Rename embedchain to mem0 and open sourcing code for long term memory (#1474)

Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>

.env.example

@@ -1 +0,0 @@
-OPENAI_API_KEY="your-openai-api-key"

.gitignore

@@ -179,3 +179,6 @@ notebooks/*.yaml
 
 # cache db
 *.db
+
+# local directories for testing
+eval/

.pre-commit-config.yaml

@@ -1,20 +0,0 @@
-repos:
-  - repo: https://github.com/psf/black
-    rev: 23.3.0
-    hooks:
-      - id: black
-  - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: 'v0.0.252'
-    hooks:
-      - id: ruff
-        name: ruff
-        # Respect `exclude` and `extend-exclude` settings.
-        args: ["--force-exclude"]
-  - repo: local
-    hooks:
-      - id: pytest-check
-        name: pytest-check
-        entry: poetry run pytest
-        language: system
-        pass_filenames: false
-        always_run: true

Makefile

@@ -1,46 +1,26 @@
+.PHONY: format sort lint
+
 # Variables
-PYTHON := python3
-PIP := $(PYTHON) -m pip
-PROJECT_NAME := embedchain
+RUFF_OPTIONS = --line-length 120
+ISORT_OPTIONS = --profile black
 
-# Targets
-.PHONY: install format lint clean test ci_lint ci_test coverage
-
-install:
-	poetry install
-
-# TODO: use a more efficient way to install these packages
-install_all:
-	poetry install --all-extras
-	poetry run pip install pinecone-text pinecone-client langchain-anthropic "unstructured[local-inference, all-docs]" ollama langchain_together==0.1.3 \
-		langchain_cohere==0.1.5 deepgram-sdk==3.2.7 langchain-huggingface psutil clarifai==10.0.1 flask==2.3.3 twilio==8.5.0 fastapi-poe==0.0.16 discord==2.3.2 \
-	 	slack-sdk==3.21.3 huggingface_hub==0.23.0 gitpython==3.1.38 yt_dlp==2023.11.14 PyGithub==1.59.1 feedparser==6.0.10 newspaper3k==0.2.8 listparser==0.19 \
-	 	modal==0.56.4329 dropbox==11.36.2 boto3==1.34.20 youtube-transcript-api==0.6.1 pytube==15.0.0 beautifulsoup4==4.12.3
-
-install_es:
-	poetry install --extras elasticsearch
-
-install_opensearch:
-	poetry install --extras opensearch
-
-install_milvus:
-	poetry install --extras milvus
-
-shell:
-	poetry shell
-
-py_shell:
-	poetry run python
+# Default target
+all: format sort lint
 
+# Format code with ruff
 format:
-	$(PYTHON) -m black .
-	$(PYTHON) -m isort .
+	poetry run ruff check . --fix $(RUFF_OPTIONS)
 
-clean:
-	rm -rf dist build *.egg-info
+# Sort imports with isort
+sort:
+	poetry run isort . $(ISORT_OPTIONS)
 
+# Lint code with ruff
 lint:
-	poetry run ruff .
+	poetry run ruff check . $(RUFF_OPTIONS)
+
+docs:
+	cd docs && mintlify dev
 
 build:
 	poetry build
@@ -48,9 +28,5 @@ build:
 publish:
 	poetry publish
 
-# for example: make test file=tests/test_factory.py
-test:
-	poetry run pytest $(file)
-
-coverage:
-	poetry run pytest --cov=$(PROJECT_NAME) --cov-report=xml
+clean:
+	poetry run rm -rf dist

README.md

@@ -1,125 +1,197 @@
-<p align="center">
-  <img src="docs/logo/dark.svg" width="400px" alt="Embedchain Logo">
-</p>
+# Mem0: Long-Term Memory for LLMs
 
-<p align="center">
-  <a href="https://pypi.org/project/embedchain/">
-    <img src="https://img.shields.io/pypi/v/embedchain" alt="PyPI">
-  </a>
-  <a href="https://pepy.tech/project/embedchain">
-    <img src="https://static.pepy.tech/badge/embedchain" alt="Downloads">
-  </a>
-  <a href="https://embedchain.ai/slack">
-    <img src="https://img.shields.io/badge/slack-embedchain-brightgreen.svg?logo=slack" alt="Slack">
-  </a>
-  <a href="https://embedchain.ai/discord">
-    <img src="https://dcbadge.vercel.app/api/server/6PzXDgEjG5?style=flat" alt="Discord">
-  </a>
-  <a href="https://twitter.com/embedchain">
-    <img src="https://img.shields.io/twitter/follow/embedchain" alt="Twitter">
-  </a>
-  <a href="https://colab.research.google.com/drive/138lMWhENGeEu7Q1-6lNbNTHGLZXBBz_B?usp=sharing">
-    <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab">
-  </a>
-  <a href="https://codecov.io/gh/embedchain/embedchain">
-    <img src="https://codecov.io/gh/embedchain/embedchain/graph/badge.svg?token=EMRRHZXW1Q" alt="codecov">
-  </a>
-</p>
+Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.
 
