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[Bug Fix] Handle chat sessions properly during app.chat() calls (#1084)

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This commit is contained in:
Deshraj Yadav
2023-12-30 15:36:24 +05:30
committed by GitHub
parent 52b4577d3b
commit a54dde0509
10 changed files with 124 additions and 187 deletions
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25
embedchain/embedchain.py
View File

@@ -7,9 +7,7 @@ from typing import Any, Dict, List, Optional, Tuple, Union
from dotenv import load_dotenv from dotenv import load_dotenv
from langchain.docstore.document import Document from langchain.docstore.document import Document
from embedchain.cache import (adapt, get_gptcache_session, from embedchain.cache import adapt, get_gptcache_session, gptcache_data_convert, gptcache_update_cache_callback
gptcache_data_convert,
gptcache_update_cache_callback)
from embedchain.chunkers.base_chunker import BaseChunker from embedchain.chunkers.base_chunker import BaseChunker
from embedchain.config import AddConfig, BaseLlmConfig, ChunkerConfig from embedchain.config import AddConfig, BaseLlmConfig, ChunkerConfig
from embedchain.config.base_app_config import BaseAppConfig from embedchain.config.base_app_config import BaseAppConfig
@@ -19,8 +17,7 @@ from embedchain.embedder.base import BaseEmbedder
from embedchain.helpers.json_serializable import JSONSerializable from embedchain.helpers.json_serializable import JSONSerializable
from embedchain.llm.base import BaseLlm from embedchain.llm.base import BaseLlm
from embedchain.loaders.base_loader import BaseLoader from embedchain.loaders.base_loader import BaseLoader
from embedchain.models.data_type import (DataType, DirectDataType, from embedchain.models.data_type import DataType, DirectDataType, IndirectDataType, SpecialDataType
IndirectDataType, SpecialDataType)
from embedchain.telemetry.posthog import AnonymousTelemetry from embedchain.telemetry.posthog import AnonymousTelemetry
from embedchain.utils import detect_datatype, is_valid_json_string from embedchain.utils import detect_datatype, is_valid_json_string
from embedchain.vectordb.base import BaseVectorDB from embedchain.vectordb.base import BaseVectorDB
@@ -580,6 +577,7 @@ class EmbedChain(JSONSerializable):
input_query: str, input_query: str,
config: Optional[BaseLlmConfig] = None, config: Optional[BaseLlmConfig] = None,
dry_run=False, dry_run=False,
session_id: str = "default",
where: Optional[Dict[str, str]] = None, where: Optional[Dict[str, str]] = None,
citations: bool = False, citations: bool = False,
**kwargs: Dict[str, Any], **kwargs: Dict[str, Any],
@@ -599,6 +597,8 @@ class EmbedChain(JSONSerializable):
:param dry_run: A dry run does everything except send the resulting prompt to :param dry_run: A dry run does everything except send the resulting prompt to
the LLM. The purpose is to test the prompt, not the response., defaults to False the LLM. The purpose is to test the prompt, not the response., defaults to False
:type dry_run: bool, optional :type dry_run: bool, optional
:param session_id: The session id to use for chat history, defaults to 'default'.
:type session_id: Optional[str], optional
:param where: A dictionary of key-value pairs to filter the database results., defaults to None :param where: A dictionary of key-value pairs to filter the database results., defaults to None
:type where: Optional[Dict[str, str]], optional :type where: Optional[Dict[str, str]], optional
:param kwargs: To read more params for the query function. Ex. we use citations boolean :param kwargs: To read more params for the query function. Ex. we use citations boolean
@@ -616,6 +616,9 @@ class EmbedChain(JSONSerializable):
else: else:
contexts_data_for_llm_query = contexts contexts_data_for_llm_query = contexts
# Update the history beforehand so that we can handle multiple chat sessions in the same python session
self.llm.update_history(app_id=self.config.id, session_id=session_id)
if self.cache_config is not None: if self.cache_config is not None:
logging.info("Cache enabled. Checking cache...") logging.info("Cache enabled. Checking cache...")
answer = adapt( answer = adapt(
@@ -634,7 +637,7 @@ class EmbedChain(JSONSerializable):
) )
# add conversation in memory # add conversation in memory
self.llm.add_history(self.config.id, input_query, answer) self.llm.add_history(self.config.id, input_query, answer, session_id=session_id)
# Send anonymous telemetry # Send anonymous telemetry
self.telemetry.capture(event_name="chat", properties=self._telemetry_props) self.telemetry.capture(event_name="chat", properties=self._telemetry_props)
@@ -684,12 +687,8 @@ class EmbedChain(JSONSerializable):
self.telemetry.capture(event_name="reset", properties=self._telemetry_props) self.telemetry.capture(event_name="reset", properties=self._telemetry_props)
def get_history(self, num_rounds: int = 10, display_format: bool = True): def get_history(self, num_rounds: int = 10, display_format: bool = True):
return self.llm.memory.get_recent_memories( return self.llm.memory.get(app_id=self.config.id, num_rounds=num_rounds, display_format=display_format)
app_id=self.config.id,
num_rounds=num_rounds,
display_format=display_format,
)
def delete_chat_history(self): def delete_chat_history(self, session_id: str = "default"):
self.llm.memory.delete_chat_history(app_id=self.config.id) self.llm.memory.delete(app_id=self.config.id, session_id=session_id)
self.llm.update_history(app_id=self.config.id) self.llm.update_history(app_id=self.config.id)

