diff --git a/agent/templates/advanced_ingestion_pipeline.json b/agent/templates/advanced_ingestion_pipeline.json index 02b58c2e22..27ba006df0 100644 --- a/agent/templates/advanced_ingestion_pipeline.json +++ b/agent/templates/advanced_ingestion_pipeline.json @@ -14,17 +14,17 @@ "canvas_category": "dataflow_canvas", "dsl": { "components": { - "Extractor:CleverPianosInvite": { + "Extractor:CurlyEmusJam": { "downstream": [ - "Tokenizer:ShyBalloonsSmell" + "Tokenizer:WittySunsListen" ], "obj": { "component_name": "Extractor", "params": { - "field_name": "summary", + "field_name": "metadata", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -37,25 +37,25 @@ "presence_penalty": 0.4, "prompts": [ { - "content": "Text to Summarize:\n{Extractor:SunnyCooksSpend@chunks}", + "content": "Content:\n{Extractor:SmartWindowsHammer@chunks}", "role": "user" } ], - "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", + "sys_prompt": "Extract important structured information from the given content. Output ONLY a valid JSON string with no additional text. If no important structured information is found, output an empty JSON object: {}.\n\nImportant structured information may include: names, dates, locations, events, key facts, numerical data, or other extractable entities.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 } }, "upstream": [ - "Extractor:SunnyCooksSpend" + "Extractor:SmartWindowsHammer" ] }, - "Extractor:EasyToesFail": { + "Extractor:LazyCarpetsKiss": { "downstream": [ - "Extractor:SunnyCooksSpend" + "Extractor:LovelyPearsRest" ], "obj": { "component_name": "Extractor", @@ -63,7 +63,7 @@ "field_name": "summary", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -76,25 +76,25 @@ "presence_penalty": 0.4, "prompts": [ { - "content": "Text to Summarize:\n{TokenChunker:SixtyShirtsFeel@chunks}", + "content": "Text to Summarize:\n{TokenChunker:BumpyStarsPress@chunks}", "role": "user" } ], "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 } }, "upstream": [ - "TokenChunker:SixtyShirtsFeel" + "TokenChunker:BumpyStarsPress" ] }, - "Extractor:SunnyCooksSpend": { + "Extractor:LovelyPearsRest": { "downstream": [ - "Extractor:CleverPianosInvite" + "Extractor:SmartWindowsHammer" ], "obj": { "component_name": "Extractor", @@ -102,7 +102,7 @@ "field_name": "keywords", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -115,20 +115,59 @@ "presence_penalty": 0.4, "prompts": [ { - "content": "Text Content\n{Extractor:EasyToesFail@chunks}", + "content": "Text Content\n{Extractor:LazyCarpetsKiss@chunks}", "role": "user" } ], "sys_prompt": "Role\nYou are a text analyzer.\n\nTask\nExtract the most important keywords/phrases of a given piece of text content.\n\nRequirements\n- Summarize the text content, and give the top 5 important keywords/phrases.\n- The keywords MUST be in the same language as the given piece of text content.\n- The keywords are delimited by ENGLISH COMMA.\n- Output keywords ONLY.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 } }, "upstream": [ - "Extractor:EasyToesFail" + "Extractor:LazyCarpetsKiss" + ] + }, + "Extractor:SmartWindowsHammer": { + "downstream": [ + "Extractor:CurlyEmusJam" + ], + "obj": { + "component_name": "Extractor", + "params": { + "field_name": "questions", + "frequencyPenaltyEnabled": true, + "frequency_penalty": 0.7, + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", + "maxTokensEnabled": false, + "max_tokens": 256, + "outputs": { + "chunks": { + "type": "Array", + "value": [] + } + }, + "presencePenaltyEnabled": true, + "presence_penalty": 0.4, + "prompts": [ + { + "content": "Text Content\n{Extractor:LovelyPearsRest@chunks}", + "role": "user" + } + ], + "sys_prompt": "Role\nYou are a text analyzer.\n\nTask\nPropose 3 questions about a given piece of text content.\n\nRequirements\n- Understand and summarize the text content, and propose the top 3 important questions.\n- The questions SHOULD NOT have overlapping meanings.\n- The questions SHOULD cover the main content of the text as much as possible.\n- The questions MUST be in the same language as the given piece of text content.\n- One question per line.