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@ -75,7 +75,7 @@ def load_prompts_from_json() -> Dict[str, str]:
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if not isinstance(details, dict) or "system_prompt" not in details:
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continue
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prompts[f"agent.{agent_name}"] = details["system_prompt"]
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prompts[f"agent-{agent_name}"] = details["system_prompt"]
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if not prompts:
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# Load default prompts
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@ -504,7 +504,10 @@ def create_app():
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)
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async def run_task_wrapper(task, max_loops, dynamic_temp, swarm_type, agent_prompt_selector, flow_text):
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"""Execute the task and update the UI with progress."""
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"""
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Execute the task and update the UI with progress, saving the raw AgentRearrange response
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and parsing it for display.
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"""
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try:
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if not task:
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yield "Please provide a task description.", "Error: Missing task"
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@ -514,7 +517,6 @@ def create_app():
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yield "Please select at least one agent.", "Error: No agents selected"
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return
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# Update status
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yield "Processing...", "Running task..."
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@ -526,7 +528,7 @@ def create_app():
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return
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flow = flow_text
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# Execute task
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# Execute the task
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result, router, error = await execute_task(
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task=task,
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max_loops=max_loops,
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@ -540,33 +542,73 @@ def create_app():
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yield f"Error: {error}", "Error occurred"
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return
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# Format output based on swarm type
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output_lines = []
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if swarm_type == "SpreadSheetSwarm":
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output_lines.append(f"### Spreadsheet Output ###\n{result}\n{'=' * 50}\n")
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elif isinstance(result, dict): # checking if result is dict or string.
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# Process result based on swarm type
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if swarm_type == "AgentRearrange":
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for key, value in result.items():
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output_lines.append(f"### Step {key} ###\n{value}\n{'=' * 50}\n")
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elif swarm_type == "MixtureOfAgents":
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# Add individual agent outputs
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for key, value in result.items():
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if key != "Aggregated Summary":
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output_lines.append(f"### {key} ###\n{value}\n")
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# Add aggregated summary at the end
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if "Aggregated Summary" in result:
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output_lines.append(f"\n### Aggregated Summary ###\n{result['Aggregated Summary']}\n{'=' * 50}\n")
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else: # SequentialWorkflow, ConcurrentWorkflow, Auto
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# Store raw response in a temporary JSON file
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temp_json_path = "temp_agent_rearrange.json"
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with open(temp_json_path, "w", encoding="utf-8") as temp_file:
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json.dump(result, temp_file, indent=4)
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# Read from the temporary JSON file
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with open(temp_json_path, "r", encoding="utf-8") as temp_file:
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temp_json = json.load(temp_file)
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# Parse and format the JSON output
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formatted_output = parse_agent_rearrange_output(temp_json)
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yield formatted_output, "Completed"
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return
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# Generic processing for other swarm types
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output_lines = []
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if isinstance(result, dict): # For JSON-like outputs
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for key, value in result.items():
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output_lines.append(f"### {key} ###\n{value}\n{'=' * 50}\n")
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elif isinstance(result, str):
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output_lines.append(str(result))
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output_lines.append(result)
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yield "\n".join(output_lines), "Completed"
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except Exception as e:
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yield f"Error: {str(e)}", "Error occurred"
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def parse_agent_rearrange_output(raw_json: dict) -> str:
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"""
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Parse the AgentRearrange JSON output and format it for display.
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"""
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output_lines = []
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# Input Section
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input_data = raw_json.get("input", {})
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swarm_id = input_data.get("swarm_id", "N/A")
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swarm_name = input_data.get("name", "N/A")
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flow = input_data.get("flow", "N/A")
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output_lines.append(f"### Swarm ID: {swarm_id} ###")
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output_lines.append(f"### Swarm Name: {swarm_name} ###")
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output_lines.append(f"### Flow: {flow} ###")
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# Outputs Section
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outputs = raw_json.get("outputs", [])
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for i, agent_output in enumerate(outputs, start=1):
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agent_name = agent_output.get("agent_name", "N/A")
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task = agent_output.get("task", "N/A")
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output_lines.append(f"\n#### Agent: {agent_name} (Step {i}) ####")
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output_lines.append(f"Task: {task}")
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# Steps Section
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steps = agent_output.get("steps", [])
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for step_idx, step in enumerate(steps, start=1):
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role = step.get("role", "N/A")
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content = step.get("content", "N/A")
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output_lines.append(f" - **Loop 1: Role:** {role} **Content:** {content}")
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output_lines.append(f"{'=' * 30}\n")
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return "\n".join(output_lines)
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# Connect the update functions
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agent_selector.change(
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fn=update_ui_for_swarm_type,
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harshalmore31
4 months ago