Metadata-Version: 2.4
Name: memorer
Version: 0.5.2
Summary: Semantic memory for conversational AI - remember, recall, forget. Sub-100ms retrieval with emotional ranking and graph reasoning.
Project-URL: Homepage, https://memorer.ai
Project-URL: Documentation, https://docs.memorer.ai
Project-URL: Repository, https://github.com/memorer/memorer-python
Project-URL: Issues, https://github.com/memorer/memorer-python/issues
Project-URL: Changelog, https://github.com/memorer/memorer-python/releases
Author-email: Memorer Team <bahaa@memorer.ai>
License: Apache-2.0
License-File: LICENSE
Keywords: ai,chatbot,conversational-ai,knowledge-graph,llm,memory,multi-tenant,rag,retrieval,semantic-search
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Typing :: Typed
Requires-Python: >=3.9
Requires-Dist: httpx>=0.24.0
Requires-Dist: pydantic>=2.0.0
Provides-Extra: dev
Requires-Dist: mypy>=1.0.0; extra == 'dev'
Requires-Dist: pytest-asyncio>=0.21.0; extra == 'dev'
Requires-Dist: pytest-cov>=4.0.0; extra == 'dev'
Requires-Dist: pytest>=7.0.0; extra == 'dev'
Requires-Dist: ruff>=0.1.0; extra == 'dev'
Description-Content-Type: text/markdown

# Memorer Python SDK

Memory for AI agents. Remember conversations, recall context, forget when needed.

```bash
pip install memorer
```

## Usage

```python
from memorer import Memorer

client = Memorer(api_key="mem_sk_...")
user = client.for_user("user-123")

# During conversation, store what matters
user.remember("User mentioned they're allergic to shellfish")
user.remember("Has a meeting with Sarah next Friday at 2pm")
user.remember("Just adopted a dog named Biscuit")

# Before responding, recall relevant context
results = user.recall("any dietary restrictions?")
print(results.context)
# → "User is allergic to shellfish"

results = user.recall("what's on their schedule?")
print(results.context)
# → "Meeting with Sarah on Friday at 2pm"
```

## Conversations

Track conversation history (short-term memory) combined with semantic recall (long-term memory):

```python
# Start or continue a conversation
conv = user.conversation("session-123")  # existing session
# or
conv = user.conversation()  # create new

# Add messages (auto-extracts memories)
conv.add("user", "I just moved to Seattle and love coffee")
conv.add("assistant", "Welcome to Seattle! Great city for coffee lovers.")

# Query with conversation context + long-term memories
result = conv.recall("where does the user live")
print(result.context)  # Combined context ready for LLM
# → Recent conversation + "User lives in Seattle" (extracted memory)

# Get recent messages
messages = conv.messages(limit=20)
```

## Graph Reasoning

Connect memories across conversations:

```python
results = user.recall(
    "gift ideas for them",
    use_graph_reasoning=True,
)
# → Connects: new dog + mentioned liking outdoors → dog hiking gear
```

## Resources

```python
entities = user.entities.list()
memories = user.memories.list()
conversations = user.conversations.list()
communities = client.graph.communities()
```

## Links

- [Docs](https://docs.memorer.ai)
- [API Reference](https://docs.memorer.ai/api)