\n- Output questions ONLY.", + "temperature": 0.1, + "temperatureEnabled": true, + "tenant_llm_id": 63, + "topPEnabled": true, + "top_p": 0.3 + } + }, + "upstream": [ + "Extractor:LovelyPearsRest" ] }, "File": { @@ -143,7 +182,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TokenChunker:SixtyShirtsFeel" + "TokenChunker:BumpyStarsPress" ], "obj": { "component_name": "Parser", @@ -175,6 +214,7 @@ ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -221,6 +261,7 @@ "system_prompt": "" }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -231,6 +272,7 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -249,6 +291,7 @@ ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -286,9 +329,9 @@ "File" ] }, - "TokenChunker:SixtyShirtsFeel": { + "TokenChunker:BumpyStarsPress": { "downstream": [ - "Extractor:EasyToesFail" + "Extractor:LazyCarpetsKiss" ], "obj": { "component_name": "TokenChunker", @@ -312,7 +355,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:ShyBalloonsSmell": { + "Tokenizer:WittySunsListen": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -327,7 +370,7 @@ } }, "upstream": [ - "Extractor:CleverPianosInvite" + "Extractor:CurlyEmusJam" ] } }, @@ -337,9 +380,6 @@ "graph": { "edges": [ { - "data": { - "isHovered": false - }, "id": "xy-edge__Filestart-Parser:HipSignsRhymeend", "source": "File", "sourceHandle": "start", @@ -347,54 +387,59 @@ "targetHandle": "end" }, { - "data": { - "isHovered": false - }, - "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:SixtyShirtsFeelend", + "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:BumpyStarsPressend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TokenChunker:SixtyShirtsFeel", + "target": "TokenChunker:BumpyStarsPress", "targetHandle": "end" }, { - "data": { - "isHovered": false - }, - "id": "xy-edge__TokenChunker:SixtyShirtsFeelstart-Extractor:EasyToesFailend", - "source": "TokenChunker:SixtyShirtsFeel", + "id": "xy-edge__TokenChunker:BumpyStarsPressstart-Extractor:LazyCarpetsKissend", + "source": "TokenChunker:BumpyStarsPress", "sourceHandle": "start", - "target": "Extractor:EasyToesFail", + "target": "Extractor:LazyCarpetsKiss", "targetHandle": "end" }, { "data": { "isHovered": false }, - "id": "xy-edge__Extractor:EasyToesFailstart-Extractor:SunnyCooksSpendend", + "id": "xy-edge__Extractor:LazyCarpetsKissstart-Extractor:LovelyPearsRestend", + "source": "Extractor:LazyCarpetsKiss", + "sourceHandle": "start", + "target": "Extractor:LovelyPearsRest", + "targetHandle": "end" + }, + { + "data": { + "isHovered": false + }, + "id": "xy-edge__Extractor:LovelyPearsReststart-Extractor:SmartWindowsHammerend", "selected": false, - "source": "Extractor:EasyToesFail", + "source": "Extractor:LovelyPearsRest", "sourceHandle": "start", - "target": "Extractor:SunnyCooksSpend", + "target": "Extractor:SmartWindowsHammer", "targetHandle": "end" }, { "data": { "isHovered": false }, - "id": "xy-edge__Extractor:SunnyCooksSpendstart-Extractor:CleverPianosInviteend", - "source": "Extractor:SunnyCooksSpend", + "id": "xy-edge__Extractor:SmartWindowsHammerstart-Extractor:CurlyEmusJamend", + "selected": false, + "source": "Extractor:SmartWindowsHammer", "sourceHandle": "start", - "target": "Extractor:CleverPianosInvite", + "target": "Extractor:CurlyEmusJam", "targetHandle": "end" }, { "data": { "isHovered": false }, - "id": "xy-edge__Extractor:CleverPianosInvitestart-Tokenizer:ShyBalloonsSmellend", - "source": "Extractor:CleverPianosInvite", + "id": "xy-edge__Extractor:CurlyEmusJamstart-Tokenizer:WittySunsListenend", + "source": "Extractor:CurlyEmusJam", "sourceHandle": "start", - "target": "Tokenizer:ShyBalloonsSmell", + "target": "Tokenizer:WittySunsListen", "targetHandle": "end" } ], @@ -406,7 +451,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -441,12 +486,14 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content" }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content" @@ -475,6 +522,7 @@ }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -495,6 +543,7 @@ }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -547,9 +596,9 @@ "label": "TokenChunker", "name": "Token