feat: migrate from Anthropic API to OpenRouter
Replace direct Anthropic API integration with OpenRouter to enable more flexible LLM provider access while maintaining Claude 3.5 Sonnet. Changes: - Replace anthropic package with openai in requirements.txt - Update config to use OPENROUTER_API_KEY instead of ANTHROPIC_API_KEY - Migrate LLMAnalyzer from Anthropic client to OpenAI client with OpenRouter base URL (https://openrouter.ai/api/v1) - Update model identifier to OpenRouter format: anthropic/claude-3.5-sonnet - Convert API calls from messages.create() to chat.completions.create() - Update response parsing to match OpenAI format - Rename API key parameter in CompanyAnalyzer from anthropic_api_key to openrouter_api_key - Update all tests to mock OpenAI client instead of Anthropic - Fix client initialization to accept direct API key parameter 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
parent
8971ebc913
commit
af4114969a
@ -13,13 +13,13 @@ from typing import List
|
||||
class CompanyAnalyzer:
|
||||
"""Orchestrates end-to-end company performance analysis via patents."""
|
||||
|
||||
def __init__(self, anthropic_api_key: str | None = None):
|
||||
def __init__(self, openrouter_api_key: str | None = None):
|
||||
"""Initialize the company analyzer.
|
||||
|
||||
Args:
|
||||
anthropic_api_key: Optional Anthropic API key. If None, loads from config.
|
||||
openrouter_api_key: Optional OpenRouter API key. If None, loads from config.
|
||||
"""
|
||||
self.llm_analyzer = LLMAnalyzer(api_key=anthropic_api_key)
|
||||
self.llm_analyzer = LLMAnalyzer(api_key=openrouter_api_key)
|
||||
|
||||
def analyze_company(self, company_name: str) -> str:
|
||||
"""Analyze a company's performance based on their patent portfolio.
|
||||
|
||||
@ -10,5 +10,5 @@ load_dotenv()
|
||||
# SerpAPI key for patent search
|
||||
api_key = os.getenv("API_KEY")
|
||||
|
||||
# Anthropic API key for LLM analysis
|
||||
anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
|
||||
# OpenRouter API key for LLM analysis
|
||||
openrouter_api_key = os.getenv("OPENROUTER_API_KEY")
|
||||
|
||||
23
SPARC/llm.py
23
SPARC/llm.py
@ -1,6 +1,6 @@
|
||||
"""LLM integration for patent analysis using Anthropic's Claude."""
|
||||
"""LLM integration for patent analysis using OpenRouter."""
|
||||
|
||||
from anthropic import Anthropic
|
||||
from openai import OpenAI
|
||||
from SPARC import config
|
||||
from typing import Dict
|
||||
|
||||
@ -12,14 +12,17 @@ class LLMAnalyzer:
|
||||
"""Initialize the LLM analyzer.
|
||||
|
||||
Args:
|
||||
api_key: Anthropic API key. If None, will attempt to load from config.
|
||||
api_key: OpenRouter API key. If None, will attempt to load from config.
|
||||
test_mode: If True, print prompts instead of making API calls
|
||||
"""
|
||||
self.test_mode = test_mode
|
||||
|
||||
if config.anthropic_api_key and not test_mode:
|
||||
self.client = Anthropic(api_key=api_key or config.anthropic_api_key)
|
||||
self.model = "claude-3-5-sonnet-20241022"
|
||||
if (api_key or config.openrouter_api_key) and not test_mode:
|
||||
self.client = OpenAI(
|
||||
api_key=api_key or config.openrouter_api_key,
|
||||
base_url="https://openrouter.ai/api/v1"
|
||||
)
|
||||
self.model = "anthropic/claude-3.5-sonnet"
|
||||
else:
|
||||
self.client = None
|
||||
|
||||
@ -55,12 +58,12 @@ Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals
|
||||
return "[TEST MODE - No API call made]"
|
||||
|
||||
if self.client:
|
||||
message = self.client.messages.create(
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model,
|
||||
max_tokens=1024,
|
||||
messages=[{"role": "user", "content": prompt}],
|
||||
)
|
||||
return message.content[0].text
|
||||
return response.choices[0].message.content
|
||||
|
||||
def analyze_patent_portfolio(
|
||||
self, patents_data: list[Dict[str, str]], company_name: str
|
||||
@ -103,13 +106,13 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
|
||||
return "[TEST MODE]"
|
||||
|
||||
try:
|
||||
message = self.client.messages.create(
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model,
|
||||
max_tokens=2048,
|
||||
messages=[{"role": "user", "content": prompt}],
|
||||
)
|
||||
|
||||
return message.content[0].text
|
||||
return response.choices[0].message.content
|
||||
except AttributeError:
|
||||
return prompt
|
||||
|
||||
|
||||
@ -4,4 +4,4 @@ pdfplumber
|
||||
requests
|
||||
pytest
|
||||
pytest-mock
|
||||
anthropic
|
||||
openai
|
||||
|
||||
@ -13,7 +13,7 @@ class TestCompanyAnalyzer:
|
||||
"""Test analyzer initialization with API key."""
