🐛 fix: fix the LLM logic

app/services/llm.py

@@ -3,6 +3,7 @@ import logging
 import re
 from typing import List
 
+import g4f
 from loguru import logger
 from openai import AzureOpenAI, OpenAI
 from openai.types.chat import ChatCompletion
@@ -13,243 +14,244 @@ _max_retries = 5
 
 
 def _generate_response(prompt: str) -> str:
-    content = ""
+    try:
-    llm_provider = config.app.get("llm_provider", "openai")
+        content = ""
-    logger.info(f"llm provider: {llm_provider}")
+        llm_provider = config.app.get("llm_provider", "openai")
-    if llm_provider == "g4f":
+        logger.info(f"llm provider: {llm_provider}")
-        model_name = config.app.get("g4f_model_name", "")
+        if llm_provider == "g4f":
-        if not model_name:
+            model_name = config.app.get("g4f_model_name", "")
-            model_name = "gpt-3.5-turbo-16k-0613"
+            if not model_name:
-        import g4f
+                model_name = "gpt-3.5-turbo-16k-0613"
-
+            content = g4f.ChatCompletion.create(
-        content = g4f.ChatCompletion.create(
+                model=model_name,
-            model=model_name,
+                messages=[{"role": "user", "content": prompt}],
-            messages=[{"role": "user", "content": prompt}],
+            )
-        )
-    else:
-        api_version = ""  # for azure
-        if llm_provider == "moonshot":
-            api_key = config.app.get("moonshot_api_key")
-            model_name = config.app.get("moonshot_model_name")
-            base_url = "https://api.moonshot.cn/v1"
-        elif llm_provider == "ollama":
-            # api_key = config.app.get("openai_api_key")
-            api_key = "ollama"  # any string works but you are required to have one
-            model_name = config.app.get("ollama_model_name")
-            base_url = config.app.get("ollama_base_url", "")
-            if not base_url:
-                base_url = "http://localhost:11434/v1"
-        elif llm_provider == "openai":
-            api_key = config.app.get("openai_api_key")
-            model_name = config.app.get("openai_model_name")
-            base_url = config.app.get("openai_base_url", "")
-            if not base_url:
-                base_url = "https://api.openai.com/v1"
-        elif llm_provider == "oneapi":
-            api_key = config.app.get("oneapi_api_key")
-            model_name = config.app.get("oneapi_model_name")
-            base_url = config.app.get("oneapi_base_url", "")
-        elif llm_provider == "azure":
-            api_key = config.app.get("azure_api_key")
-            model_name = config.app.get("azure_model_name")
-            base_url = config.app.get("azure_base_url", "")
-            api_version = config.app.get("azure_api_version", "2024-02-15-preview")
-        elif llm_provider == "gemini":
-            api_key = config.app.get("gemini_api_key")
-            model_name = config.app.get("gemini_model_name")
-            base_url = "***"
-        elif llm_provider == "qwen":
-            api_key = config.app.get("qwen_api_key")
-            model_name = config.app.get("qwen_model_name")
-            base_url = "***"
-        elif llm_provider == "cloudflare":
-            api_key = config.app.get("cloudflare_api_key")
-            model_name = config.app.get("cloudflare_model_name")
-            account_id = config.app.get("cloudflare_account_id")
-            base_url = "***"
-        elif llm_provider == "deepseek":
-            api_key = config.app.get("deepseek_api_key")
-            model_name = config.app.get("deepseek_model_name")
-            base_url = config.app.get("deepseek_base_url")
-            if not base_url:
-                base_url = "https://api.deepseek.com"
-        elif llm_provider == "ernie":
-            api_key = config.app.get("ernie_api_key")
-            secret_key = config.app.get("ernie_secret_key")
-            base_url = config.app.get("ernie_base_url")
-            model_name = "***"
-            if not secret_key:
-                raise ValueError(
-                    f"{llm_provider}: secret_key is not set, please set it in the config.toml file."
-                )
         else:
-            raise ValueError(
+            api_version = ""  # for azure
-                "llm_provider is not set, please set it in the config.toml file."
+            if llm_provider == "moonshot":
-            )
+                api_key = config.app.get("moonshot_api_key")
+                model_name = config.app.get("moonshot_model_name")
+                base_url = "https://api.moonshot.cn/v1"
+            elif llm_provider == "ollama":
+                # api_key = config.app.get("openai_api_key")
+                api_key = "ollama"  # any string works but you are required to have one
+                model_name = config.app.get("ollama_model_name")
+                base_url = config.app.get("ollama_base_url", "")
+                if not base_url:
+                    base_url = "http://localhost:11434/v1"
+            elif llm_provider == "openai":
+                api_key = config.app.get("openai_api_key")
+                model_name = config.app.get("openai_model_name")
+                base_url = config.app.get("openai_base_url", "")
+                if not base_url:
+                    base_url = "https://api.openai.com/v1"
+            elif llm_provider == "oneapi":
+                api_key = config.app.get("oneapi_api_key")
+                model_name = config.app.get("oneapi_model_name")
+                base_url = config.app.get("oneapi_base_url", "")
+            elif llm_provider == "azure":
+                api_key = config.app.get("azure_api_key")
+                model_name = config.app.get("azure_model_name")
+                base_url = config.app.get("azure_base_url", "")
+                api_version = config.app.get("azure_api_version", "2024-02-15-preview")
+            elif llm_provider == "gemini":
+                api_key = config.app.get("gemini_api_key")
+                model_name = config.app.get("gemini_model_name")
+                base_url = "***"
+            elif llm_provider == "qwen":
+                api_key = config.app.get("qwen_api_key")
+                model_name = config.app.get("qwen_model_name")
+                base_url = "***"
+            elif llm_provider == "cloudflare":
+                api_key = config.app.get("cloudflare_api_key")
+                model_name = config.app.get("cloudflare_model_name")
+                account_id = config.app.get("cloudflare_account_id")
+                base_url = "***"
+            elif llm_provider == "deepseek":
+                api_key = config.app.get("deepseek_api_key")
+                model_name = config.app.get("deepseek_model_name")
+                base_url = config.app.get("deepseek_base_url")
+                if not base_url:
+                    base_url = "https://api.deepseek.com"
+            elif llm_provider == "ernie":
+                api_key = config.app.get("ernie_api_key")
+                secret_key = config.app.get("ernie_secret_key")
+                base_url = config.app.get("ernie_base_url")
+                model_name = "***"
+                if not secret_key:
+                    raise ValueError(
+                        f"{llm_provider}: secret_key is not set, please set it in the config.toml file."
+                    )
+            else:
+                raise ValueError(
+                    "llm_provider is not set, please set it in the config.toml file."
+                )
 