27
embedchain/llm/base.py
View File

@@ -8,7 +8,7 @@ from embedchain.config.llm.base import (DEFAULT_PROMPT,
DEFAULT_PROMPT_WITH_HISTORY_TEMPLATE, DEFAULT_PROMPT_WITH_HISTORY_TEMPLATE,
DOCS_SITE_PROMPT_TEMPLATE) DOCS_SITE_PROMPT_TEMPLATE)
from embedchain.helpers.json_serializable import JSONSerializable from embedchain.helpers.json_serializable import JSONSerializable
from embedchain.memory.base import ECChatMemory from embedchain.memory.base import ChatHistory
from embedchain.memory.message import ChatMessage from embedchain.memory.message import ChatMessage
@@ -24,7 +24,7 @@ class BaseLlm(JSONSerializable):
else: else:
self.config = config self.config = config
self.memory = ECChatMemory() self.memory = ChatHistory()
self.is_docs_site_instance = False self.is_docs_site_instance = False
self.online = False self.online = False
self.history: Any = None self.history: Any = None
@@ -45,17 +45,24 @@ class BaseLlm(JSONSerializable):
""" """
self.history = history self.history = history
def update_history(self, app_id: str): def update_history(self, app_id: str, session_id: str = "default"):
"""Update class history attribute with history in memory (for chat method)""" """Update class history attribute with history in memory (for chat method)"""
chat_history = self.memory.get_recent_memories(app_id=app_id, num_rounds=10) chat_history = self.memory.get(app_id=app_id, session_id=session_id, num_rounds=10)
self.set_history([str(history) for history in chat_history]) self.set_history([str(history) for history in chat_history])
def add_history(self, app_id: str, question: str, answer: str, metadata: Optional[Dict[str, Any]] = None): def add_history(
self,
app_id: str,
question: str,
answer: str,
metadata: Optional[Dict[str, Any]] = None,
session_id: str = "default",
):
chat_message = ChatMessage() chat_message = ChatMessage()
chat_message.add_user_message(question, metadata=metadata) chat_message.add_user_message(question, metadata=metadata)
chat_message.add_ai_message(answer, metadata=metadata) chat_message.add_ai_message(answer, metadata=metadata)
self.memory.add(app_id=app_id, chat_message=chat_message) self.memory.add(app_id=app_id, chat_message=chat_message, session_id=session_id)
self.update_history(app_id=app_id) self.update_history(app_id=app_id, session_id=session_id)
def generate_prompt(self, input_query: str, contexts: List[str], **kwargs: Dict[str, Any]) -> str: def generate_prompt(self, input_query: str, contexts: List[str], **kwargs: Dict[str, Any]) -> str:
""" """
@@ -212,7 +219,9 @@ class BaseLlm(JSONSerializable):
# Restore previous config # Restore previous config
self.config: BaseLlmConfig = BaseLlmConfig.deserialize(prev_config) self.config: BaseLlmConfig = BaseLlmConfig.deserialize(prev_config)
def chat(self, input_query: str, contexts: List[str], config: BaseLlmConfig = None, dry_run=False): def chat(
self, input_query: str, contexts: List[str], config: BaseLlmConfig = None, dry_run=False, session_id: str = None
):
""" """
Queries the vector database on the given input query. Queries the vector database on the given input query.
Gets relevant doc based on the query and then passes it to an Gets relevant doc based on the query and then passes it to an
@@ -230,6 +239,8 @@ class BaseLlm(JSONSerializable):
:param dry_run: A dry run does everything except send the resulting prompt to :param dry_run: A dry run does everything except send the resulting prompt to
the LLM. The purpose is to test the prompt, not the response., defaults to False the LLM. The purpose is to test the prompt, not the response., defaults to False
:type dry_run: bool, optional :type dry_run: bool, optional
:param session_id: Session ID to use for the conversation, defaults to None
:type session_id: str, optional
:return: The answer to the query or the dry run result :return: The answer to the query or the dry run result
:rtype: str :rtype: str
""" """

