single tooltip component

controller.py

@@ -402,7 +402,7 @@ def handle_out_of_range_float(value):
 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.)
+- For multiple charts, arrange them in a format (2x2, 3x3, etc.)
 - Use colorblind-friendly palette
 - Read above instructions and follow them.
 
@@ -479,189 +479,6 @@ def groq_chart(csv_url: str, question: str):
 
 
 
-# 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)}")
-    
-#     return "Chart generation failed after all retries"
-
-# @app.post("/api/csv-chart")
-# async def csv_chart(request: dict, authorization: str = Header(None)):
-#     # Authorization verification
-#     if not authorization or not authorization.startswith("Bearer "):
-#         raise HTTPException(status_code=401, detail="Authorization required")
-    
-#     token = authorization.split(" ")[1]
-#     if token != os.getenv("AUTH_TOKEN"):
-#         raise HTTPException(status_code=403, detail="Invalid credentials")
-
-#     try:
-#         query = request.get("query", "")
-#         csv_url = unquote(request.get("csv_url", ""))
-        
-#         # Parallel processing with thread pool
-#         if if_initial_chart_question(query):
-#             chart_paths = await asyncio.to_thread(
-#                 langchain_csv_chart, csv_url, query, True
-#             )
-#             print(chart_paths)
-        
-#             if len(chart_paths) > 0:
-#                return FileResponse(f"{image_file_path}/{chart_paths[0]}", media_type="image/png")
-        
-#         # Groq-based chart generation
-#         groq_result = await asyncio.to_thread(groq_chart, csv_url, query)
-#         print(f"Generated Chart: {groq_result}")
-#         if groq_result != 'Chart not generated':
-#             return FileResponse(groq_result, media_type="image/png")
-          
-        
-#         # Fallback to Langchain
-#         langchain_paths = await asyncio.to_thread(
-#             langchain_csv_chart, csv_url, query, True
-#         )
-        
-#         print (langchain_paths)
-       
-#         if len(langchain_paths) > 0:
-#            return FileResponse(f"{image_file_path}/{langchain_paths[0]}", media_type="image/png")
-#         else:
-#            return {"error": "All chart generation methods failed"}
-
-#     except Exception as e:
-#         print(f"Critical chart error: {str(e)}")
-#         return {"error": "Internal system error"}
-    
-    
-    
-
-
-
-# MERGED CALL
-
-# class CSVData(BaseModel):
-#     csv_url: str
-#     query: str
-#     chart_required: bool
-
-# @app.post("/api/v1/csv_chat")
-# async def csv_chat(csv_data: CSVData, authorization: str = Header(None)):
-#     # Authorization verification
-#     if not authorization or not authorization.startswith("Bearer "):
-#         raise HTTPException(status_code=401, detail="Authorization required")
-
-#     token = authorization.split(" ")[1]
-#     if token != os.getenv("AUTH_TOKEN"):
-#         raise HTTPException(status_code=403, detail="Invalid credentials")
-
-#     csv_url = csv_data.csv_url
-#     query = csv_data.query
-#     chart_required = csv_data.chart_required
-    
-#     if(chart_required == True):
-#         try:
-#             # Parallel processing with thread pool
-#             if if_initial_chart_question(query):
-#                 chart_path = await asyncio.to_thread(
-#                     langchain_csv_chart, csv_url, query, True
-#                 )
-#                 if "temp" in chart_path:
-#                    print("langchain chart Generated")
-#                    return FileResponse('temp.png', media_type="image/png")
-#                 return {"error": "Chart generation failed"}
-            
-#             # Groq-based chart generation
-#             groq_result = await asyncio.to_thread(groq_chart, csv_url, query)
-#             if groq_result == "Chart Generated":
-#                 return FileResponse("exports/charts/temp_chart.png")
-#             # Fallback to Langchain
-#             langchain_path = await asyncio.to_thread(
-#                 langchain_csv_chart, csv_url, query, True
-#             )
-#             if "temp" in langchain_path:
-#                 print("langchain chart Generated")
-#                 return FileResponse('temp.png', media_type="image/png")
-#             return {"error": "All chart generation methods failed"}
-
-#         except Exception as e:
-#             print(f"Critical chart error: {str(e)}")
-#             raise HTTPException(status_code=500, detail="Internal server error")
-#     else:
-#         try:            
-#             if if_initial_chat_question(query):
-#                 answer = await asyncio.to_thread(
-#                  langchain_csv_chat, csv_url, query, False
-#                 )
-#                 print("langchain_answer:", answer)
-#                 return {"answer": jsonable_encoder(answer)}
-
-#             # Process with groq_chat first
-#             groq_answer = await asyncio.to_thread(groq_chat, csv_url, 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):
-#               lang_answer = await asyncio.to_thread(
-#                 langchain_csv_chat, csv_url, query, False
-#               )
-#               if process_answer(lang_answer):
-#                 return {"answer": "error"}
-#               return {"answer": jsonable_encoder(lang_answer)}
-
-#             return {"answer": jsonable_encoder(groq_answer)}
-
-#         except Exception as e:
-#             print(f"Error processing request: {str(e)}")
-#             raise HTTPException(status_code=500, detail="Internal server error")
-    
-        
-
-
 
 # Global locks for key rotation (chart endpoints)
 # current_groq_chart_key_index = 0
@@ -673,86 +490,6 @@ current_langchain_chart_lock = threading.Lock()
 # Use a process pool to run CPU-bound charts generation
 process_executor = ProcessPoolExecutor(max_workers=max_cpus-2)
 
-# --- GROQ-BASED CHART GENERATION ---
-# def groq_chart(csv_url: str, question: str):
-#     """
-#     Generate a chart using the groq-based method.
-#     Modifications:
-#       • No deletion of a shared cache file (avoid interference).
-#       • After chart generation, close all matplotlib figures.
-#       • Return the full path of the saved chart.
-#     """
-#     global current_groq_chart_key_index, current_groq_chart_lock
-    
-#     for attempt in range(len(groq_api_keys)):
-#         try:
-#             # Instead of deleting a global cache file, you might later configure a per-request cache.
-#             cache_db_path = "/app/cache/cache_db_0.11.db"
-#             if os.path.exists(cache_db_path):
-#                 try:
-#                     os.remove(cache_db_path)
-#                     print(f"Deleted cache DB file: {cache_db_path}")
-#                 except Exception as e:
-#                     print(f"Error deleting cache DB file: {e}")
-                    
-#             chart_dir = "generated_charts"
-#             if not os.path.exists(chart_dir):
-#                os.makedirs(chart_dir)
-                    
-#             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 a unique filename and full path for the chart
-#             chart_filename = f"chart_{uuid.uuid4().hex}.png"
-#             chart_path = os.path.join("generated_charts", chart_filename)
-            
-#             # Configure your dataframe tool (e.g. using SmartDataframe) to save charts.
-#             # (Assuming your SmartDataframe uses these settings to save charts.)
-#             from pandasai import SmartDataframe  # Import here if not already imported
-#             df = SmartDataframe(
-#                 data,
-#                 config={
-#                     'llm': llm,
-#                     'save_charts': True,
-#                     'open_charts': False,
-#                     'save_charts_path': os.path.dirname(chart_path),
-#                     'custom_chart_filename': chart_filename
-#                 }
-#             )
-            
-#             # Append any extra instructions if needed
-#             instructions = """
-#             - Ensure each value is clearly visible.
-#             - Adjust font sizes, rotate labels if necessary.
-#             - Use a colorblind-friendly palette.
-#             - Arrange multiple charts in a grid if needed.
-#             """
-#             answer = df.chat(question + instructions)
-            
-#             # Make sure to close figures so they don't conflict between processes
-#             plt.close('all')
-            
-#             # If process_answer indicates a problem, return a failure message.
-#             if process_answer(answer):
-#                 return "Chart not generated"
-#             # Return the chart path that was used for saving
-#             return chart_path
-
-#         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"Groq chart generation error: {error}")
-#                 return {"error": error}
-    
-#     return {"error": "All API keys exhausted for chart generation"}
-
-
 # --- LANGCHAIN-BASED CHART GENERATION ---
 def langchain_csv_chart(csv_url: str, question: str, chart_required: bool):
     """

gemini_langchain_agent.py

@@ -128,206 +128,3 @@ def langchain_gemini_csv_handler(csv_url: str, question: str, chart_required: bo
     print("All LLM instances have been exhausted.")
     return None
 
