Fix generate messages on error in gui

g4f/Provider/Copilot.py

@@ -93,13 +93,11 @@ def create_completion(
                 if return_conversation:
                     yield Conversation(conversation_id, session.cookies.jar, access_token)
                 prompt = format_prompt(messages)
-                if debug.logging:
-                    print(f"Copilot: Created conversation: {conversation_id}")
+                debug.log(f"Copilot: Created conversation: {conversation_id}")
             else:
                 conversation_id = conversation.conversation_id
                 prompt = messages[-1]["content"]
-                if debug.logging:
-                    print(f"Copilot: Use conversation: {conversation_id}")
+                debug.log(f"Copilot: Use conversation: {conversation_id}")
 
             images = []
             if image is not None:
@@ -143,8 +141,7 @@ async def get_access_token_and_cookies(cls, proxy: str = None):
         if not has_nodriver:
             raise MissingRequirementsError('Install "nodriver" package | pip install -U nodriver')
         user_data_dir = user_config_dir("g4f-nodriver") if has_platformdirs else None
-        if debug.logging:
-            print(f"Copilot: Open nodriver with user_dir: {user_data_dir}")
+        debug.log(f"Copilot: Open nodriver with user_dir: {user_data_dir}")
         browser = await nodriver.start(
             user_data_dir=user_data_dir,
             browser_args=None if proxy is None else [f"--proxy-server={proxy}"],