-<hr />
+## Features
 
-## What is Embedchain?
+- Persistent memory for users, sessions, and agents
+- Self-improving personalization
+- Simple API for easy integration
+- Cross-platform consistency
 
-Embedchain is an Open Source Framework for personalizing LLM responses. It makes it easy to create and deploy personalized AI apps. At its core, Embedchain follows the design principle of being *"Conventional but Configurable"* to serve both software engineers and machine learning engineers.
+## Quick Start
 
-Embedchain streamlines the creation of personalized LLM applications, offering a seamless process for managing various types of unstructured data. It efficiently segments data into manageable chunks, generates relevant embeddings, and stores them in a vector database for optimized retrieval. With a suite of diverse APIs, it enables users to extract contextual information, find precise answers, or engage in interactive chat conversations, all tailored to their own data.
+### Installation
 
-## 🔧 Quick install
-
-### Python API
 
 ```bash
-pip install embedchain
+pip install mem0ai
 ```
 
-## ✨ Live demo
+## Usage
 
-Checkout the [Chat with PDF](https://embedchain.ai/demo/chat-pdf) live demo we created using Embedchain. You can find the source code [here](https://github.com/embedchain/embedchain/tree/main/examples/chat-pdf).
-
-## 🔍 Usage
-
-<!-- Demo GIF or Image -->
-<p align="center">
-  <img src="docs/images/cover.gif" width="900px" alt="Embedchain Demo">
-</p>
-
-For example, you can create an Elon Musk bot using the following code:
+### Instantiate
 
 ```python
-import os
-from embedchain import App
+from mem0 import Memory
 
-# Create a bot instance
-os.environ["OPENAI_API_KEY"] = "<YOUR_API_KEY>"
-app = App()
-
-# Embed online resources
-app.add("https://en.wikipedia.org/wiki/Elon_Musk")
-app.add("https://www.forbes.com/profile/elon-musk")
-
-# Query the app
-app.query("How many companies does Elon Musk run and name those?")
-# Answer: Elon Musk currently runs several companies. As of my knowledge, he is the CEO and lead designer of SpaceX, the CEO and product architect of Tesla, Inc., the CEO and founder of Neuralink, and the CEO and founder of The Boring Company. However, please note that this information may change over time, so it's always good to verify the latest updates.
+m = Memory()
 ```
 
-You can also try it in your browser with Google Colab:
+If you want to use Qdrant in server mode, use the following method to instantiate.
 
-[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/17ON1LPonnXAtLaZEebnOktstB_1cJJmh?usp=sharing)
+Run qdrant first:
 
-## 📖 Documentation
-Comprehensive guides and API documentation are available to help you get the most out of Embedchain:
-
-- [Introduction](https://docs.embedchain.ai/get-started/introduction#what-is-embedchain)
-- [Getting Started](https://docs.embedchain.ai/get-started/quickstart)
-- [Examples](https://docs.embedchain.ai/examples)
-- [Supported data types](https://docs.embedchain.ai/components/data-sources/overview)
-
-## 🔗 Join the Community
-
-* Connect with fellow developers by joining our [Slack Community](https://embedchain.ai/slack) or [Discord Community](https://embedchain.ai/discord).
-
-* Dive into [GitHub Discussions](https://github.com/embedchain/embedchain/discussions), ask questions, or share your experiences.
-
-## 🤝 Schedule a 1-on-1 Session
-
-Book a [1-on-1 Session](https://cal.com/taranjeetio/ec) with the founders, to discuss any issues, provide feedback, or explore how we can improve Embedchain for you.
-
-## 🌐 Contributing
-
-Contributions are welcome! Please check out the issues on the repository, and feel free to open a pull request.
-For more information, please see the [contributing guidelines](CONTRIBUTING.md).
-
-For more reference, please go through [Development Guide](https://docs.embedchain.ai/contribution/dev) and [Documentation Guide](https://docs.embedchain.ai/contribution/docs).
-
-<a href="https://github.com/embedchain/embedchain/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=embedchain/embedchain" />
-</a>
-
-## Anonymous Telemetry
-
-We collect anonymous usage metrics to enhance our package's quality and user experience. This includes data like feature usage frequency and system info, but never personal details. The data helps us prioritize improvements and ensure compatibility. If you wish to opt-out, set the environment variable `EC_TELEMETRY=false`. We prioritize data security and don't share this data externally.
-
-## Citation
-
-If you utilize this repository, please consider citing it with:
+```bash
+docker pull qdrant/qdrant
 