85
embedchain/memory/base.py
View File

@@ -9,40 +9,41 @@ from embedchain.memory.message import ChatMessage
from embedchain.memory.utils import merge_metadata_dict from embedchain.memory.utils import merge_metadata_dict
CHAT_MESSAGE_CREATE_TABLE_QUERY = """ CHAT_MESSAGE_CREATE_TABLE_QUERY = """
CREATE TABLE IF NOT EXISTS chat_history ( CREATE TABLE IF NOT EXISTS ec_chat_history (
app_id TEXT, app_id TEXT,
id TEXT, id TEXT,
question TEXT, session_id TEXT,
answer TEXT, question TEXT,
metadata TEXT, answer TEXT,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, metadata TEXT,
PRIMARY KEY (id, app_id) created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
) PRIMARY KEY (id, app_id, session_id)
""" )
"""
class ECChatMemory: class ChatHistory:
def __init__(self) -> None: def __init__(self) -> None:
with sqlite3.connect(SQLITE_PATH, check_same_thread=False) as self.connection: with sqlite3.connect(SQLITE_PATH, check_same_thread=False) as self.connection:
self.cursor = self.connection.cursor() self.cursor = self.connection.cursor()
self.cursor.execute(CHAT_MESSAGE_CREATE_TABLE_QUERY) self.cursor.execute(CHAT_MESSAGE_CREATE_TABLE_QUERY)
self.connection.commit() self.connection.commit()
def add(self, app_id, chat_message: ChatMessage) -> Optional[str]: def add(self, app_id, session_id, chat_message: ChatMessage) -> Optional[str]:
memory_id = str(uuid.uuid4()) memory_id = str(uuid.uuid4())
metadata_dict = merge_metadata_dict(chat_message.human_message.metadata, chat_message.ai_message.metadata) metadata_dict = merge_metadata_dict(chat_message.human_message.metadata, chat_message.ai_message.metadata)
if metadata_dict: if metadata_dict:
metadata = self._serialize_json(metadata_dict) metadata = self._serialize_json(metadata_dict)
ADD_CHAT_MESSAGE_QUERY = """ ADD_CHAT_MESSAGE_QUERY = """
INSERT INTO chat_history (app_id, id, question, answer, metadata) INSERT INTO ec_chat_history (app_id, id, session_id, question, answer, metadata)
VALUES (?, ?, ?, ?, ?) VALUES (?, ?, ?, ?, ?, ?)
""" """
self.cursor.execute( self.cursor.execute(
ADD_CHAT_MESSAGE_QUERY, ADD_CHAT_MESSAGE_QUERY,
( (
app_id, app_id,
memory_id, memory_id,
session_id,
chat_message.human_message.content, chat_message.human_message.content,
chat_message.ai_message.content, chat_message.ai_message.content,
metadata if metadata_dict else "{}", metadata if metadata_dict else "{}",
@@ -52,37 +53,41 @@ class ECChatMemory:
logging.info(f"Added chat memory to db with id: {memory_id}") logging.info(f"Added chat memory to db with id: {memory_id}")
return memory_id return memory_id
def delete_chat_history(self, app_id: str): def delete(self, app_id: str, session_id: str):
DELETE_CHAT_HISTORY_QUERY = """
DELETE FROM chat_history WHERE app_id=?
""" """
self.cursor.execute( Delete all chat history for a given app_id and session_id.
