Add unittests for async client (#1830)

* Add unittests for async client

* Add pollyfill for anext

* Update integration tests

etc/unittest/__main__.py

@@ -4,6 +4,7 @@ from .backend import *
 from .main import *
 from .model import *
 from .client import *
+from .async_client import *
 from .include import *
 from .integration import *
 

etc/unittest/async_client.py

@@ -0,0 +1,56 @@
+import unittest
+
+from g4f.client import AsyncClient, ChatCompletion, ChatCompletionChunk
+from .mocks import AsyncGeneratorProviderMock, ModelProviderMock, YieldProviderMock
+
+DEFAULT_MESSAGES = [{'role': 'user', 'content': 'Hello'}]
+
+class AsyncTestPassModel(unittest.IsolatedAsyncioTestCase):
+
+    async def test_response(self):
+        client = AsyncClient(provider=AsyncGeneratorProviderMock)
+        response = await client.chat.completions.create(DEFAULT_MESSAGES, "")
+        self.assertIsInstance(response, ChatCompletion)
+        self.assertEqual("Mock", response.choices[0].message.content)
+
+    async def test_pass_model(self):
+        client = AsyncClient(provider=ModelProviderMock)
+        response = await client.chat.completions.create(DEFAULT_MESSAGES, "Hello")
+        self.assertIsInstance(response, ChatCompletion)
+        self.assertEqual("Hello", response.choices[0].message.content)
+
+    async def test_max_tokens(self):
+        client = AsyncClient(provider=YieldProviderMock)
+        messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
+        response = await client.chat.completions.create(messages, "Hello", max_tokens=1)
+        self.assertIsInstance(response, ChatCompletion)
+        self.assertEqual("How ", response.choices[0].message.content)
+        response = await client.chat.completions.create(messages, "Hello", max_tokens=2)
+        self.assertIsInstance(response, ChatCompletion)
+        self.assertEqual("How are ", response.choices[0].message.content)
+
+    async def test_max_stream(self):
+        client = AsyncClient(provider=YieldProviderMock)
+        messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
+        response = client.chat.completions.create(messages, "Hello", stream=True)
+        async for chunk in response:
+            self.assertIsInstance(chunk, ChatCompletionChunk)
+            if chunk.choices[0].delta.content is not None:
+                self.assertIsInstance(chunk.choices[0].delta.content, str)
+        messages = [{'role': 'user', 'content': chunk} for chunk in ["You ", "You ", "Other", "?"]]
+        response = client.chat.completions.create(messages, "Hello", stream=True, max_tokens=2)
+        response = [chunk async for chunk in response]
+        self.assertEqual(len(response), 3)
+        for chunk in response:
+            if chunk.choices[0].delta.content is not None:
+                self.assertEqual(chunk.choices[0].delta.content, "You ")
+
+    async def test_stop(self):
+        client = AsyncClient(provider=YieldProviderMock)
+        messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
+        response = await client.chat.completions.create(messages, "Hello", stop=["and"])
+        self.assertIsInstance(response, ChatCompletion)
+        self.assertEqual("How are you?", response.choices[0].message.content)
+
+if __name__ == '__main__':
+    unittest.main()

etc/unittest/integration.py

@@ -8,7 +8,7 @@ except ImportError:
     has_nest_asyncio = False 
 
 from g4f.client import Client, ChatCompletion
-from g4f.Provider import Bing, OpenaiChat
+from g4f.Provider import Bing, OpenaiChat, DuckDuckGo
 
 DEFAULT_MESSAGES = [{"role": "system", "content": 'Response in json, Example: {"success: true"}'},
                     {"role": "user", "content": "Say success true in json"}]
@@ -19,11 +19,19 @@ class TestProviderIntegration(unittest.TestCase):
             self.skipTest("nest_asyncio is not installed")
 
     def test_bing(self):
+        self.skipTest("Not stable")
         client = Client(provider=Bing)
         response = client.chat.completions.create(DEFAULT_MESSAGES, "", response_format={"type": "json_object"})
         self.assertIsInstance(response, ChatCompletion)
         self.assertIn("success", json.loads(response.choices[0].message.content))
 
