llama-index-llms-perplexity 0.3.1

llama-index llms perplexity integration

LlamaIndex Llms Integration: Perplexity

Installation

To install the required packages, run:

%pip install llama-index-llms-perplexity
!pip install llama-index

Setup

Import Libraries and Configure API Key

Import the necessary libraries and set your Perplexity API key:

from llama_index.llms.perplexity import Perplexity

pplx_api_key = "your-perplexity-api-key"  # Replace with your actual API key

Initialize the Perplexity LLM

Create an instance of the Perplexity LLM with your API key and desired model settings:

llm = Perplexity(
    api_key=pplx_api_key, model="mistral-7b-instruct", temperature=0.5
)

Chat Example

Sending a Chat Message

You can send a chat message using the chat method. Here’s how to do that:

from llama_index.core.llms import ChatMessage

messages_dict = [
    {"role": "system", "content": "Be precise and concise."},
    {"role": "user", "content": "Tell me 5 sentences about Perplexity."},
]

messages = [ChatMessage(**msg) for msg in messages_dict]

# Get response from the model
response = llm.chat(messages)
print(response)

Async Chat

To send messages asynchronously, you can use the achat method:

response = await llm.achat(messages)
print(response)

Stream Chat

For streaming responses, you can use the stream_chat method:

resp = llm.stream_chat(messages)
for r in resp:
    print(r.delta, end="")

Async Stream Chat

To stream responses asynchronously, use the astream_chat method:

resp = await llm.astream_chat(messages)
async for delta in resp:
    print(delta.delta, end="")

LLM Implementation example

https://docs.llamaindex.ai/en/stable/examples/llm/perplexity/