-        if not api_key:
+            if not api_key:
-            raise ValueError(
+                raise ValueError(
-                f"{llm_provider}: api_key is not set, please set it in the config.toml file."
+                    f"{llm_provider}: api_key is not set, please set it in the config.toml file."
-            )
+                )
-        if not model_name:
+            if not model_name:
-            raise ValueError(
+                raise ValueError(
-                f"{llm_provider}: model_name is not set, please set it in the config.toml file."
+                    f"{llm_provider}: model_name is not set, please set it in the config.toml file."
-            )
+                )
-        if not base_url:
+            if not base_url:
-            raise ValueError(
+                raise ValueError(
-                f"{llm_provider}: base_url is not set, please set it in the config.toml file."
+                    f"{llm_provider}: base_url is not set, please set it in the config.toml file."
-            )
+                )
 
-        if llm_provider == "qwen":
+            if llm_provider == "qwen":
-            import dashscope
+                import dashscope
-            from dashscope.api_entities.dashscope_response import GenerationResponse
+                from dashscope.api_entities.dashscope_response import GenerationResponse
 
-            dashscope.api_key = api_key
+                dashscope.api_key = api_key
-            response = dashscope.Generation.call(
+                response = dashscope.Generation.call(
+                    model=model_name, messages=[{"role": "user", "content": prompt}]
+                )
+                if response:
+                    if isinstance(response, GenerationResponse):
+                        status_code = response.status_code
+                        if status_code != 200:
+                            raise Exception(
+                                f'[{llm_provider}] returned an error response: "{response}"'
+                            )
+
+                        content = response["output"]["text"]
+                        return content.replace("\n", "")
+                    else:
+                        raise Exception(
+                            f'[{llm_provider}] returned an invalid response: "{response}"'
+                        )
+                else:
+                    raise Exception(f"[{llm_provider}] returned an empty response")
+
+            if llm_provider == "gemini":
+                import google.generativeai as genai
+
+                genai.configure(api_key=api_key, transport="rest")
+
+                generation_config = {
+                    "temperature": 0.5,
+                    "top_p": 1,
+                    "top_k": 1,
+                    "max_output_tokens": 2048,
+                }
+
+                safety_settings = [
+                    {
+                        "category": "HARM_CATEGORY_HARASSMENT",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                    {
+                        "category": "HARM_CATEGORY_HATE_SPEECH",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                    {
+                        "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                    {
+                        "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+                        "threshold": "BLOCK_ONLY_HIGH",
+                    },
+                ]
+
+                model = genai.GenerativeModel(
+                    model_name=model_name,
+                    generation_config=generation_config,
+                    safety_settings=safety_settings,
+                )
+
+                try:
+                    response = model.generate_content(prompt)
+                    candidates = response.candidates
+                    generated_text = candidates[0].content.parts[0].text
+                except (AttributeError, IndexError) as e:
+                    print("Gemini Error:", e)
+
+                return generated_text
+
+            if llm_provider == "cloudflare":
+                import requests
+
+                response = requests.post(
+                    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model_name}",
+                    headers={"Authorization": f"Bearer {api_key}"},
+                    json={
+                        "messages": [
+                            {"role": "system", "content": "You are a friendly assistant"},
+                            {"role": "user", "content": prompt},
+                        ]
+                    },
+                )
+                result = response.json()
+                logger.info(result)
+                return result["result"]["response"]
+
+            if llm_provider == "ernie":
+                import requests
+
+                params = {
+                    "grant_type": "client_credentials",
+                    "client_id": api_key,
+                    "client_secret": secret_key,
+                }
+                access_token = (
+                    requests.post("https://aip.baidubce.com/oauth/2.0/token", params=params)
+                    .json()
+                    .get("access_token")
+                )
+                url = f"{base_url}?access_token={access_token}"
+
+                payload = json.dumps(
+                    {
+                        "messages": [{"role": "user", "content": prompt}],
+                        "temperature": 0.5,
+                        "top_p": 0.8,
+                        "penalty_score": 1,
+                        "disable_search": False,
+                        "enable_citation": False,
+                        "response_format": "text",
+                    }
+                )
+                headers = {"Content-Type": "application/json"}
+
+                response = requests.request(
+                    "POST", url, headers=headers, data=payload
+                ).json()
