klas/t6_mem0
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Update notebooks to work with the latest version (#870)

Browse Source
This commit is contained in:
Sidharth Mohanty
2023-10-30 11:36:43 +05:30
committed by GitHub
parent d3726134b2
commit 3b4409cfad
15 changed files with 374 additions and 256 deletions
Download Patch File Download Diff File Expand all files Collapse all files

11
notebooks/anthropic.ipynb
View File

@@ -34,6 +34,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -54,7 +63,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\"\n",
"os.environ[\"ANTHROPIC_API_KEY\"] = \"xxx\""

12
notebooks/azure-openai.ipynb
View File

@@ -26,6 +26,16 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "692ff37b",
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"id": "ac982a56",
@@ -44,7 +54,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_TYPE\"] = \"azure\"\n",
"os.environ[\"OPENAI_API_BASE\"] = \"https://xxx.openai.azure.com/\"\n",

165
notebooks/chromadb.ipynb
View File

@@ -1,84 +1,84 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"## Cookbook for using ChromaDB with Embedchain"
],
"metadata": {
"id": "b02n_zJ_hl3d"
}
},
"source": [
"## Cookbook for using ChromaDB with Embedchain"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-1: Install embedchain package"
],
"metadata": {
"id": "gyJ6ui2vhtMY"
}
},
"source": [
"### Step-1: Install embedchain package"
]
},
{
"cell_type": "code",
"source": [
"!pip install embedchain"
],
"execution_count": null,
"metadata": {
"id": "-NbXjAdlh0vJ"
},
"outputs": [],
"source": [
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"outputs": []
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nGnpSYAAh2bQ"
},
"source": [
"### Step-2: Set OpenAI environment variables\n",
"\n",
"You can find this env variable on your [OpenAI dashboard](https://platform.openai.com/account/api-keys)."
],
"metadata": {
"id": "nGnpSYAAh2bQ"
}
]
},
{
"cell_type": "code",
"source": [
"import os\n",
"from embedchain import App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
],
"execution_count": null,
"metadata": {
"id": "0fBdQ9GAiRvK"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"import os\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
]
},
{
"cell_type": "markdown",
"source": [
"### Step-3: Define your Vector Database config"
],
"metadata": {
"id": "Ns6RhPfbiitr"
}
},
"source": [
"### Step-3: Define your Vector Database config"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "S9CkxVjriotB"
},
"outputs": [],
"source": [
"config = \"\"\"\n",
"vectordb:\n",
@@ -95,64 +95,64 @@
"# Write the multi-line string to a YAML file\n",
"with open('chromadb.yaml', 'w') as file:\n",
" file.write(config)"
],
"metadata": {
"id": "S9CkxVjriotB"
},
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
"source": [
"### Step-4 Create embedchain app based on the config"
],
"metadata": {
"id": "PGt6uPLIi1CS"
}
},
"source": [
"### Step-4 Create embedchain app based on the config"
]
},
{
"cell_type": "code",
"source": [
"app = App.from_config(yaml_path=\"chromadb.yaml\")"
],
"execution_count": null,
"metadata": {
"id": "Amzxk3m-i3tD"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"app = App.from_config(yaml_path=\"chromadb.yaml\")"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-5: Add data sources to your app"
],
"metadata": {
"id": "XNXv4yZwi7ef"
}
},
"source": [
"### Step-5: Add data sources to your app"
]
},
{
"cell_type": "code",
"source": [
"app.add(\"https://www.forbes.com/profile/elon-musk\")"
],
"execution_count": null,
"metadata": {
"id": "Sn_0rx9QjIY9"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"app.add(\"https://www.forbes.com/profile/elon-musk\")"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-6: All set. Now start asking questions related to your data"
],
"metadata": {
"id": "_7W6fDeAjMAP"
}
},
"source": [
"### Step-6: All set. Now start asking questions related to your data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cvIK7dWRjN_f"
},
"outputs": [],
"source": [
"while(True):\n",
" question = input(\"Enter question: \")\n",
@@ -160,12 +160,21 @@
" break\n",
" answer = app.query(question)\n",
" print(answer)"
],
"metadata": {
"id": "cvIK7dWRjN_f"
},
"execution_count": null,
"outputs": []
]
}
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}

11
notebooks/cohere.ipynb
View File

@@ -33,6 +33,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -69,7 +78,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\"\n",
"os.environ[\"COHERE_API_KEY\"] = \"xxx\""

