# Copyright 2025 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # MedGemma endpoint import requests from auth import create_credentials, get_access_token_refresh_if_needed import os from cache import cache _endpoint_url = os.environ.get('GCP_MEDGEMMA_ENDPOINT') # Create credentials secret_key_json = os.environ.get('GCP_MEDGEMMA_SERVICE_ACCOUNT_KEY') medgemma_credentials = create_credentials(secret_key_json) # https://cloud.google.com/vertex-ai/docs/reference/rest/v1beta1/projects.locations.endpoints.chat/completions @cache.memoize() def medgemma_get_text_response( messages: list, temperature: float = 0.1, max_tokens: int = 4096, stream: bool = False, top_p: float | None = None, seed: int | None = None, stop: list[str] | str | None = None, frequency_penalty: float | None = None, presence_penalty: float | None = None, model: str="tgi" ): """ Makes a chat completion request to the configured LLM API (OpenAI-compatible). """ headers = { "Authorization": f"Bearer {get_access_token_refresh_if_needed(medgemma_credentials)}", "Content-Type": "application/json", } # Based on the openai format payload = { "messages": messages, "max_tokens": max_tokens } if temperature is not None: payload["temperature"] = temperature if top_p is not None: payload["top_p"] = top_p if seed is not None: payload["seed"] = seed if stop is not None: payload["stop"] = stop if frequency_penalty is not None: payload["frequency_penalty"] = frequency_penalty if presence_penalty is not None: payload["presence_penalty"] = presence_penalty response = requests.post(_endpoint_url, headers=headers, json=payload, stream=stream, timeout=60) try: response.raise_for_status() return response.json()["choices"][0]["message"]["content"] except requests.exceptions.JSONDecodeError: # Log the problematic response for easier debugging in the future. print(f"Error: Failed to decode JSON from MedGemma. Status: {response.status_code}, Response: {response.text}") # Re-raise the exception so the caller knows something went wrong. raise