+                return response.get("result")
+
+            if llm_provider == "azure":
+                client = AzureOpenAI(
+                    api_key=api_key,
+                    api_version=api_version,
+                    azure_endpoint=base_url,
+                )
+            else:
+                client = OpenAI(
+                    api_key=api_key,
+                    base_url=base_url,
+                )
+
+            response = client.chat.completions.create(
                 model=model_name, messages=[{"role": "user", "content": prompt}]
             )
             if response:
-                if isinstance(response, GenerationResponse):
+                if isinstance(response, ChatCompletion):
-                    status_code = response.status_code
+                    content = response.choices[0].message.content
-                    if status_code != 200:
-                        raise Exception(
-                            f'[{llm_provider}] returned an error response: "{response}"'
-                        )
-
-                    content = response["output"]["text"]
-                    return content.replace("\n", "")
                 else:
                     raise Exception(
-                        f'[{llm_provider}] returned an invalid response: "{response}"'
+                        f'[{llm_provider}] returned an invalid response: "{response}", please check your network '
+                        f"connection and try again."
                     )
-            else:
-                raise Exception(f"[{llm_provider}] returned an empty response")
-
-        if llm_provider == "gemini":
-            import google.generativeai as genai
-
-            genai.configure(api_key=api_key, transport="rest")
-
-            generation_config = {
-                "temperature": 0.5,
-                "top_p": 1,
-                "top_k": 1,
-                "max_output_tokens": 2048,
-            }
-
-            safety_settings = [
-                {
-                    "category": "HARM_CATEGORY_HARASSMENT",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-                {
-                    "category": "HARM_CATEGORY_HATE_SPEECH",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-                {
-                    "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-                {
-                    "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
-                    "threshold": "BLOCK_ONLY_HIGH",
-                },
-            ]
-
-            model = genai.GenerativeModel(
-                model_name=model_name,
-                generation_config=generation_config,
-                safety_settings=safety_settings,
-            )
-
-            try:
-                response = model.generate_content(prompt)
-                candidates = response.candidates
-                generated_text = candidates[0].content.parts[0].text
-            except (AttributeError, IndexError) as e:
-                print("Gemini Error:", e)
-
-            return generated_text
-
-        if llm_provider == "cloudflare":
-            import requests
-
-            response = requests.post(
-                f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model_name}",
-                headers={"Authorization": f"Bearer {api_key}"},
-                json={
-                    "messages": [
-                        {"role": "system", "content": "You are a friendly assistant"},
-                        {"role": "user", "content": prompt},
-                    ]
-                },
-            )
-            result = response.json()
-            logger.info(result)
-            return result["result"]["response"]
-
-        if llm_provider == "ernie":
-            import requests
-
-            params = {
-                "grant_type": "client_credentials",
-                "client_id": api_key,
-                "client_secret": secret_key,
-            }
-            access_token = (
-                requests.post("https://aip.baidubce.com/oauth/2.0/token", params=params)
-                .json()
-                .get("access_token")
-            )
-            url = f"{base_url}?access_token={access_token}"
-
-            payload = json.dumps(
-                {
-                    "messages": [{"role": "user", "content": prompt}],
-                    "temperature": 0.5,
-                    "top_p": 0.8,
-                    "penalty_score": 1,
-                    "disable_search": False,
-                    "enable_citation": False,
-                    "response_format": "text",
-                }
-            )
-            headers = {"Content-Type": "application/json"}
-
-            response = requests.request(
-                "POST", url, headers=headers, data=payload
-            ).json()
-            return response.get("result")
-
-        if llm_provider == "azure":
-            client = AzureOpenAI(
-                api_key=api_key,
-                api_version=api_version,
-                azure_endpoint=base_url,
-            )
-        else:
-            client = OpenAI(
-                api_key=api_key,
-                base_url=base_url,
-            )
-
-        response = client.chat.completions.create(
-            model=model_name, messages=[{"role": "user", "content": prompt}]
-        )
-        if response:
-            if isinstance(response, ChatCompletion):
-                content = response.choices[0].message.content
             else:
                 raise Exception(
-                    f'[{llm_provider}] returned an invalid response: "{response}", please check your network '
+                    f"[{llm_provider}] returned an empty response, please check your network connection and try again."
-                    f"connection and try again."
                 )
-        else:
-            raise Exception(
-                f"[{llm_provider}] returned an empty response, please check your network connection and try again."
-            )
 
