app.py

from smolagents import CodeAgent, DuckDuckGoSearchTool, load_tool, tool, LiteLLMModel #,
import smolagents  # Added for aliasing
# from smolagents.security import E2BSandbox 
import datetime
import pytz
import yaml
from skyfield.api import load, Topos, load_file
from skyfield import almanac
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
import os
import base64

# Add the alias before instrumentation
smolagents.ApiModel = smolagents.HfApiModel
# smolagents.ApiModel = smolagents.LiteLLMModel

LANGFUSE_PUBLIC_KEY="pk-lf-133099c7-8644-49e8-8f6e-ec8bd6d543fd"
LF_SECRET_KEY = os.environ["LANGFUSE_SECRET_KEY"]
LANGFUSE_AUTH=base64.b64encode(f"{LANGFUSE_PUBLIC_KEY}:{LF_SECRET_KEY}".encode()).decode()

os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://cloud.langfuse.com/api/public/otel" # EU data region
# os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://us.cloud.langfuse.com/api/public/otel" # US data region
os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Basic {LANGFUSE_AUTH}"

from opentelemetry.sdk.trace import TracerProvider
from openinference.instrumentation.smolagents import SmolagentsInstrumentor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

trace_provider = TracerProvider()
trace_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter()))

SmolagentsInstrumentor().instrument(tracer_provider=trace_provider)

# Load ephemeris and timescale
planets = load('https://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk/planets/de440.bsp')
ts = load.timescale()

# Define Zodiac signs and their boundaries (0° to 360° ecliptic longitude)
ZODIAC_SIGNS = [
    ("Aries", 0, 30),
    ("Taurus", 30, 60),
    ("Gemini", 60, 90),
    ("Cancer", 90, 120),
    ("Leo", 120, 150),
    ("Virgo", 150, 180),
    ("Libra", 180, 210),
    ("Scorpio", 210, 240),
    ("Sagittarius", 240, 270),
    ("Capricorn", 270, 300),
    ("Aquarius", 300, 330),
    ("Pisces", 330, 360),
]

# Moon phase boundaries (0° to 360° phase angle) for display purposes
MOON_PHASES = [
    ("New Moon", 0, 45),
    ("Waxing Crescent", 45, 90),
    ("First Quarter", 90, 135),
    ("Waxing Gibbous", 135, 180),
    ("Full Moon", 180, 225),
    ("Waning Gibbous", 225, 270),
    ("Last Quarter", 270, 315),
    ("Waning Crescent", 315, 360),
]

# Fertility sign coefficients (applicable to all plants)
FERTILITY_SIGN_COEFFS = {
    "Aries": 1,
    "Taurus": 2,
    "Gemini": 0,
    "Cancer": 2,
    "Leo": 1,
    "Virgo": 0,
    "Libra": 0.5,
    "Scorpio": 1.5,
    "Sagittarius": 1,
    "Capricorn": 1,
    "Aquarius": 0,
    "Pisces": 2,
}

# Pruning sign coefficients (applicable to all plants)
PRUNING_SIGN_COEFFS = {
    "Aries": 1,
    "Taurus": 0,
    "Gemini": 2,
    "Cancer": 0,
    "Leo": 1,
    "Virgo": 2,
    "Libra": 1.5,
    "Scorpio": 0.5,
    "Sagittarius": 1,
    "Capricorn": 1,
    "Aquarius": 2,
    "Pisces": 0,
}

# Fertility phase coefficients for above-ground plants
FERTILITY_PHASE_COEFFS_ABOVE = {
    "New Moon": 0,
    "Waxing Moon": 1,
    "Full Moon": 0,
    "Waning Moon": 0.5,
}

# Fertility phase coefficients for root crops
FERTILITY_PHASE_COEFFS_ROOT = {
    "New Moon": 0,
    "Waxing Moon": 0.5,
    "Full Moon": 0,
    "Waning Moon": 1,
}

# Pruning phase coefficients
PRUNING_PHASE_COEFFS = {
    "New Moon": 0,
    "Waxing Moon": 1,
    "Full Moon": 0,
    "Waning Moon": 0.5,
}

@tool
def get_moon_info(date_time: str) -> dict:
    """
    Returns Moon's Zodiac position, phase, and fertility and pruning indices for the given date/time.
    
