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chatchat-space / Langchain-Chatchat

Langchain-Chatchat（原Langchain-ChatGLM, Qwen 与 Llama 等）基于 Langchain 与 ChatGLM 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain
Apache License 2.0
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使用pg向量数据库报错，端口未占用的前提下无法连接数据库 #3619

Closed WSC741606 closed 3 months ago

WSC741606 commented 3 months ago

新建知识库选择pg向量数据库报错，是需要我先怎么操作启动pg数据库吗？ 防火墙已关闭，5432端口经检查无占用 Python startup.py -a 启动的

报错如下： The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/uvicorn/protocols/http/httptools_impl.py", line 411, in run_asgi result = await app( # type: ignore[func-returns-value] File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/uvicorn/middleware/proxy_headers.py", line 69, in call return await self.app(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/fastapi/applications.py", line 1054, in call await super().call(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/applications.py", line 119, in call await self.middleware_stack(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/middleware/errors.py", line 186, in call raise exc File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/middleware/errors.py", line 164, in call await self.app(scope, receive, _send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/middleware/exceptions.py", line 62, in call await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app raise exc File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app await app(scope, receive, sender) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/routing.py", line 762, in call await self.middleware_stack(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/routing.py", line 782, in app await route.handle(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/routing.py", line 297, in handle await self.app(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/routing.py", line 77, in app await wrap_app_handling_exceptions(app, request)(scope, receive, send) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app raise exc File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app await app(scope, receive, sender) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/routing.py", line 72, in app response = await func(request) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/fastapi/routing.py", line 299, in app raise e File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/fastapi/routing.py", line 294, in app raw_response = await run_endpoint_function( File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/fastapi/routing.py", line 193, in run_endpoint_function return await run_in_threadpool(dependant.call, *values) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/starlette/concurrency.py", line 40, in run_in_threadpool return await anyio.to_thread.run_sync(func, args) File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/anyio/to_thread.py", line 56, in run_sync return await get_async_backend().run_sync_in_worker_thread( File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 2144, in run_sync_in_worker_thread return await future File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 851, in run result = context.run(func, *args) File "/data/home/user/Test/GitLibrary/Langchain-Chatchat/server/knowledge_base/kb_api.py", line 29, in create_kb kb = KBServiceFactory.get_service(knowledge_base_name, vector_store_type, embed_model) File "/data/home/user/Test/GitLibrary/Langchain-Chatchat/server/knowledge_base/kb_service/base.py", line 324, in get_service return PGKBService(kb_name, embed_model=embed_model) File "/data/home/user/Test/GitLibrary/Langchain-Chatchat/server/knowledge_base/kb_service/base.py", line 64, in init self.do_init() File "/data/home/user/Test/GitLibrary/Langchain-Chatchat/server/knowledge_base/kb_service/pg_kb_service.py", line 39, in do_init self._load_pg_vector() File "/data/home/user/Test/GitLibrary/Langchain-Chatchat/server/knowledge_base/kb_service/pg_kb_service.py", line 23, in _load_pg_vector self.pg_vector = PGVector(embedding_function=EmbeddingsFunAdapter(self.embed_model), File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/langchain_community/vectorstores/pgvector.py", line 212, in init self.post_init__() File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/langchain_community/vectorstores/pgvector.py", line 218, in post_init__ self.create_vector_extension() File "/data/home/user/Test/Langchain-Chatchat-Env/lib/python3.9/site-packages/langchain_community/vectorstores/pgvector.py", line 256, in create_vector_extension raise Exception(f"Failed to create vector extension: {e}") from e Exception: Failed to create vector extension: (psycopg2.OperationalError) connection to server at "127.0.0.1", port 5432 failed: Connection refused Is the server running on that host and accepting TCP/IP connections?

(Background on this error at: https://sqlalche.me/e/20/e3q8) （蹲机器人的自动回复）

dosubot[bot] commented 3 months ago

Hey there, @WSC741606! 😄 Long time no see in the digital realm of issues and code. How's the tech wizardry going on your end?

