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Mem0 1.0.0 (#3545)

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This commit is contained in:
Parshva Daftari
2025-10-16 15:50:20 +05:30
committed by GitHub
parent 8f5151c344
commit 394203d1b5
77 changed files with 3445 additions and 990 deletions
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docs/integrations/agno.mdx
+2 -2
View File
@@ -120,7 +120,7 @@ def chat_user(
})
# Store messages in memory
client.add(messages, user_id=user_id, output_format='v1.1')
client.add(messages, user_id=user_id)
print("✅ Image and text stored in memory.")
if user_input:
@@ -151,7 +151,7 @@ User question:
# Store the interaction in memory
interaction_message = [{"role": "user", "content": f"User: {user_input}\nAssistant: {response.content}"}]
client.add(interaction_message, user_id=user_id, output_format='v1.1')
client.add(interaction_message, user_id=user_id)
return response.content
return "No user input or image provided."
docs/integrations/elevenlabs.mdx
+4 -13
View File
@@ -122,10 +122,8 @@ Define the two key memory functions that will be registered as tools:
"""Add a message to the memory store"""
message = parameters.get("message")
await mem0_client.add(
messages=message,
user_id=USER_ID,
output_format="v1.1",
version="v2"
messages=message,
user_id=USER_ID
)
return "Memory added successfully"
@@ -133,19 +131,12 @@ Define the two key memory functions that will be registered as tools:
"""Retrieve relevant memories based on the input message"""
message = parameters.get("message")
# Set up filters to retrieve memories for this specific user
filters = {
"AND": [
{
"user_id": USER_ID
}
]
}
# For Platform API, user_id goes in filters
filters = {"user_id": USER_ID}
# Search for relevant memories using the message as a query
results = await mem0_client.search(
query=message,
version="v2",
filters=filters
)
docs/integrations/google-ai-adk.mdx
+12 -5
View File
@@ -50,7 +50,9 @@ mem0 = MemoryClient()
# Define memory function tools
def search_memory(query: str, user_id: str) -> dict:
"""Search through past conversations and memories"""
memories = mem0.search(query, user_id=user_id)
# For Platform API, user_id goes in filters
filters = {"user_id": user_id}
memories = mem0.search(query, filters=filters)
if memories.get('results', []):
memory_list = memories['results']
memory_context = "\n".join([f"- {mem['memory']}" for mem in memory_list])
@@ -255,12 +257,17 @@ if __name__ == "__main__":
Customize memory behavior and agent setup:
```python
# Configure memory search with metadata
# Configure memory search with filters
# For Platform API, all filters including user_id go in filters object
memories = mem0.search(
query="travel preferences",
user_id="alice",
limit=5,
filters={"category": "travel"} # Filter by category if supported
filters={
"AND": [
{"user_id": "alice"},
{"categories": {"contains": "travel"}}
]
},
limit=5
)
# Configure agent with custom model settings
docs/integrations/langchain-tools.mdx
+10 -19
View File
@@ -53,7 +53,6 @@ class Message(BaseModel):
class AddMemoryInput(BaseModel):
messages: List[Message] = Field(description="List of messages to add to memory")
user_id: str = Field(description="ID of the user associated with these messages")
output_format: str = Field(description="Version format for the output")
metadata: Optional[Dict[str, Any]] = Field(description="Additional metadata for the messages", default=None)
class Config:
@@ -64,7 +63,6 @@ class AddMemoryInput(BaseModel):
{"role": "assistant", "content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy."}
],
"user_id": "alex",
"output_format": "v1.1",
"metadata": {"food": "vegan"}
}]
}
@@ -73,10 +71,10 @@ class AddMemoryInput(BaseModel):
#### Implementation
```python
def add_memory(messages: List[Message], user_id: str, output_format: str, metadata: Optional[Dict[str, Any]] = None) -> Any:
def add_memory(messages: List[Message], user_id: str, metadata: Optional[Dict[str, Any]] = None) -> Any:
"""Add messages to memory with associated user ID and metadata."""
