adds anthropic model claude 3 opus

prospector/llm/instantiation.py

@@ -9,6 +9,7 @@
 from langchain_mistralai import ChatMistralAI
 from langchain_openai import ChatOpenAI
 
+from llm.models.anthropic import Anthropic
 from llm.models.gemini import Gemini
 from llm.models.mistral import Mistral
 from llm.models.openai import OpenAI
@@ -26,6 +27,7 @@
     # "gpt-4o": OpenAI,  # currently TBD
     "gemini-1.0-pro": Gemini,
     "mistral-large": Mistral,
+    "claude-3-opus": Anthropic,
 }
 
 

prospector/llm/llm_service.py

@@ -113,9 +113,9 @@ def classify_commit(
         except Exception as e:
             raise RuntimeError(f"Prompt-model chain could not be invoked: {e}")
 
-        if is_relevant == "True":
+        if is_relevant in ["True", "ANSWER:True"]:
             return True
-        elif is_relevant == "False":
+        elif is_relevant in ["False", "ANSWER:False"]:
             return False
         else:
             raise RuntimeError(f"The model returned an invalid response: {is_relevant}")

prospector/llm/models/anthropic.py

@@ -0,0 +1,74 @@
+from typing import Any, Dict, List, Optional
+
+import requests
+from langchain_core.language_models.llms import LLM
+
+import llm.instantiation as instantiation
+from log.logger import logger
+
+
+class Anthropic(LLM):
+    model_name: str
+    deployment_url: str
+    temperature: float
+    ai_core_sk_filepath: str
+
+    @property
+    def _llm_type(self) -> str:
+        return "SAP Anthropic"
+
+    @property
+    def _identifying_params(self) -> Dict[str, Any]:
+        """Return a dictionary of identifying parameters."""
+        return {
+            "model_name": self.model_name,
+            "deployment_url": self.deployment_url,
+            "temperature": self.temperature,
+            "ai_core_sk_filepath": self.ai_core_sk_filepath,
+        }
+
+    def _call(
+        self, prompt: str, stop: Optional[List[str]] = None, **kwargs: Any
+    ) -> str:
+        endpoint = f"{self.deployment_url}/invoke"
+        headers = instantiation.get_headers(self.ai_core_sk_filepath)
+        data = {
+            "anthropic_version": "bedrock-2023-05-31",
+            "max_tokens": 100,
+            "messages": [
+                {
+                    "role": "user",
+                    "content": f"{prompt}",
+                }
+            ],
+            "temperature": self.temperature,
+        }
+
+        try:
+            response = requests.post(endpoint, headers=headers, json=data)
+            response.raise_for_status()
+            return self.parse(response.json())
+        except requests.exceptions.HTTPError as http_error:
+            logger.error(
+                f"HTTP error occurred when sending a request through AI Core: {http_error}"
+            )
+            raise
+        except requests.exceptions.Timeout as timeout_err:
+            logger.error(
+                f"Timeout error occured when sending a request through AI Core: {timeout_err}"
+            )
+            raise
+        except requests.exceptions.ConnectionError as conn_err:
+            logger.error(
+                f"Connection error occurred when sending a request through AI Core: {conn_err}"
+            )
+            raise
+        except requests.exceptions.RequestException as req_err:
+            logger.error(
+                f"A request error occured when sending a request through AI Core: {req_err}"
+            )
+            raise
+
+    def parse(self, message) -> str:
+        """Parse the returned JSON object from OpenAI."""
+        return message["content"][0]["text"]