# Import necessary modules
import asyncio
import os
import threading
import uuid
from fastapi.encoders import jsonable_encoder
import numpy as np
import pandas as pd
from pandasai import SmartDataframe
from langchain_groq.chat_models import ChatGroq
from dotenv import load_dotenv
from pydantic import BaseModel
from csv_service import clean_data, extract_chart_filenames
from langchain_groq import ChatGroq
import pandas as pd
from langchain_experimental.tools import PythonAstREPLTool
from langchain_experimental.agents import create_pandas_dataframe_agent
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import seaborn as sns
from supabase_service import upload_image_to_supabase
from util_service import _prompt_generator, process_answer
import matplotlib
matplotlib.use('Agg')


load_dotenv()

image_file_path = os.getenv("IMAGE_FILE_PATH")
image_not_found = os.getenv("IMAGE_NOT_FOUND")
allowed_hosts = os.getenv("ALLOWED_HOSTS", "").split(",")


# Load environment variables
groq_api_keys = os.getenv("GROQ_API_KEYS").split(",")
model_name = os.getenv("GROQ_LLM_MODEL")

class CsvUrlRequest(BaseModel):
    csv_url: str
    
class ImageRequest(BaseModel):
    image_path: str
    
class CsvCommonHeadersRequest(BaseModel):
  file_urls: list[str]
  
class CsvsMergeRequest(BaseModel):
    file_urls: list[str]
    merge_type: str
    common_columns_name: list[str]

# Thread-safe key management for groq_chat
current_groq_key_index = 0
current_groq_key_lock = threading.Lock()

# Thread-safe key management for langchain_csv_chat
current_langchain_key_index = 0
current_langchain_key_lock = threading.Lock()


# CHAT CODING STARTS FROM HERE
def handle_out_of_range_float(value):
    if isinstance(value, float):
        if np.isnan(value):
            return None
        elif np.isinf(value):
            return "Infinity"
    return value


# Modified groq_chat function with thread-safe key rotation
def groq_chat(csv_url: str, question: str):
    global current_groq_key_index, current_groq_key_lock

    while True:
        with current_groq_key_lock:
            if current_groq_key_index >= len(groq_api_keys):
                return {"error": "All API keys exhausted."}
            current_api_key = groq_api_keys[current_groq_key_index]

        try:
            # Delete cache file if exists
            cache_db_path = "/workspace/cache/cache_db_0.11.db"
            if os.path.exists(cache_db_path):
                try:
                    os.remove(cache_db_path)
                except Exception as e:
                    print(f"Error deleting cache DB file: {e}")

            data = clean_data(csv_url)
            llm = ChatGroq(model=model_name, api_key=current_api_key)
            # Generate unique filename using UUID
            chart_filename = f"chart_{uuid.uuid4()}.png"
            chart_path = os.path.join("generated_charts", chart_filename)
            
            # Configure SmartDataframe with chart settings
            df = SmartDataframe(
                data,
                config={
                    'llm': llm,
                    'save_charts': True,  # Enable chart saving
                    'open_charts': False,
                    'save_charts_path': os.path.dirname(chart_path),  # Directory to save
                    'custom_chart_filename': chart_filename  # Unique filename
                }
            )
            
            answer = df.chat(question)

            # Process different response types
            if isinstance(answer, pd.DataFrame):
                processed = answer.apply(handle_out_of_range_float).to_dict(orient="records")
            elif isinstance(answer, pd.Series):
                processed = answer.apply(handle_out_of_range_float).to_dict()
            elif isinstance(answer, list):
                processed = [handle_out_of_range_float(item) for item in answer]
            elif isinstance(answer, dict):
                processed = {k: handle_out_of_range_float(v) for k, v in answer.items()}
            else:
                processed = {"answer": str(handle_out_of_range_float(answer))}

            return processed

        except Exception as e:
            error_message = str(e)
            if "429" in error_message:
                with current_groq_key_lock:
                    current_groq_key_index += 1
                    if current_groq_key_index >= len(groq_api_keys):
                        print("All API keys exhausted.")
                        return None
            else:
                print(f"Error with API key index {current_groq_key_index}: {error_message}")
                return None
    