+docker run -p 6333:6333 -p 6334:6334 \
+    -v $(pwd)/qdrant_storage:/qdrant/storage:z \
+    qdrant/qdrant
 ```
-@misc{embedchain,
-  author = {Taranjeet Singh, Deshraj Yadav},
-  title = {Embedchain: The Open Source RAG Framework},
-  year = {2023},
-  publisher = {GitHub},
-  journal = {GitHub repository},
-  howpublished = {\url{https://github.com/embedchain/embedchain}},
+
+Then, instantiate memory with qdrant server:
+
+```python
+from mem0 import Memory
+
+config = {
+    "vector_store": {
+        "provider": "qdrant",
+        "config": {
+            "host": "localhost",
+            "port": 6333,
+        }
+    },
 }
+
+m = Memory.from_config(config)
 ```
+
+### Store a Memory
+
+```python
+m.add("Likes to play cricket over weekend", user_id="alex", metadata={"foo": "bar"})
+# Output:
+# [
+#   {
+#     'id': 'm1',
+#     'event': 'add',
+#     'data': 'Likes to play cricket over weekend'
+#   }
+# ]
+
+# Similarly, you can store a memory for an agent
+m.add("Agent X is best travel agent in Paris", agent_id="agent-x", metadata={"type": "long-term"})
+```
+
+### Retrieve all memories
+
+#### 1. Get all memories
+```python
+m.get_all()
+# Output:
+# [
+#   {
+#     'id': 'm1',
+#     'text': 'Likes to play cricket over weekend',
+#     'metadata': {
+#       'data': 'Likes to play cricket over weekend'
+#     }
+#   },
+#   {
+#     'id': 'm2',
+#     'text': 'Agent X is best travel agent in Paris',
+#     'metadata': {
+#       'data': 'Agent X is best travel agent in Paris'
+#     }
+#   }
+# ]
+
+```
+#### 2. Get memories for specific user
+
+```python
+m.get_all(user_id="alex")
+```
+
+#### 3. Get memories for specific agent
+
+```python
+m.get_all(agent_id="agent-x")
+```
+
+#### 4. Get memories for a user during an agent run
+
+```python
+m.get_all(agent_id="agent-x", user_id="alex")
+```
+
+### Retrieve a Memory
+
+```python
+memory_id = "m1"
+m.get(memory_id)
+# Output:
+# {
+#   'id': '1',
+#   'text': 'Likes to play cricket over weekend',
+#   'metadata': {
+#     'data': 'Likes to play cricket over weekend'
+#   }
+# }
+```
+
+### Search for related memories
+
+```python
+m.search(query="What is my name", user_id="deshraj")
+```
+
+### Update a Memory
+
+```python
+m.update(memory_id="m1", data="Likes to play tennis")
+```
+
+### Get history of a Memory
+
+```python
+m.history(memory_id="m1")
+# Output:
+# [
+#   {
+#     'id': 'h1',
+#     'memory_id': 'm1',
+#     'prev_value': None,
+#     'new_value': 'Likes to play cricket over weekend',
+#     'event': 'add',
+#     'timestamp': '2024-06-12 21:00:54.466687',
+#     'is_deleted': 0
+#   },
+#   {
+#     'id': 'h2',
+#     'memory_id': 'm1',
+#     'prev_value': 'Likes to play cricket over weekend',
+#     'new_value': 'Likes to play tennis',
+#     'event': 'update',
+#     'timestamp': '2024-06-12 21:01:17.230943',
+#     'is_deleted': 0
+#   }
+# ]
+```
+
+### Delete a Memory
+
+#### Delete specific memory
+
+```python
+m.delete(memory_id="m1")
+```
+
+#### Delete memories for a user or agent
+
+```python
+m.delete_all(user_id="alex")
+m.delete_all(agent_id="agent-x")
+```
+
+#### Delete all Memories
+
+```python
+m.reset()
+```
+
+## License
+
+[Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0)

docs/README.md

@@ -1,7 +1,14 @@
-# Contributing to embedchain docs
+# Mintlify Starter Kit
 
+Click on `Use this template` to copy the Mintlify starter kit. The starter kit contains examples including
 
-### 👩‍💻 Development
+- Guide pages
+- Navigation
+- Customizations
+- API Reference pages
+- Use of popular components
+
+### Development
 
 Install the [Mintlify CLI](https://www.npmjs.com/package/mintlify) to preview the documentation changes locally. To install, use the following command
 
