Update agent.py

agent.py

@@ -1,196 +1,196 @@
-from google.adk.agents import Agent
-from google.adk.tools import BaseTool, ToolContext
-from google.adk.models import LlmRequest, LlmResponse
-from google.adk.tools import FunctionTool
-from google.adk.agents import Agent
-import requests
-from datetime import datetime, timedelta
-from typing import List, Optional
-import json
-from datetime import datetime, timedelta
-from typing import Optional, List, Dict
-from dateutil import parser
-import requests
-
-class ExtractScheduleDetailsTool(BaseTool):
-    def __init__(self):
-        super().__init__(
-            name="extract_schedule_details",
-            description="Extracts date, time, and attendee emails from a task description."
-        )
-
-    async def run_llm(self, tool_context: ToolContext, task: str) -> Dict:
-        prompt = f"""
-You will be given a user task. Extract the following if present:
-- date (in YYYY-MM-DD)
-- time (in HH:MM 24-hr format)
-- location
-- attendees (only email addresses)
-
-Respond in JSON like this:
-{{
-  "date": "...",
-  "time": "...",
-  "location": "...",
-  "attendees": ["email1@example.com", "email2@example.com"]
-}}
-
-If any field is missing, set it to null or empty list.
-Task: {task}
-"""
-        llm_request = LlmRequest(prompt=prompt.strip())
-        llm_response: LlmResponse = await tool_context.llm.complete(llm_request)
-        try:
-            return json.loads(llm_response.text)
-        except Exception:
-            return {"date": None, "time": None, "location": None, "attendees": []}
-
-# -- TOOL 1: Decompose Task --
-class DecomposeTaskTool(BaseTool):
-    def __init__(self):
-        super().__init__(
-            name="decompose_task",
-            description="Decomposes a task into subtasks and estimates XP using prompting."
-        )
-
-    async def run_llm(self, tool_context: ToolContext, task: str) -> str:
-        prompt = f"""
-You are an intelligent task planner that receives a user task and decides whether the task needs to be broken down into subtasks.
-
-Respond in the following format:
-
----
-task: {task}
-
-If the task is simple and doesn’t need subtasks:
-subtasks required: 0
-note: This task is straightforward and does not require subtasking.
-
-If the task needs to be broken down:
-subtasks required: <number of subtasks>
-subtask1: <subtask description> | XP: <estimated XP>
-subtask2: <subtask description> | XP: <estimated XP>
-...
-total XP: <sum of all XP values>
----
-
-Guidelines:
-- Skip subtasks for trivial tasks like “water the plants”.
-- XP should reflect effort (sum up to 100 if fully scoped).
-"""
-        llm_request = LlmRequest(prompt=prompt.strip())
-        llm_response: LlmResponse = await tool_context.llm.complete(llm_request)
-        return llm_response.text.strip()
-
-    async def run(self, tool_context: ToolContext, task: str) -> str:
-        return await self.run_llm(tool_context, task)
-
-# -- TOOL 2: Estimate XP --
-class EstimateXPTool(BaseTool):
-    def __init__(self):
-        super().__init__(
-            name="estimate_xp",
-            description="Estimates XP score for subtasks."
-        )
-
-    async def run(self, tool_context: ToolContext, task: str, subtasks: List[str]) -> Dict:
-        xp_per_subtask = {}
-        for i, subtask in enumerate(subtasks):
-            xp_per_subtask[subtask] = 10 + 5 * i
-        total_xp = sum(xp_per_subtask.values())
-
-        return {
-            "status": "success",
-            "report": {
-                "task": task,
-                "subtasks_required": len(subtasks),
-                "subtask_details": [{"subtask": s, "xp": xp_per_subtask[s]} for s in subtasks],
-                "total_xp": total_xp
-            }
-        }
-
-def schedule_event(
-    date: str,
-    time: Optional[str] = None,
-    location: str = "",
-    description: str = "",
-    attendees: Optional[List[Dict[str,str]]] = None
-) -> str:
-    event_details = {
-        "summary": description,
-        "location": location,
-        "description": description,
-        "timeZone": "Asia/Kolkata"
-    }
-
-    try:
-        if time and time.lower() != "unknown":
-            # Try to parse the time using dateutil for flexibility
-            parsed_time = parser.parse(time)
-            start_datetime = datetime.strptime(date, "%Y-%m-%d").replace(
-                hour=parsed_time.hour, minute=parsed_time.minute, second=0
-            )
-            end_datetime = start_datetime + timedelta(minutes=30)
-
-            # Format to ISO strings for scheduling
-            event_details["start"] = start_datetime.isoformat()
-            event_details["end"] = end_datetime.isoformat()
-        else:
-            # # All-day event
-            event_details["start"] = date
-            event_details["end"] = date
-            # event_details["allDay"] = True
-            
-    except Exception as e:
-        return f"Error parsing time: {str(e)}"
-
-    if attendees:
-        event_details["attendees"] = [email for email in attendees]
-
-    try:
-        print(event_details) #http://127.0.0.1:5000/schedule
-        response = requests.post("https://e04c-49-206-114-222.ngrok-free.app/schedule", json=event_details) #https://d49c-49-206-114-222.ngrok-free.app
-        if response.status_code == 200:
-            return f"Event scheduled: {description} on {date}"
-        else:
-            return f"Failed to schedule event. Server response: {response.text}"
-    except Exception as e:
-        return f"Error during scheduling: {str(e)}"
-
-schedule_event_tool = FunctionTool(func=schedule_event)
-
-# -- ROOT AGENT --
-root_agent =  Agent(
-        name="personaliser",
-        description="Agent to gamify tasks and create calendar events.",
-        model="gemini-2.0-flash",
-        instruction=("""
-            You are a productivity assistant that gamifies and schedules tasks.