# Modified langchain_csv_chat with thread-safe key rotation
def langchain_csv_chat(csv_url: str, question: str, chart_required: bool):
    global current_langchain_key_index, current_langchain_key_lock

    data = clean_data(csv_url)
    attempts = 0

    while attempts < len(groq_api_keys):
        with current_langchain_key_lock:
            if current_langchain_key_index >= len(groq_api_keys):
                current_langchain_key_index = 0
            api_key = groq_api_keys[current_langchain_key_index]
            current_key = current_langchain_key_index
            current_langchain_key_index += 1
            attempts += 1

        try:
            llm = ChatGroq(model=model_name, api_key=api_key)
            tool = PythonAstREPLTool(locals={
                "df": data,
                "pd": pd,
                "np": np,
                "plt": plt,
                "sns": sns,
                "matplotlib": matplotlib
            })

            agent = create_pandas_dataframe_agent(
                llm,
                data,
                agent_type="openai-tools",
                verbose=True,
                allow_dangerous_code=True,
                extra_tools=[tool],
                return_intermediate_steps=True
            )

            prompt = _prompt_generator(question, chart_required)
            result = agent.invoke({"input": prompt})
            return result.get("output")

        except Exception as e:
            print(f"Error with key index {current_key}: {str(e)}")

    # If all keys are exhausted, return None
    print("All API keys have been exhausted.")
    return None


def handle_out_of_range_float(value):
    if isinstance(value, float):
        if np.isnan(value):
            return None
        elif np.isinf(value):
            return "Infinity"
    return value







# CHART CODING STARTS FROM HERE

instructions = """

- Please ensure that each value is clearly visible, You may need to adjust the font size, rotate the labels, or use truncation to improve readability (if needed).
- For multiple charts, arrange them in a grid format (2x2, 3x3, etc.)
- Use colorblind-friendly palette
- Read above instructions and follow them.

"""

# Thread-safe configuration for chart endpoints
current_groq_chart_key_index = 0
current_groq_chart_lock = threading.Lock()

current_langchain_chart_key_index = 0
current_langchain_chart_lock = threading.Lock()

def model():
    global current_groq_chart_key_index, current_groq_chart_lock
    with current_groq_chart_lock:
        if current_groq_chart_key_index >= len(groq_api_keys):
            raise Exception("All API keys exhausted for chart generation")
        api_key = groq_api_keys[current_groq_chart_key_index]
    return ChatGroq(model=model_name, api_key=api_key)

def groq_chart(csv_url: str, question: str):
    global current_groq_chart_key_index, current_groq_chart_lock
    
    for attempt in range(len(groq_api_keys)):
        try:
            # Clean cache before processing
            cache_db_path = "/workspace/cache/cache_db_0.11.db"
            if os.path.exists(cache_db_path):
                try:
                    os.remove(cache_db_path)
                except Exception as e:
                    print(f"Cache cleanup error: {e}")

            data = clean_data(csv_url)
            with current_groq_chart_lock:
                current_api_key = groq_api_keys[current_groq_chart_key_index]
            
            llm = ChatGroq(model=model_name, api_key=current_api_key)
            
            # Generate unique filename using UUID
            chart_filename = f"chart_{uuid.uuid4()}.png"
            chart_path = os.path.join("generated_charts", chart_filename)
            
            # Configure SmartDataframe with chart settings
            df = SmartDataframe(
                data,
                config={
                    'llm': llm,
                    'save_charts': True,  # Enable chart saving
                    'open_charts': False,
                    'save_charts_path': os.path.dirname(chart_path),  # Directory to save
                    'custom_chart_filename': chart_filename  # Unique filename
                }
            )
            
            answer = df.chat(question + instructions)
            
            if process_answer(answer):
                return "Chart not generated"
            return answer

        except Exception as e:
            error = str(e)
            if "429" in error:
                with current_groq_chart_lock:
                    current_groq_chart_key_index = (current_groq_chart_key_index + 1) % len(groq_api_keys)
            else:
                print(f"Chart generation error: {error}")
                return {"error": error}
    
    print("All API keys exhausted for chart generation") 
    return None



def langchain_csv_chart(csv_url: str, question: str, chart_required: bool):
    global current_langchain_chart_key_index, current_langchain_chart_lock
    
    data = clean_data(csv_url)

    for attempt in range(len(groq_api_keys)):
        try:
            with current_langchain_chart_lock:
                api_key = groq_api_keys[current_langchain_chart_key_index]
                current_key = current_langchain_chart_key_index
                current_langchain_chart_key_index = (current_langchain_chart_key_index + 1) % len(groq_api_keys)

            llm = ChatGroq(model=model_name, api_key=api_key)
            tool = PythonAstREPLTool(locals={
                "df": data,
                "pd": pd,
                "np": np,
                "plt": plt,
                "sns": sns,
                "matplotlib": matplotlib,
                "uuid": uuid
            })

            agent = create_pandas_dataframe_agent(
                llm,
                data,
                agent_type="openai-tools",
                verbose=True,
                allow_dangerous_code=True,
                extra_tools=[tool],
                return_intermediate_steps=True
            )

            result = agent.invoke({"input": _prompt_generator(question, True)})
            output = result.get("output", "")

            # Verify chart file creation
            chart_files = extract_chart_filenames(output)
            if len(chart_files) > 0:
                return chart_files

            if attempt < len(groq_api_keys) - 1:
                print(f"Langchain chart error (key {current_key}): {output}")

        except Exception as e:
            print(f"Langchain chart error (key {current_key}): {str(e)}")
    
    print("All API keys exhausted for chart generation")
    return None




###########################################################################################################################




async def csv_chart(csv_url: str, query: str):
    try:
        # First try Groq-based chart generation
        try:
            groq_result = await asyncio.to_thread(groq_chart, csv_url, query)
            print(f"Generated Chart (Groq): {groq_result}")
            
            if groq_result != 'Chart not generated':
                unique_file_name = f'{str(uuid.uuid4())}.png'
                image_public_url = await upload_image_to_supabase(groq_result, unique_file_name)
                print(f"Image uploaded to Supabase: {image_public_url}")
                return {"image_url": image_public_url}
                
        except Exception as groq_error:
            print(f"Groq chart generation failed, falling back to Langchain: {str(groq_error)}")

        # Fallback to Langchain if Groq fails
        try:
            langchain_paths = await asyncio.to_thread(langchain_csv_chart, csv_url, query, True)
            print("Fallback langchain chart result:", langchain_paths)
            
            if isinstance(langchain_paths, list) and len(langchain_paths) > 0:
                unique_file_name = f'{str(uuid.uuid4())}.png'
                print("Uploading the chart to supabase...")
                image_public_url = await upload_image_to_supabase(langchain_paths[0], unique_file_name)
                print("Image uploaded to Supabase and Image URL is... ", image_public_url)
                return {"image_url": image_public_url}
                
        except Exception as langchain_error:
            print(f"Langchain chart generation also failed: {str(langchain_error)}")

        # If both methods fail
        return {"error": "All chart generation methods failed"}

    except Exception as e:
        print(f"Critical chart error: {str(e)}")
        return {"error": "Internal system error"}
    
    
    
    
    
    
async def csv_chat(csv_url: str, query: str):
    try:
        updated_query = f"{query} and Do not show any charts or graphs."
        
        # Process with langchain_chat first
        try:
            lang_answer = await asyncio.to_thread(
                langchain_csv_chat, csv_url, query, False
            )
            if not process_answer(lang_answer):
                return {"answer": jsonable_encoder(lang_answer)}
            return {"answer": "Sorry, I couldn't find relevant data..."}
        except Exception as langchain_error:
            print(f"Langchain error, falling back to Groq: {str(langchain_error)}")
            
            # Process with groq_chat if langchain fails
            try:
                groq_answer = await asyncio.to_thread(groq_chat, csv_url, updated_query)
                print("groq_answer:", groq_answer)
                
                if process_answer(groq_answer) == "Empty response received.":
                    return {"answer": "Sorry, I couldn't find relevant data..."}
                
                if process_answer(groq_answer):
                    return {"answer": "error"}
                
                return {"answer": jsonable_encoder(groq_answer)}
            except Exception as groq_error:
                print(f"Groq processing error: {str(groq_error)}")
                return {"answer": "error"}
                
    except Exception as e:
        print(f"Error processing request: {str(e)}")
        return {"answer": "error"}