Key results

• AI tools, such as chatgpt, can support both experienced and novel cryptographic investors to track portfolios easily, releasing time for other investment activities and increasing process access.

• Determining specific requirements, such as cryptocurrencies for tracking and desired data points, is necessary to build effective tracking of the portfolio adapted to investment purposes.

• By combining chatgpt with cryptographic data in real time from API interfaces, such as Coinmarketcap, you can generate valuable comments and market analysis, providing a deeper insight into the portfolio performance. Developing additional functions, such as price notifications, performance analysis and user -friendly interface can boost the tracker’s functioning, helping in overtaking market trends and manage your cryptic investments.

If you are a cryptocurrency investor, you clearly have a powerful risk appetite! The cryptocurrency portfolio includes many engaging stages, from stationary tests on the profitability of cryptocurrencies to energetic crypto -trade to monitoring regulations. Cryptocurrency portfolio management can be sophisticated and time consuming, even for experienced investors.

And vice versa, if you are a novice in the world of cryptocurrencies and you want to put yourself on success, you can be discouraged by the complexity of all this.

The good news is that artificial intelligence (AI) offers valuable tools for the cryptographic industry, helping to simplify the tracking and analysis of the wallet when it is effectively used.

As an experienced cryptographic investor, this can support release valuable time to focus on other activities in the investment cycle. If you are a novel investor, artificial intelligence can support you make this most vital first step. Read on to see how AI, specifically ChatgPT, can support build a tailored portfolio tracking.

To start with, what is it?

Let’s find out.

What is chatgpt?

ChatgPT is a conversational AI model that can provide various tasks using the user-defined prompts-in including data search, analysis and visualization.

GPT means “pre -trained transformer”, which refers to the fact that it is a gigantic language model, widely trained for profuse amounts of text from various sources on the Internet and designed to understand the context and ensure possible results for end users.

CHATGPT intelligence makes it a powerful resource to build a cryptographic portfolio tracking specially addressed to your investment profile and goals.

Let’s find out how to build a non -standard tracker portfolio from chatgpt.

Step 1: Define your requirements

Despite the technical details, it is first to define what you expect from tracking the cryptographic portfolio. Let’s consider, for example, the following questions:

• What cryptocurrencies will you follow?

• What is your investment approach? Do you want to actively divide commercial cryptocurrencies or do you want to “buy and hold” them in the long run?

• What data points do you need to compile to track? They may include, among others, the price, market capitalization, volume, and even summaries of network messages that could significantly change your investment decisions.

• What exactly do you need to deliver you? Real time updates? Periodic summaries? Maybe the combination of both?

• What do you want to look like? Alerts, performance analysis, historical data or something else?

After clearly understanding your requirements, you can go to the next steps. The best practice is to save requirements in a consolidated specification document so that you can improve them later.

Step 2: Configure ChatgPT instance

This is a witty piece! Well, it’s if you like geeking on the code. Remember that chatgpt is a gigantic language model with a huge amount of intelligence sitting under it.

Therefore, the effective apply of CHATGPT requires access to the base model, which can be done via the application interface or API interface.

A company that owns ChatGPT – OpenAI – provides access to the API to the tool that you can apply to build tracking. It’s easier than you might think. You can apply a basic three -stage process to configure your own CHATGPT instance:

1. Go to OPENENAI and register to get the API key.

2. Configure the environment for making API connections. Python is the perfect choice for this, but there are alternatives such as node.js.

3. Write a basic script for communication with chatgpt using the API key. Here is a questionable script, which can be useful to include OpenAI’s capabilities in Python. (It should be noted that this is only a representative example of explaining OpenAI integration and is not perceived as financial advice).

Step 3: Integrate the source of cryptocurrency data

After configuring the CHATGPT instance, it’s time to complete the second part of the puzzle, namely the source of cryptocurrency data. There are many places to look, and several API interfaces can support in the information required for this step.

Examples include Coingecko, Coinmarketcap and Cryptocompary. Perform research on these options and choose those that meet your requirements. After making the choice, choose one that meets your requirements and integrate it with the ChatgPT instance, which you turned as part of step 2.

For example, if you decide to apply the API Coinmarketcap interface, the following code will receive the latest Bitcoin price that you can trade as part of the cryptographic portfolio.