    The fertility and pruning indices are calculated as sum of sign and phase fertility values of the Moon position. Moon sign fertility
        amounts up to 2.0 value and phase fertility value could be 1.0 max.
        It is observed that when Moon is in different Zodiac signs, the fertility of new plants and impact of pruning differs.
        When Moon is in fertile sign the plant is in the active phase, when all processes are particularly intense, and any intervention 
        such as pruning can be very traumatic for the plant. Here:
            Most fertile signs: Taurus, Pisces, Cancer - Plants are in the active growth phase, juices and nutrients actively circulate 
                in the plant, and it is best time for fertilizers, harvasting cutting, vaccination, rooting. 
            Conditionally fertile: Scorpio
            Neutral: Aries, Leo, Sagittarius, Capricorn
            Conditionally sterile: Libra
            Sterile: Gemini, Virgo, Aquarius
        
        Fertility indices ranges from 0.0 to 3.0 where proportionaly
            0 - minimal expected fertility
            3.0 - most favorable fertility for platining, 
        and depends on type of plant (root crop or produce above ground).
        
        Pruning indices ranges from 0 to 3 where proportionaly:
            0 - pruning is not recommended as it causes most damage to tree and can lead to:
                    Increased sap production from the cut points
                    Increased vulnerability to infections
                    Delayed wound healing
                    Possible weakening of the plant.
                Instead of pruning into fertile signs, you can do:
                    Crown formation
                    Pinching the shoots
                    Removing dead branches
                    Sanitary treatment
            1.0 - pruning is not recommended,
            2.0 - allowed only minimum or sanitary pruning,
            3.0 - most favorable time for pruning.

    Args:
        date_time (str): ISO 8601 formatted datetime (YYYY-MM-DDTHH:MM:SS)

    Returns:
        dict: {
            "zodiac_position": "Leo 15°30'",
            "moon_phase": "Waxing Gibbous",
            "fertility_above_ground": 2.0,
            "fertility_root_crop": 1.5,
            "pruning": 2.0

        }
    """
    try:
        # Parse input datetime and localize to UTC
        user_time = datetime.datetime.strptime(date_time, "%Y-%m-%dT%H:%M:%S")
        user_time = pytz.utc.localize(user_time)

        # Use loaded ephemeris and timescale
        t = ts.from_datetime(user_time)

        # Define celestial bodies
        earth = planets['earth']
        moon = planets['moon']
        sun = planets['sun']

# Calculate Moon's ecliptic longitude
        astrometric = earth.at(t).observe(moon)
        ecliptic_lat, ecliptic_lon, distance = astrometric.ecliptic_latlon()
        lon_deg = ecliptic_lon.degrees % 360

        # Calculate the phase angle using almanac.moon_phase
        phase = almanac.moon_phase(planets, t)
        phase_angle = phase.degrees

        # Determine Zodiac sign and position
        zodiac_sign = "Unknown"
        position_degrees = 0
        for sign, start, end in ZODIAC_SIGNS:
            if start <= lon_deg < end:
                zodiac_sign = sign
                position_degrees = lon_deg - start
                break

        # Format position to degrees and minutes
        degrees = int(position_degrees)
        minutes = int((position_degrees % 1) * 60)
        position_str = f"{zodiac_sign} {degrees}°{minutes:02}'"

        # Determine moon phase for display
        moon_phase = "Unknown"
        for phase, start, end in MOON_PHASES:
            if start <= phase_angle < end:
                moon_phase = phase
                break