-
-        Your workflow:
-        1. Detect the task.
-        2. Gamify it using `decompose_task` and `estimate_xp`.
-        3. Use `extract_schedule_details` to identify if a date/time is mentioned.
-        4. If the task has:
-        - a date
-        - a valid description (the task itself)
-        Then call `schedule_event`.
-
-        Always summarize in this format:
-        - Main Task
-        - Subtasks (with XP)
-        - Total XP
-        - Event Details (date, time, location, attendees)
-
-        **Important**:
-        - Never show internal tool names, JSON structures, or debug logs to the user.
-        - Your tone should be friendly, helpful, and focused on making the user's tasks more enjoyable and efficient.
-        - If the task is trivial (e.g., “water the plants”), skip subtasks but still assign an XP score and acknowledge completion."""
-        ),
-        tools=[
-            DecomposeTaskTool(),
-            EstimateXPTool(),
-            ExtractScheduleDetailsTool(),
-            schedule_event_tool
-        ]
-    )
+from google.adk.agents import Agent
+from google.adk.tools import BaseTool, ToolContext
+from google.adk.models import LlmRequest, LlmResponse
+from google.adk.tools import FunctionTool
+from google.adk.agents import Agent
+import requests
+from datetime import datetime, timedelta
+from typing import List, Optional
+import json
+from datetime import datetime, timedelta
+from typing import Optional, List, Dict
+from dateutil import parser
+import requests
+
+class ExtractScheduleDetailsTool(BaseTool):
+    def __init__(self):
+        super().__init__(
+            name="extract_schedule_details",
+            description="Extracts date, time, and attendee emails from a task description."
+        )
+
+    async def run_llm(self, tool_context: ToolContext, task: str) -> Dict:
+        prompt = f"""
+You will be given a user task. Extract the following if present:
+- date (in YYYY-MM-DD)
+- time (in HH:MM 24-hr format)
+- location
+- attendees (only email addresses)
+
+Respond in JSON like this:
+{{
+  "date": "...",
+  "time": "...",
+  "location": "...",
+  "attendees": ["email1@example.com", "email2@example.com"]
+}}
+
+If any field is missing, set it to null or empty list.
+Task: {task}
+"""
+        llm_request = LlmRequest(prompt=prompt.strip())
+        llm_response: LlmResponse = await tool_context.llm.complete(llm_request)
+        try:
+            return json.loads(llm_response.text)
+        except Exception:
+            return {"date": None, "time": None, "location": None, "attendees": []}
+
+# -- TOOL 1: Decompose Task --
+class DecomposeTaskTool(BaseTool):
+    def __init__(self):
+        super().__init__(
+            name="decompose_task",
+            description="Decomposes a task into subtasks and estimates XP using prompting."
+        )
+
+    async def run_llm(self, tool_context: ToolContext, task: str) -> str:
+        prompt = f"""
+You are an intelligent task planner that receives a user task and decides whether the task needs to be broken down into subtasks.
+
+Respond in the following format:
+
+---
+task: {task}
+
+If the task is simple and doesn’t need subtasks:
+subtasks required: 0
+note: This task is straightforward and does not require subtasking.
