cannot pickle '_thread.RLock' object when save Agent Object to Redis

[dobahoang]

System Info

I use last version pandas AI,
OS: WINDOWS

🐛 Describe the bug

How can I save Object Agent to Redis successfully?
My goal is to serve multiple users, each user has its own context. So the idea is that when the user sends the conversation_id, IT WILL load in Redis, to get the correct Agent object, then I can call the function chat(). for example :

df = Agent([df], config={"llm": llm})
df.chat('Which are the 5 happiest countries?')

def save_agent_to_redis(agent, conversation_id):
"""
Serialize and save the Agent object to Redis.
"""
redis_conn = get_redis_connection()
agent_bytes = pickle.dumps(agent)
redis_conn.set(conversation_id, agent_bytes)

but when I try to save to Redis, the error I get is:
The error TypeError: cannot pickle '_thread.RLock' object occurs when you try to pickle (serialize) an object that contains a thread lock or other non-picklable objects. Pickling is the process of converting a Python object into a byte stream that can be saved to a file or sent over a network.( in my case, i need to save to Redis)
I have used some libraries specialized for serialization (pickle, dill) but without success
The Agent class is also quite special, it will automatically create a Conversation_id every time a new Agent is created, we do not control the Conversation_id, so if we choose to serialize some properties and ignore the remaining properties, then recreate them, will generate a different conversation_id than before

Can anyone give me suggestions, please

[dosubot]

To save an Agent object to Redis, you need to handle the non-picklable objects like thread locks. You can achieve this by implementing custom serialization and deserialization methods. Here's how:

1. Custom Serialization Method: Serialize only the picklable attributes of the Agent object.
2. Custom Deserialization Method: Deserialize the object and restore the non-picklable attributes.

Here's an example:

import pickle
import redis
import uuid

class Agent:
    def __init__(self, dfs, config):
        self.dfs = dfs
        self.config = config
        self.conversation_id = uuid.uuid4()
        self.logger = self.initialize_logger()
        self.context = self.initialize_context()
        self.pipeline = self.initialize_pipeline()

    def initialize_logger(self):
        return Logger(save_logs=self.config.get('save_logs', False), verbose=self.config.get('verbose', False))

    def initialize_context(self):
        return PipelineContext(dfs=self.dfs, config=self.config)

    def initialize_pipeline(self):
        return GenerateChatPipeline(self.context, self.logger)

    def __getstate__(self):
        state = self.__dict__.copy()
        del state['logger']
        del state['context']
        del state['pipeline']
        return state

    def __setstate__(self, state):
        self.__dict__.update(state)
        self.logger = self.initialize_logger()
        self.context = self.initialize_context()
        self.pipeline = self.initialize_pipeline()

    def save_to_redis(self, redis_client, key):
        serialized_agent = pickle.dumps(self)
        redis_client.set(key, serialized_agent)

    @classmethod
    def load_from_redis(cls, redis_client, key):
        serialized_agent = redis_client.get(key)
        if serialized_agent is None:
            return None
        return pickle.loads(serialized_agent)

    def chat(self, message):
        pass

def get_redis_connection():
    return redis.StrictRedis(host='localhost', port=6379, db=0)

df = Agent([df], config={"llm": llm})
df.chat('Which are the 5 happiest countries?')

def save_agent_to_redis(agent, conversation_id):
    redis_conn = get_redis_connection()
    agent.save_to_redis(redis_conn, conversation_id)

def load_agent_from_redis(conversation_id):
    redis_conn = get_redis_connection()
    return Agent.load_from_redis(redis_conn, conversation_id)

save_agent_to_redis(df, str(df.conversation_id))
loaded_agent = load_agent_from_redis(str(df.conversation_id))
loaded_agent.chat('Which are the 5 happiest countries?')

This approach ensures that the conversation_id remains consistent and the non-picklable objects are properly handled.