Chunker_0" }, - "id": "TokenChunker:SixtyShirtsFeel", + "id": "TokenChunker:BumpyStarsPress", "measured": { - "height": 73, + "height": 74, "width": 200 }, "position": { @@ -567,7 +616,7 @@ "field_name": "summary", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -578,26 +627,25 @@ }, "presencePenaltyEnabled": true, "presence_penalty": 0.4, - "prompts": "Text to Summarize:\n{TokenChunker:SixtyShirtsFeel@chunks}", + "prompts": "Text to Summarize:\n{TokenChunker:BumpyStarsPress@chunks}", "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 }, "label": "Extractor", "name": "Summarization" }, - "dragging": false, - "id": "Extractor:EasyToesFail", + "id": "Extractor:LazyCarpetsKiss", "measured": { - "height": 89, + "height": 90, "width": 200 }, "position": { - "x": 606.9117864444606, - "y": 295.54747604679164 + "x": 916.9952409420641, + "y": 195.39629819663406 }, "selected": false, "sourcePosition": "right", @@ -610,7 +658,7 @@ "field_name": "keywords", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -621,26 +669,26 @@ }, "presencePenaltyEnabled": true, "presence_penalty": 0.4, - "prompts": "Text Content\n{Extractor:EasyToesFail@chunks}", + "prompts": "Text Content\n{Extractor:LazyCarpetsKiss@chunks}", "sys_prompt": "Role\nYou are a text analyzer.\n\nTask\nExtract the most important keywords/phrases of a given piece of text content.\n\nRequirements\n- Summarize the text content, and give the top 5 important keywords/phrases.\n- The keywords MUST be in the same language as the given piece of text content.\n- The keywords are delimited by ENGLISH COMMA.\n- Output keywords ONLY.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 }, "label": "Extractor", - "name": "Auto Keywords" + "name": "Auto Keyword" }, "dragging": false, - "id": "Extractor:SunnyCooksSpend", + "id": "Extractor:LovelyPearsRest", "measured": { - "height": 89, + "height": 90, "width": 200 }, "position": { - "x": 598.3422026718366, - "y": 414.3467657992519 + "x": 983.5410692821999, + "y": 301.1557383781162 }, "selected": false, "sourcePosition": "right", @@ -650,10 +698,10 @@ { "data": { "form": { - "field_name": "summary", + "field_name": "questions", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -664,26 +712,69 @@ }, "presencePenaltyEnabled": true, "presence_penalty": 0.4, - "prompts": "Text to Summarize:\n{Extractor:SunnyCooksSpend@chunks}", - "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", + "prompts": "Text Content\n{Extractor:LovelyPearsRest@chunks}", + "sys_prompt": "Role\nYou are a text analyzer.\n\nTask\nPropose 3 questions about a given piece of text content.\n\nRequirements\n- Understand and summarize the text content, and propose the top 3 important questions.\n- The questions SHOULD NOT have overlapping meanings.\n- The questions SHOULD cover the main content of the text as much as possible.\n- The questions MUST be in the same language as the given piece of text content.\n- One question per line.\n- Output questions ONLY.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 }, "label": "Extractor", - "name": "Auto Questions" + "name": "Auto Question" }, "dragging": false, - "id": "Extractor:CleverPianosInvite", + "id": "Extractor:SmartWindowsHammer", "measured": { - "height": 89, + "height": 90, "width": 200 }, "position": { - "x": 594.401162655802, - "y": 536.2317513894384 + "x": 1021.1009769800036, + "y": 421.67760363913044 + }, + "selected": false, + "sourcePosition": "right", + "targetPosition": "left", + "type": "contextNode" + }, + { + "data": { + "form": { + "field_name": "metadata", + "frequencyPenaltyEnabled": true, + "frequency_penalty": 0.7, + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", + "maxTokensEnabled": false, + "max_tokens": 256, + "outputs": { + "chunks": { + "type": "Array", + "value": [] + } + }, + "presencePenaltyEnabled": true, + "presence_penalty": 0.4, + "prompts": "Content:\n{Extractor:SmartWindowsHammer@chunks}", + "sys_prompt": "Extract important structured information from the given content. Output ONLY a valid JSON string with no additional text. If no important structured information is found, output an empty JSON object: {}.