feat: add Google AI Studio API support with platform-based detection (#502)

* feat: add Google AI Studio API support with platform-based detection * chore: update configuration_guide.md * fix the uv.lock formate error --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-04-03 14:22:13 +08:00 · 2025-09-13 08:49:05 +08:00
parent dd9af1eb50
commit bbc49a04a6
5 changed files with 215 additions and 3 deletions
--- a/conf.yaml.example
+++ b/conf.yaml.example
@@ -12,6 +12,13 @@ BASIC_MODEL:
  api_key: xxxx
  # max_retries: 3 # Maximum number of retries for LLM calls
  # verify_ssl: false  # Uncomment this line to disable SSL certificate verification for self-signed certificates
+
+# To use Google Ai Studio as your basic platform:
+# BASIC_MODEL:
+#   platform: "google_aistudio"
+#   model: "gemini-2.5-flash"  # or "gemini-1.5-pro", "gemini-2.5-flash-exp", etc.
+#   api_key: your_gemini_api_key  # Get from https://aistudio.google.com/app/apikey
+#   max_retries: 3
 
 # Reasoning model is optional.
 # Uncomment the following settings if you want to use reasoning model
--- a/docs/configuration_guide.md
+++ b/docs/configuration_guide.md
@@ -97,7 +97,30 @@ AGENT_LLM_MAP: dict[str, LLMType] = {
    "prompt_enhancer": "basic",
 }

+
+### How to use Google AI Studio models?
+
+DeerFlow supports native integration with Google AI Studio (formerly Google Generative AI) API. This provides direct access to Google's Gemini models with their full feature set and optimized performance.
+
+To use Google AI Studio models, you need to:
+1. Get your API key from [Google AI Studio](https://aistudio.google.com/app/apikey)
+2. Set the `platform` field to `"google_aistudio"` in your configuration
+3. Configure your model and API key
+
+The following is a configuration example for using Google AI Studio models:
+
+```yaml
+# Google AI Studio native API (recommended for Google models)
+BASIC_MODEL:
+  platform: "google_aistudio"
+  model: "gemini-2.5-flash"  # or "gemini-1.5-pro" ,...
+  api_key: YOUR_GOOGLE_API_KEY # Get from https://aistudio.google.com/app/apikey
+
 ```
+
+**Note:** The `platform: "google_aistudio"` field is required to distinguish from other providers that may offer Gemini models through OpenAI-compatible APIs.
+```
+
 ### How to use models with self-signed SSL certificates?

 If your LLM server uses self-signed SSL certificates, you can disable SSL certificate verification by adding the `verify_ssl: false` parameter to your model configuration:
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,6 +33,7 @@ dependencies = [
    "mcp>=1.11.0",
    "langchain-mcp-adapters>=0.0.9",
    "langchain-deepseek>=0.1.3",
+    "langchain-google-genai>=2.0.6",
    "wikipedia>=1.4.0",
    "langchain-tavily<0.3",
    "langgraph-checkpoint-mongodb>=0.1.4",
--- a/src/llms/llm.py
+++ b/src/llms/llm.py
@@ -8,7 +8,9 @@ from typing import Any, Dict, get_args
 import httpx
 from langchain_core.language_models import BaseChatModel
 from langchain_deepseek import ChatDeepSeek
+from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_openai import AzureChatOpenAI, ChatOpenAI
+from typing import get_args

 from src.config import load_yaml_config
 from src.config.agents import LLMType
@@ -83,6 +85,28 @@ def _create_llm_use_conf(llm_type: LLMType, conf: Dict[str, Any]) -> BaseChatMod
        merged_conf["http_client"] = http_client
        merged_conf["http_async_client"] = http_async_client

+    # Check if it's Google AI Studio platform based on configuration
+    platform = merged_conf.get("platform", "").lower()
+    is_google_aistudio = platform == "google_aistudio" or platform == "google-aistudio"
+
+    if is_google_aistudio:
+        # Handle Google AI Studio specific configuration
+        gemini_conf = merged_conf.copy()
+
+        # Map common keys to Google AI Studio specific keys
+        if "api_key" in gemini_conf:
+            gemini_conf["google_api_key"] = gemini_conf.pop("api_key")
+
+        # Remove base_url and platform since Google AI Studio doesn't use them
+        gemini_conf.pop("base_url", None)
+        gemini_conf.pop("platform", None)
+
+        # Remove unsupported parameters for Google AI Studio
+        gemini_conf.pop("http_client", None)
+        gemini_conf.pop("http_async_client", None)
+
+        return ChatGoogleGenerativeAI(**gemini_conf)
+
    if "azure_endpoint" in merged_conf or os.getenv("AZURE_OPENAI_ENDPOINT"):
        return AzureChatOpenAI(**merged_conf)

--- a/uv.lock
+++ b/uv.lock
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@@ -396,6 +405,7 @@ dependencies = [
    { name = "langchain-community" },
    { name = "langchain-deepseek" },
    { name = "langchain-experimental" },
+    { name = "langchain-google-genai" },
    { name = "langchain-mcp-adapters" },
    { name = "langchain-milvus" },
    { name = "langchain-openai" },
@@ -446,6 +456,7 @@ requires-dist = [
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    { name = "langchain-deepseek", specifier = ">=0.1.3" },
    { name = "langchain-experimental", specifier = ">=0.3.4" },
+    { name = "langchain-google-genai", specifier = ">=2.0.6" },
    { name = "langchain-mcp-adapters", specifier = ">=0.0.9" },
    { name = "langchain-milvus", specifier = ">=0.2.1" },
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