@@ -15,9 +22,9 @@ Run the following command at the root of your documentation (where mint.json is)
 mintlify dev
 ```
 
-### 😎 Publishing Changes
+### Publishing Changes
 
-Changes will be deployed to production automatically after your PR is merged to the main branch.
+Install our Github App to auto propagate changes from your repo to your deployment. Changes will be deployed to production automatically after pushing to the default branch. Find the link to install on your dashboard. 
 
 #### Troubleshooting
 

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docs/introduction.mdx

@@ -0,0 +1,191 @@
+---
+title: Introduction
+description: 'Welcome to the Mem0 documentation'
+---
+
+Mem0 is the long-term memory for AI Agents.
+
+## Installation
+
+```bash
+pip install mem0ai
+```
+
+## Usage
+
+### Instantiate
+
+```python
+from mem0 import Memory
+m = Memory()
+```
+
+Mem0 uses Qdrant by default for storing the semantic memories. If you want to use Qdrant in server mode, use the following method to instantiate.
+
+Run qdrant first:
+
+```bash
+docker pull qdrant/qdrant
+
+docker run -p 6333:6333 -p 6334:6334 \
+    -v $(pwd)/qdrant_storage:/qdrant/storage:z \
+    qdrant/qdrant
+```
+
+Then, instantiate memory with qdrant server:
+
+```python
+from mem0 import Memory
+
+config = {
+    "vector_store": {
+        "provider": "qdrant",
+        "config": {
+            "host": "localhost",
+            "port": 6333,
+        }
+    },
+}
+
+m = Memory.from_config(config)
+```
+
+### Store a Memory
+
+```python
+m.add("Likes to play cricket over weekend", user_id="deshraj", metadata={"foo": "bar"})
+# Output:
+# [
+#   {
+#     'id': 'm1',
+#     'event': 'add',
+#     'data': 'Likes to play cricket over weekend'
+#   }
+# ]
+
+# Similarly, you can store a memory for an agent
+m.add("Agent X is best travel agent in Paris", agent_id="agent-x", metadata={"type": "long-term"})
+```
+
+### Retrieve all memories
+
+#### 1. Get all memories
+```python
+m.get_all()
+# Output:
+# [
+#   {
+#     'id': 'm1',
+#     'text': 'Likes to play cricket over weekend',
+#     'metadata': {
+#       'data': 'Likes to play cricket over weekend'
+#     }
+#   },
+#   {
+#     'id': 'm2',
+#     'text': 'Agent X is best travel agent in Paris',
+#     'metadata': {
+#       'data': 'Agent X is best travel agent in Paris'
+#     }
+#   }
+# ]
+
+```
+#### 2. Get memories for specific user
+
+```python
+m.get_all(user_id="deshraj")
+```
+
+#### 3. Get memories for specific agent
+
+```python
+m.get_all(agent_id="agent-x")
+```
+
+#### 4. Get memories for a user during an agent run
+
+```python
+m.get_all(agent_id="agent-x", user_id="deshraj")
+```
+
+### Retrieve a Memory
+
+```python
+memory_id = "m1"
+m.get(memory_id)
+# Output:
+# {
+#   'id': '1',
+#   'text': 'Likes to play cricket over weekend',
+#   'metadata': {
+#     'data': 'Likes to play cricket over weekend'
+#   }
+# }
+```
+
+### Search for related memories
+
+```python
+m.search(query="What is my name", user_id="deshraj")
+```
+
+### Update a Memory
+
+```python
+m.update(memory_id="m1", data="Likes to play tennis")
+```
+
+### Get history of a Memory
+
+```python
+m.history(memory_id="m1")
+# Output:
+# [
+#   {
+#     'id': 'h1',
+#     'memory_id': 'm1',
+#     'prev_value': None,
+#     'new_value': 'Likes to play cricket over weekend',
+#     'event': 'add',
+#     'timestamp': '2024-06-12 21:00:54.466687',
+#     'is_deleted': 0
+#   },
+#   {
+#     'id': 'h2',
+#     'memory_id': 'm1',
+#     'prev_value': 'Likes to play cricket over weekend',
+#     'new_value': 'Likes to play tennis',
+#     'event': 'update',
+#     'timestamp': '2024-06-12 21:01:17.230943',
+#     'is_deleted': 0
+#   }
+# ]
+```
+
+### Delete a Memory
+
+```python
+m.delete(memory_id="m1")
+```
+
+### Delete memories of a user or agent
+
+```python
+m.delete_all(user_id="deshraj")
+m.delete_all(agent_id="agent-x")
+```
+
+### Delete all Memories
+
+```python
+m.reset()
+```
+
+## Contributing
+
+Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.
+
+## License
+
+[Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0)

docs/mint.json

@@ -1,12 +1,7 @@
 {
   "$schema": "https://mintlify.com/schema.json",
-  "name": "Embedchain",
-  "logo": {
-    "dark": "/logo/dark-rt.svg",
-    "light": "/logo/light-rt.svg",
-    "href": "https://github.com/embedchain/embedchain"
-  },
-  "favicon": "/favicon.png",
+  "name": "Mem0.ai",
+  "favicon": "/logo/light.svg",
   "colors": {
     "primary": "#3B2FC9",
     "light": "#6673FF",
@@ -16,262 +11,40 @@
       "light": "#fff"
     }
   },
-  "modeToggle": {
-    "default": "dark"
+  "logo": {
+    "dark": "/logo/dark.svg",
+    "light": "/logo/light.svg",
+    "href": "https://github.com/embedchain/embedchain"
   },
-  "openapi": ["/rest-api.json"],
-  "metadata": {
-    "og:image": "/images/og.png",
-    "twitter:site": "@embedchain"
-  },
-  "tabs": [
+  "topbarLinks": [
     {
-      "name": "Examples",
-      "url": "examples"
-    },
-    {