DELETE_CHAT_HISTORY_QUERY, This is useful for deleting chat history for a given user.
(app_id,),
) :param app_id: The app_id to delete chat history for
:param session_id: The session_id to delete chat history for
:return: None
"""
DELETE_CHAT_HISTORY_QUERY = "DELETE FROM ec_chat_history WHERE app_id=? AND session_id=?"
self.cursor.execute(DELETE_CHAT_HISTORY_QUERY, (app_id, session_id))
self.connection.commit() self.connection.commit()
def get_recent_memories(self, app_id, num_rounds=10, display_format=False) -> List[ChatMessage]: def get(self, app_id, session_id, num_rounds=10, display_format=False) -> List[ChatMessage]:
""" """
Get the most recent num_rounds rounds of conversations Get the most recent num_rounds rounds of conversations
between human and AI, for a given app_id. between human and AI, for a given app_id.
""" """
QUERY = """ QUERY = """
SELECT * FROM chat_history SELECT * FROM ec_chat_history
WHERE app_id=? WHERE app_id=? AND session_id=?
ORDER BY created_at DESC ORDER BY created_at DESC
LIMIT ? LIMIT ?
""" """
self.cursor.execute( self.cursor.execute(
QUERY, QUERY,
(app_id, num_rounds), (app_id, session_id, num_rounds),
) )
results = self.cursor.fetchall() results = self.cursor.fetchall()
history = [] history = []
for result in results: for result in results:
app_id, _, question, answer, metadata, timestamp = result app_id, _, session_id, question, answer, metadata, timestamp = result
metadata = self._deserialize_json(metadata=metadata) metadata = self._deserialize_json(metadata=metadata)
# Return list of dict if display_format is True # Return list of dict if display_format is True
if display_format: if display_format:
@@ -94,6 +99,20 @@ class ECChatMemory:
history.append(memory) history.append(memory)
return history return history
def count(self, app_id: str, session_id: str):
"""
Count the number of chat messages for a given app_id and session_id.
:param app_id: The app_id to count chat history for
:param session_id: The session_id to count chat history for
:return: The number of chat messages for a given app_id and session_id
"""
QUERY = "SELECT COUNT(*) FROM ec_chat_history WHERE app_id=? AND session_id=?"
self.cursor.execute(QUERY, (app_id, session_id))
count = self.cursor.fetchone()[0]
return count
def _serialize_json(self, metadata: Dict[str, Any]): def _serialize_json(self, metadata: Dict[str, Any]):
return json.dumps(metadata) return json.dumps(metadata)
@@ -102,15 +121,3 @@ class ECChatMemory:
def close_connection(self): def close_connection(self):
self.connection.close() self.connection.close()
def count_history_messages(self, app_id: str):
QUERY = """
SELECT COUNT(*) FROM chat_history
WHERE app_id=?
"""
self.cursor.execute(
QUERY,
(app_id,),
)
count = self.cursor.fetchone()[0]
return count