175
notebooks/elasticsearch.ipynb
View File

@@ -1,95 +1,95 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"## Cookbook for using ElasticSearchDB with Embedchain"
],
"metadata": {
"id": "b02n_zJ_hl3d"
}
},
"source": [
"## Cookbook for using ElasticSearchDB with Embedchain"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-1: Install embedchain package"
],
"metadata": {
"id": "gyJ6ui2vhtMY"
}
},
"source": [
"### Step-1: Install embedchain package"
]
},
{
"cell_type": "code",
"source": [
"!pip install embedchain"
],
"execution_count": null,
"metadata": {
"id": "-NbXjAdlh0vJ"
},
"outputs": [],
"source": [
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"outputs": []
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nGnpSYAAh2bQ"
},
"source": [
"### Step-2: Set OpenAI environment variables and install the dependencies.\n",
"\n",
"You can find this env variable on your [OpenAI dashboard](https://platform.openai.com/account/api-keys). Now lets install the dependencies needed for Elasticsearch."
],
"metadata": {
"id": "nGnpSYAAh2bQ"
}
]
},
{
"cell_type": "code",
"source": [
"!pip install --upgrade 'embedchain[elasticsearch]'"
],
"execution_count": null,
"metadata": {
"id": "-MUFRfxV7Jk7"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"!pip install --upgrade 'embedchain[elasticsearch]'"
]
},
{
"cell_type": "code",
"source": [
"import os\n",
"from embedchain import App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
],
"execution_count": null,
"metadata": {
"id": "0fBdQ9GAiRvK"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"import os\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
]
},
{
"cell_type": "markdown",
"source": [
"### Step-3: Define your Vector Database config"
],
"metadata": {
"id": "Ns6RhPfbiitr"
}
},
"source": [
"### Step-3: Define your Vector Database config"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "S9CkxVjriotB"
},
"outputs": [],
"source": [
"config = \"\"\"\n",
"vectordb:\n",
@@ -104,64 +104,64 @@
"# Write the multi-line string to a YAML file\n",
"with open('elasticsearch.yaml', 'w') as file:\n",
" file.write(config)"
],
"metadata": {
"id": "S9CkxVjriotB"
},
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
"source": [
"### Step-4 Create embedchain app based on the config"
],
"metadata": {
"id": "PGt6uPLIi1CS"
}
},
"source": [
"### Step-4 Create embedchain app based on the config"
]
},
{
"cell_type": "code",
"source": [
"app = App.from_config(yaml_path=\"elasticsearch.yaml\")"
],
"execution_count": null,
"metadata": {
"id": "Amzxk3m-i3tD"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"app = App.from_config(yaml_path=\"elasticsearch.yaml\")"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-5: Add data sources to your app"
],
"metadata": {
"id": "XNXv4yZwi7ef"
}
},
"source": [
"### Step-5: Add data sources to your app"
]
},
{
"cell_type": "code",
"source": [
"app.add(\"https://www.forbes.com/profile/elon-musk\")"
],
"execution_count": null,
"metadata": {
"id": "Sn_0rx9QjIY9"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"app.add(\"https://www.forbes.com/profile/elon-musk\")"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-6: All set. Now start asking questions related to your data"
],
"metadata": {
"id": "_7W6fDeAjMAP"
}
},
"source": [
"### Step-6: All set. Now start asking questions related to your data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cvIK7dWRjN_f"
},
"outputs": [],
"source": [
"while(True):\n",
" question = input(\"Enter question: \")\n",
@@ -169,12 +169,21 @@
" break\n",
" answer = app.query(question)\n",
" print(answer)"
],
"metadata": {
"id": "cvIK7dWRjN_f"
},
"execution_count": null,
"outputs": []
]
}
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}

2
notebooks/embedchain-chromadb-server.ipynb
View File

@@ -33,7 +33,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"from embedchain.config import AppConfig\n",
"\n",
"\n",

2
notebooks/embedchain-docs-site-example.ipynb
View File

@@ -7,7 +7,7 @@
"metadata": {},
"outputs": [],
"source": [
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"embedchain_docs_bot = App()"
]

11
notebooks/gpt4all.ipynb
View File

@@ -33,6 +33,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -67,7 +76,7 @@
},
"outputs": [],
"source": [
"from embedchain import App"
"from embedchain import Pipeline as App"
]
},
{

11
notebooks/hugging_face_hub.ipynb
View File

@@ -34,6 +34,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -84,7 +93,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"HUGGINGFACE_ACCESS_TOKEN\"] = \"hf_xxx\""
]

11
notebooks/jina.ipynb
View File

@@ -34,6 +34,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -54,7 +63,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\"\n",
"os.environ[\"JINACHAT_API_KEY\"] = \"xxx\""