-    return content.replace("\n", "")
+        return content.replace("\n", "")
+    except Exception as e:
+        return f"Error: {str(e)}"
 
 
 def generate_script(
@@ -319,8 +321,10 @@ Generate a script for a video, depending on the subject of the video.
 
         if i < _max_retries:
             logger.warning(f"failed to generate video script, trying again... {i + 1}")
-
+    if "Error: " in final_script:
-    logger.success(f"completed: \n{final_script}")
+        logger.error(f"failed to generate video script: {final_script}")
+    else:
+        logger.success(f"completed: \n{final_script}")
     return final_script.strip()
 
 
@@ -358,6 +362,9 @@ Please note that you must use English for generating video search terms; Chinese
     for i in range(_max_retries):
         try:
             response = _generate_response(prompt)
+            if "Error: " in response:
+                logger.error(f"failed to generate video script: {response}")
+                return response
             search_terms = json.loads(response)
             if not isinstance(search_terms, list) or not all(
                 isinstance(term, str) for term in search_terms

app/services/task.py

@@ -214,7 +214,7 @@ def start(task_id, params: VideoParams, stop_at: str = "video"):
 
     # 1. Generate script
     video_script = generate_script(task_id, params)
-    if not video_script:
+    if not video_script or "Error: " in video_script:
         sm.state.update_task(task_id, state=const.TASK_STATE_FAILED)
         return
 

webui/Main.py

@@ -449,8 +449,12 @@ with left_panel:
         selected_index = st.selectbox(
             tr("Script Language"),
             index=0,
-            options=range(len(video_languages)),  # 使用索引作为内部选项值
+            options=range(
-            format_func=lambda x: video_languages[x][0],  # 显示给用户的是标签
+                len(video_languages)
+            ),  # Use the index as the internal option value
+            format_func=lambda x: video_languages[x][
+                0
+            ],  # The label is displayed to the user
         )
         params.video_language = video_languages[selected_index][1]
 