Step 4: Connect the ChatgPT and Crypto data

You have done a hard bit, and considering that you now have both the AI ​​(chatgpt) function and the source of cryptocurrency data (Coinmarketcap in this example), you are ready to build a cryptographic portfolio tracker. To do this, you can apply rapid engineering to apply ChatGPT intelligence to demand data and generate insights.

For example, if you want your tracker to return the cryptocurrency price summary at the desired time, summarized in the data frame for visualization, consider writing the following code:

==================================================================

“ Python

# Set the Openai AP

Client = openai (api_key = openai_api_key)

Messages = [

        {“role”: “system”, “content”: “You are an expert market analyst with expertise in cryptocurrency trends.”},

        {“role”: “user”, “content”: f”Given that the current price of {symbol} is ${price:.2f} as of {date}, provide a concise commentary on the market status, including a recommendation.”}

    ]

to try:

response = client.chat.completions.create (

Model = “GPT-4-Mini”,

News = news,

max_tokens = 100,

Temperature = 0.7

)

Comment = Response.choices[0].Message.Content

Comment Return

except for the exception as E:

print (f “error of obtaining a comment for {symbol}: {e}”)

Return “No comments available”.

Def build_crypto_dataframe (CMC_API_KEY: p., OpenAI_API_KEY: p. Symbols: List, convert: Str = “USD”) -> Pd.dataframe:

records = []

# Once capture the current datetime to get consistency in all queries.

Current_timestamp = Datetime.now (). Strtime (“%y-%m-%d%h:%m:%s”)

For the symbol in symbols:

Price = Get_Crypto_PRICE (CMC_API_KEY, SYMBOL, CONVERT)

If the price is none:

Comment = “No comments available due to the price of collecting errors”.

otherwise:

Comment = Get_OPENAI_COMMENTARY (OPENAI_API_KEY, SYMBOL, PRICE, CURENT_TIMESTAM)

Records.append ({{

“Symbol”: symbol,

“Price”: price,

“Data”: current_timestamp,

“Market comment”: Comment

})

df = pd.dataframe (records)

df

# Sample apply:

If __Name__ == ‘__Main__’:

# Replace the real keys of the API.

kmc_api_key = “your_api_key”

openai_api_key = ‘your_api_key’ ‘

# Enter the cryptocurrencies of interest.

Crypto_sembols = [“BTC”, “ETH”, “XRP”]

# Build a data frame containing price and commentary.

crypto_df = build_crypto_dataframe (cmc_api_key, openai_api_key, crypto_sembols)

# Print the resulting data frame.

Print (Crypto_DF)

“ `

==================================================================

The above piece of code requires three cryptocurrencies in your portfolio – Bitcoin (BTC), Ether (ETH) and XRP (XRP) and uses the API CHATGPT interface to get the current price on the market, as shown in the source of Coinmarketcap data. Organizes results in a table with market comments generated by AI, ensuring a uncomplicated way to monitor the portfolio and assess market conditions.

Step 5: Develop additional functions

You can now improve tracking by adding more functions or including attractive visualizations. For example, consider:

• Alerts: Configure E -Mail or SMS alerts for significant price changes.

• Performance analysis: Follow the portfolio performance in time and provide insight.

• Visualizations: Integrate historical data to visualize price trends. For an experienced investor, this can support identify another vital market change.

Step 6: Create a user interface

To make your Crypto Tracker -friendly portfolio, it is recommended to develop an internet or mobile interface. Again, Python Frameworks, such as Folask, Smreme or Django, can support in ahead of uncomplicated, but intuitive internet applications, with alternatives such as React Native or Flutter, helping in mobile applications. Regardless of the choice, simplicity is crucial.

Do you know? Flask offers slight flexibility, improved data visualization, and Django provides solid, secure balls. They are all useful for building tools for tracking prices and market trends!

Step 7: Test and implement

Make sure you test your tracking thoroughly to ensure accuracy and reliability. After testing, implement it on a server or cloud platform, such as AWS or Herok. Monitor the usefulness of tracking over time and improve functions as needed.

Integration of artificial intelligence with cryptocurrencies can support track your portfolio. It allows you to build a non -standard tracker with market viewing to manage cryptocurrency resources. Consider the risk: AI forecasts may be faulty, API data may delay, and excessive rely on decisions. Continue carefully.

Cheerful AI drive trade!

This article does not contain investment advice or recommendations. Each investment and commercial movement involves risk, and readers should conduct their own research when making decisions.