# Learn how to use the Clarifai Python SDK

Here are comprehensive step-by-step walkthroughs within Jupyter or Colab notebooks that showcase how to harness the power of the Clarifai SDKs.

| Notebook | Description | Open in Colab |
| --- | --- | --- |
| [Basics](https://github.com/Clarifai/examples/blob/main/basics/basics.ipynb) | Create, manage, update, and delete Clarifai resources, including apps, datasets, inputs, and models |  |
| [CLI](https://github.com/Clarifai/examples/blob/main/CLI/compute_orchestration.ipynb) | Clarifai provides a user-friendly command line interface (CLI) that simplifies various tasks |  |
| [Compute Orchestration](https://github.com/Clarifai/examples/blob/main/ComputeOrchestration/crud_operations.ipynb) | Use our Compute Orchestration system to create, get, list, and delete compute clusters, nodepools, and model deployments. |  |
| [Data Utils](https://github.com/Clarifai/examples/tree/main/Data_Utils) | Get a range of multimedia data utilities designed to streamline your data management and processing operations. <br>- [Image annotation loader](https://github.com/Clarifai/examples/blob/main/Data_Utils/Image%20Annotation/image_annotation_loader.ipynb) — A comprehensive framework for loading, exporting, and analyzing different annotated datasets. <br>- [Data ingestion pipelines](https://github.com/Clarifai/examples/blob/main/Data_Utils/Ingestion%20pipelines/README.md) — Load text files (PDF, DOC, etc.), transform and chunk the content, and upload it to the Clarifai platform. <br>  - [Multimodal dataloader](https://github.com/Clarifai/examples/blob/main/Data_Utils/Ingestion%20pipelines/Multimodal_dataloader.ipynb)<br>  - [Ready-to-use foundational pipelines](https://github.com/Clarifai/examples/blob/main/Data_Utils/Ingestion%20pipelines/Ready_to_use_foundational_pipelines.ipynb) |  |
| [RAG](https://github.com/Clarifai/examples/blob/main/RAG/RAG.ipynb) | Use Retrieval Augmented Generation (RAG) to improve Large Language Models (LLMs) |  |
| [Concept management](https://github.com/Clarifai/examples/blob/main/concepts/concept_management.ipynb) | Establish a hierarchical relationship between concepts using concept relations |  |
| [Datasets basics](https://github.com/Clarifai/examples/blob/main/datasets/basics.ipynb) | Merge datasets and list inputs of a dataset |  |
| [Dataset export](https://github.com/Clarifai/examples/blob/main/datasets/export/dataset_export.ipynb) | Export datasets from a Clarifai app |  |
| [Dataset upload](https://github.com/Clarifai/examples/blob/main/datasets/upload/dataset_upload.ipynb) | Upload datasets into a Clarifai app |  |
| [Inputs upload](https://github.com/Clarifai/examples/blob/main/datasets/upload/input_upload.ipynb) | Upload inputs with various types of data, such as metadata, geo info, or bounding box annotations, into a Clarifai app |  |
| [Models predict (inference)](https://github.com/Clarifai/examples/tree/main/models/model_predict) | Get predictions with text, image, video, and audio inputs with different types of models |  |
| [Evaluation for embedding classification](https://github.com/Clarifai/examples/blob/main/models/model_eval/embedding_classifier_eval.ipynb) | Evaluate the performance of embedding classifier models |  |
| [Evaluation for text classification](https://github.com/Clarifai/examples/blob/main/models/model_eval/text_classification_eval.ipynb) | Evaluate the performance of text classifier models |  |
| [Evaluation for visual classification](https://github.com/Clarifai/examples/blob/main/models/model_eval/visual_classifier_eval.ipynb) | Evaluate the performance of visual classifier models |  |
| [Evaluation for visual detection](https://github.com/Clarifai/examples/blob/main/models/model_eval/visual_detector_eval.ipynb) | Evaluate the performance of visual detector models |  |
| [Training for image classification](https://github.com/Clarifai/examples/blob/main/models/model_train/image-classification_training.ipynb) | Train image classifier models |  |
| [Training for image detection](https://github.com/Clarifai/examples/blob/main/models/model_train/image-detection_training.ipynb) | Train image detector models |  |
| [Training for image segmentation](https://github.com/Clarifai/examples/blob/main/models/model_train/image-segmentation_training.ipynb) | Train image segmentation models |  |
| [Training for text classification](https://github.com/Clarifai/examples/blob/main/models/model_train/text-classification_training.ipynb) | Train text classifier models |  |
| [Training for transfer learn](https://github.com/Clarifai/examples/blob/main/models/model_train/transfer_learn.ipynb) | Train transfer learn models |  |
| [Model upload](https://github.com/Clarifai/examples/tree/main/models/model_upload) | - [Upload image classifiers](https://github.com/Clarifai/examples/tree/main/models/model_upload/image-classifier/nsfw-image-classifier)<br>- [Upload image detectors](https://github.com/Clarifai/examples/tree/main/models/model_upload/image-detector/detr-resnet-image-detection)<br>- [Upload LLMs](https://github.com/Clarifai/examples/tree/main/models/model_upload/llms)<br>- [Upload speech recognition models](https://github.com/Clarifai/examples/tree/main/models/model_upload/speech-recognition/openai-whisper) |  |
| [Cross-modal search](https://github.com/Clarifai/examples/blob/main/search/cross_modal_search.ipynb) | Perform vector search over your own data |  |
| [Create workflows](https://github.com/Clarifai/examples/blob/main/workflows/create_workflow.ipynb) | Create various types of workflows |  |
| [Export workflows](https://github.com/Clarifai/examples/blob/main/workflows/export_workflow.ipynb) | Download a YAML file representing your workflow |  |
| [Patch workflows](https://github.com/Clarifai/examples/blob/main/workflows/patch_workflow.ipynb) | Perform patch operations by merging, removing, or overwriting data |  |

