Merge pull request #1313 from yu-iskw/support-google-ai-studio

Support Google AI Studio

docs/docs/usage-guide/changing_a_model.md

@@ -133,9 +133,26 @@ Your [application default credentials](https://cloud.google.com/docs/authenticat
 
 If you do want to set explicit credentials, then you can use the `GOOGLE_APPLICATION_CREDENTIALS` environment variable set to a path to a json credentials file.
 
+### Google AI Studio
+
+To use [Google AI Studio](https://aistudio.google.com/) models, set the relevant models in the configuration section of the configuration file:
+
+```toml
+[config] # in configuration.toml
+model="google_ai_studio/gemini-1.5-flash"
+model_turbo="google_ai_studio/gemini-1.5-flash"
+fallback_models=["google_ai_studio/gemini-1.5-flash"]
+
+[google_ai_studio] # in .secrets.toml
+gemini_api_key = "..."
+```
+
+If you don't want to set the API key in the .secrets.toml file, you can set the `GOOGLE_AI_STUDIO.GEMINI_API_KEY` environment variable.
+
 ### Anthropic
 
 To use Anthropic models, set the relevant models in the configuration section of the configuration file:
+
 ```
 [config]
 model="anthropic/claude-3-opus-20240229"

pr_agent/algo/__init__.py

@@ -38,6 +38,8 @@ MAX_TOKENS = {
     'vertex_ai/gemini-1.5-pro': 1048576,
     'vertex_ai/gemini-1.5-flash': 1048576,
     'vertex_ai/gemma2': 8200,
+    'gemini/gemini-1.5-pro': 1048576,
+    'gemini/gemini-1.5-flash': 1048576,
     'codechat-bison': 6144,
     'codechat-bison-32k': 32000,
     'anthropic.claude-instant-v1': 100000,

pr_agent/algo/ai_handlers/litellm_ai_handler.py

@@ -83,6 +83,11 @@ class LiteLLMAIHandler(BaseAiHandler):
             litellm.vertex_location = get_settings().get(
                 "VERTEXAI.VERTEX_LOCATION", None
             )
+        # Google AI Studio
+        # SEE https://docs.litellm.ai/docs/providers/gemini
+        if get_settings().get("GOOGLE_AI_STUDIO.GEMINI_API_KEY", None):
+          os.environ["GEMINI_API_KEY"] = get_settings().google_ai_studio.gemini_api_key
+
     def prepare_logs(self, response, system, user, resp, finish_reason):
         response_log = response.dict().copy()
         response_log['system'] = system

pr_agent/settings/.secrets_template.toml

@@ -43,6 +43,9 @@ api_base = "" # the base url for your local Llama 2, Code Llama, and other model
 vertex_project = "" # the google cloud platform project name for your vertexai deployment
 vertex_location = "" # the google cloud platform location for your vertexai deployment
 
+[google_ai_studio]
+gemini_api_key = "" # the google AI Studio API key
+
 [github]
 # ---- Set the following only for deployment type == "user"
 user_token = ""  # A GitHub personal access token with 'repo' scope.

requirements.txt

@@ -8,6 +8,7 @@ dynaconf==3.2.4
 fastapi==0.111.0
 GitPython==3.1.41
 google-cloud-aiplatform==1.38.0
+google-generativeai==0.8.3
 google-cloud-storage==2.10.0
 Jinja2==3.1.2
 litellm==1.50.2