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# 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"} |