chatchat inti初始化报错

[kenvinsuxun]

模型配置项

默认选用的 LLM 名称

DEFAULT_LLM_MODEL: deepseek-r1:7b

默认选用的 Embedding 名称

DEFAULT_EMBEDDING_MODEL: quentinz/bge-large-zh-v1.5:latest

AgentLM模型的名称 (可以不指定，指定之后就锁定进入Agent之后的Chain的模型，不指定就是 DEFAULT_LLM_MODEL)

Agent_MODEL: ''

默认历史对话轮数

HISTORY_LEN: 10

大模型最长支持的长度，如果不填写，则使用模型默认的最大长度，如果填写，则为用户设定的最大长度

MAX_TOKENS:

LLM通用对话参数

TEMPERATURE: 0.7

支持的Agent模型

SUPPORT_AGENT_MODELS:

• chatglm3-6b
• glm-4
• openai-api
• Qwen-2
• qwen2-instruct
• gpt-3.5-turbo
• gpt-4o

LLM模型配置，包括了不同模态初始化参数。

model 如果留空则自动使用 DEFAULT_LLM_MODEL

LLM_MODEL_CONFIG:
preprocess_model:
model: ''
temperature: 0.05
max_tokens: 4096
history_len: 10
prompt_name: default
callbacks: false
llm_model:
model: ''
temperature: 0.9
max_tokens: 4096
history_len: 10
prompt_name: default
callbacks: true
action_model:
model: ''
temperature: 0.01
max_tokens: 4096
history_len: 10
prompt_name: ChatGLM3
callbacks: true
postprocess_model:
model: ''
temperature: 0.01
max_tokens: 4096
history_len: 10
prompt_name: default
callbacks: true
image_model:
model: sd-turbo
size: 256*256

# 模型加载平台配置

# 平台名称

platform_name: ollama

# 平台类型

# 可选值：['xinference', 'ollama', 'oneapi', 'fastchat', 'openai', 'custom openai']

platform_type: ollama

# openai api url

api_base_url: http://127.0.0.1:9997/v1

# api key if available

api_key: EMPTY

# API 代理

api_proxy: ''

# 该平台单模型最大并发数

api_concurrencies: 5

# 是否自动获取平台可用模型列表。设为 True 时下方不同模型类型可自动检测

auto_detect_model: false

# 该平台支持的大语言模型列表，auto_detect_model 设为 True 时自动检测

llm_models: []

# 该平台支持的嵌入模型列表，auto_detect_model 设为 True 时自动检测

embed_models: []

# 该平台支持的图像生成模型列表，auto_detect_model 设为 True 时自动检测

text2image_models: []

# 该平台支持的多模态模型列表，auto_detect_model 设为 True 时自动检测

image2text_models: []

# 该平台支持的重排模型列表，auto_detect_model 设为 True 时自动检测

rerank_models: []

# 该平台支持的 STT 模型列表，auto_detect_model 设为 True 时自动检测

speech2text_models: []

# 该平台支持的 TTS 模型列表，auto_detect_model 设为 True 时自动检测

text2speech_models: []

MODEL_PLATFORMS:

• platform_name: ollama
  platform_type: ollama
  api_base_url: http://127.0.0.1:11434/v1
  api_key: EMPTY
  api_proxy: ''
  api_concurrencies: 5
  auto_detect_model: false
  llm_models:
  • qwen:7b
  • qwen2:7b
  • deepseek-r1:7b
  • deepseek-r1:1.5b
    embed_models:
  • quentinz/bge-large-zh-v1.5:latest
    text2image_models: []
    image2text_models: []
    rerank_models: []
    speech2text_models: []
    text2speech_models: []

运行 chatchat init之后 报错
chatchat_data\data\knowledge_base\samples\content\test_files\test.txt'}
文档切分示例：page_content='See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/372669736\nCreating Large Language Model Applications Utilizing LangChain: A Primer on\nDeveloping LLM App
s Fast\nArticle\xa0\xa0in\xa0\xa0International Conference on Applied Engineering and Natural Sciences · July 2023\nDOI: 10.59287/icaens.1127\nCITATIONS\n0\nREADS\n47\n2 authors:\nSome of the authors of this publication are also working on these
related projects:\nTHALIA: Test Harness for the Assessment of Legacy Information Integration Approaches View project\nAnalysis of Feroresonance with Signal Processing Technique View project\nOguzhan Topsakal\nFlorida Polytechnic University\n29 PUBLICATIONS\xa0\xa0\xa0155 CITATIONS\nSEE PROFILE' metadata={'source': 'D:\chatchat_data\data\knowledge_base\samples\content\test_files\langchain.pdf'}
2025-04-01 06:35:54.652 | ERROR | chatchat.init_database:worker:61 - Error raised by inference API HTTP code: 500, {"error":{}}
请问哪里的api配置错误了

[dosubot]

@kenvinsuxun 你好！我是Dosu，我是一个能够帮助你解决 bug、回答问题，并成为贡献者的机器人。我会在等待人类维护者的过程中协助你。

I found a similar discussion regarding issues during the initialization of Langchain-Chatchat, specifically related to model loading problems. You can check it out here ^[1]. However, it seems that no solution was found in the comments.

Regarding your issue, the error message indicates an HTTP 500 error, which is a server-side error. This could be due to several reasons, such as incorrect API configuration or server issues. Here are a few things you might want to check:

1. API Base URL: Ensure that the api_base_url for the 'ollama' platform is correctly set to http://127.0.0.1:11434/v1 and that the server is running and accessible at this address ^[2].

2. Model Configuration: Verify that the models specified in your configuration are available and correctly set up. Since auto_detect_model is set to false, you need to manually ensure that the models listed under llm_models and embed_models are correctly configured and available ^[2].

3. Server Logs: Check the server logs for more detailed error messages that might give you a clue about what is going wrong.

4. Database Initialization: Ensure that the database is properly initialized and that there are no issues with the database connection or schema ^[3].

5. File Paths and Permissions: Make sure that the file paths specified in your configuration are correct and that the application has the necessary permissions to access these files ^[3].

If these steps do not resolve the issue, you might want to look into the server-side application logs for more detailed error information.

To continue talking to Dosu, mention @dosu.

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