-      "name": "API Reference",
-      "url": "api-reference"
+      "name": "Support",
+      "url": "mailto:founders@mem0.ai"
     }
   ],
   "anchors": [
     {
-      "name": "Talk to founders",
-      "icon": "calendar",
-      "url": "https://cal.com/taranjeetio/ec"
-    }
-  ],
-  "topbarLinks": [
+      "name": "Slack",
+      "icon": "slack",
+      "url": "https://mem0.ai/slack/"
+    },
     {
-      "name": "GitHub",
-      "url": "https://github.com/embedchain/embedchain"
+      "name": "Discord",
+      "icon": "discord",
+      "url": "https://mem0.ai/discord/"
     }
   ],
-  "topbarCtaButton": {
-    "name": "Join our slack",
-    "url": "https://embedchain.ai/slack"
-  },
-  "primaryTab": {
-    "name": "Documentation"
-  },
   "navigation": [
     {
       "group": "Get Started",
       "pages": [
-        "get-started/quickstart",
-        "get-started/introduction",
-        "get-started/faq",
-        "get-started/full-stack",
-        {
-          "group": "🔗 Integrations",
-          "pages": [
-            "integration/langsmith",
-            "integration/chainlit",
-            "integration/streamlit-mistral",
-            "integration/openlit",
-            "integration/helicone"
+        "introduction"
       ]
     }
-      ]
-    },
-    {
-      "group": "Use cases",
-      "pages": [
-        "use-cases/introduction",
-        "use-cases/chatbots",
-        "use-cases/question-answering",
-        "use-cases/semantic-search"
-      ]
-    },
-    {
-      "group": "Components",
-      "pages": [
-        "components/introduction",
-        {
-          "group": "🗂️ Data sources",
-          "pages": [
-            "components/data-sources/overview",
-            {
-              "group": "Data types",
-              "pages": [
-                "components/data-sources/pdf-file",
-                "components/data-sources/csv",
-                "components/data-sources/json",
-                "components/data-sources/text",
-                "components/data-sources/directory",
-                "components/data-sources/web-page",
-                "components/data-sources/youtube-channel",
-                "components/data-sources/youtube-video",
-                "components/data-sources/docs-site",
-                "components/data-sources/mdx",
-                "components/data-sources/docx",
-                "components/data-sources/notion",
-                "components/data-sources/sitemap",
-                "components/data-sources/xml",
-                "components/data-sources/qna",
-                "components/data-sources/openapi",
-                "components/data-sources/gmail",
-                "components/data-sources/github",
-                "components/data-sources/postgres",
-                "components/data-sources/mysql",
-                "components/data-sources/slack",
-                "components/data-sources/discord",
-                "components/data-sources/discourse",
-                "components/data-sources/substack",
-                "components/data-sources/beehiiv",
-                "components/data-sources/directory",
-                "components/data-sources/dropbox",
-                "components/data-sources/image",
-                "components/data-sources/custom"
-              ]
-            },
-            "components/data-sources/data-type-handling"
-          ]
-        },
-        {
-          "group": "🗄️ Vector databases",
-          "pages": [
-            "components/vector-databases/chromadb",
-            "components/vector-databases/elasticsearch",
-            "components/vector-databases/pinecone",
-            "components/vector-databases/opensearch",
-            "components/vector-databases/qdrant",
-            "components/vector-databases/weaviate",
-            "components/vector-databases/zilliz"
-          ]
-        },
-        "components/llms",
-        "components/embedding-models",
-        "components/evaluation"
-      ]
-    },
-    {
-      "group": "Deployment",
-      "pages": [
-        "get-started/deployment",
-        "deployment/fly_io",
-        "deployment/modal_com",
-        "deployment/render_com",
-        "deployment/railway",
-        "deployment/streamlit_io",
-        "deployment/gradio_app",
-        "deployment/huggingface_spaces"
-      ]
-    },
-    {
-      "group": "Community",
-      "pages": ["community/connect-with-us"]
-    },
-    {
-      "group": "Examples",
-      "pages": [
-        "examples/chat-with-PDF",
-        "examples/notebooks-and-replits",
-        {
-          "group": "REST API Service",
-          "pages": [
-            "examples/rest-api/getting-started",
-            "examples/rest-api/create",
-            "examples/rest-api/get-all-apps",
-            "examples/rest-api/add-data",
-            "examples/rest-api/get-data",
-            "examples/rest-api/query",
-            "examples/rest-api/deploy",
-            "examples/rest-api/delete",
-            "examples/rest-api/check-status"