|
||||
mock_llm = mocker.patch("SPARC.analyzer.LLMAnalyzer")
|
||||
|
||||
analyzer = CompanyAnalyzer(anthropic_api_key="test-key")
|
||||
analyzer = CompanyAnalyzer(openrouter_api_key="test-key")
|
||||
|
||||
mock_llm.assert_called_once_with(api_key="test-key")
|
||||
|
||||
|
||||
@ -10,33 +10,39 @@ class TestLLMAnalyzer:
|
||||
|
||||
def test_analyzer_initialization_with_api_key(self, mocker):
|
||||
"""Test that analyzer initializes with provided API key."""
|
||||
mock_anthropic = mocker.patch("SPARC.llm.Anthropic")
|
||||
mock_openai = mocker.patch("SPARC.llm.OpenAI")
|
||||
|
||||
analyzer = LLMAnalyzer(api_key="test-key-123")
|
||||
|
||||
mock_anthropic.assert_called_once_with(api_key="test-key-123")
|
||||
assert analyzer.model == "claude-3-5-sonnet-20241022"
|
||||
mock_openai.assert_called_once_with(
|
||||
api_key="test-key-123",
|
||||
base_url="https://openrouter.ai/api/v1"
|
||||
)
|
||||
assert analyzer.model == "anthropic/claude-3.5-sonnet"
|
||||
|
||||
def test_analyzer_initialization_from_config(self, mocker):
|
||||
"""Test that analyzer loads API key from config when not provided."""
|
||||
mock_anthropic = mocker.patch("SPARC.llm.Anthropic")
|
||||
mock_openai = mocker.patch("SPARC.llm.OpenAI")
|
||||
mock_config = mocker.patch("SPARC.llm.config")
|
||||
mock_config.anthropic_api_key = "config-key-456"
|
||||
mock_config.openrouter_api_key = "config-key-456"
|
||||
|
||||
analyzer = LLMAnalyzer()
|
||||
|
||||
mock_anthropic.assert_called_once_with(api_key="config-key-456")
|
||||
mock_openai.assert_called_once_with(
|
||||
api_key="config-key-456",
|
||||
base_url="https://openrouter.ai/api/v1"
|
||||
)
|
||||
|
||||
def test_analyze_patent_content(self, mocker):
|
||||
"""Test single patent content analysis."""
|
||||
mock_anthropic = mocker.patch("SPARC.llm.Anthropic")
|
||||
mock_openai = mocker.patch("SPARC.llm.OpenAI")
|
||||
mock_client = Mock()
|
||||
mock_anthropic.return_value = mock_client
|
||||
mock_openai.return_value = mock_client
|
||||
|
||||
# Mock the API response
|
||||
mock_response = Mock()
|
||||
mock_response.content = [Mock(text="Innovative GPU architecture.")]
|
||||
mock_client.messages.create.return_value = mock_response
|
||||
mock_response.choices = [Mock(message=Mock(content="Innovative GPU architecture."))]
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
analyzer = LLMAnalyzer(api_key="test-key")
|
||||
result = analyzer.analyze_patent_content(
|
||||
@ -45,26 +51,26 @@ class TestLLMAnalyzer:
|
||||
)
|
||||
|
||||
assert result == "Innovative GPU architecture."
|
||||
mock_client.messages.create.assert_called_once()
|
||||
mock_client.chat.completions.create.assert_called_once()
|
||||
|
||||
# Verify the prompt includes company name and content
|
||||
call_args = mock_client.messages.create.call_args
|
||||
call_args = mock_client.chat.completions.create.call_args
|
||||
prompt_text = call_args[1]["messages"][0]["content"]
|
||||
assert "NVIDIA" in prompt_text
|
||||
assert "GPU with new cache design" in prompt_text
|
||||
|
||||
def test_analyze_patent_portfolio(self, mocker):
|
||||
"""Test portfolio analysis with multiple patents."""