## Integration Examples

| Notebook | Description | Open in Colab |
| --- | --- | --- |
| [LangChain](https://github.com/Clarifai/examples/tree/main/Integrations/Langchain) |  |  |
|  | [Agent: Doc-retrieval using ReAct Docstore](https://github.com/Clarifai/examples/blob/main/Integrations/Langchain/Agents/Doc-retrieve_using_Langchain-ReAct_Agent.ipynb) |  |
|  | [Agent: Retrieval QA using Clarifai vector store with conversation memory](https://github.com/Clarifai/examples/blob/main/Integrations/Langchain/Agents/Retrieval_QA_with_Conversation_memory.ipynb) |  |
|  | [Chains: Using PostgreSQL database with LangChain](https://github.com/Clarifai/examples/blob/main/Integrations/Langchain/Chains/PostgreSQL_LLM.ipynb) |  |
|  | [Chains: Prompt templates and chains](https://github.com/Clarifai/examples/blob/main/Integrations/Langchain/Chains/Prompt-templates_and_chains.ipynb) |  |
|  | [Chains: Retrieval QA Chain with Clarifai vector store](https://github.com/Clarifai/examples/blob/main/Integrations/Langchain/Chains/Retrieval_QA_chain_with_Clarifai_Vectorstore.ipynb) |  |
|  | [Chains: Router Chain with Clarifai SDK prompt templates](https://github.com/Clarifai/examples/blob/main/Integrations/Langchain/Chains/Router_chain_examples_with_Clarifai_SDK.ipynb) |  |
|  |  |  |
| [Unstructured.io](https://github.com/Clarifai/examples/blob/main/Integrations/Unstructured/readme.md) |  |  |
|  | [S3 data ingestion](https://github.com/Clarifai/examples/blob/main/Integrations/Unstructured/Clarifai_Unstructured_integration_demo.ipynb) |  |
|  | [GitHub data ingestion](https://github.com/Clarifai/examples/blob/main/Integrations/Unstructured/Clarifai_github_using_unstructured_io_integration_example.ipynb) |  |
|  | [DropBox data ingestion](https://github.com/Clarifai/examples/blob/main/Integrations/Unstructured/Dropbox_Clarifai_Unstructured_integration_example.ipynb) |  |