-          ]
-        },
-        "examples/full_stack",
-        "examples/openai-assistant",
-        "examples/opensource-assistant",
-        "examples/nextjs-assistant",
-        "examples/slack-AI"
-      ]
-    },
-    {
-      "group": "Chatbots",
-      "pages": [
-        "examples/discord_bot",
-        "examples/slack_bot",
-        "examples/telegram_bot",
-        "examples/whatsapp_bot",
-        "examples/poe_bot"
-      ]
-    },
-    {
-      "group": "Showcase",
-      "pages": ["examples/showcase"]
-    },
-    {
-      "group": "API Reference",
-      "pages": [
-        "api-reference/app/overview",
-        {
-          "group": "App methods",
-          "pages": [
-            "api-reference/app/add",
-            "api-reference/app/query",
-            "api-reference/app/chat",
-            "api-reference/app/search",
-            "api-reference/app/get",
-            "api-reference/app/evaluate",
-            "api-reference/app/deploy",
-            "api-reference/app/reset",
-            "api-reference/app/delete"
-          ]
-        },
-        "api-reference/store/openai-assistant",
-        "api-reference/store/ai-assistants",
-        "api-reference/advanced/configuration"
-      ]
-    },
-    {
-      "group": "Contributing",
-      "pages": [
-        "contribution/guidelines",
-        "contribution/dev",
-        "contribution/docs",
-        "contribution/python"
-      ]
-    },
-    {
-      "group": "Product",
-      "pages": ["product/release-notes"]
-    }
   ],
   "footerSocials": {
-    "website": "https://embedchain.ai",
-    "github": "https://github.com/embedchain/embedchain",
-    "slack": "https://embedchain.ai/slack",
-    "discord": "https://discord.gg/6PzXDgEjG5",
-    "twitter": "https://twitter.com/embedchain",
-    "linkedin": "https://www.linkedin.com/company/embedchain"
-  },
-  "isWhiteLabeled": true,
-  "analytics": {
-    "posthog": {
-      "apiKey": "phc_PHQDA5KwztijnSojsxJ2c1DuJd52QCzJzT2xnSGvjN2",
-      "apiHost": "https://app.embedchain.ai/ingest"
-    },
-    "ga4": {
-      "measurementId": "G-4QK7FJE6T3"
+    "x": "https://x.com/mem0ai",
+    "github": "https://github.com/embedchain/embedchain/mem0",
+    "linkedin": "https://www.linkedin.com/company/mem0/"
   }
-  },
-  "feedback": {
-    "suggestEdit": true,
-    "raiseIssue": true,
-    "thumbsRating": true
-  },
-  "search": {
-    "prompt": "✨ Search embedchain docs..."
-  },
-  "api": {
-    "baseUrl": "http://localhost:8080"
-  },
-  "redirects": [
-    {
-      "source": "/changelog/command-line",
-      "destination": "/get-started/introduction"
-    }
-  ]
 }

docs/snippets/snippet-intro.mdx

@@ -0,0 +1,4 @@
+One of the core principles of software development is DRY (Don't Repeat
+Yourself). This is a principle that apply to documentation as
+well. If you find yourself repeating the same content in multiple places, you
+should consider creating a custom snippet to keep your content in sync.

embedchain/Makefile

@@ -0,0 +1,56 @@
+# Variables
+PYTHON := python3
+PIP := $(PYTHON) -m pip
+PROJECT_NAME := embedchain
+
+# Targets
+.PHONY: install format lint clean test ci_lint ci_test coverage
+
+install:
+	poetry install
+
+# TODO: use a more efficient way to install these packages
+install_all:
+	poetry install --all-extras
+	poetry run pip install pinecone-text pinecone-client langchain-anthropic "unstructured[local-inference, all-docs]" ollama langchain_together==0.1.3 \
+		langchain_cohere==0.1.5 deepgram-sdk==3.2.7 langchain-huggingface psutil clarifai==10.0.1 flask==2.3.3 twilio==8.5.0 fastapi-poe==0.0.16 discord==2.3.2 \
+	 	slack-sdk==3.21.3 huggingface_hub==0.23.0 gitpython==3.1.38 yt_dlp==2023.11.14 PyGithub==1.59.1 feedparser==6.0.10 newspaper3k==0.2.8 listparser==0.19 \
+	 	modal==0.56.4329 dropbox==11.36.2 boto3==1.34.20 youtube-transcript-api==0.6.1 pytube==15.0.0 beautifulsoup4==4.12.3
+
+install_es:
+	poetry install --extras elasticsearch
+
+install_opensearch:
+	poetry install --extras opensearch
+
+install_milvus:
+	poetry install --extras milvus
+
+shell:
+	poetry shell
+
+py_shell:
+	poetry run python
+
+format:
+	$(PYTHON) -m black .
+	$(PYTHON) -m isort .
+
+clean:
+	rm -rf dist build *.egg-info
+
+lint:
+	poetry run ruff .
+
+build:
+	poetry build
+
+publish:
+	poetry publish
+
+# for example: make test file=tests/test_factory.py
+test:
+	poetry run pytest $(file)
+
+coverage:
+	poetry run pytest --cov=$(PROJECT_NAME) --cov-report=xml

embedchain/README.md

@@ -0,0 +1,125 @@
+<p align="center">
+  <img src="docs/logo/dark.svg" width="400px" alt="Embedchain Logo">
+</p>
+
+<p align="center">
+  <a href="https://pypi.org/project/embedchain/">
+    <img src="https://img.shields.io/pypi/v/embedchain" alt="PyPI">
+  </a>
+  <a href="https://pepy.tech/project/embedchain">
+    <img src="https://static.pepy.tech/badge/embedchain" alt="Downloads">
+  </a>
+  <a href="https://embedchain.ai/slack">
+    <img src="https://img.shields.io/badge/slack-embedchain-brightgreen.svg?logo=slack" alt="Slack">