|
||||
mock_anthropic = mocker.patch("SPARC.llm.Anthropic")
|
||||
mock_openai = mocker.patch("SPARC.llm.OpenAI")
|
||||
mock_client = Mock()
|
||||
mock_anthropic.return_value = mock_client
|
||||
mock_openai.return_value = mock_client
|
||||
|
||||
# Mock the API response
|
||||
mock_response = Mock()
|
||||
mock_response.content = [
|
||||
Mock(text="Strong portfolio in AI and graphics.")
|
||||
mock_response.choices = [
|
||||
Mock(message=Mock(content="Strong portfolio in AI and graphics."))
|
||||
]
|
||||
mock_client.messages.create.return_value = mock_response
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
analyzer = LLMAnalyzer(api_key="test-key")
|
||||
patents_data = [
|
||||
@ -77,10 +83,10 @@ class TestLLMAnalyzer:
|
||||
)
|
||||
|
||||
assert result == "Strong portfolio in AI and graphics."
|
||||
mock_client.messages.create.assert_called_once()
|
||||
mock_client.chat.completions.create.assert_called_once()
|
||||
|
||||
# Verify the prompt includes all patents
|
||||
call_args = mock_client.messages.create.call_args
|
||||
call_args = mock_client.chat.completions.create.call_args
|
||||
prompt_text = call_args[1]["messages"][0]["content"]
|
||||
assert "US123" in prompt_text
|
||||
assert "US456" in prompt_text
|
||||
@ -89,36 +95,36 @@ class TestLLMAnalyzer:
|
||||
|
||||
def test_analyze_patent_portfolio_with_correct_token_limit(self, mocker):
|
||||
"""Test that portfolio analysis uses higher token limit."""
|
||||
mock_anthropic = mocker.patch("SPARC.llm.Anthropic")
|
||||
mock_openai = mocker.patch("SPARC.llm.OpenAI")
|
||||
mock_client = Mock()
|
||||
mock_anthropic.return_value = mock_client
|
||||
mock_openai.return_value = mock_client
|
||||
|
||||
mock_response = Mock()
|
||||
mock_response.content = [Mock(text="Analysis result.")]
|
||||
mock_client.messages.create.return_value = mock_response
|
||||
mock_response.choices = [Mock(message=Mock(content="Analysis result."))]
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
analyzer = LLMAnalyzer(api_key="test-key")
|
||||
patents_data = [{"patent_id": "US123", "content": "Test content"}]
|
||||
|
||||
analyzer.analyze_patent_portfolio(patents_data, "TestCo")
|
||||
|
||||
call_args = mock_client.messages.create.call_args
|
||||
call_args = mock_client.chat.completions.create.call_args
|
||||
# Portfolio analysis should use 2048 tokens
|
||||
assert call_args[1]["max_tokens"] == 2048
|
||||
|
||||
def test_analyze_single_patent_with_correct_token_limit(self, mocker):
|
||||
"""Test that single patent analysis uses lower token limit."""
|
||||
mock_anthropic = mocker.patch("SPARC.llm.Anthropic")
|
||||
mock_openai = mocker.patch("SPARC.llm.OpenAI")
|
||||
mock_client = Mock()
|
||||
mock_anthropic.return_value = mock_client
|
||||
mock_openai.return_value = mock_client
|
||||
|
||||
mock_response = Mock()
|
||||
mock_response.content = [Mock(text="Analysis result.")]
|
||||
mock_client.messages.create.return_value = mock_response
|
||||
mock_response.choices = [Mock(message=Mock(content="Analysis result."))]
|
||||
mock_client.chat.completions.create.return_value = mock_response
|
||||
|
||||
analyzer = LLMAnalyzer(api_key="test-key")
|
||||
analyzer.analyze_patent_content("Test content", "TestCo")
|
||||
|
||||
call_args = mock_client.messages.create.call_args
|
||||
call_args = mock_client.chat.completions.create.call_args
|
||||
# Single patent should use 1024 tokens
|
||||
assert call_args[1]["max_tokens"] == 1024
|
||||
|
||||
Loading…
Reference in New Issue
Block a user