message_dicts = [msg.dict() for msg in messages]
return client.add(message_dicts, user_id=user_id, output_format=output_format, metadata=metadata)
return client.add(message_dicts, user_id=user_id, metadata=metadata)
add_tool = StructuredTool(
name="add_memory",
@@ -96,7 +94,6 @@ add_input = {
{"role": "assistant", "content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy."}
],
"user_id": "alex",
"output_format": "v1.1",
"metadata": {"food": "vegan"}
}
add_result = add_tool.invoke(add_input)
@@ -132,7 +129,6 @@ The SEARCH tool enables querying stored memories using natural language queries
class SearchMemoryInput(BaseModel):
query: str = Field(description="The search query string")
filters: Dict[str, Any] = Field(description="Filters to apply to the search")
version: str = Field(description="Version of the memory to search")
class Config:
json_schema_extra = {
@@ -143,8 +139,7 @@ class SearchMemoryInput(BaseModel):
{"user_id": "alex"},
{"created_at": {"gte": "2024-01-01", "lte": "2024-12-31"}}
]
},
"version": "v2"
}
}]
}
```
@@ -152,9 +147,9 @@ class SearchMemoryInput(BaseModel):
#### Implementation
```python
def search_memory(query: str, filters: Dict[str, Any], version: str) -> Any:
def search_memory(query: str, filters: Dict[str, Any]) -> Any:
"""Search memory with the given query and filters."""
return client.search(query=query, version=version, filters=filters)
return client.search(query=query, filters=filters)
search_tool = StructuredTool(
name="search_memory",
@@ -172,11 +167,10 @@ search_input = {
"query": "what is my name?",
"filters": {
"AND": [
{"created_at": {"gte": "2024-07-20", "lte": "2024-12-10"}},
{"user_id": "alex"}
{"user_id": "alex"},
{"created_at": {"gte": "2024-07-20", "lte": "2024-12-10"}}
]
},
"version": "v2"
}
}
result = search_tool.invoke(search_input)
```
@@ -210,7 +204,6 @@ The GET_ALL tool retrieves all memories matching specified criteria, with suppor
```python
class GetAllMemoryInput(BaseModel):
version: str = Field(description="Version of the memory to retrieve")
filters: Dict[str, Any] = Field(description="Filters to apply to the retrieval")
page: Optional[int] = Field(description="Page number for pagination", default=1)
page_size: Optional[int] = Field(description="Number of items per page", default=50)
@@ -218,7 +211,6 @@ class GetAllMemoryInput(BaseModel):
class Config:
json_schema_extra = {
"examples": [{
"version": "v2",
"filters": {
"AND": [
{"user_id": "alex"},
@@ -235,9 +227,9 @@ class GetAllMemoryInput(BaseModel):
#### Implementation
```python
def get_all_memory(version: str, filters: Dict[str, Any], page: int = 1, page_size: int = 50) -> Any:
def get_all_memory(filters: Dict[str, Any], page: int = 1, page_size: int = 50) -> Any:
"""Retrieve all memories matching the specified criteria."""
return client.get_all(version=version, filters=filters, page=page, page_size=page_size)
return client.get_all(filters=filters, page=page, page_size=page_size)
get_all_tool = StructuredTool(
name="get_all_memory",
@@ -252,7 +244,6 @@ get_all_tool = StructuredTool(
<CodeGroup>
```python Code
get_all_input = {
"version": "v2",
"filters": {
"AND": [
{"user_id": "alex"},
docs/integrations/llama-index.mdx
+1 -2
View File
@@ -41,7 +41,6 @@ context = {"user_id": "alice"}
memory_from_client = Mem0Memory.from_client(
context=context,
search_msg_limit=4, # optional, default is 5
output_format='v1.1', # Remove deprecation warnings
)
```
@@ -103,7 +102,7 @@ memory_from_config = Mem0Memory.from_config(
context=context,
config=config,
search_msg_limit=4, # optional, default is 5
output_format='v1.1', # Remove deprecation warnings
# Remove deprecation warnings
)
```