@@ -462,9 +466,13 @@ with left_panel:
                     video_subject=params.video_subject, language=params.video_language
                 )
                 terms = llm.generate_terms(params.video_subject, script)
-                st.session_state["video_script"] = script
+                if "Error: " in script:
-                st.session_state["video_terms"] = ", ".join(terms)
+                    st.error(tr(script))
-
+                elif "Error: " in terms:
+                    st.error(tr(terms))
+                else:
+                    st.session_state["video_script"] = script
+                    st.session_state["video_terms"] = ", ".join(terms)
         params.video_script = st.text_area(
             tr("Video Script"), value=st.session_state["video_script"], height=280
         )
@@ -475,7 +483,10 @@ with left_panel:
 
             with st.spinner(tr("Generating Video Keywords")):
                 terms = llm.generate_terms(params.video_subject, params.video_script)
-                st.session_state["video_terms"] = ", ".join(terms)
+                if "Error: " in terms:
+                    st.error(tr(terms))
+                else:
+                    st.session_state["video_terms"] = ", ".join(terms)
 
         params.video_terms = st.text_area(
             tr("Video Keywords"), value=st.session_state["video_terms"]
@@ -522,8 +533,12 @@ with middle_panel:
         selected_index = st.selectbox(
             tr("Video Concat Mode"),
             index=1,
-            options=range(len(video_concat_modes)),  # 使用索引作为内部选项值
+            options=range(
-            format_func=lambda x: video_concat_modes[x][0],  # 显示给用户的是标签
+                len(video_concat_modes)
+            ),  # Use the index as the internal option value
+            format_func=lambda x: video_concat_modes[x][
+                0
+            ],  # The label is displayed to the user
         )
         params.video_concat_mode = VideoConcatMode(
             video_concat_modes[selected_index][1]
@@ -535,8 +550,12 @@ with middle_panel:
         ]
         selected_index = st.selectbox(
             tr("Video Ratio"),
-            options=range(len(video_aspect_ratios)),  # 使用索引作为内部选项值
+            options=range(
-            format_func=lambda x: video_aspect_ratios[x][0],  # 显示给用户的是标签
+                len(video_aspect_ratios)
+            ),  # Use the index as the internal option value
+            format_func=lambda x: video_aspect_ratios[x][
+                0
+            ],  # The label is displayed to the user
         )
         params.video_aspect = VideoAspect(video_aspect_ratios[selected_index][1])
 
@@ -648,13 +667,17 @@ with middle_panel:
         selected_index = st.selectbox(
             tr("Background Music"),
             index=1,
-            options=range(len(bgm_options)),  # 使用索引作为内部选项值
+            options=range(
-            format_func=lambda x: bgm_options[x][0],  # 显示给用户的是标签
+                len(bgm_options)
+            ),  # Use the index as the internal option value
+            format_func=lambda x: bgm_options[x][
+                0
+            ],  # The label is displayed to the user
         )
-        # 获取选择的背景音乐类型
+        # Get the selected background music type
         params.bgm_type = bgm_options[selected_index][1]
 
-        # 根据选择显示或隐藏组件
+        # Show or hide components based on the selection
         if params.bgm_type == "custom":
             custom_bgm_file = st.text_input(tr("Custom Background Music File"))
             if custom_bgm_file and os.path.exists(custom_bgm_file):
@@ -733,15 +756,6 @@ if start_button:
         scroll_to_bottom()
         st.stop()
 
-    if (
-        llm_provider != "g4f"
-        and llm_provider != "ollama"
-        and not config.app.get(f"{llm_provider}_api_key", "")
-    ):
-        st.error(tr("Please Enter the LLM API Key"))
-        scroll_to_bottom()
-        st.stop()
-
     if params.video_source not in ["pexels", "pixabay", "local"]:
         st.error(tr("Please Select a Valid Video Source"))
         scroll_to_bottom()