orchestrator_functions.py

# Import necessary modules
import asyncio
import logging
import os
import threading
from typing import Dict
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 gemini_langchain_agent import langchain_gemini_csv_handler
from openai_pandasai_service import openai_chart
from supabase_service import upload_file_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

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)


# 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:
                    logger.info(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):
                        logger.info("All API keys exhausted.")
                        return None
            else:
                logger.info(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="tool-calling",
                verbose=True,
                allow_dangerous_code=True,
                extra_tools=[tool],
                return_intermediate_steps=True
            )

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

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

    # If all keys are exhausted, return None
    logger.info("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:
                    logger.info(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:
                logger.info(f"Chart generation error: {error}")
                return {"error": error}
    
    logger.info("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="tool-calling",
                verbose=True,
                allow_dangerous_code=True,
                extra_tools=[tool],
                return_intermediate_steps=True
            )

            result = agent.invoke({"input": _prompt_generator(question, True, csv_url)})
            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:
                logger.info(f"Langchain chart error (key {current_key}): {output}")

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




####################################### Orchestrator Function for Chat #######################################

async def csv_chat(csv_url: str, query: str) -> dict:
    """
    Generate a response based on the provided CSV URL and query.
    Prioritizes LangChain-Gemini first, then falls back to LangChain-Groq.
    
    Parameters:
    - csv_url (str): The URL of the CSV file.
    - query (str): The query for generating the response.
    
    Returns:
    - dict: A dictionary containing the generated response or error message.
    
    Example:
    - csv_url: "https://example.com/data.csv"
    - query: "What is the total sales for the year 2022?"
    Returns:
    - dict: {"answer": "The total sales for 2022 is $100,000."}
    """
    updated_query = f"{query} and Do not show any charts or graphs."
    error_messages = []
    
    # --- 1. First Attempt: LangChain Gemini ---
    try:
        gemini_answer = await asyncio.to_thread(
            langchain_gemini_csv_handler, csv_url, updated_query, False
        )
        logger.info(f"LangChain-Gemini answer: {gemini_answer}")
        
        if gemini_answer and is_valid_response(gemini_answer):
            return {"answer": jsonable_encoder(gemini_answer)}
        
        error_messages.append("LangChain-Gemini response not usable")
    except Exception as gemini_error:
        error_messages.append(f"LangChain-Gemini error: {str(gemini_error)}")
        logger.error(f"LangChain-Gemini failed: {str(gemini_error)}")
    
    # --- 2. Fallback Attempt: LangChain Groq ---
    try:
        lang_groq_answer = await asyncio.to_thread(
            langchain_csv_chat, csv_url, updated_query, False
        )
        logger.info(f"LangChain-Groq answer: {lang_groq_answer}")
        
        if lang_groq_answer and is_valid_response(lang_groq_answer):
            return {"answer": jsonable_encoder(lang_groq_answer)}
        
        error_messages.append("LangChain-Groq response not usable")
    except Exception as lang_groq_error:
        error_messages.append(f"LangChain-Groq error: {str(lang_groq_error)}")
        logger.error(f"LangChain-Groq failed: {str(lang_groq_error)}")
    
    # --- Final Fallback when all attempts fail ---
    logger.error(f"All attempts failed. Errors: {'; '.join(error_messages)}")
    return {"answer": "Sorry, I couldn't process your request with the available data."}

def is_valid_response(response) -> bool:
    """Check if the response is valid and not empty."""
    if not response:
        return False
    if isinstance(response, str) and response.strip() == "":
        return False
    if isinstance(response, dict) and not response.get("answer"):
        return False
    return True




####################################### Orchestrator Function for Chart #######################################


async def csv_chart(csv_url: str, query: str, chat_id: str) -> Dict[str, str]:
    """
    Generate a chart based on the provided CSV URL and query.
    Prioritizes LangChain-Gemini first, then falls back to LangChain-Groq.
    
    Parameters:
    - csv_url (str): URL of the CSV file
    - query (str): Query for generating the chart
    - chat_id (str): Chat session ID for file storage
    
    Returns:
    - dict: Either {"image_url": "url"} on success or {"error": "message"} on failure
    
    Example:
    - csv_url: "https://example.com/data.csv"
    - query: "Show sales trends as line chart"
    Returns:
    - dict: {"image_url": "https://storage.example.com/chart_uuid.png"}
    """
    error_messages = []
    
    async def upload_and_return(image_path: str) -> Dict[str, str]:
        """Handle image upload and return public URL"""
        unique_name = f'{uuid.uuid4()}.png'
        public_url = await upload_file_to_supabase(image_path, unique_name, chat_id)
        logger.info(f"Uploaded chart to: {public_url}")
        try:
            os.remove(image_path)
        except OSError as e:
            logger.warning(f"Could not delete temp file {image_path}: {str(e)}")
        return {"image_url": public_url}

    # --- 1. First Attempt: LangChain Gemini ---
    try:
        gemini_result = await asyncio.to_thread(
            langchain_gemini_csv_handler, csv_url, query, True
        )
        logger.info(f"LangChain-Gemini chart result: {gemini_result}")
        
        if gemini_result:
            # Handle string or list response
            if isinstance(gemini_result, str):
                clean_path = gemini_result.strip()
                if os.path.exists(clean_path):
                    return await upload_and_return(clean_path)
            
            if isinstance(gemini_result, list) and gemini_result:
                first_path = gemini_result[0]
                if os.path.exists(first_path):
                    return await upload_and_return(first_path)
        
        error_messages.append("LangChain-Gemini returned invalid result")
    except Exception as gemini_error:
        error_messages.append(f"LangChain-Gemini error: {str(gemini_error)}")
        logger.error(f"Gemini chart failed: {str(gemini_error)}")

    # --- 2. Fallback Attempt: LangChain Groq ---
    try:
        lc_groq_paths = await asyncio.to_thread(
            langchain_csv_chart, csv_url, query, True
        )
        logger.info(f"LangChain-Groq chart result: {lc_groq_paths}")
        
        if lc_groq_paths:
            if isinstance(lc_groq_paths, list) and lc_groq_paths:
                first_path = lc_groq_paths[0]
                if os.path.exists(first_path):
                    return await upload_and_return(first_path)
            
            if isinstance(lc_groq_paths, str) and os.path.exists(lc_groq_paths):
                return await upload_and_return(lc_groq_paths)
        
        error_messages.append("LangChain-Groq returned invalid result")
    except Exception as lc_groq_error:
        error_messages.append(f"LangChain-Groq error: {str(lc_groq_error)}")
        logger.error(f"Groq chart failed: {str(lc_groq_error)}")

    # --- Final Error Handling ---
    logger.error(f"All chart generation failed. Errors: {'; '.join(error_messages)}")
    return {"error": "Could not generate chart from the provided data"}