1 files changed, 86 insertions, 0 deletions

diff --git a/g4f/Provider/GeminiPro.py b/g4f/Provider/GeminiPro.py
new file mode 100644
index 00000000..b296f253
--- /dev/null
+++ b/g4f/Provider/GeminiPro.py
@@ -0,0 +1,86 @@
+from __future__ import annotations
+
+import base64
+import json
+from aiohttp import ClientSession
+
+from ..typing import AsyncResult, Messages, ImageType
+from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
+from ..image import to_bytes, is_accepted_format
+
+
+class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
+    url = "https://ai.google.dev"
+    working = True
+    supports_message_history = True
+    default_model = "gemini-pro"
+    models = ["gemini-pro", "gemini-pro-vision"]
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        stream: bool = False,
+        proxy: str = None,
+        api_key: str = None,
+        image: ImageType = None,
+        **kwargs
+    ) -> AsyncResult:
+        model = "gemini-pro-vision" if not model and image else model
+        model = cls.get_model(model)
+        api_key = api_key if api_key else kwargs.get("access_token")
+        headers = {
+            "Content-Type": "application/json",
+        }
+        async with ClientSession(headers=headers) as session:
+            method = "streamGenerateContent" if stream else "generateContent"
+            url = f"https://generativelanguage.googleapis.com/v1beta/models/{model}:{method}"
+            contents = [
+                {
+                    "role": "model" if message["role"] == "assistant" else message["role"],
+                    "parts": [{"text": message["content"]}]
+                }
+                for message in messages
+            ]
+            if image:
+                image = to_bytes(image)
+                contents[-1]["parts"].append({
+                    "inline_data": {
+                        "mime_type": is_accepted_format(image),
+                        "data": base64.b64encode(image).decode()
+                    }
+                })
+            data = {
+                "contents": contents,
+                # "generationConfig": {
+                #     "stopSequences": kwargs.get("stop"),
+                #     "temperature": kwargs.get("temperature"),
+                #     "maxOutputTokens": kwargs.get("max_tokens"),
+                #     "topP": kwargs.get("top_p"),
+                #     "topK": kwargs.get("top_k"),
+                # }
+            }
+            async with session.post(url, params={"key": api_key}, json=data, proxy=proxy) as response:
+                if not response.ok:
+                    data = await response.json()
+                    raise RuntimeError(data[0]["error"]["message"])
+                if stream:
+                    lines = []
+                    async for chunk in response.content:
+                        if chunk == b"[{\n":
+                            lines = [b"{\n"]
+                        elif chunk == b",\r\n" or chunk == b"]":
+                            try:
+                                data = b"".join(lines)
+                                data = json.loads(data)
+                                yield data["candidates"][0]["content"]["parts"][0]["text"]
+                            except:
+                                data = data.decode() if isinstance(data, bytes) else data
+                                raise RuntimeError(f"Read text failed. data: {data}")
+                            lines = []
+                        else:
+                            lines.append(chunk)
+                else:
+                    data = await response.json()
+                    yield data["candidates"][0]["content"]["parts"][0]["text"]
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