14
embedchain/memory/message.py
View File

@@ -14,16 +14,16 @@ class BaseMessage(JSONSerializable):
# The string content of the message. # The string content of the message.
content: str content: str
# The creator of the message. AI, Human, Bot etc. # The created_by of the message. AI, Human, Bot etc.
by: str created_by: str
# Any additional info. # Any additional info.
metadata: Dict[str, Any] metadata: Dict[str, Any]
def __init__(self, content: str, creator: str, metadata: Optional[Dict[str, Any]] = None) -> None: def __init__(self, content: str, created_by: str, metadata: Optional[Dict[str, Any]] = None) -> None:
super().__init__() super().__init__()
self.content = content self.content = content
self.creator = creator self.created_by = created_by
self.metadata = metadata self.metadata = metadata
@property @property
@@ -36,7 +36,7 @@ class BaseMessage(JSONSerializable):
return True return True
def __str__(self) -> str: def __str__(self) -> str:
return f"{self.creator}: {self.content}" return f"{self.created_by}: {self.content}"
class ChatMessage(JSONSerializable): class ChatMessage(JSONSerializable):
@@ -57,7 +57,7 @@ class ChatMessage(JSONSerializable):
overwritting it with new message." overwritting it with new message."
) )
self.human_message = BaseMessage(content=message, creator="human", metadata=metadata) self.human_message = BaseMessage(content=message, created_by="human", metadata=metadata)
def add_ai_message(self, message: str, metadata: Optional[dict] = None): def add_ai_message(self, message: str, metadata: Optional[dict] = None):
if self.ai_message: if self.ai_message:
@@ -66,7 +66,7 @@ class ChatMessage(JSONSerializable):
overwritting it with new message." overwritting it with new message."
) )
self.ai_message = BaseMessage(content=message, creator="ai", metadata=metadata) self.ai_message = BaseMessage(content=message, created_by="ai", metadata=metadata)
def __str__(self) -> str: def __str__(self) -> str:
return f"{self.human_message}\n{self.ai_message}" return f"{self.human_message}\n{self.ai_message}"

103
poetry.lock generated
View File

@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. # This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
[[package]] [[package]]
name = "aiofiles" name = "aiofiles"
@@ -354,26 +354,6 @@ description = "The uncompromising code formatter."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
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lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.9,<3.12" python-versions = ">=3.9,<3.12"
content-hash = "335c42c91a2b5e4a1c3d8a7c39dee8665fd1eee0410e1bc6cb6cb1d6f6722445" content-hash = "2d59f37483caac14b4c0e10331facdab174deba143480df53340756330214010"

2
pyproject.toml
View File

@@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "embedchain" name = "embedchain"
version = "0.1.48" version = "0.1.49"
description = "Data platform for LLMs - Load, index, retrieve and sync any unstructured data" description = "Data platform for LLMs - Load, index, retrieve and sync any unstructured data"
authors = [ authors = [
"Taranjeet Singh <taranjeet@embedchain.ai>", "Taranjeet Singh <taranjeet@embedchain.ai>",

6
tests/embedchain/test_embedchain.py
View File

@@ -7,7 +7,7 @@ from embedchain import App
from embedchain.config import AppConfig, ChromaDbConfig from embedchain.config import AppConfig, ChromaDbConfig
from embedchain.embedchain import EmbedChain from embedchain.embedchain import EmbedChain
from embedchain.llm.base import BaseLlm from embedchain.llm.base import BaseLlm
from embedchain.memory.base import ECChatMemory from embedchain.memory.base import ChatHistory
from embedchain.vectordb.chroma import ChromaDB from embedchain.vectordb.chroma import ChromaDB
os.environ["OPENAI_API_KEY"] = "test-api-key" os.environ["OPENAI_API_KEY"] = "test-api-key"
@@ -31,7 +31,7 @@ def test_whole_app(app_instance, mocker):
BaseLlm, BaseLlm,
"add_history", "add_history",
) )
mocker.patch.object(ECChatMemory, "delete_chat_history", autospec=True) mocker.patch.object(ChatHistory, "delete", autospec=True)
app_instance.add(knowledge, data_type="text") app_instance.add(knowledge, data_type="text")
app_instance.query("What text did I give you?") app_instance.query("What text did I give you?")
@@ -50,7 +50,7 @@ def test_add_after_reset(app_instance, mocker):
app_instance = App(config=config, db=db) app_instance = App(config=config, db=db)
# mock delete chat history # mock delete chat history
mocker.patch.object(ECChatMemory, "delete_chat_history", autospec=True) mocker.patch.object(ChatHistory, "delete", autospec=True)
app_instance.reset() app_instance.reset()