+    def test_duckduckgo(self):
+        self.skipTest("Not working")
+        client = Client(provider=DuckDuckGo)
+        response = client.chat.completions.create(DEFAULT_MESSAGES, "", response_format={"type": "json_object"})
+        self.assertIsInstance(response, ChatCompletion)
+        self.assertIn("success", json.loads(response.choices[0].message.content))
+
     def test_openai(self):
         client = Client(provider=OpenaiChat)
         response = client.chat.completions.create(DEFAULT_MESSAGES, "", response_format={"type": "json_object"})

g4f/Provider/Vercel.py

@@ -11,7 +11,7 @@ except ImportError:
 from ..typing       import Messages, CreateResult
 from .base_provider import AbstractProvider
 from ..requests     import raise_for_status
-from ..errors       import MissingRequirementsError, RateLimitError, ResponseStatusError
+from ..errors       import MissingRequirementsError
 
 class Vercel(AbstractProvider):
     url = 'https://chat.vercel.ai'

g4f/client/async_client.py

@@ -16,6 +16,13 @@ from ..errors import NoImageResponseError
 from ..image import ImageResponse as ImageProviderResponse
 from ..providers.base_provider import AsyncGeneratorProvider
 
+try:
+    anext
+except NameError:
+    async def anext(iter):
+        async for chunk in iter:
+            return chunk
+
 async def iter_response(
     response: AsyncIterator[str],
     stream: bool,

g4f/gui/client/static/js/chat.v1.js

@@ -1262,7 +1262,7 @@ if (SpeechRecognition) {
 
     function may_stop() {
         if (microLabel.classList.contains("recognition")) {
-            //recognition.stop();
+            recognition.stop();
         }
     }
 
@@ -1272,15 +1272,12 @@ if (SpeechRecognition) {
     recognition.onstart = function() {
         microLabel.classList.add("recognition");
         startValue = messageInput.value;
-        messageInput.placeholder = "";
         lastDebounceTranscript = "";
         timeoutHandle = window.setTimeout(may_stop, 10000);
     };
     recognition.onend = function() {
         microLabel.classList.remove("recognition");
-        messageInput.value = messageInput.placeholder;
-        messageInput.placeholder = "Ask a question";
-        //messageInput.focus();
+        messageInput.focus();
     };
     recognition.onresult = function(event) {
         if (!event.results) {
@@ -1298,9 +1295,9 @@ if (SpeechRecognition) {
             lastDebounceTranscript = transcript;
         }
         if (transcript) {
-            messageInput.placeholder = `${startValue ? startValue+"\n" : ""}${transcript.trim()}`;
+            messageInput.value = `${startValue ? startValue+"\n" : ""}${transcript.trim()}`;
             if (isFinal) {
-                startValue = messageInput.placeholder;
+                startValue = messageInput.value;
             }
             messageInput.style.height = messageInput.scrollHeight  + "px";
             messageInput.scrollTop = messageInput.scrollHeight;

g4f/requests/curl_cffi.py

@@ -34,15 +34,13 @@ class StreamResponse:
         """Asynchronously parse the JSON response content."""
         return json.loads(await self.inner.acontent(), **kwargs)
 
-    async def iter_lines(self) -> AsyncGenerator[bytes, None]:
+    def iter_lines(self) -> AsyncGenerator[bytes, None]:
         """Asynchronously iterate over the lines of the response."""
-        async for line in self.inner.aiter_lines():
-            yield line
+        return  self.inner.aiter_lines()
 
-    async def iter_content(self) -> AsyncGenerator[bytes, None]:
+    def iter_content(self) -> AsyncGenerator[bytes, None]:
         """Asynchronously iterate over the response content."""
-        async for chunk in self.inner.aiter_content():
-            yield chunk
+        return self.inner.aiter_content()
 
     async def __aenter__(self):
         """Asynchronously enter the runtime context for the response object."""