Based on the error message you provided, it seems like the application is unable to connect to the PostgreSQL database. This could be due to several reasons, including incorrect connection details, the database not running, or network issues. Here are some steps you can take to troubleshoot this issue:

  1. Correct Connection URI: Verify that the connection_uri provided in your kbs_config is correct. The URI should follow the format: postgresql://user:password@host:port/dbname. Ensure that the user, password, host, port, and dbname are correctly specified and match the credentials of your PostgreSQL database.

  2. Database Running and Accessible: Ensure that your PostgreSQL database is running and accessible from the machine where you're trying to set up the knowledge base. You can test this by trying to connect to your database using a PostgreSQL client with the same credentials and connection details.

  3. Permissions and Roles: Check if the database user specified in the connection_uri has the necessary permissions to create tables, insert data, and perform other required operations in the specified database.

  4. Network Issues: Although you mentioned having the firewall disabled and port 5432 open, it's still worth double-checking any network configurations, including any intermediate firewalls, network ACLs, or security groups that might be blocking the connection.

  5. PostgreSQL Configuration: Ensure that your PostgreSQL server is configured to listen on the correct network interface (listen_addresses in postgresql.conf) and that the pg_hba.conf file is configured to allow connections from your application's host.

  6. Dependencies and Libraries: Make sure all required Python libraries and dependencies for Langchain-Chatchat and PG vector database integration are correctly installed and up to date. This includes libraries such as psycopg2 or SQLAlchemy for interacting with PostgreSQL from Python, and the pgvector extension for efficient vector search in PostgreSQL.

If after checking these points the issue persists, consider enabling detailed logging for both your application and the PostgreSQL server to get more insights into what might be causing the connection refusal. You can set the log_level variable to "INFO" or "DEBUG" for more detailed output in Langchain-Chatchat.

For more information, you can refer to similar issues in the Langchain-Chatchat issue tracker, such as 启动失败, [BUG] python startup.py -a后无法启动, and [BUG] 创建向量库报connection refused 500 错误.

If the issue still persists, please provide more environment configuration information, such as the operating system version, Python version, and whether the program is running in a virtual environment. If any modifications have been made to the code, please provide that information as well.

Sources

#### About Dosu This response is meant to be useful and save you time. It is **not meant to be a precise solution**, but rather a starting point for your own research. Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant. If you want to continue the conversation, start your reply with @dosu-bot.
WSC741606 commented 3 months ago

Hey there, @WSC741606! 😄 Long time no see in the digital realm of issues and code. How's the tech wizardry going on your end?

Based on the error message you provided, it seems like the application is unable to connect to the PostgreSQL database. This could be due to several reasons, including incorrect connection details, the database not running, or network issues. Here are some steps you can take to troubleshoot this issue:

  1. Correct Connection URI: Verify that the connection_uri provided in your kbs_config is correct. The URI should follow the format: postgresql://user:password@host:port/dbname. Ensure that the user, password, host, port, and dbname are correctly specified and match the credentials of your PostgreSQL database.
  2. Database Running and Accessible: Ensure that your PostgreSQL database is running and accessible from the machine where you're trying to set up the knowledge base. You can test this by trying to connect to your database using a PostgreSQL client with the same credentials and connection details.
  3. Permissions and Roles: Check if the database user specified in the connection_uri has the necessary permissions to create tables, insert data, and perform other required operations in the specified database.
  4. Network Issues: Although you mentioned having the firewall disabled and port 5432 open, it's still worth double-checking any network configurations, including any intermediate firewalls, network ACLs, or security groups that might be blocking the connection.
  5. PostgreSQL Configuration: Ensure that your PostgreSQL server is configured to listen on the correct network interface (listen_addresses in postgresql.conf) and that the pg_hba.conf file is configured to allow connections from your application's host.
  6. Dependencies and Libraries: Make sure all required Python libraries and dependencies for Langchain-Chatchat and PG vector database integration are correctly installed and up to date. This includes libraries such as psycopg2 or SQLAlchemy for interacting with PostgreSQL from Python, and the pgvector extension for efficient vector search in PostgreSQL.

If after checking these points the issue persists, consider enabling detailed logging for both your application and the PostgreSQL server to get more insights into what might be causing the connection refusal. You can set the log_level variable to "INFO" or "DEBUG" for more detailed output in Langchain-Chatchat.