10
tests/llm/test_chat.py
View File

@@ -5,7 +5,7 @@ from unittest.mock import MagicMock, patch
from embedchain import App from embedchain import App
from embedchain.config import AppConfig, BaseLlmConfig from embedchain.config import AppConfig, BaseLlmConfig
from embedchain.llm.base import BaseLlm from embedchain.llm.base import BaseLlm
from embedchain.memory.base import ECChatMemory from embedchain.memory.base import ChatHistory
from embedchain.memory.message import ChatMessage from embedchain.memory.message import ChatMessage
@@ -36,11 +36,11 @@ class TestApp(unittest.TestCase):
with patch.object(BaseLlm, "add_history") as mock_history: with patch.object(BaseLlm, "add_history") as mock_history:
first_answer = app.chat("Test query 1") first_answer = app.chat("Test query 1")
self.assertEqual(first_answer, "Test answer") self.assertEqual(first_answer, "Test answer")
mock_history.assert_called_with(app.config.id, "Test query 1", "Test answer") mock_history.assert_called_with(app.config.id, "Test query 1", "Test answer", session_id="default")
second_answer = app.chat("Test query 2") second_answer = app.chat("Test query 2", session_id="test_session")
self.assertEqual(second_answer, "Test answer") self.assertEqual(second_answer, "Test answer")
mock_history.assert_called_with(app.config.id, "Test query 2", "Test answer") mock_history.assert_called_with(app.config.id, "Test query 2", "Test answer", session_id="test_session")
@patch.object(App, "_retrieve_from_database", return_value=["Test context"]) @patch.object(App, "_retrieve_from_database", return_value=["Test context"])
@patch.object(BaseLlm, "get_answer_from_llm", return_value="Test answer") @patch.object(BaseLlm, "get_answer_from_llm", return_value="Test answer")
@@ -51,7 +51,7 @@ class TestApp(unittest.TestCase):
Also tests that a dry run does not change the history Also tests that a dry run does not change the history
""" """
with patch.object(ECChatMemory, "get_recent_memories") as mock_memory: with patch.object(ChatHistory, "get") as mock_memory:
mock_message = ChatMessage() mock_message = ChatMessage()
mock_message.add_user_message("Test query 1") mock_message.add_user_message("Test query 1")
mock_message.add_ai_message("Test answer") mock_message.add_ai_message("Test answer")