\n\nImportant structured information may include: names, dates, locations, events, key facts, numerical data, or other extractable entities.", + "temperature": 0.1, + "temperatureEnabled": true, + "tenant_llm_id": 63, + "topPEnabled": true, + "top_p": 0.3 + }, + "label": "Extractor", + "name": "Auto Metadata" + }, + "dragging": false, + "id": "Extractor:CurlyEmusJam", + "measured": { + "height": 90, + "width": 200 + }, + "position": { + "x": 1065.7115140232393, + "y": 527.4370438206126 }, "selected": true, "sourcePosition": "right", @@ -705,14 +796,14 @@ "name": "Indexer_0" }, "dragging": false, - "id": "Tokenizer:ShyBalloonsSmell", + "id": "Tokenizer:WittySunsListen", "measured": { - "height": 113, + "height": 114, "width": 200 }, "position": { - "x": 911.3724897632962, - "y": 186.00527380751004 + "x": 1327.3247542536642, + "y": 164.72133416115918 }, "selected": false, "sourcePosition": "right", diff --git a/agent/templates/chunk_summary.json b/agent/templates/chunk_summary.json index 06935a21c7..8001576520 100644 --- a/agent/templates/chunk_summary.json +++ b/agent/templates/chunk_summary.json @@ -14,9 +14,9 @@ "canvas_category": "dataflow_canvas", "dsl": { "components": { - "Extractor:PublicPlumsKiss": { + "Extractor:SharpTaxisSay": { "downstream": [ - "Tokenizer:FullBottlesDeny" + "Tokenizer:ShaggyShrimpsLose" ], "obj": { "component_name": "Extractor", @@ -24,7 +24,7 @@ "field_name": "summary", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -37,20 +37,20 @@ "presence_penalty": 0.4, "prompts": [ { - "content": "Text to Summarize:\n{TokenChunker:FancyCitiesStick@chunks}", + "content": "Text to Summarize:\n{TokenChunker:ModernPetsKneel@chunks}", "role": "user" } ], "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 } }, "upstream": [ - "TokenChunker:FancyCitiesStick" + "TokenChunker:ModernPetsKneel" ] }, "File": { @@ -65,7 +65,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TokenChunker:FancyCitiesStick" + "TokenChunker:ModernPetsKneel" ], "obj": { "component_name": "Parser", @@ -97,6 +97,7 @@ ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -143,6 +144,7 @@ "system_prompt": "" }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -153,6 +155,7 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -171,6 +174,7 @@ ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -208,9 +212,9 @@ "File" ] }, - "TokenChunker:FancyCitiesStick": { + "TokenChunker:ModernPetsKneel": { "downstream": [ - "Extractor:PublicPlumsKiss" + "Extractor:SharpTaxisSay" ], "obj": { "component_name": "TokenChunker", @@ -234,7 +238,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:FullBottlesDeny": { + "Tokenizer:ShaggyShrimpsLose": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -249,17 +253,12 @@ } }, "upstream": [ - "Extractor:PublicPlumsKiss" + "Extractor:SharpTaxisSay" ] } }, "globals": { - "sys.conversation_turns": 0, - "sys.date": "", - "sys.files": [], - "sys.history": [], - "sys.query": "", - "sys.user_id": "" + "sys.history": [] }, "graph": { "edges": [ @@ -271,28 +270,31 @@ "targetHandle": "end" }, { - "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:FancyCitiesStickend", + "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:ModernPetsKneelend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TokenChunker:FancyCitiesStick", + "target": "TokenChunker:ModernPetsKneel", + "targetHandle": "end" + }, + { + "id": "xy-edge__TokenChunker:ModernPetsKneelstart-Extractor:SharpTaxisSayend", + "source": "TokenChunker:ModernPetsKneel", + "sourceHandle": "start", + "target": "Extractor:SharpTaxisSay", "targetHandle": "end" }, { "data": { "isHovered": false }, - "id": "xy-edge__TokenChunker:FancyCitiesStickstart-Extractor:PublicPlumsKissend", - "source": "TokenChunker:FancyCitiesStick", + "id": "xy-edge__Extractor:SharpTaxisSaystart-Tokenizer:ShaggyShrimpsLoseend", + "markerEnd": "logo", + "source": "Extractor:SharpTaxisSay", "sourceHandle": "start", - "target": "Extractor:PublicPlumsKiss", - "targetHandle": "end" - }, - { - "id": "xy-edge__Extractor:PublicPlumsKissstart-Tokenizer:FullBottlesDenyend", - "source": "Extractor:PublicPlumsKiss", - "sourceHandle": "start", - "target": "Tokenizer:FullBottlesDeny", - "targetHandle": "end" + "target": "Tokenizer:ShaggyShrimpsLose", + "targetHandle": "end", + "type": "buttonEdge", + "zIndex": 