From 126496d3cacd06a4fa8cbb4e5bde417ce6bb5b4a Mon Sep 17 00:00:00 2001
From: Heiner Lohaus <heiner.lohaus@netformic.com>
Date: Fri, 25 Aug 2023 06:41:32 +0200
Subject: Add OpenaiChat and Hugchat Provider Add tests for providers with auth
 Improve async support / 2x faster Shared get_cookies by domain  function

---
 g4f/Provider/Hugchat.py | 67 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 67 insertions(+)
 create mode 100644 g4f/Provider/Hugchat.py

(limited to 'g4f/Provider/Hugchat.py')

diff --git a/g4f/Provider/Hugchat.py b/g4f/Provider/Hugchat.py
new file mode 100644
index 00000000..cedf8402
--- /dev/null
+++ b/g4f/Provider/Hugchat.py
@@ -0,0 +1,67 @@
+has_module = False
+try:
+    from hugchat.hugchat import ChatBot
+except ImportError:
+    has_module = False
+
+from .base_provider import BaseProvider, get_cookies
+from g4f.typing import CreateResult
+
+class Hugchat(BaseProvider):
+    url = "https://huggingface.co/chat/"
+    needs_auth = True
+    working = has_module
+    llms = ['OpenAssistant/oasst-sft-6-llama-30b-xor', 'meta-llama/Llama-2-70b-chat-hf']
+
+    @classmethod
+    def create_completion(
+        cls,
+        model: str,
+        messages: list[dict[str, str]],
+        stream: bool = False,
+        proxy: str = None,
+        cookies: str = get_cookies(".huggingface.co"),
+        **kwargs
+    ) -> CreateResult:
+        bot = ChatBot(
+            cookies=cookies
+        )
+        
+        if proxy and "://" not in proxy:
+            proxy = f"http://{proxy}"
+            bot.session.proxies = {"http": proxy, "https": proxy}
+
+        if model:
+            try:
+                if not isinstance(model, int):
+                    model = cls.llms.index(model)
+                bot.switch_llm(model)
+            except:
+                raise RuntimeError(f"Model are not supported: {model}")
+
+        if len(messages) > 1:
+            formatted = "\n".join(
+                ["%s: %s" % (message["role"], message["content"]) for message in messages]
+            )
+            prompt = f"{formatted}\nAssistant:"
+        else:
+            prompt = messages.pop()["content"]
+
+        try:
+            yield bot.chat(prompt, **kwargs)
+        finally:
+            bot.delete_conversation(bot.current_conversation)
+            bot.current_conversation = ""
+            pass
+
+    @classmethod
+    @property
+    def params(cls):
+        params = [
+            ("model", "str"),
+            ("messages", "list[dict[str, str]]"),
+            ("stream", "bool"),
+            ("proxy", "str"),
+        ]
+        param = ", ".join([": ".join(p) for p in params])
+        return f"g4f.provider.{cls.__name__} supports: ({param})"
-- 
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