> ## Documentation Index
> Fetch the complete documentation index at: https://docs.graphext.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Enrich

| Step | Fast | Description |
| - | - | - |
| [caption\_images](https://docs.graphext.com/api-docs/prepare/enrich/caption_images) | | Predict image captions using pretrained DL models |
| [classify\_text](https://docs.graphext.com/api-docs/prepare/enrich/classify_text) | | Classify texts using any model from the [Hugging Face hub](https://huggingface.co/models) |
| [clean\_categories](https://docs.graphext.com/api-docs/prepare/enrich/clean_categories) | | Clean a given column of categories or lists of categories using OpenAI |
| [describe\_clusters](https://docs.graphext.com/api-docs/prepare/enrich/describe_clusters) | | Describe your clusters from their given relevant TF-IDF terms using OpenAI |
| [explore\_database](https://docs.graphext.com/api-docs/prepare/enrich/explore_database) | | Explore database structure — generates a dataset of column metadata with statistics, relationships, and semantic descr… |
| [fetch\_apify\_dataset](https://docs.graphext.com/api-docs/prepare/enrich/fetch_apify_dataset) | | Fetch data from an existing Apify dataset |
| [fetch\_demographics\_es](https://docs.graphext.com/api-docs/prepare/enrich/fetch_demographics_es) | | Fetch Spanish demographic census data given a geographical location in each row |
| [fetch\_from\_sql](https://docs.graphext.com/api-docs/prepare/enrich/fetch_from_sql) | | Fetch data from a SQL database query and return it as a dataset |
| [fetch\_full\_contact\_domains](https://docs.graphext.com/api-docs/prepare/enrich/fetch_full_contact_domains) | | Enrich a dataset containing links (URLs) to companies' online presence using the FullContact service |
| [fetch\_full\_contact\_emails](https://docs.graphext.com/api-docs/prepare/enrich/fetch_full_contact_emails) | | Enrich a dataset containing email addresses with personal information using the *FullContact* service |
| [fetch\_google\_places](https://docs.graphext.com/api-docs/prepare/enrich/fetch_google_places) | | Fetch information about the most relevant places surrounding a location |
| [fetch\_google\_vision](https://docs.graphext.com/api-docs/prepare/enrich/fetch_google_vision) | | Analyze images given their URL using the Google Vision API |
| [fetch\_location](https://docs.graphext.com/api-docs/prepare/enrich/fetch_location) | | Extract formatted address, locality, area, state, country and geographical coordinates from one or more address columns |
| [fetch\_openreview](https://docs.graphext.com/api-docs/prepare/enrich/fetch_openreview) | | Fetch publications submitted to one or more conferences via [OpenReview](https://openreview.net/) |
| [fetch\_social\_shares](https://docs.graphext.com/api-docs/prepare/enrich/fetch_social_shares) | | Fetch the number of times a Url was shared on Facebook |
| [fetch\_twitter](https://docs.graphext.com/api-docs/prepare/enrich/fetch_twitter) | | Enriches a dataset containing tweets with information about their authors |
| [fetch\_twitter\_api\_io](https://docs.graphext.com/api-docs/prepare/enrich/fetch_twitter_api_io) | | Fetch tweets from Twitter/X using TwitterAPI.io advanced search |
| [fetch\_url\_content](https://docs.graphext.com/api-docs/prepare/enrich/fetch_url_content) | | Fetch the main text from a web URL, and return its title, author, content, excerpt and domain |
| [infer\_aspect\_polarity](https://docs.graphext.com/api-docs/prepare/enrich/infer_aspect_polarity) | | Extract aspect-based polarity from texts using OpenAI. Identifies entities mentioned in textsand separates them into p… |
| [infer\_aspect\_sentiment](https://docs.graphext.com/api-docs/prepare/enrich/infer_aspect_sentiment) | | Extract aspect-based sentiments from texts using OpenAI. Identifies entities mentioned in textswith clear positive or … |
| [infer\_gender](https://docs.graphext.com/api-docs/prepare/enrich/infer_gender) | | Try to infer a person's gender given a first name |
| [infer\_language](https://docs.graphext.com/api-docs/prepare/enrich/infer_language) | | Detect the language used for each text in the input column |
| [infer\_missing](https://docs.graphext.com/api-docs/prepare/enrich/infer_missing) | | Train and use a machine learning model to predict (impute) the missing values in a column |
| [infer\_missing\_with\_probs](https://docs.graphext.com/api-docs/prepare/enrich/infer_missing_with_probs) | | Train and use a machine learning model to predict (impute) the missing values in a column |
| [infer\_sentiment](https://docs.graphext.com/api-docs/prepare/enrich/infer_sentiment) | | Parse text and calculate the overall positive or negative sentiment polarity |
| [infer\_topics](https://docs.graphext.com/api-docs/prepare/enrich/infer_topics) | | Generate topics and subtopics for given texts using OpenAI. Infers a hierarchical topic structurefrom (a sample of) th… |
| [prompt\_ai](https://docs.graphext.com/api-docs/prepare/enrich/prompt_ai) | | Call OpenAI's models on each row of the dataset for a given prompt |
| [run\_apify\_actor](https://docs.graphext.com/api-docs/prepare/enrich/run_apify_actor) | | Run an Apify actor and fetch the resulting dataset |
| [zeroshot\_classify\_text](https://docs.graphext.com/api-docs/prepare/enrich/zeroshot_classify_text) | | Classify texts using custom labels/categories |


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