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Fix typo and error (#5479)
### What problem does this PR solve? _Briefly describe what this PR aims to solve. Include background context that will help reviewers understand the purpose of the PR._ ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Documentation Update --------- Signed-off-by: Jin Hai <haijin.chn@gmail.com>
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@ -5,7 +5,7 @@ slug: /text2sql_agent
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# Create a Text2SQL agent
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Build a Text2SQL agent leverging RAGFlow's RAG capabilities. Contributed by @TeslaZY.
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Build a Text2SQL agent leveraging RAGFlow's RAG capabilities. Contributed by @TeslaZY.
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## Scenario
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@ -343,7 +343,7 @@ Synonyms: laptop computer,laptop pc
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3. Create a Retrieval node and name it Thesaurus; create an ExeSQL node.
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4. Configure the Q->SQL, DDL, DB_Description, and TextSQL_Thesaurus knowledge bases. Please refer to the following:
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5. Configure the Generate node, named LLM‘s prompt:
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5. Configure the Generate node, named LLM's prompt:
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- Add this content to the prompt provided by the template to provide the thesaurus content to the LLM:
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```plaintext
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## You may use the following Thesaurus statements. For example, what I ask is from Synonyms, you must use Standard noun to generate SQL. Use responses to past questions also to guide you: {sql_thesaurus}.
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@ -25,7 +25,7 @@ Knowledge graphs are especially useful for multi-hop question-answering involvin
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## Prerequisites
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The system's default chat model is used to generate knowledge graph. Before proceeding, ensure that you have an chat model properly configured:
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The system's default chat model is used to generate knowledge graph. Before proceeding, ensure that you have a chat model properly configured:
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@ -60,10 +60,10 @@ In a knowledge graph, a community is a cluster of entities linked by relationshi
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1. On the **Configuration** page of your knowledge base, switch on **Extract knowledge graph** or adjust its settings as needed, and click **Save** to confirm your changes.
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- *The default knowledge graph configurations for your knowlege base are now set and files uploaded from this point onward will automatically use these settings during parsing.*
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- *The default knowledge graph configurations for your knowledge base are now set and files uploaded from this point onward will automatically use these settings during parsing.*
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- *Files parsed before this update will retain their original knowledge graph settings.*
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2. The knowledge graph of your knowlege base does *not* automatically update *until* a newly uploaded file is parsed.
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2. The knowledge graph of your knowledge base does *not* automatically update *until* a newly uploaded file is parsed.
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_A **Knowledge graph** entry appears under **Configuration** once a knowledge graph is created._
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@ -59,20 +59,20 @@ success
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### 2. Ensure Ollama is accessible
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If RAGFlow runs in Docker and Ollama runs on the same host machine, check if ollama is accessiable from inside the RAGFlow container:
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If RAGFlow runs in Docker and Ollama runs on the same host machine, check if ollama is accessible from inside the RAGFlow container:
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```bash
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sudo docker exec -it ragflow-server bash
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root@8136b8c3e914:/ragflow# curl http://host.docker.internal:11434/
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Ollama is running
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```
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If RAGFlow runs from source code and Ollama runs on the same host machine, check if ollama is accessiable from RAGFlow host machine:
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If RAGFlow runs from source code and Ollama runs on the same host machine, check if ollama is accessible from RAGFlow host machine:
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```bash
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curl http://localhost:11434/
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Ollama is running
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```
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If RAGFlow and Ollama run on different machines, check if ollama is accessiable from RAGFlow host machine:
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If RAGFlow and Ollama run on different machines, check if ollama is accessible from RAGFlow host machine:
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```bash
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curl http://${IP_OF_OLLAMA_MACHINE}:11434/
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Ollama is running
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