For more information, you can refer to similar issues in the Langchain-Chatchat issue tracker, such as 启动失败, [BUG] python startup.py -a后无法启动, and [BUG] 创建向量库报connection refused 500 错误.

If the issue still persists, please provide more environment configuration information, such as the operating system version, Python version, and whether the program is running in a virtual environment. If any modifications have been made to the code, please provide that information as well.

Sources

About Dosu

pg向量数据库到底是个啥 需要我自己先配置什么数据库后端吗？@dosubot

dosubot[bot] commented 3 months ago

To address the "Connection refused" error when setting up a PostgreSQL vector database backend for Langchain-Chatchat, ensure your DEFAULT_VS_TYPE in the configuration file is set to "pg" and the connection_uri under the "pg" key in the kbs_config dictionary correctly reflects your PostgreSQL connection string, as shown below:

DEFAULT_VS_TYPE = "pg"

kbs_config = {
    "pg": {
        "connection_uri": "postgresql://postgres:postgres@127.0.0.1:5432/langchain_chatchat",
    },
    # other configurations...
}

If the issue persists, consider the following steps:

  1. PostgreSQL Server Listening Address: Edit the postgresql.conf file to set listen_addresses to '*' or the specific IP address of the interface you want PostgreSQL to listen on.

  2. PostgreSQL Client Authentication: Modify the pg_hba.conf file to ensure client authentication allows connections from your application's host.

  3. Firewall Rules: Check any firewall between your application and the PostgreSQL server to allow traffic on the PostgreSQL port (default is 5432).

  4. Network Issues: Ensure no network issues are preventing your application from reaching the PostgreSQL server.

Consult the PostgreSQL server logs for messages related to failed connection attempts for more specific information on why the connection was refused.

Additionally, a similar issue was addressed in the Langchain-Chatchat repository (issue #413) by adding the following lines in webui.py:

import os
os.environ["no_proxy"] = "localhost,0.0.0.0,::8090"

Replace 8090 with your actual server port number.

Required Python libraries and dependencies for integration include psycopg2 or asyncpg for PostgreSQL connections, pgvector for operations, and SQLAlchemy for ORM. Indirect dependencies might include numpy and pandas for data handling. Additional libraries or specific versions may be required based on Langchain-Chatchat and PostgreSQL vector database setup needs.

Sources

#### About Dosu This response is meant to be useful and save you time. It is **not meant to be a precise solution**, but rather a starting point for your own research. Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant. If you want to continue the conversation, start your reply with @dosu-bot.
WSC741606 commented 3 months ago

我需要自己维护一个PostgreSQL数据库是吗@dosubot

dosubot[bot] commented 3 months ago

Yes, for Langchain-Chatchat to function correctly with a PostgreSQL vector database backend, you need to maintain a PostgreSQL database. Here's a concise guide to ensure everything is set up correctly:

  1. Verify PostgreSQL Service: Confirm that the PostgreSQL server is actively running on the designated host and port. You can use psql or another PostgreSQL client to test the connection.

  2. Database Setup: Make sure the database, user, and permissions required by Langchain-Chatchat are properly configured. This involves creating a specific database and user with the necessary privileges.

  3. Configuration in Langchain-Chatchat: The connection details (hostname, port, database name, username, and password) must match your PostgreSQL setup. Langchain-Chatchat uses a configuration value named SQLALCHEMY_DATABASE_URI for these details, which is found in the server/db/base.py file.

If after following these steps you encounter issues, reviewing resolved similar issues might provide insights. For example, the resolution for [BUG] 创建向量库报connection refused 500 错误 involved commenting out unnecessary tools, which helped the user resolve their issue.

This should guide you through setting up and troubleshooting the PostgreSQL database for Langchain-Chatchat. If further clarification is needed, feel free to ask.

Sources

#### About Dosu This response is meant to be useful and save you time. It is **not meant to be a precise solution**, but rather a starting point for your own research. Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant. If you want to continue the conversation, start your reply with @dosu-bot.
WSC741606 commented 3 months ago

我自己没先搭PostgreSQL Service导致的 还是faiss方便