From afcbc20de3b80f4b2e71243caf5ee58a83b6e7fe Mon Sep 17 00:00:00 2001 From: Vissidarte-Herman Date: Wed, 17 Apr 2024 16:18:27 +0800 Subject: [PATCH 1/2] Added some debugging FAQs --- README.md | 4 ++-- docs/faq.md | 43 ++++++++++++++++++++++++++++++++++++++++++- 2 files changed, 44 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index d9420348896..250d50d6933 100644 --- a/README.md +++ b/README.md @@ -56,7 +56,7 @@ ## 📌 Latest Features - 2024-04-16 Add an embedding model 'bce-embedding-base_v1' from [BCEmbedding](https://github.com/netease-youdao/BCEmbedding). -- 2024-04-16 Add [FastEmbed](https://github.com/qdrant/fastembed) is designed for light and speeding embedding. +- 2024-04-16 Add [FastEmbed](https://github.com/qdrant/fastembed), which is designed specifically for light and speedy embedding. - 2024-04-11 Support [Xinference](./docs/xinference.md) for local LLM deployment. - 2024-04-10 Add a new layout recognization model for analyzing Laws documentation. - 2024-04-08 Support [Ollama](./docs/ollama.md) for local LLM deployment. @@ -139,7 +139,7 @@ ``` 5. In your web browser, enter the IP address of your server and log in to RAGFlow. - > In the given scenario, you only need to enter `http://IP_OF_YOUR_MACHINE` (sans port number) as the default HTTP serving port `80` can be omitted when using the default configurations. + > In the given scenario, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default HTTP serving port `80` can be omitted when using the default configurations. 6. In [service_conf.yaml](./docker/service_conf.yaml), select the desired LLM factory in `user_default_llm` and update the `API_KEY` field with the corresponding API key. > See [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md) for more information. diff --git a/docs/faq.md b/docs/faq.md index 563f91c82cd..383aad01a67 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -96,6 +96,8 @@ Parsing requests have to wait in queue due to limited server resources. We are c ### Why does my document parsing stall at under one percent? +![stall](https://github.com/infiniflow/ragflow/assets/93570324/3589cc25-c733-47d5-bbfc-fedb74a3da50) + If your RAGFlow is deployed *locally*, try the following: 1. Check the log of your RAGFlow server to see if it is running properly: @@ -105,6 +107,16 @@ docker logs -f ragflow-server 2. Check if the **tast_executor.py** process exist. 3. Check if your RAGFlow server can access hf-mirror.com or huggingface.com. +### `MaxRetryError: HTTPSConnectionPool(host='hf-mirror.com', port=443)` + +This error suggests that you do not have Internet access or are unable to connect to hf-mirror.com. Try the following: + +1. Manually download the resource files from [huggingface.co/InfiniFlow/deepdoc](https://huggingface.co/InfiniFlow/deepdoc) to your local folder **~/deepdoc**. +2. Add a volumes to **docker-compose.yml**, for example: +``` +- ~/deepdoc:/ragflow/rag/res/deepdoc +``` + ### `Index failure` An index failure usually indicates an unavailable Elasticsearch service. @@ -165,7 +177,7 @@ Your IP address or port number may be incorrect. If you are using the default co A correct Ollama IP address and port is crucial to adding models to Ollama: -- If you are on demo.ragflow.io, ensure that the server hosting Ollama has a publicly accessible IP address. 127.0.0.1 is not an accessible IP address. +- If you are on demo.ragflow.io, ensure that the server hosting Ollama has a publicly accessible IP address.Note that 127.0.0.1 is not a publicly accessible IP address. - If you deploy RAGFlow locally, ensure that Ollama and RAGFlow are in the same LAN and can comunicate with each other. ### Do you offer examples of using deepdoc to parse PDF or other files? @@ -191,3 +203,32 @@ docker compose up ragflow -d ``` *Now you should be able to upload files of sizes less than 100MB.* +### `Table 'rag_flow.document' doesn't exist exception` + +This exception occurs when starting up the RAGFlow server. Try the following: + + 1. Prolong the sleep time: Go to **docker/entrypoint.sh**, locate line 26, and replace sleep 60 with sleep 280. + 2. Go to **docker/docker-compose.yml**, add the following after line 109: + ```bash + ./entrypoint.sh:/ragflow/entrypoint.sh + ``` + 3. Change directory: + ```bash + cd docker + ``` + 4. Stop the RAGFlow server: + ```bash + docker compose stop + ``` + 5. Restart up the RAGFlow server: + ```bash + docker compose up + ``` + +### `hint : 102 Fail to access model Connection error` + +![hint102](https://github.com/infiniflow/ragflow/assets/93570324/6633d892-b4f8-49b5-9a0a-37a0a8fba3d2) + +1. Ensure that the RAGFlow server can access the base URL. +2. Do not forget to append **/v1/** to **http://IP:port**: + **http://IP:port/v1/** \ No newline at end of file From 4266354996d099d0d9c1350dabe311624299a318 Mon Sep 17 00:00:00 2001 From: Vissidarte-Herman Date: Wed, 17 Apr 2024 16:31:41 +0800 Subject: [PATCH 2/2] editorial updates --- docs/faq.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/faq.md b/docs/faq.md index 383aad01a67..7ac92c7d2a5 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -203,13 +203,13 @@ docker compose up ragflow -d ``` *Now you should be able to upload files of sizes less than 100MB.* -### `Table 'rag_flow.document' doesn't exist exception` +### `Table 'rag_flow.document' doesn't exist` This exception occurs when starting up the RAGFlow server. Try the following: - 1. Prolong the sleep time: Go to **docker/entrypoint.sh**, locate line 26, and replace sleep 60 with sleep 280. + 1. Prolong the sleep time: Go to **docker/entrypoint.sh**, locate line 26, and replace `sleep 60` with `sleep 280`. 2. Go to **docker/docker-compose.yml**, add the following after line 109: - ```bash + ``` ./entrypoint.sh:/ragflow/entrypoint.sh ``` 3. Change directory: