Anthropic Provider¶

GroundlensAnthropic wraps the Anthropic Python SDK and automatically scores every Claude response for hallucination risk using groundlens.

Installation¶

pip install "groundlens[anthropic]"

Quick Start¶

from groundlens.providers.anthropic import GroundlensAnthropic

llm = GroundlensAnthropic(api_key="sk-ant-...")

# With context (SGI scoring)
resp = llm.chat(
    "Summarize the key findings.",
    context="The study found that regular exercise reduces cardiovascular risk by 30%...",
)
print(resp.text)
print(resp.groundlens_score.method)         # 'sgi'
print(resp.groundlens_score.flagged)        # False

# Without context (DGI scoring)
resp = llm.chat("What is the Pythagorean theorem?")
print(resp.groundlens_score.method)         # 'dgi'

Configuration¶

llm = GroundlensAnthropic(
    api_key="sk-ant-...",
    model="claude-sonnet-4-20250514",      # Claude model for generation
    groundlens_model="all-MiniLM-L6-v2",    # Sentence-transformer for scoring
    groundlens_threshold=0.45,               # Reserved for future use
)

Parameter	Default	Description
`api_key`	Required	Anthropic API key
`model`	`"claude-sonnet-4-20250514"`	Claude model for generation
`groundlens_model`	`"all-MiniLM-L6-v2"`	Embedding model for scoring
`groundlens_threshold`	`0.45`	Reserved for future threshold customization

Response Object¶

The LLMResponse returned by chat() contains:

Field	Type	Description
`text`	`str`	Generated response text
`model`	`str`	Model identifier
`usage`	`dict`	Token usage (`input_tokens`, `output_tokens`)
`groundlens_score`	`GroundlensScore`	Full groundlens evaluation result

Passing Extra Parameters¶

Additional keyword arguments are forwarded to messages.create:

resp = llm.chat(
    "Explain the theory of relativity.",
    max_tokens=1000,
)

The max_tokens parameter defaults to 4096 if not specified.

Convenience Method¶

# complete() delegates to chat()
resp = llm.complete("Summarize this document.", context=document_text)

Environment Variable for API Key¶

import os
from groundlens.providers.anthropic import GroundlensAnthropic

llm = GroundlensAnthropic(api_key=os.environ["ANTHROPIC_API_KEY"])