# 🌐 NeuraNET Python API library
The Official NeuraNET Python Library
---
## 🛠 Installation
To get started with the library, simply run the following command:
```bash
pip install neuranet
```
## 💬 Chat Usage
Using the Chat AIs library is straightforward. Below is an example of a conversation:
```python
import neuranet
api_key = "YOUR_API_KEY_HERE"
mode = 'chat'
client = neuranet.client(api_key, mode)
# Set up the conversation history and model
conversation_history = [
{"sender": "instruct", "content": "You are a helpful assistant."},
{"sender": "user", "content": "Hello."},
{"sender": "assistant", "content": "Hello, how can I assist you?"},
{"sender": "user", "content": "How are you?"}
]
model = "nlite" # options: nlite, npro, npro-vision
# Get the response
try:
response = client.generate(conversation_history, model)
print(response)
except Exception as e:
print(f"An error occurred: {e}")
```
## 🎨 Image Usage
Using the Image generation AIs library is straightforward. Below is an example of a conversation:
```python
import neuranet
api_key = "YOUR_API_KEY_HERE"
mode = 'image'
client = neuranet.client(api_key, mode)
model = "vinci-mini" # options: vinci-mini, vinci-max
prompt = "A large oak tree"
response = client.generate(prompt, model)
print(response)
```
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"description": "\r\n# \ud83c\udf10 NeuraNET Python API library\r\n\r\n\r\n\r\nThe Official NeuraNET Python Library\r\n\r\n\r\n\r\n---\r\n\r\n\r\n\r\n## \ud83d\udee0 Installation\r\n\r\n\r\n\r\nTo get started with the library, simply run the following command:\r\n\r\n\r\n\r\n```bash\r\n\r\npip install neuranet\r\n\r\n```\r\n\r\n\r\n\r\n## \ud83d\udcac Chat Usage\r\n\r\nUsing the Chat AIs library is straightforward. Below is an example of a conversation:\r\n\r\n```python\r\n\r\nimport neuranet\r\n\r\n\r\n\r\napi_key = \"YOUR_API_KEY_HERE\"\r\n\r\nmode = 'chat'\r\n\r\nclient = neuranet.client(api_key, mode)\r\n\r\n\r\n\r\n# Set up the conversation history and model\r\n\r\nconversation_history = [\r\n\r\n {\"sender\": \"instruct\", \"content\": \"You are a helpful assistant.\"},\r\n\r\n {\"sender\": \"user\", \"content\": \"Hello.\"},\r\n\r\n {\"sender\": \"assistant\", \"content\": \"Hello, how can I assist you?\"},\r\n\r\n {\"sender\": \"user\", \"content\": \"How are you?\"}\r\n\r\n]\r\n\r\n\r\n\r\nmodel = \"nlite\" # options: nlite, npro, npro-vision\r\n\r\n\r\n\r\n# Get the response\r\n\r\ntry:\r\n\r\n response = client.generate(conversation_history, model)\r\n\r\n print(response)\r\n\r\nexcept Exception as e:\r\n\r\n print(f\"An error occurred: {e}\")\r\n\r\n```\r\n\r\n\r\n\r\n## \ud83c\udfa8 Image Usage\r\n\r\nUsing the Image generation AIs library is straightforward. Below is an example of a conversation:\r\n\r\n```python\r\n\r\nimport neuranet\r\n\r\n\r\n\r\napi_key = \"YOUR_API_KEY_HERE\"\r\n\r\nmode = 'image'\r\n\r\nclient = neuranet.client(api_key, mode)\r\n\r\nmodel = \"vinci-mini\" # options: vinci-mini, vinci-max\r\n\r\n\r\n\r\nprompt = \"A large oak tree\"\r\n\r\n\r\n\r\nresponse = client.generate(prompt, model)\r\n\r\nprint(response)\r\n\r\n```\r\n\r\n",
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