g4f/Provider/needs_auth/OpenaiChat.py

@@ -282,8 +282,11 @@ async def get_generated_image(cls, session: StreamSession, headers: dict, elemen
         Raises:
             RuntimeError: If there'san error in downloading the image, including issues with the HTTP request or response.
         """
-        prompt = element["metadata"]["dalle"]["prompt"]
-        file_id = element["asset_pointer"].split("file-service://", 1)[1]
+        try:
+            prompt = element["metadata"]["dalle"]["prompt"]
+            file_id = element["asset_pointer"].split("file-service://", 1)[1]
+        except Exception as e:
+            raise RuntimeError(f"No Image: {e.__class__.__name__}: {e}")
         try:
             async with session.get(f"{cls.url}/backend-api/files/{file_id}/download", headers=headers) as response:
                 cls._update_request_args(session)
@@ -380,9 +383,8 @@ async def create_async_generator(
                 image_request = await cls.upload_image(session, cls._headers, image, image_name) if image else None
             except Exception as e:
                 image_request = None
-                if debug.logging:
-                    print("OpenaiChat: Upload image failed")
-                    print(f"{e.__class__.__name__}: {e}")
+                debug.log("OpenaiChat: Upload image failed")
+                debug.log(f"{e.__class__.__name__}: {e}")
             model = cls.get_model(model)
             if conversation is None:
                 conversation = Conversation(conversation_id, str(uuid.uuid4()) if parent_id is None else parent_id)
@@ -419,11 +421,10 @@ async def create_async_generator(
                         user_agent=cls._headers["user-agent"],
                         proof_token=RequestConfig.proof_token
                     )
-                if debug.logging:
-                    print(
-                        'Arkose:', False if not need_arkose else RequestConfig.arkose_token[:12]+"...",
-                        'Proofofwork:', False if proofofwork is None else proofofwork[:12]+"...",
-                    )
+                [debug.log(text) for text in (
+                    f"Arkose: {'False' if not need_arkose else RequestConfig.arkose_token[:12]+'...'}",
+                    f"Proofofwork: {'False' if proofofwork is None else proofofwork[:12]+'...'}",
+                )]
                 ws = None
                 if need_arkose:
                     async with session.post(f"{cls.url}/backend-api/register-websocket", headers=cls._headers) as response:
@@ -444,6 +445,7 @@ async def create_async_generator(
                 }
                 if conversation.conversation_id is not None:
                     data["conversation_id"] = conversation.conversation_id
+                    debug.log(f"OpenaiChat: Use conversation: {conversation.conversation_id}")
                 if action != "continue":
                     messages = messages if conversation_id is None else [messages[-1]]
                     data["messages"] = cls.create_messages(messages, image_request)
@@ -468,8 +470,7 @@ async def create_async_generator(
                     cls._update_request_args(session)
                     if response.status == 403 and max_retries > 0:
                         max_retries -= 1
-                        if debug.logging:
-                            print(f"Retry: Error {response.status}: {await response.text()}")
+                        debug.log(f"Retry: Error {response.status}: {await response.text()}")
                         await asyncio.sleep(5)
                         continue
                     await raise_for_status(response)
@@ -553,20 +554,27 @@ async def iter_messages_line(cls, session: StreamSession, line: bytes, fields: C
             elif isinstance(v, dict):
                 if fields.conversation_id is None:
                     fields.conversation_id = v.get("conversation_id")
-                fields.message_id = v.get("message", {}).get("id")
-                c = v.get("message", {}).get("content", {})
-                if c.get("content_type") == "multimodal_text":
-                    generated_images = []
-                    for element in c.get("parts"):
-                        if element.get("content_type") == "image_asset_pointer":
-                            generated_images.append(
-                                cls.get_generated_image(session, cls._headers, element)
-                            )
-                        elif element.get("content_type") == "text":
-                            for part in element.get("parts", []):
-                                yield part
-                    for image_response in await asyncio.gather(*generated_images):
-                        yield image_response
+                    debug.log(f"OpenaiChat: New conversation: {fields.conversation_id}")
+                m = v.get("message", {})
+                if m.get("author", {}).get("role") == "assistant":
+                    fields.message_id = v.get("message", {}).get("id")
+                    c = m.get("content", {})
+                    if c.get("content_type") == "multimodal_text":
+                        generated_images = []
+                        for element in c.get("parts"):
+                            if isinstance(element, str):
+                                debug.log(f"No image or text: {line}")
+                            elif element.get("content_type") == "image_asset_pointer":
+                                generated_images.append(
+                                    cls.get_generated_image(session, cls._headers, element)
+                                )
+                            elif element.get("content_type") == "text":
+                                for part in element.get("parts", []):
+                                    yield part
+                        for image_response in await asyncio.gather(*generated_images):
+                            yield image_response
+            else:
+                debug.log(f"OpenaiChat: {line}")
             return
         if "error" in line and line.get("error"):
             raise RuntimeError(line.get("error"))
@@ -579,8 +587,7 @@ async def nodriver_auth(cls, proxy: str = None):
             user_data_dir = user_config_dir("g4f-nodriver")
         else:
             user_data_dir = None
-        if debug.logging:
-            print(f"Open nodriver with user_dir: {user_data_dir}")
+        debug.log(f"Open nodriver with user_dir: {user_data_dir}")
         browser = await nodriver.start(
             user_data_dir=user_data_dir,
             browser_args=None if proxy is None else [f"--proxy-server={proxy}"],

g4f/Provider/openai/har_file.py

@@ -71,8 +71,7 @@ def readHAR():
                     if "openai-sentinel-turnstile-token" in v_headers:
                         RequestConfig.turnstile_token = v_headers["openai-sentinel-turnstile-token"]
                 except Exception as e:
-                    if debug.logging:
-                        print(f"Read proof token: {e}")
+                    debug.log(f"Read proof token: {e}")
                 if arkose_url == v['request']['url']:
                     RequestConfig.arkose_request = parseHAREntry(v)
                 elif v['request']['url'] == start_url or v['request']['url'].startswith(conversation_url):
@@ -150,7 +149,7 @@ def getN() -> str:
     return base64.b64encode(timestamp.encode()).decode()
 
 async def get_request_config(proxy: str) -> RequestConfig:
-    if RequestConfig.arkose_request is None or RequestConfig.access_token is None:
+    if RequestConfig.access_token is None:
         readHAR()
     if RequestConfig.arkose_request is not None:
         RequestConfig.arkose_token = await sendRequest(genArkReq(RequestConfig.arkose_request), proxy)

g4f/client/service.py

@@ -83,11 +83,10 @@ def get_model_and_provider(model    : Union[Model, str],
     if not ignore_stream and not provider.supports_stream and stream:
         raise StreamNotSupportedError(f'{provider.__name__} does not support "stream" argument')
 