-
-
-
-
-
-
-
-
-
-
-
-
-
-# import os
-# import re
-# import uuid
-# from langchain_google_genai import ChatGoogleGenerativeAI
-# import pandas as pd
-# from langchain_core.prompts import ChatPromptTemplate
-# from langchain_experimental.tools import PythonAstREPLTool
-# from langchain_experimental.agents import create_pandas_dataframe_agent
-# from dotenv import load_dotenv
-# import numpy as np
-# import matplotlib.pyplot as plt
-# import matplotlib
-# import seaborn as sns
-# import datetime as dt
-
-# # Set the backend for matplotlib to 'Agg' to avoid GUI issues
-# matplotlib.use('Agg')
-
-# load_dotenv()
-# model_name = 'gemini-2.0-flash'  # Specify the model name
-# google_api_keys = os.getenv("GEMINI_API_KEYS").split(",")
-
-# # Create pre-initialized LLM instances
-# llm_instances = [
-#     ChatGoogleGenerativeAI(model=model_name, api_key=key)
-#     for key in google_api_keys
-# ]
-# current_instance_index = 0  # Track current instance being used
-
-# def is_retryable_error(error: Exception) -> bool:
-#     """Check if the error should trigger a retry with next instance"""
-#     error_str = str(error).lower()
-    
-#     retry_conditions = [
-#         # Rate limiting and quota errors
-#         '429' in error_str,
-#         'quota' in error_str,
-#         'rate limit' in error_str,
-#         'resource exhausted' in error_str,
-#         'exceeded' in error_str,
-#         'limit reached' in error_str,
-        
-#         # Authentication and permission errors
-#         'permission denied' in error_str,
-#         'invalid api key' in error_str,
-#         'authentication' in error_str,
-        
-#         # Server errors
-#         '500' in error_str,
-#         '503' in error_str,
-#         'service unavailable' in error_str,
-        
-#         # Connection issues
-#         'timeout' in error_str,
-#         'connection' in error_str,
-        
-#         # Content policy
-#         'content policy' in error_str,
-#         'safety' in error_str,
-#         'blocked' in error_str
-#     ]
-    
-#     return any(retry_conditions)
-
-# def create_agent(llm, data, tools):
-#     """Create agent with tool names"""
-#     return create_pandas_dataframe_agent(
-#         llm,
-#         data,
-#         agent_type="tool-calling",
-#         verbose=True,
-#         allow_dangerous_code=True,
-#         extra_tools=tools,
-#         return_intermediate_steps=True
-#     )
-    
-# def _prompt_generator(question: str, chart_required: bool):
-#     chat_prompt = f"""You are a senior data analyst working with CSV data. Adhere strictly to the following guidelines:  
-
-#                      1. **Data Verification:** Always inspect the data with `.sample(5).to_dict()` before performing any analysis.  
-#                      2. **Data Integrity:** Ensure proper handling of null values to maintain accuracy and reliability.  
-#                      3. **Communication:** Provide concise, professional, and well-structured responses.
-#                      4. Avoid including any internal processing details or references to the methods used to generate your response (ex: based on the tool call, using the function -> These types of phrases.)
-
-#                      **Query:** {question}  
-#                  """               
-        
-#     chart_prompt = f"""You are a senior data analyst working with CSV data. Follow these rules STRICTLY:
-
-#                    1. Generate ONE unique identifier FIRST using: unique_id = uuid.uuid4().hex
-#                    2. Visualization requirements:
-#                    - Adjust font sizes, rotate labels (45° if needed), truncate for readability
-#                    - Figure size: (12, 6)
-#                    - Descriptive titles (fontsize=14)
-#                    - Colorblind-friendly palettes
-#                    3. File handling rules:
-#                    - Create MAXIMUM 2 charts if absolutely necessary
-#                    - For multiple charts:
-#                        * Arrange in grid format (2x1 vertical layout preferred)
-#                        * Use SAME unique_id with suffixes: 
-#                        - f"{{unique_id}}_1.png"
-#                        - f"{{unique_id}}_2.png"
-#                    - Save EXCLUSIVELY to "generated_charts" folder