11
notebooks/llama2.ipynb
View File

@@ -33,6 +33,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -64,7 +73,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\"\n",
"os.environ[\"REPLICATE_API_TOKEN\"] = \"xxx\""

11
notebooks/openai.ipynb
View File

@@ -34,6 +34,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -54,7 +63,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
]

175
notebooks/opensearch.ipynb
View File

@@ -1,95 +1,95 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"## Cookbook for using OpenSearchDB with Embedchain"
],
"metadata": {
"id": "b02n_zJ_hl3d"
}
},
"source": [
"## Cookbook for using OpenSearchDB with Embedchain"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-1: Install embedchain package"
],
"metadata": {
"id": "gyJ6ui2vhtMY"
}
},
"source": [
"### Step-1: Install embedchain package"
]
},
{
"cell_type": "code",
"source": [
"!pip install embedchain"
],
"execution_count": null,
"metadata": {
"id": "-NbXjAdlh0vJ"
},
"outputs": [],
"source": [
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"outputs": []
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nGnpSYAAh2bQ"
},
"source": [
"### Step-2: Set OpenAI environment variables and install the dependencies.\n",
"\n",
"You can find this env variable on your [OpenAI dashboard](https://platform.openai.com/account/api-keys). Now lets install the dependencies needed for Opensearch."
],
"metadata": {
"id": "nGnpSYAAh2bQ"
}
]
},
{
"cell_type": "code",
"source": [
"!pip install --upgrade 'embedchain[opensearch]'"
],
"execution_count": null,
"metadata": {
"id": "-MUFRfxV7Jk7"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"!pip install --upgrade 'embedchain[opensearch]'"
]
},
{
"cell_type": "code",
"source": [
"import os\n",
"from embedchain import App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
],
"execution_count": null,
"metadata": {
"id": "0fBdQ9GAiRvK"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"import os\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
]
},
{
"cell_type": "markdown",
"source": [
"### Step-3: Define your Vector Database config"
],
"metadata": {
"id": "Ns6RhPfbiitr"
}
},
"source": [
"### Step-3: Define your Vector Database config"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "S9CkxVjriotB"
},
"outputs": [],
"source": [
"config = \"\"\"\n",
"vectordb:\n",
@@ -108,64 +108,64 @@
"# Write the multi-line string to a YAML file\n",
"with open('opensearch.yaml', 'w') as file:\n",
" file.write(config)"
],
"metadata": {
"id": "S9CkxVjriotB"
},
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
"source": [
"### Step-4 Create embedchain app based on the config"
],
"metadata": {
"id": "PGt6uPLIi1CS"
}
},
"source": [
"### Step-4 Create embedchain app based on the config"
]
},
{
"cell_type": "code",
"source": [
"app = App.from_config(yaml_path=\"opensearch.yaml\")"
],
"execution_count": null,
"metadata": {
"id": "Amzxk3m-i3tD"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"app = App.from_config(yaml_path=\"opensearch.yaml\")"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-5: Add data sources to your app"
],
"metadata": {
"id": "XNXv4yZwi7ef"
}
},
"source": [
"### Step-5: Add data sources to your app"
]
},
{
"cell_type": "code",
"source": [
"app.add(\"https://www.forbes.com/profile/elon-musk\")"
],
"execution_count": null,
"metadata": {
"id": "Sn_0rx9QjIY9"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"app.add(\"https://www.forbes.com/profile/elon-musk\")"
]
},
{
"cell_type": "markdown",
"source": [
"### Step-6: All set. Now start asking questions related to your data"
],
"metadata": {
"id": "_7W6fDeAjMAP"
}
},
"source": [
"### Step-6: All set. Now start asking questions related to your data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cvIK7dWRjN_f"
},
"outputs": [],
"source": [
"while(True):\n",
" question = input(\"Enter question: \")\n",
@@ -173,12 +173,21 @@
" break\n",
" answer = app.query(question)\n",
" print(answer)"
],
"metadata": {
"id": "cvIK7dWRjN_f"
},
"execution_count": null,
"outputs": []
]
}
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}

11
notebooks/pinecone.ipynb
View File

@@ -29,6 +29,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -60,7 +69,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\"\n",
"os.environ[\"PINECONE_API_KEY\"] = \"xxx\"\n",

11
notebooks/vertex_ai.ipynb
View File

@@ -33,6 +33,15 @@
"!pip install embedchain"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install embedchain[dataloaders]"
]
},
{
"cell_type": "markdown",
"metadata": {
@@ -64,7 +73,7 @@
"outputs": [],
"source": [
"import os\n",
"from embedchain import App\n",
"from embedchain import Pipeline as App\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-xxx\""
]