運行大型語言模型LLM的初學者指南

# First, install the Anthropic Python library
!pip install anthropic
import anthropic
import os
client = anthropic.Anthropic(
   api_key=os.environ.get("YOUR_API_KEY"),  # Store your API key as an environment variable
)

import anthropic
import os
from typing import Dict, List, Optional


class ClaudeDocumentQA:
   """
   An agent that uses Claude to answer questions based strictly on the content
   of a provided document.
   """


   def __init__(self, api_key: Optional(str) = None):
       """Initialize the Claude client with API key."""
       self.client = anthropic.Anthropic(
           api_key="YOUR_API_KEY",
       )
       # Updated to use the correct model string format
       self.model = "claude-3-7-sonnet-20250219"


   def process_question(self, document: str, question: str) -> str:
       """
       Process a user question based on document context.


       Args:
           document: The text document to use as context
           question: The user's question about the document


       Returns:
           Claude's response answering the question based on the document
       """
       # Create a system prompt that instructs Claude to only use the provided document
       system_prompt = """
       You are a helpful assistant that answers questions based ONLY on the information
       provided in the DOCUMENT below. If the answer cannot be found in the document,
       say "I cannot find information about this in the provided document."
       Do not use any prior knowledge outside of what's explicitly stated in the document.
       """


       # Construct the user message with document and question
       user_message = f"""
       DOCUMENT:
       {document}


       QUESTION:
       {question}


       Answer the question using only information from the DOCUMENT above. If the information
       isn't in the document, say so clearly.
       """


       try:
           # Send request to Claude
           response = self.client.messages.create(
               model=self.model,
               max_tokens=1000,
               temperature=0.0,  # Low temperature for factual responses
               system=system_prompt,
               messages=(
                   {"role": "user", "content": user_message}
               )
           )


           return response.content(0).text
       except Exception as e:
           # Better error handling with details
           return f"Error processing request: {str(e)}"


   def batch_process(self, document: str, questions: List(str)) -> Dict(str, str):
       """
       Process multiple questions about the same document.


       Args:
           document: The text document to use as context
           questions: List of questions to answer


       Returns:
           Dictionary mapping questions to answers
       """
       results = {}
       for question in questions:
           results = self.process_question(document, question)
       return results

### Test Code
if __name__ == "__main__":
   # Sample document (an instruction manual excerpt)
   sample_document = """
   QUICKSTART GUIDE: MODEL X3000 COFFEE MAKER


   SETUP INSTRUCTIONS:
   1. Unpack the coffee maker and remove all packaging materials.
   2. Rinse the water reservoir and fill with fresh, cold water up to the MAX line.
   3. Insert the gold-tone filter into the filter basket.
   4. Add ground coffee (1 tbsp per cup recommended).
   5. Close the lid and ensure the carafe is properly positioned on the warming plate.
   6. Plug in the coffee maker and press the POWER button.
   7. Press the BREW button to start brewing.


   FEATURES:
   - Programmable timer: Set up to 24 hours in advance
   - Strength control: Choose between Regular, Strong, and Bold
   - Auto-shutoff: Machine turns off automatically after 2 hours
   - Pause and serve: Remove carafe during brewing for up to 30 seconds


   CLEANING:
   - Daily: Rinse removable parts with warm water
   - Weekly: Clean carafe and filter basket with mild detergent
   - Monthly: Run a descaling cycle using white vinegar solution (1:2 vinegar to water)


   TROUBLESHOOTING:
   - Coffee not brewing: Check water reservoir and power connection
   - Weak coffee: Use STRONG setting or add more coffee grounds
   - Overflow: Ensure filter is properly seated and use correct amount of coffee
   - Error E01: Contact customer service for heating element replacement
   """


   # Sample questions
   sample_questions = (
       "How much coffee should I use per cup?",
       "How do I clean the coffee maker?",
       "What does error code E02 mean?",
       "What is the auto-shutoff time?",
       "How long can I remove the carafe during brewing?"
   )


   # Create and use the agent
   agent = ClaudeDocumentQA()






   # Process a single question
   print("=== Single Question ===")
   answer = agent.process_question(sample_document, sample_questions(0))
   print(f"Q: {sample_questions(0)}")
   print(f"A: {answer}\n")


   # Process multiple questions
   print("=== Batch Processing ===")
   results = agent.batch_process(sample_document, sample_questions)
   for question, answer in results.items():
       print(f"Q: {question}")
       print(f"A: {answer}\n")