-#                    - File naming: f"chart_{{unique_id}}.png" (for single chart)
-#                    4. FINAL OUTPUT MUST BE:
-#                    - For single chart: f"generated_charts/chart_{{unique_id}}.png"
-#                    - For multiple charts: f"generated_charts/chart_{{unique_id}}.png" (combined grid image)
-#                    - **ONLY return this full path string, nothing else**
-
-#                    **Query:** {question}
-
-#                    IMPORTANT: 
-#                    - Generate the unique_id FIRST before any operations
-#                    - Use THE SAME unique_id throughout entire process
-#                    - NEVER generate new UUIDs after initial creation
-#                    - Return EXACT filepath string of the final saved chart
-#                    """
-
-#     if chart_required:
-#         return ChatPromptTemplate.from_template(chart_prompt)
-#     else:
-#         return ChatPromptTemplate.from_template(chat_prompt)
-
-# def langchain_gemini_csv_handler(csv_url: str, question: str, chart_required: bool):
-#     global current_instance_index
-#     data = pd.read_csv(csv_url)
-    
-#     # Track first error in case all instances fail
-#     first_error = None
-    
-#     while current_instance_index < len(llm_instances):
-#         try:
-#             llm = llm_instances[current_instance_index]
-#             print(f"Attempting with LLM instance {current_instance_index + 1}/{len(llm_instances)}")
-
-#             # Create tool with validated name
-#             tool = PythonAstREPLTool(
-#                 locals={
-#                     "df": data,
-#                     "pd": pd,
-#                     "np": np,
-#                     "plt": plt,
-#                     "sns": sns,
-#                     "matplotlib": matplotlib,
-#                     "uuid": uuid,
-#                     "dt": dt
-#                 },
-#             )
-
-#             agent = create_agent(llm, data, [tool])
-#             prompt = _prompt_generator(question, chart_required)
-#             result = agent.invoke({"input": prompt})
-#             output = result.get("output")
-            
-#             if output is None:
-#                 raise ValueError("Received None response from agent")
-                
-#             if isinstance(output, str) and any(err in output.lower() for err in ['quota', 'limit', 'exhausted']):
-#                 raise ValueError(f"API limitation detected in response: {output}")
-                
-#             return output
-        
-#         except Exception as e:
-#             error_msg = f"Error with instance {current_instance_index}: {str(e)}"
-#             print(error_msg)
-            
-#             # Store first error if not set
-#             if first_error is None:
-#                 first_error = error_msg
-                
-#             # Check if we should try next instance
-#             if is_retryable_error(e):
-#                 current_instance_index += 1
-#                 continue
-#             else:
-#                 # Non-retryable error - return immediately
-#                 return {
-#                     "error": "Non-retryable error occurred",
-#                     "details": str(e),
-#                     "instance": current_instance_index
-#                 }
-
-#     # All instances exhausted
-#     error_response = {
-#         "error": "All API instances failed",
-#         "details": first_error or "Unknown error",
-#         "attempted_instances": current_instance_index
-#     }
-#     print(error_response)
-#     return error_response

groq_chart.py

@@ -29,7 +29,7 @@ logger = logging.getLogger(__name__)
 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.)
+- For multiple charts, arrange them in a format (2x2, 3x3, etc.)
 - Use colorblind-friendly palette
 - Read above instructions and follow them.
 - Please do not use any visualization library other than matplotlib or seaborn.

openai_pandasai_service.py

@@ -20,7 +20,7 @@ current_llm_index = 0
 
 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.)
+- For multiple charts, arrange them in a format (2x2, 3x3, etc.)
 - Use professional and color-blind friendly palettes.
 - Do not use sns.set_palette()
 - Read above instructions and follow them.