"suggestions": result.suggestions,
"confidence_score": result.confidence_score,
}
)
def process_request_tool(
self,
prompt: str,
style_preference: str = None,
panels: int = 4,
language: str = "english",
extras: str = "[]",
) -> str:
"""Process validated request and create structured message for Agent Bayko."""
try:
extras_list = json.loads(extras) if extras else []
except:
extras_list = []
request = StoryboardRequest(
prompt=prompt,
style_preference=style_preference,
panels=panels,
language=language,
extras=extras_list,
)
# Store for later use
self._current_request = request
message = self.brown.process_request(request)
return json.dumps(
{
"message_id": message.message_id,
"session_id": self.brown.session_id,
"enhanced_prompt": message.payload.get("prompt", ""),
"style_tags": message.payload.get("style_tags", []),
"panels": message.payload.get("panels", 4),
"status": "ready_for_bayko",
}
)
def simulate_bayko_generation(self, message_data: str) -> str:
"""Simulate Agent Bayko's content generation for demo purposes."""
try:
data = json.loads(message_data)
except:
data = {"panels": 4}
panels_count = data.get("panels", 4)
style_tags = data.get("style_tags", ["studio_ghibli", "soft_lighting"])
enhanced_prompt = data.get("enhanced_prompt", "")
original_prompt = data.get("original_prompt", "")
# Simulate Bayko's response with realistic image URLs for multimodal analysis
bayko_response = {
"session_id": self.brown.session_id,
"panels": [
{
"id": i + 1,
"description": f"Panel {i+1}: {original_prompt} - {', '.join(style_tags)} style",
"image_path": f"storyboard/{self.brown.session_id}/content/panel_{i+1}.png",
"image_url": f"https://example.com/generated/panel_{i+1}.png", # For multimodal analysis
"audio_path": (
f"panel_{i+1}.mp3"
if "narration" in str(data)
else None
),
"subtitles_path": (
f"panel_{i+1}.vtt"
if "subtitles" in str(data)
else None
),
}
for i in range(panels_count)
],
"style_tags": style_tags,
"metadata": {
"generation_time": "45s",
"total_panels": panels_count,
"status": "completed",
"enhanced_prompt": enhanced_prompt,
"original_prompt": original_prompt,
},
}
return json.dumps(bayko_response)
def review_bayko_output_tool(
self, bayko_response_json: str, original_prompt: str
) -> str:
"""Review Agent Bayko's output and determine if refinement is needed."""
try:
bayko_response = json.loads(bayko_response_json)
except:
# Fallback response for demo
bayko_response = {
"panels": [{"id": 1, "description": "Generated content"}],
"style_tags": ["studio_ghibli"],
"metadata": {"generation_time": "45s"},
}
# Use stored request or create new one
request = self._current_request or StoryboardRequest(
prompt=original_prompt
)
result = self.brown.review_output(bayko_response, request)
if result:
# Extract decision from the result
payload = result.payload
if "approved_content" in payload:
decision = "APPROVED"
reason = "Content meets quality standards"
elif "feedback" in payload:
decision = (
payload["feedback"].get("decision", "REFINE").upper()
)
reason = payload["feedback"].get(
"reason", "Quality assessment needed"
)
else:
decision = "REFINE"
reason = "Content needs improvement"
else:
decision = "APPROVED"
reason = "Content meets quality standards"
return json.dumps(
{
"decision": decision,
"reason": reason,
"iteration": self.brown.iteration_count,
"max_iterations": self.brown.max_iterations,
"final": decision in ["APPROVED", "REJECTED"],
}
)
def get_session_info_tool(self) -> str:
"""Get current session information and processing state."""
info = self.brown.get_session_info()
return json.dumps(
{
"session_id": info.get("session_id"),
"iteration_count": info.get("iteration_count", 0),
"max_iterations": info.get("max_iterations", 3),
"memory_size": info.get("memory_size", 0),
"status": "active" if info.get("session_id") else "inactive",
}
)
def create_llamaindex_tools(self) -> List[FunctionTool]:
"""Create LlamaIndex FunctionTools from Brown's methods"""
return [
FunctionTool.from_defaults(
fn=self.validate_input_tool,
name="validate_input",
description="Validate user input for comic generation. MUST be called first for any user prompt. Returns validation status, issues, and suggestions.",
),
FunctionTool.from_defaults(
fn=self.process_request_tool,
name="process_request",
description="Process validated request and create structured message for Agent Bayko. Call after validation passes. Returns enhanced prompt and generation parameters.",
),
FunctionTool.from_defaults(
fn=self.simulate_bayko_generation,
name="simulate_bayko_generation",
description="Simulate Agent Bayko's content generation process. Takes processed request data and returns generated comic content.",
),
FunctionTool.from_defaults(
fn=self.review_bayko_output_tool,
name="review_bayko_output",
description="Review Agent Bayko's generated content and decide if refinement is needed. Returns approval, refinement request, or rejection decision.",
),
FunctionTool.from_defaults(
fn=self.get_session_info_tool,
name="get_session_info",
description="Get current session information and processing state. Use to track progress and iterations.",
),
]
def create_brown_tools(max_iterations: int = 3) -> BrownTools:
"""Factory function to create BrownTools instance"""
return BrownTools(max_iterations=max_iterations)
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