-    if debug.logging:
-        if model:
-            print(f'Using {provider.__name__} provider and {model} model')
-        else:
-            print(f'Using {provider.__name__} provider')
+    if model:
+        debug.log(f'Using {provider.__name__} provider and {model} model')
+    else:
+        debug.log(f'Using {provider.__name__} provider')
 
     debug.last_provider = provider
     debug.last_model = model

g4f/debug.py

@@ -4,4 +4,9 @@
 version_check: bool = True
 last_provider: ProviderType = None
 last_model: str = None
-version: str = None
+version: str = None
+log_handler: callable = print
+
+def log(text):
+    if logging:
+        log_handler(text)

g4f/gui/client/index.html

@@ -170,6 +170,10 @@ <h3>Settings</h3>
                     <i class="fa-solid fa-download"></i>
                     <a href="" onclick="return false;">Export Conversations</a>
                 </button>
+                <button id="showLog">
+                    <i class="fa-solid fa-terminal"></i>
+                    <a href="" onclick="return false;">Show log</a>
+                </button>
             </div>
         </div>
         <div class="conversation">
@@ -257,6 +261,7 @@ <h3>Settings</h3>
                 </div>
             </div>
         </div>
+        <div class="log hidden"></div>
     </div>
     <div class="mobile-sidebar">
         <i class="fa-solid fa-bars"></i>

g4f/gui/client/static/css/style.css

@@ -1051,13 +1051,22 @@ a:-webkit-any-link {
     padding: var(--inner-gap) var(--inner-gap) var(--inner-gap) 0;
 }
 
-.settings, .images {
+.settings, .log {
     width: 100%;
     display: flex;
     flex-direction: column;
     overflow: auto;
 }
 
+.log {
+    white-space: pre-wrap;
+    font-family: Consolas, "Andale Mono WT", "Andale Mono", "Lucida Console", "Lucida Sans Typewriter", "DejaVu Sans Mono", "Bitstream Vera Sans Mono", "Liberation Mono", "Nimbus Mono L", Monaco, "Courier New", Courier, monospace;
+}
+
+.log.hidden {
+    display: none;
+}
+
 .settings .paper {
     flex-direction: column;
     min-width: 400px;

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

@@ -19,13 +19,15 @@ const systemPrompt      = document.getElementById("systemPrompt");
 const settings          = document.querySelector(".settings");
 const chat              = document.querySelector(".conversation");
 const album             = document.querySelector(".images");
+const log_storage       = document.querySelector(".log");
 
 const optionElements = document.querySelectorAll(".settings input, .settings textarea, #model, #model2, #provider")
 
 let provider_storage = {};
 let message_storage = {};
 let controller_storage = {};
-let content_storage = {}
+let content_storage = {};
+let error_storage = {};
 
 messageInput.addEventListener("blur", () => {
     window.scrollTo(0, 0);
@@ -256,14 +258,14 @@ const delete_conversations = async () => {
 const handle_ask = async () => {
     messageInput.style.height = "82px";
     messageInput.focus();
-    window.scrollTo(0, 0);
+    await scroll_to_bottom();
 
     let message = messageInput.value;
     if (message.length <= 0) {
         return;
     }
     messageInput.value = "";
-    count_input()
+    await count_input()
     await add_conversation(window.conversation_id, message);
 
     if ("text" in fileInput.dataset) {
@@ -396,9 +398,12 @@ async function add_message_chunk(message, message_index) {
     } else if (message.type == "message") {
         console.error(message.message)
     } else if (message.type == "error") {
-        window.error = message.error
+        error_storage[message_index] = message.error
         console.error(message.error);
         content_map.inner.innerHTML += `<p><strong>An error occured:</strong> ${message.error}</p>`;
+        let p = document.createElement("p");
+        p.innerText = message.error;
+        log_storage.appendChild(p);
     } else if (message.type == "preview") {
         content_map.inner.innerHTML = markdown_render(message.preview);
     } else if (message.type == "content") {
@@ -418,6 +423,10 @@ async function add_message_chunk(message, message_index) {
         content_map.inner.innerHTML = html;
         content_map.count.innerText = count_words_and_tokens(message_storage[message_index], provider_storage[message_index]?.model);
         highlight(content_map.inner);
+    } else if (message.type == "log") {
+        let p = document.createElement("p");
+        p.innerText = message.log;
+        log_storage.appendChild(p);
     }
     window.scrollTo(0, 0);
     if (message_box.scrollTop >= message_box.scrollHeight - message_box.clientHeight - 100) {
@@ -469,7 +478,6 @@ const ask_gpt = async (message_index = -1, message_id) => {
     `;
 