27
tests/memory/test_chat_memory.py
View File

@@ -1,17 +1,18 @@
import pytest import pytest
from embedchain.memory.base import ECChatMemory from embedchain.memory.base import ChatHistory
from embedchain.memory.message import ChatMessage from embedchain.memory.message import ChatMessage
# Fixture for creating an instance of ECChatMemory # Fixture for creating an instance of ChatHistory
@pytest.fixture @pytest.fixture
def chat_memory_instance(): def chat_memory_instance():
return ECChatMemory() return ChatHistory()
def test_add_chat_memory(chat_memory_instance): def test_add_chat_memory(chat_memory_instance):
app_id = "test_app" app_id = "test_app"
session_id = "test_session"
human_message = "Hello, how are you?" human_message = "Hello, how are you?"
ai_message = "I'm fine, thank you!" ai_message = "I'm fine, thank you!"
@@ -19,14 +20,15 @@ def test_add_chat_memory(chat_memory_instance):
chat_message.add_user_message(human_message) chat_message.add_user_message(human_message)
chat_message.add_ai_message(ai_message) chat_message.add_ai_message(ai_message)
chat_memory_instance.add(app_id, chat_message) chat_memory_instance.add(app_id, session_id, chat_message)
assert chat_memory_instance.count_history_messages(app_id) == 1 assert chat_memory_instance.count(app_id, session_id) == 1
chat_memory_instance.delete_chat_history(app_id) chat_memory_instance.delete(app_id, session_id)
def test_get_recent_memories(chat_memory_instance): def test_get(chat_memory_instance):
app_id = "test_app" app_id = "test_app"
session_id = "test_session"
for i in range(1, 7): for i in range(1, 7):
human_message = f"Question {i}" human_message = f"Question {i}"
@@ -36,15 +38,16 @@ def test_get_recent_memories(chat_memory_instance):
chat_message.add_user_message(human_message) chat_message.add_user_message(human_message)
chat_message.add_ai_message(ai_message) chat_message.add_ai_message(ai_message)
chat_memory_instance.add(app_id, chat_message) chat_memory_instance.add(app_id, session_id, chat_message)
recent_memories = chat_memory_instance.get_recent_memories(app_id, num_rounds=5) recent_memories = chat_memory_instance.get(app_id, session_id, num_rounds=5)
assert len(recent_memories) == 5 assert len(recent_memories) == 5
def test_delete_chat_history(chat_memory_instance): def test_delete_chat_history(chat_memory_instance):
app_id = "test_app" app_id = "test_app"
session_id = "test_session"
for i in range(1, 6): for i in range(1, 6):
human_message = f"Question {i}" human_message = f"Question {i}"
@@ -54,11 +57,11 @@ def test_delete_chat_history(chat_memory_instance):
chat_message.add_user_message(human_message) chat_message.add_user_message(human_message)
chat_message.add_ai_message(ai_message) chat_message.add_ai_message(ai_message)
chat_memory_instance.add(app_id, chat_message) chat_memory_instance.add(app_id, session_id, chat_message)
chat_memory_instance.delete_chat_history(app_id) chat_memory_instance.delete(app_id, session_id)
assert chat_memory_instance.count_history_messages(app_id) == 0 assert chat_memory_instance.count(app_id, session_id) == 0
@pytest.fixture @pytest.fixture

12
tests/memory/test_memory_messages.py
View File

@@ -3,17 +3,17 @@ from embedchain.memory.message import BaseMessage, ChatMessage
def test_ec_base_message(): def test_ec_base_message():
content = "Hello, how are you?" content = "Hello, how are you?"
creator = "human" created_by = "human"
metadata = {"key": "value"} metadata = {"key": "value"}
message = BaseMessage(content=content, creator=creator, metadata=metadata) message = BaseMessage(content=content, created_by=created_by, metadata=metadata)
assert message.content == content assert message.content == content
assert message.creator == creator assert message.created_by == created_by
assert message.metadata == metadata assert message.metadata == metadata
assert message.type is None assert message.type is None
assert message.is_lc_serializable() is True assert message.is_lc_serializable() is True
assert str(message) == f"{creator}: {content}" assert str(message) == f"{created_by}: {content}"
def test_ec_base_chat_message(): def test_ec_base_chat_message():
@@ -27,11 +27,11 @@ def test_ec_base_chat_message():
chat_message.add_ai_message(ai_message_content, metadata=ai_metadata) chat_message.add_ai_message(ai_message_content, metadata=ai_metadata)
assert chat_message.human_message.content == human_message_content assert chat_message.human_message.content == human_message_content
assert chat_message.human_message.creator == "human" assert chat_message.human_message.created_by == "human"
assert chat_message.human_message.metadata == human_metadata assert chat_message.human_message.metadata == human_metadata
assert chat_message.ai_message.content == ai_message_content assert chat_message.ai_message.content == ai_message_content
assert chat_message.ai_message.creator == "ai" assert chat_message.ai_message.created_by == "ai"
assert chat_message.ai_message.metadata == ai_metadata assert chat_message.ai_message.metadata == ai_metadata
assert str(chat_message) == f"human: {human_message_content}\nai: {ai_message_content}" assert str(chat_message) == f"human: {human_message_content}\nai: {ai_message_content}"