        # Determine phase category for indices with 15° orbis for New and Full Moon
        if (phase_angle >= 345 or phase_angle < 15):
            phase_category = "New Moon"  # 345° to 15° (30° total orbis)
        elif 15 <= phase_angle < 165:
            phase_category = "Waxing Moon"
        elif 165 <= phase_angle < 195:
            phase_category = "Full Moon"  # 165° to 195° (30° total orbis)
        elif 195 <= phase_angle < 345:
            phase_category = "Waning Moon"
        else:
            phase_category = "Unknown"

        # Calculate fertility and pruning indices
        if zodiac_sign in FERTILITY_SIGN_COEFFS and phase_category in FERTILITY_PHASE_COEFFS_ABOVE:
            fertility_above_ground = FERTILITY_SIGN_COEFFS[zodiac_sign] + FERTILITY_PHASE_COEFFS_ABOVE[phase_category]
            fertility_root_crop = FERTILITY_SIGN_COEFFS[zodiac_sign] + FERTILITY_PHASE_COEFFS_ROOT[phase_category]
            pruning = PRUNING_SIGN_COEFFS[zodiac_sign] + PRUNING_PHASE_COEFFS[phase_category]
        else:
            fertility_above_ground = None
            fertility_root_crop = None
            pruning = None

        return {
            "zodiac_position": position_str,
            "moon_phase": moon_phase,
            "fertility_above_ground": fertility_above_ground,
            "fertility_root_crop": fertility_root_crop,
            "pruning": pruning
        }

    except Exception as e:
        raise ValueError(f"Error in get_moon_info: {str(e)}")

@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """
    Returns the current local time in the specified timezone with description.

    Args:
        timezone (str): A string representing a valid timezone (e.g., 'UTC')


    Returns:
        str: Formatted local time with timezone description
    """
    try:
        tz = pytz.timezone(timezone)
        now = datetime.datetime.now(tz)
        return f"Local time in {timezone}: {now.strftime('%Y-%m-%d %H:%M:%S')}"
    except Exception as e:
        return f"Error: {str(e)}"

@tool
def get_current_time_raw(timezone: str) -> str:
    """
    Returns current local time in specified timezone as ISO 8601 string.

    Args:
        timezone (str): A string representing a valid timezone (e.g., 'UTC')

    Returns:
        str: Datetime in ISO 8601 format (YYYY-MM-DDTHH:MM:SS)
    """
    try:
        tz = pytz.timezone(timezone)
        now = datetime.datetime.now(tz)
        return now.strftime("%Y-%m-%dT%H:%M:%S")
    except Exception as e:
        return f"Error: {str(e)}"

# Model configuration
final_answer = FinalAnswerTool()

# model = HfApiModel(
#    max_tokens=2096,
#    temperature=0.5,
#    model_id="gemini/gemini-2.0-flash-lite-001",
#    api_key = os.environ["GEMINI_KEY"], #userdata.get("GEMINI_KEY")
#    model_id="https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud/",
#    custom_role_conversions=None,
# )

model = LiteLLMModel(
    model_id="gemini/gemini-2.0-flash",
    api_key=os.getenv("GEMINI_KEY"),
    max_tokens=8192,
    temperature=0.7
)

# Load image tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

# Load prompt templates
with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)

# Initialize agent with all tools
agent = CodeAgent(
    model=model,
    tools=[final_answer, get_moon_info, get_current_time_in_timezone, get_current_time_raw, image_generation_tool],
    max_steps=6,
    verbosity_level=1,
    prompt_templates=prompt_templates
#    execution_env=E2BSandbox(  
#        allowed_imports=["numpy", "pandas"], # Explicitly permitted packages  
#        blocked_imports=["subprocess"], # Prevent system access  
#    ),  
#    safe_mode=True, # Enable safe code execution  
#    timeout=10, # Seconds before execution timeout  
#    max_memory=512, # MB memory limit  
#    file_system_access=False, # Disable disk write access  
#    network_access=False, # Block network operations  
#    max_code_iterations=100, # Prevent infinite loops
)

if __name__ == "__main__":
    GradioUI(agent).launch()

# Change to your username and repo name
# agent.push_to_hub('sergeyo7/Garden_Magus')