     controller_storage[message_index] = new AbortController();
-    let error = false;
 
     let content_el = document.getElementById(`gpt_${message_id}`)
     let content_map = content_storage[message_index] = {
@@ -478,8 +486,7 @@ const ask_gpt = async (message_index = -1, message_id) => {
         count: content_el.querySelector('.count'),
     }
 
-    message_box.scrollTop = message_box.scrollHeight;
-    window.scrollTo(0, 0);
+    await scroll_to_bottom();
     try {
         const input = imageInput && imageInput.files.length > 0 ? imageInput : cameraInput;
         const file = input && input.files.length > 0 ? input.files[0] : null;
@@ -501,7 +508,7 @@ const ask_gpt = async (message_index = -1, message_id) => {
             auto_continue: auto_continue,
             api_key: api_key
         }, file, message_index);
-        if (!error) {
+        if (!error_storage[message_index]) {
             html = markdown_render(message_storage[message_index]);
             content_map.inner.innerHTML = html;
             highlight(content_map.inner);
@@ -513,26 +520,31 @@ const ask_gpt = async (message_index = -1, message_id) => {
     } catch (e) {
         console.error(e);
         if (e.name != "AbortError") {
-            error = true;
+            error_storage[message_index] = true;
             content_map.inner.innerHTML += `<p><strong>An error occured:</strong> ${e}</p>`;
         }
     }
     delete controller_storage[message_index];
-    if (!error && message_storage[message_index]) {
+    if (!error_storage[message_index] && message_storage[message_index]) {
         const message_provider = message_index in provider_storage ? provider_storage[message_index] : null;
         await add_message(window.conversation_id, "assistant", message_storage[message_index], message_provider);
         await safe_load_conversation(window.conversation_id);
     } else {
         let cursorDiv = message_box.querySelector(".cursor");
         if (cursorDiv) cursorDiv.parentNode.removeChild(cursorDiv);
     }
-    window.scrollTo(0, 0);
-    message_box.scrollTop = message_box.scrollHeight;
+    await scroll_to_bottom();
     await remove_cancel_button();
     await register_message_buttons();
     await load_conversations();
+    regenerate.classList.remove("regenerate-hidden");
 };
 
+async function scroll_to_bottom() {
+    window.scrollTo(0, 0);
+    message_box.scrollTop = message_box.scrollHeight;
+}
+
 const clear_conversations = async () => {
     const elements = box_conversations.childNodes;
     let index = elements.length;
@@ -631,6 +643,7 @@ const set_conversation = async (conversation_id) => {
     await load_conversation(conversation_id);
     load_conversations();
     hide_sidebar();
+    log_storage.classList.add("hidden");
 };
 
 const new_conversation = async () => {
@@ -643,6 +656,7 @@ const new_conversation = async () => {
     }
     load_conversations();
     hide_sidebar();
+    log_storage.classList.add("hidden");
     say_hello();
 };
 
@@ -941,6 +955,7 @@ function open_settings() {
         settings.classList.add("hidden");
         chat.classList.remove("hidden");
     }
+    log_storage.classList.add("hidden");
 }
 
 function open_album() {
@@ -1472,3 +1487,9 @@ if (SpeechRecognition) {
         }
     });
 }
+
+document.getElementById("showLog").addEventListener("click", ()=> {
+    log_storage.classList.remove("hidden");
+    settings.classList.add("hidden");
+    log_storage.scrollTop = log_storage.scrollHeight;
+});