+  </a>
+  <a href="https://embedchain.ai/discord">
+    <img src="https://dcbadge.vercel.app/api/server/6PzXDgEjG5?style=flat" alt="Discord">
+  </a>
+  <a href="https://twitter.com/embedchain">
+    <img src="https://img.shields.io/twitter/follow/embedchain" alt="Twitter">
+  </a>
+  <a href="https://colab.research.google.com/drive/138lMWhENGeEu7Q1-6lNbNTHGLZXBBz_B?usp=sharing">
+    <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab">
+  </a>
+  <a href="https://codecov.io/gh/embedchain/embedchain">
+    <img src="https://codecov.io/gh/embedchain/embedchain/graph/badge.svg?token=EMRRHZXW1Q" alt="codecov">
+  </a>
+</p>
+
+<hr />
+
+## What is Embedchain?
+
+Embedchain is an Open Source Framework for personalizing LLM responses. It makes it easy to create and deploy personalized AI apps. At its core, Embedchain follows the design principle of being *"Conventional but Configurable"* to serve both software engineers and machine learning engineers.
+
+Embedchain streamlines the creation of personalized LLM applications, offering a seamless process for managing various types of unstructured data. It efficiently segments data into manageable chunks, generates relevant embeddings, and stores them in a vector database for optimized retrieval. With a suite of diverse APIs, it enables users to extract contextual information, find precise answers, or engage in interactive chat conversations, all tailored to their own data.
+
+## 🔧 Quick install
+
+### Python API
+
+```bash
+pip install embedchain
+```
+
+## ✨ Live demo
+
+Checkout the [Chat with PDF](https://embedchain.ai/demo/chat-pdf) live demo we created using Embedchain. You can find the source code [here](https://github.com/embedchain/embedchain/tree/main/examples/chat-pdf).
+
+## 🔍 Usage
+
+<!-- Demo GIF or Image -->
+<p align="center">
+  <img src="docs/images/cover.gif" width="900px" alt="Embedchain Demo">
+</p>
+
+For example, you can create an Elon Musk bot using the following code:
+
+```python
+import os
+from embedchain import App
+
+# Create a bot instance
+os.environ["OPENAI_API_KEY"] = "<YOUR_API_KEY>"
+app = App()
+
+# Embed online resources
+app.add("https://en.wikipedia.org/wiki/Elon_Musk")
+app.add("https://www.forbes.com/profile/elon-musk")
+
+# Query the app
+app.query("How many companies does Elon Musk run and name those?")
+# Answer: Elon Musk currently runs several companies. As of my knowledge, he is the CEO and lead designer of SpaceX, the CEO and product architect of Tesla, Inc., the CEO and founder of Neuralink, and the CEO and founder of The Boring Company. However, please note that this information may change over time, so it's always good to verify the latest updates.
+```
+
+You can also try it in your browser with Google Colab:
+
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/17ON1LPonnXAtLaZEebnOktstB_1cJJmh?usp=sharing)
+
+## 📖 Documentation
+Comprehensive guides and API documentation are available to help you get the most out of Embedchain:
+
+- [Introduction](https://docs.embedchain.ai/get-started/introduction#what-is-embedchain)
+- [Getting Started](https://docs.embedchain.ai/get-started/quickstart)
+- [Examples](https://docs.embedchain.ai/examples)
+- [Supported data types](https://docs.embedchain.ai/components/data-sources/overview)
+
+## 🔗 Join the Community
+
+* Connect with fellow developers by joining our [Slack Community](https://embedchain.ai/slack) or [Discord Community](https://embedchain.ai/discord).
+
+* Dive into [GitHub Discussions](https://github.com/embedchain/embedchain/discussions), ask questions, or share your experiences.
+
+## 🤝 Schedule a 1-on-1 Session
+
+Book a [1-on-1 Session](https://cal.com/taranjeetio/ec) with the founders, to discuss any issues, provide feedback, or explore how we can improve Embedchain for you.
+
+## 🌐 Contributing
+
+Contributions are welcome! Please check out the issues on the repository, and feel free to open a pull request.
+For more information, please see the [contributing guidelines](CONTRIBUTING.md).
+
+For more reference, please go through [Development Guide](https://docs.embedchain.ai/contribution/dev) and [Documentation Guide](https://docs.embedchain.ai/contribution/docs).
+
+<a href="https://github.com/embedchain/embedchain/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=embedchain/embedchain" />
+</a>
+
+## Anonymous Telemetry
+
+We collect anonymous usage metrics to enhance our package's quality and user experience. This includes data like feature usage frequency and system info, but never personal details. The data helps us prioritize improvements and ensure compatibility. If you wish to opt-out, set the environment variable `EC_TELEMETRY=false`. We prioritize data security and don't share this data externally.
+
+## Citation
+
+If you utilize this repository, please consider citing it with:
+
+```
+@misc{embedchain,
+  author = {Taranjeet Singh, Deshraj Yadav},
+  title = {Embedchain: The Open Source RAG Framework},
+  year = {2023},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  howpublished = {\url{https://github.com/embedchain/embedchain}},
+}
+```

embedchain/core/db/database.py

@@ -1,88 +0,0 @@
-import os
-
-from alembic import command
-from alembic.config import Config
-from sqlalchemy import create_engine
-from sqlalchemy.engine.base import Engine
-from sqlalchemy.orm import Session as SQLAlchemySession
-from sqlalchemy.orm import scoped_session, sessionmaker
-
-from .models import Base
-
-
-class DatabaseManager:
-    def __init__(self, echo: bool = False):
-        self.database_uri = os.environ.get("EMBEDCHAIN_DB_URI")
-        self.echo = echo
-        self.engine: Engine = None
-        self._session_factory = None
-
-    def setup_engine(self) -> None:
-        """Initializes the database engine and session factory."""
-        if not self.database_uri:
-            raise RuntimeError("Database URI is not set. Set the EMBEDCHAIN_DB_URI environment variable.")
-        connect_args = {}
-        if self.database_uri.startswith("sqlite"):
-            connect_args["check_same_thread"] = False
-        self.engine = create_engine(self.database_uri, echo=self.echo, connect_args=connect_args)
-        self._session_factory = scoped_session(sessionmaker(bind=self.engine))
-        Base.metadata.bind = self.engine
-
-    def init_db(self) -> None:
-        """Creates all tables defined in the Base metadata."""
-        if not self.engine:
-            raise RuntimeError("Database engine is not initialized. Call setup_engine() first.")
-        Base.metadata.create_all(self.engine)
-
-    def get_session(self) -> SQLAlchemySession:
-        """Provides a session for database operations."""
-        if not self._session_factory:
-            raise RuntimeError("Session factory is not initialized. Call setup_engine() first.")
-        return self._session_factory()
-
-    def close_session(self) -> None:
-        """Closes the current session."""
-        if self._session_factory:
-            self._session_factory.remove()
-
-    def execute_transaction(self, transaction_block):
-        """Executes a block of code within a database transaction."""
-        session = self.get_session()
-        try:
-            transaction_block(session)
-            session.commit()
-        except Exception as e:
-            session.rollback()
-            raise e
-        finally:
-            self.close_session()
-
-
-# Singleton pattern to use throughout the application
-database_manager = DatabaseManager()
-
-
-# Convenience functions for backward compatibility and ease of use
-def setup_engine(database_uri: str, echo: bool = False) -> None:
-    database_manager.database_uri = database_uri
-    database_manager.echo = echo
-    database_manager.setup_engine()
-
-
-def alembic_upgrade() -> None:
-    """Upgrades the database to the latest version."""
-    alembic_config_path = os.path.join(os.path.dirname(__file__), "..", "..", "alembic.ini")
-    alembic_cfg = Config(alembic_config_path)
-    command.upgrade(alembic_cfg, "head")
-
-
-def init_db() -> None:
-    alembic_upgrade()
-
-
-def get_session() -> SQLAlchemySession:
-    return database_manager.get_session()
-
-
-def execute_transaction(transaction_block):
-    database_manager.execute_transaction(transaction_block)

embedchain/core/db/models.py

@@ -1,31 +0,0 @@
-import uuid
-
-from sqlalchemy import TIMESTAMP, Column, Integer, String, Text, func
-from sqlalchemy.orm import declarative_base
-
-Base = declarative_base()
-metadata = Base.metadata
-
-
-class DataSource(Base):
-    __tablename__ = "ec_data_sources"
-
-    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
-    app_id = Column(Text, index=True)
-    hash = Column(Text, index=True)
-    type = Column(Text, index=True)
-    value = Column(Text)
-    meta_data = Column(Text, name="metadata")
-    is_uploaded = Column(Integer, default=0)
-
-
-class ChatHistory(Base):
-    __tablename__ = "ec_chat_history"
-
-    app_id = Column(String, primary_key=True)
-    id = Column(String, primary_key=True)
-    session_id = Column(String, primary_key=True, index=True)
-    question = Column(Text)
-    answer = Column(Text)
-    meta_data = Column(Text, name="metadata")
-    created_at = Column(TIMESTAMP, default=func.current_timestamp(), index=True)

embedchain/docs/README.md

@@ -0,0 +1,25 @@
+# Contributing to embedchain docs
+
+
+### 👩‍💻 Development
+
+Install the [Mintlify CLI](https://www.npmjs.com/package/mintlify) to preview the documentation changes locally. To install, use the following command
+
+```
+npm i -g mintlify
+```
+
+Run the following command at the root of your documentation (where mint.json is)
+
+```
+mintlify dev
+```
+
+### 😎 Publishing Changes
+
+Changes will be deployed to production automatically after your PR is merged to the main branch.
+
+#### Troubleshooting
+
+- Mintlify dev isn't running - Run `mintlify install` it'll re-install dependencies.
+- Page loads as a 404 - Make sure you are running in a folder with `mint.json`