Made changes to Getting started with ALwrity and added lot of details on API keys
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@@ -1,33 +1,121 @@
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import os
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import anthropic
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from anthropic import Anthropic
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import streamlit as st
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import asyncio
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from tenacity import (
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retry,
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stop_after_attempt,
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wait_random_exponential,
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) # for exponential backoff
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# Configure standard logging
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import logging
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logging.basicConfig(level=logging.INFO, format='[%(asctime)s-%(levelname)s-%(module)s-%(lineno)d]- %(message)s')
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logger = logging.getLogger(__name__)
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def anthropic_text_response(prompt):
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""" """
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client = Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"),)
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async def test_anthropic_api_key(api_key: str) -> tuple[bool, str]:
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"""
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Test if the provided Anthropic API key is valid.
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Args:
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api_key (str): The Anthropic API key to test
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Returns:
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tuple[bool, str]: A tuple containing (is_valid, message)
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"""
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try:
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# Create Anthropic client with the provided key
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client = anthropic.Anthropic(api_key=api_key)
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# Try a simple completion as a test
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response = client.messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": prompt,
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}
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],
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# This will come from config file.
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model="claude-3-opus-20240229",
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model="claude-3-haiku-20240307",
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max_tokens=10,
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messages=[{
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"role": "user",
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"content": "Say hello"
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}]
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)
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return(message.content)
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except anthropic.APIConnectionError as e:
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st.error("The server could not be reached")
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st.error(e.__cause__) # an underlying Exception, likely raised within httpx.
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except anthropic.RateLimitError as e:
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st.error("A 429 status code was received; we should back off a bit.")
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except anthropic.APIStatusError as e:
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st.error("Another non-200-range status code was received")
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st.error(e.status_code)
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st.error(e.response)
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# If we get here, the key is valid
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return True, "Anthropic API key is valid"
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except anthropic.AuthenticationError:
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return False, "Invalid Anthropic API key"
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except anthropic.RateLimitError:
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return False, "Rate limit exceeded. Please try again later."
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except Exception as e:
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return False, f"Error testing Anthropic API key: {str(e)}"
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@retry(wait=wait_random_exponential(min=1, max=60), stop=stop_after_attempt(6))
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def anthropic_text_response(prompt, model="claude-3-haiku-20240307", temperature=0.7, max_tokens=2048, top_p=0.9, n=1, system_prompt="You are a helpful AI assistant."):
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"""
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Generate text using Anthropic's Claude model with retry logic.
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Args:
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prompt (str): The input text to generate completion for
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model (str, optional): Model to use. Defaults to "claude-3-haiku-20240307"
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temperature (float, optional): Controls randomness. Defaults to 0.7
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max_tokens (int, optional): Maximum number of tokens to generate. Defaults to 2048
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top_p (float, optional): Controls diversity. Defaults to 0.9
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n (int, optional): Number of completions to generate. Defaults to 1
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system_prompt (str, optional): System prompt to guide the model. Defaults to "You are a helpful AI assistant."
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Returns:
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str: The generated text completion
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"""
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try:
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# Create Anthropic client
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client = anthropic.Anthropic(api_key=os.getenv('ANTHROPIC_API_KEY'))
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# Generate completion
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response = client.messages.create(
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model=model,
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max_tokens=max_tokens,
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temperature=temperature,
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messages=[
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": prompt}
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]
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)
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# Return the generated text
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return response.content[0].text
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except Exception as e:
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logger.error(f"Error in Anthropic text generation: {e}")
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raise SystemExit from e
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def anthropic_text_gen(prompt, model="claude-3-haiku-20240307", temperature=0.7, max_tokens=2048):
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"""
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Generate text using Anthropic's Claude model.
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Args:
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prompt (str): The input text to generate completion for
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model (str, optional): Model to use. Defaults to "claude-3-haiku-20240307"
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temperature (float, optional): Controls randomness. Defaults to 0.7
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max_tokens (int, optional): Maximum number of tokens to generate. Defaults to 2048
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Returns:
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str: The generated text completion
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"""
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try:
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# Create Anthropic client
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client = anthropic.Anthropic(api_key=os.getenv('ANTHROPIC_API_KEY'))
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# Generate completion
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response = client.messages.create(
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model=model,
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max_tokens=max_tokens,
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temperature=temperature,
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messages=[{
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"role": "user",
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"content": prompt
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}]
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)
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# Return the generated text
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return response.content[0].text
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except Exception as e:
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logger.error(f"Error in Anthropic text generation: {e}")
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return str(e)
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