1001 } ], "nodes": [ @@ -303,7 +305,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -338,12 +340,14 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content" }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content" @@ -372,6 +376,7 @@ }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -392,6 +397,7 @@ }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -409,7 +415,7 @@ "dragging": false, "id": "Parser:HipSignsRhyme", "measured": { - "height": 197, + "height": 57, "width": 200 }, "position": { @@ -424,7 +430,6 @@ { "data": { "form": { - "children_delimiters": [], "chunk_token_size": 512, "delimiter_mode": "token_size", "delimiters": [ @@ -444,62 +449,19 @@ "label": "TokenChunker", "name": "Token Chunker_0" }, - "id": "TokenChunker:FancyCitiesStick", + "id": "TokenChunker:ModernPetsKneel", "measured": { - "height": 73, + "height": 74, "width": 200 }, "position": { "x": 616.9952409420641, "y": 195.39629819663406 }, - "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "chunkerNode" }, - { - "data": { - "form": { - "field_name": "summary", - "frequencyPenaltyEnabled": true, - "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", - "maxTokensEnabled": false, - "max_tokens": 256, - "outputs": { - "chunks": { - "type": "Array", - "value": [] - } - }, - "presencePenaltyEnabled": true, - "presence_penalty": 0.4, - "prompts": "Text to Summarize:\n{TokenChunker:FancyCitiesStick@chunks}", - "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", - "temperature": 0.1, - "temperatureEnabled": true, - "tenant_llm_id": 54, - "topPEnabled": true, - "top_p": 0.3 - }, - "label": "Extractor", - "name": "Summarizer" - }, - "id": "Extractor:PublicPlumsKiss", - "measured": { - "height": 89, - "width": 200 - }, - "position": { - "x": 916.9952409420641, - "y": 195.39629819663406 - }, - "selected": true, - "sourcePosition": "right", - "targetPosition": "left", - "type": "contextNode" - }, { "data": { "form": { @@ -514,15 +476,17 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:FullBottlesDeny", + "dragging": false, + "id": "Tokenizer:ShaggyShrimpsLose", "measured": { - "height": 113, + "height": 114, "width": 200 }, "position": { - "x": 1216.9952409420641, - "y": 195.39629819663406 + "x": 1188.9891545215792, + "y": 159.26426539640332 }, + "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "tokenizerNode" @@ -530,26 +494,45 @@ { "data": { "form": { - "text": "Using summary to build both text and vector indexes." + "field_name": "summary", + "frequencyPenaltyEnabled": true, + "frequency_penalty": 0.7, + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", + "maxTokensEnabled": false, + "max_tokens": 256, + "outputs": { + "chunks": { + "type": "Array", + "value": [] + } + }, + "presencePenaltyEnabled": true, + "presence_penalty": 0.4, + "prompts": "Text to Summarize:\n{TokenChunker:ModernPetsKneel@chunks}", + "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", + "temperature": 0.1, + "temperatureEnabled": true, + "tenant_llm_id": 63, + "topPEnabled": true, + "top_p": 0.3 }, - "label": "Note", - "name": "Index Summary" + "label": "Extractor", + "name": "Summarization" }, - "dragHandle": ".note-drag-handle", "dragging": false, - "id": "Note:ElevenKingsPick", + "id": "Extractor:SharpTaxisSay", "measured": { - "height": 127, - "width": 267 + "height": 90, + "width": 200 }, "position": { - "x": 735.9586746349814, - "y": 315.614230763182 + "x": 878.855872986265, + "y": 177.33028179651868 }, - "selected": false, + "selected": true, "sourcePosition": "right", "targetPosition": "left", - "type": "noteNode" + "type": "contextNode" } ] }, diff --git a/agent/templates/ingestion_pipeline_Book.json b/agent/templates/ingestion_pipeline_Book.json index 6136bacc74..013d9e2517 100644 --- a/agent/templates/ingestion_pipeline_Book.json +++ b/agent/templates/ingestion_pipeline_Book.json @@ -26,7 +26,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TitleChunker:RealEggsHope" + "TitleChunker:GrumpyGarlicsBake" ], "obj": { "component_name": "Parser", @@ -60,6 +60,7 @@ ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": [ "main_content" @@ -113,6 +114,7 @@ ] }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": [ "main_content" @@ -125,6 +127,7 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": [ @@ -136,6 +139,31 @@ ], "vlm": {} }, + "slides": { + "output_format": "json", + "parse_method": "DeepDOC", + "preprocess": [ + "main_content" + ], + "suffix": [ + "pptx", + "ppt" + ] + }, + "spreadsheet": { + "flatten_media_to_text": false, + "output_format": "html", + "parse_method": "DeepDOC", + "preprocess": [ + "main_content" + ], + "suffix": [ + "xls", + "xlsx", + "csv" + ], + "vlm": {} + }, "text&code": { "output_format": "json", "preprocess": [ @@ -165,9 +193,9 @@ "File" ] }, - "TitleChunker:RealEggsHope": { + "TitleChunker:GrumpyGarlicsBake": { "downstream": [ - "Tokenizer:FunkyBucketsReport" + "Tokenizer:HotDonutsRing" ], "obj": { "component_name": "TitleChunker", @@ -216,7 +244,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:FunkyBucketsReport": { + "Tokenizer:HotDonutsRing": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -231,24 +259,16 @@ } }, "upstream": [ - "TitleChunker:RealEggsHope" + "TitleChunker:GrumpyGarlicsBake" ] } }, "globals": { - "sys.conversation_turns": 0, - "sys.date": "", - "sys.files": [], - "sys.history": [], - "sys.query": "", - "sys.user_id": "" + "sys.history": [] }, "graph": { "edges": [ { - "data": { - "isHovered": false - }, "id": "xy-edge__Filestart-Parser:HipSignsRhymeend", "source": "File", "sourceHandle": "start", @@ -256,23 +276,17 @@ "targetHandle": "end" }, { - "data": { - "isHovered": false - }, - "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:RealEggsHopeend", + "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:GrumpyGarlicsBakeend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TitleChunker:RealEggsHope", + "target": "TitleChunker:GrumpyGarlicsBake", "targetHandle": "end" }, { - "data": { - "isHovered": false - }, - "id": "xy-edge__TitleChunker:RealEggsHopestart-Tokenizer:FunkyBucketsReportend", - "source": "TitleChunker:RealEggsHope", + "id": "xy-edge__TitleChunker:GrumpyGarlicsBakestart-Tokenizer:HotDonutsRingend", + "source": "TitleChunker:GrumpyGarlicsBake", "sourceHandle": "start", - "target": "Tokenizer:FunkyBucketsReport", + "target": "Tokenizer:HotDonutsRing", "targetHandle": "end" } ], @@ -284,7 +298,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -319,6 +333,7 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": [ @@ -327,6 +342,16 @@ "remove_toc": true, "vlm": {} }, + { + "fileFormat": "spreadsheet", + "flatten_media_to_text": false, + "output_format": "html", + "parse_method": "DeepDOC", + "preprocess": [ + "main_content" + ], + "vlm": {} + }, { "fileFormat": "image", "output_format": "text", @@ -354,6 +379,7 @@ }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", "preprocess": [ "main_content" @@ -385,12 +411,21 @@ }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", "preprocess": [ "main_content" ], "remove_toc": true, "vlm": {} + }, + { + "fileFormat": "slides", + "output_format": "json", + "parse_method": "DeepDOC", + "preprocess": [ + "main_content" + ] } ] }, @@ -407,7 +442,7 @@ "x": 316.99524094206413, "y": 195.39629819663406 }, - "selected": true, + "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "parserNode" @@ -519,7 +554,7 @@ "label": "TitleChunker", "name": "Title Chunker_0" }, - "id": "TitleChunker:RealEggsHope", + "id": "TitleChunker:GrumpyGarlicsBake", "measured": { "height": 74, "width": 200 @@ -528,7 +563,7 @@ "x": 616.9952409420641, "y": 195.39629819663406 }, - "selected": false, + "selected": true, "sourcePosition": "right", "targetPosition": "left", "type": "chunkerNode" @@ -547,7 +582,7 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:FunkyBucketsReport", + "id": "Tokenizer:HotDonutsRing", "measured": { "height": 114, "width": 200 @@ -556,7 +591,6 @@ "x": 916.9952409420641, "y": 195.39629819663406 }, - "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "tokenizerNode" @@ -564,9 +598,10 @@ ] }, "history": [], + "messages": [], "path": [], "retrieval": [], "variables": [] }, - "avatar": 