Details

Sources

• pandasai/agent/base.py
• tests/unit_tests/agent/test_agent.py

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[dobahoang]

the Agent class is part of a third-party library (pandasai), I cannot directly modify its code to implement custom serialization and deserialization methods.
I think create a wrapper class around the Agent class that handles the serialization and deserialization logic. This wrapper class can have its own custom serialization and deserialization methods that I can control.
But the problem is that I still can't know exactly which property is causing the non-picklable objects problem
I used it

import dill
import pickle

try:
pickle.dumps(agent)
except Exception as e:
print(e)
dill.detect.errors(agent)

and detection
cannot pickle 'duckdb.duckdb.DuckDBPyConnection' object

But I checked in the Agent class, and in the Pandas AI REPO, but couldn't find any specific properties of Agent. Can you help me find it correctly? @dosu

[dosubot]

The issue you're encountering with the duckdb.duckdb.DuckDBPyConnection object being non-picklable is common when dealing with database connections. Since you cannot modify the Agent class directly, creating a wrapper class is a good approach. Here’s how you can handle the serialization and deserialization:

1. Create a Wrapper Class: This class will handle the serialization and deserialization logic.
2. Exclude Non-Picklable Attributes: Specifically, exclude the duckdb.duckdb.DuckDBPyConnection object.

Here’s an example implementation:

import pickle
from pandasai.agent.base import Agent

class AgentWrapper:
    def __init__(self, agent: Agent):
        self.agent = agent

    def __getstate__(self):
        state = self.__dict__.copy()
        # Remove non-picklable attributes
        if hasattr(self.agent, 'context') and hasattr(self.agent.context, 'dfs'):
            dfs = self.agent.context.dfs
            if isinstance(dfs, list):
                for df in dfs:
                    if hasattr(df, 'connection'):
                        del df.connection
            elif hasattr(dfs, 'connection'):
                del dfs.connection
        return state

    def __setstate__(self, state):
        self.__dict__.update(state)
        # Re-instantiate the non-picklable attributes if needed
        if hasattr(self.agent, 'context') and hasattr(self.agent.context, 'dfs'):
            dfs = self.agent.context.dfs
            if isinstance(dfs, list):
                for df in dfs:
                    if hasattr(df, 'reconnect'):
                        df.connection = df.reconnect()
            elif hasattr(dfs, 'reconnect'):
                dfs.connection = dfs.reconnect()

# Example usage
agent = Agent(dfs=[...], config=...)
wrapper = AgentWrapper(agent)

# Serialize the wrapper object
serialized_wrapper = pickle.dumps(wrapper)

# Deserialize the wrapper object
deserialized_wrapper = pickle.loads(serialized_wrapper)

In this solution:

• The AgentWrapper class wraps around the Agent object.
• The __getstate__ method removes the non-picklable duckdb.duckdb.DuckDBPyConnection object from the state before serialization.
• The __setstate__ method restores the state and re-establishes the connection if needed.

Replace the placeholder reconnect method with the actual logic to re-establish the connection for your specific use case. This approach should help you serialize and deserialize the Agent object successfully while handling the non-picklable duckdb.duckdb.DuckDBPyConnection object.

Details

Sources

• pandasai/agent/base.py
• tests/unit_tests/agent/test_agent.py
• pandasai/ee/vectorstores/qdrant.py
• pandasai/pipelines/pipeline_context.py
• pandasai/helpers/memory.py

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[dobahoang]

I checked but I don't see the source code mentioning the "connection" attribute belong to of
self.agent.context.dfs

Can you provide me with the relevant source codes to verify the problem @dosu

[dosubot]

To handle the non-picklable duckdb.duckdb.DuckDBPyConnection object within the Agent class, you can create a wrapper class that serializes and deserializes the Agent object while excluding the non-picklable attributes. Here is an example of how you can achieve this:

import pickle
from pandasai.agent.base import Agent

class AgentWrapper:
    def __init__(self, agent: Agent):
        self.agent = agent

    def __getstate__(self):
        state = self.__dict__.copy()
        # Remove the non-picklable attributes
        if hasattr(self.agent.context.dfs, 'connection'):
            del self.agent.context.dfs.connection
        return state

    def __setstate__(self, state):
        self.__dict__.update(state)
        # Reinitialize the non-picklable attributes if necessary
        # self.agent.context.dfs.connection = <reinitialize_connection_here>

    def save_to_redis(self, redis_client, key):
        serialized_agent = pickle.dumps(self)
        redis_client.set(key, serialized_agent)

    @classmethod
    def load_from_redis(cls, redis_client, key):
        serialized_agent = redis_client.get(key)
        return pickle.loads(serialized_agent)

# Usage example
# agent = Agent(...)
# wrapper = AgentWrapper(agent)
# wrapper.save_to_redis(redis_client, 'agent_key')
# loaded_wrapper = AgentWrapper.load_from_redis(redis_client, 'agent_key')
# loaded_agent = loaded_wrapper.agent

This code defines an AgentWrapper class that handles the serialization and deserialization of the Agent object, excluding the non-picklable connection attribute. You can then use this wrapper class to save and load the Agent object to and from Redis.

Additionally, there are other non-picklable attributes within the Agent class or its related classes that need to be handled during serialization. Specifically, the logger, pipeline, and context.config.llm attributes are non-picklable. Here is how you can extend the AgentWrapper class to handle these attributes:

import pickle
from pandasai.agent.base import Agent

class AgentWrapper:
    def __init__(self, agent: Agent):
        self.agent = agent

    def __getstate__(self):
        state = self.__dict__.copy()
        # Remove the non-picklable attributes
        if hasattr(self.agent.context.dfs, 'connection'):
            del self.agent.context.dfs.connection
        if hasattr(self.agent, 'logger'):
            del self.agent.logger
        if hasattr(self.agent, 'pipeline'):
            del self.agent.pipeline
        if hasattr(self.agent.context.config, 'llm'):
            del self.agent.context.config.llm
        return state

    def __setstate__(self, state):
        self.__dict__.update(state)
        # Reinitialize the non-picklable attributes if necessary
        # self.agent.context.dfs.connection = <reinitialize_connection_here>
        # self.agent.logger = <reinitialize_logger_here>
        # self.agent.pipeline = <reinitialize_pipeline_here>
        # self.agent.context.config.llm = <reinitialize_llm_here>

    def save_to_redis(self, redis_client, key):
        serialized_agent = pickle.dumps(self)
        redis_client.set(key, serialized_agent)

    @classmethod
    def load_from_redis(cls, redis_client, key):
        serialized_agent = redis_client.get(key)
        return pickle.loads(serialized_agent)

# Usage example
# agent = Agent(...)
# wrapper = AgentWrapper(agent)
# wrapper.save_to_redis(redis_client, 'agent_key')
# loaded_wrapper = AgentWrapper.load_from_redis(redis_client, 'agent_key')
# loaded_agent = loaded_wrapper.agent

This extended AgentWrapper class now handles the serialization and deserialization of the Agent object, excluding the non-picklable connection, logger, pipeline, and context.config.llm attributes. You can reinitialize these attributes as needed in the __setstate__ method.

Details

Sources

• pandasai/agent/base.py
• tests/unit_tests/agent/test_agent.py
• pandasai/connectors/pandas.py
• pandasai/helpers/memory.py

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[sujeendran]

@dobahoang - I managed to change this a bit and got it working for my use case. Maybe this will help:

import pickle
from pandasai import Agent
from pandasai.helpers.cache import Cache

class AgentWrapper:
    def __init__(self, agent: Agent):
        self.agent = agent

    def __getstate__(self):
        state = self.__dict__.copy()
        self.remove_unpicklable()
        return state

    def __setstate__(self, state):
        self.__dict__.update(state)

    def remove_unpicklable(self):
        # Remove the non-picklable attributes
        if hasattr(self.agent.context, 'cache'):
            del self.agent.context.cache
        if hasattr(self.agent, '_vectorstore'):
            del self.agent._vectorstore
        if hasattr(self.agent.context, 'vectorstore'):
            del self.agent.context.vectorstore
        if hasattr(self.agent.context.config, 'llm'):
            del self.agent.context.config.llm

    @classmethod
    def restore_unpicklable(cls, agent, llm, vector_store=None):
        # Reinitialize the non-picklable attributes if necessary
        if agent.context.config.enable_cache:
            agent.context.cache = Cache()
        else:
            agent.context.cache = None
        agent._vectorstore = vector_store
        agent.context.vectorstore = vector_store
        agent.context.config.llm = llm
        return agent

    def save_to_redis(self, key, redis_client):
        serialized_agent = pickle.dumps(self)
        redis_client.set(key, serialized_agent)

    @classmethod
    def load_from_redis(cls, key, redis_client, llm, vector_store=None):
        serialized_agent = redis_client.get(key)
        wrapper = pickle.loads(serialized_agent)
        wrapper.agent = cls.restore_unpicklable(wrapper.agent, llm, vector_store)
        return wrapper.agent

    def save_to_pkl(self, key):
        self.remove_unpicklable()
        with open(key, 'wb') as f:
            pickle.dump(self.agent, f)

    @classmethod
    def load_from_pkl(cls, key, llm, vector_store=None):
        with open(key, 'rb') as f:
            agent = pickle.load(f)
            agent = cls.restore_unpicklable(agent, llm, vector_store)
            return agent

p.s. I havent tried writing to Redis with these functions but writing and restoring from a dict worked. So I think it shouldnt be a problem.