Comments (6)
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. Hereβs how you can handle the serialization and deserialization:
- Create a Wrapper Class: This class will handle the serialization and deserialization logic.
- Exclude Non-Picklable Attributes: Specifically, exclude the
duckdb.duckdb.DuckDBPyConnection
object.
Hereβs 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 theAgent
object. - The
__getstate__
method removes the non-picklableduckdb.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 π if this is helpful and π if it is irrelevant.
To continue the conversation, mention @dosu.
from pandas-ai.
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 π if this is helpful and π if it is irrelevant.
To continue the conversation, mention @dosu.
from pandas-ai.
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:
- Custom Serialization Method: Serialize only the picklable attributes of the
Agent
object. - 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
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 π if this is helpful and π if it is irrelevant.
To continue the conversation, mention @dosu.
from pandas-ai.
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
from pandas-ai.
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
from pandas-ai.
@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.
from pandas-ai.
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from pandas-ai.