+
+If the task needs to be broken down:
+subtasks required: <number of subtasks>
+subtask1: <subtask description> | XP: <estimated XP>
+subtask2: <subtask description> | XP: <estimated XP>
+...
+total XP: <sum of all XP values>
+---
+
+Guidelines:
+- Skip subtasks for trivial tasks like “water the plants”.
+- XP should reflect effort (sum up to 100 if fully scoped).
+"""
+        llm_request = LlmRequest(prompt=prompt.strip())
+        llm_response: LlmResponse = await tool_context.llm.complete(llm_request)
+        return llm_response.text.strip()
+
+    async def run(self, tool_context: ToolContext, task: str) -> str:
+        return await self.run_llm(tool_context, task)
+
+# -- TOOL 2: Estimate XP --
+class EstimateXPTool(BaseTool):
+    def __init__(self):
+        super().__init__(
+            name="estimate_xp",
+            description="Estimates XP score for subtasks."
+        )
+
+    async def run(self, tool_context: ToolContext, task: str, subtasks: List[str]) -> Dict:
+        xp_per_subtask = {}
+        for i, subtask in enumerate(subtasks):
+            xp_per_subtask[subtask] = 10 + 5 * i
+        total_xp = sum(xp_per_subtask.values())
+
+        return {
+            "status": "success",
+            "report": {
+                "task": task,
+                "subtasks_required": len(subtasks),
+                "subtask_details": [{"subtask": s, "xp": xp_per_subtask[s]} for s in subtasks],
+                "total_xp": total_xp
+            }
+        }
+
+def schedule_event(
+    date: str,
+    time: Optional[str] = None,
+    location: str = "",
+    description: str = "",
+    attendees: Optional[List[Dict[str,str]]] = None
+) -> str:
+    event_details = {
+        "summary": description,
+        "location": location,
+        "description": description,
+        "timeZone": "Asia/Kolkata"
+    }
+
+    try:
+        if time and time.lower() != "unknown":
+            # Try to parse the time using dateutil for flexibility
+            parsed_time = parser.parse(time)
+            start_datetime = datetime.strptime(date, "%Y-%m-%d").replace(
+                hour=parsed_time.hour, minute=parsed_time.minute, second=0
+            )
+            end_datetime = start_datetime + timedelta(minutes=30)
+
+            # Format to ISO strings for scheduling
+            event_details["start"] = start_datetime.isoformat()
+            event_details["end"] = end_datetime.isoformat()
+        else:
+            # # All-day event
+            event_details["start"] = date
+            event_details["end"] = date
+            # event_details["allDay"] = True
+            
+    except Exception as e:
+        return f"Error parsing time: {str(e)}"
+
+    if attendees:
+        event_details["attendees"] = [email for email in attendees]
+
+    try:
+        print(event_details) #http://127.0.0.1:5000/schedule
+        response = requests.post("http://localhost:7861/schedule", json=event_details) #https://d49c-49-206-114-222.ngrok-free.app
+        if response.status_code == 200:
+            return f"Event scheduled: {description} on {date}"
+        else:
+            return f"Failed to schedule event. Server response: {response.text}"
+    except Exception as e:
+        return f"Error during scheduling: {str(e)}"
+
+schedule_event_tool = FunctionTool(func=schedule_event)
+
+# -- ROOT AGENT --
+root_agent =  Agent(
+        name="personaliser",
+        description="Agent to gamify tasks and create calendar events.",
+        model="gemini-2.0-flash",
+        instruction=("""
+            You are a productivity assistant that gamifies and schedules tasks.
+
+        Your workflow:
+        1. Detect the task.
+        2. Gamify it using `decompose_task` and `estimate_xp`.
+        3. Use `extract_schedule_details` to identify if a date/time is mentioned.
+        4. If the task has:
+        - a date
+        - a valid description (the task itself)
+        Then call `schedule_event`.
+
+        Always summarize in this format:
+        - Main Task
+        - Subtasks (with XP)
+        - Total XP
+        - Event Details (date, time, location, attendees)
+
+        **Important**:
+        - Never show internal tool names, JSON structures, or debug logs to the user.
+        - Your tone should be friendly, helpful, and focused on making the user's tasks more enjoyable and efficient.
+        - If the task is trivial (e.g., “water the plants”), skip subtasks but still assign an XP score and acknowledge completion."""
+        ),
+        tools=[
+            DecomposeTaskTool(),
+            EstimateXPTool(),
+            ExtractScheduleDetailsTool(),
+            schedule_event_tool
+        ]
+    )