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} diff --git a/agent/templates/ingestion_pipeline_General.json b/agent/templates/ingestion_pipeline_General.json index 940b5d3c07..2f27340edd 100644 --- a/agent/templates/ingestion_pipeline_General.json +++ b/agent/templates/ingestion_pipeline_General.json @@ -26,7 +26,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TokenChunker:TameMangosKick" + "TokenChunker:SixApplesFall" ], "obj": { "component_name": "Parser", @@ -52,14 +52,19 @@ "setups": { "doc": { "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "doc" ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "docx" ], @@ -77,7 +82,9 @@ "attachments" ], "output_format": "text", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "eml", "msg" @@ -85,7 +92,9 @@ }, "html": { "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "htm", "html" @@ -94,18 +103,22 @@ "image": { "output_format": "text", "parse_method": "ocr", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "jpg", "jpeg", "png", "gif" - ], - "system_prompt": "" + ] }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "md", "markdown", @@ -114,9 +127,12 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "pdf" ], @@ -125,16 +141,21 @@ "slides": { "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "pptx", "ppt" ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "xls", "xlsx", @@ -144,7 +165,9 @@ }, "text&code": { "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "txt", "py", @@ -169,9 +192,9 @@ "File" ] }, - "TokenChunker:TameMangosKick": { + "TokenChunker:SixApplesFall": { "downstream": [ - "Tokenizer:StrongCoatsTalk" + "Tokenizer:LegalReadersDecide" ], "obj": { "component_name": "TokenChunker", @@ -195,7 +218,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:StrongCoatsTalk": { + "Tokenizer:LegalReadersDecide": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -210,7 +233,7 @@ } }, "upstream": [ - "TokenChunker:TameMangosKick" + "TokenChunker:SixApplesFall" ] } }, @@ -220,9 +243,6 @@ "graph": { "edges": [ { - "data": { - "isHovered": false - }, "id": "xy-edge__Filestart-Parser:HipSignsRhymeend", "source": "File", "sourceHandle": "start", @@ -230,17 +250,20 @@ "targetHandle": "end" }, { - "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:TameMangosKickend", + "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:SixApplesFallend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TokenChunker:TameMangosKick", + "target": "TokenChunker:SixApplesFall", "targetHandle": "end" }, { - "id": "xy-edge__TokenChunker:TameMangosKickstart-Tokenizer:StrongCoatsTalkend", - "source": "TokenChunker:TameMangosKick", + "data": { + "isHovered": false + }, + "id": "xy-edge__TokenChunker:SixApplesFallstart-Tokenizer:LegalReadersDecideend", + "source": "TokenChunker:SixApplesFall", "sourceHandle": "start", - "target": "Tokenizer:StrongCoatsTalk", + "target": "Tokenizer:LegalReadersDecide", "targetHandle": "end" } ], @@ -252,7 +275,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -287,22 +310,31 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "image", "output_format": "text", "parse_method": "ocr", - "preprocess": "main_content", - "system_prompt": "" + "preprocess": [ + "main_content" + ] }, { "fields": [ @@ -317,38 +349,56 @@ ], "fileFormat": "email", "output_format": "text", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "text&code", "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "html", "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "doc", "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "slides", "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] } ] }, @@ -365,7 +415,7 @@ "x": 316.99524094206413, "y": 195.39629819663406 }, - "selected": false, + "selected": true, "sourcePosition": "right", "targetPosition": "left", "type": "parserNode" @@ -393,7 +443,7 @@ "label": "TokenChunker", "name": "Token Chunker_0" }, - "id": "TokenChunker:TameMangosKick", + "id": "TokenChunker:SixApplesFall", "measured": { "height": 74, "width": 200 @@ -402,7 +452,7 @@ "x": 616.9952409420641, "y": 195.39629819663406 }, - "selected": true, + "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "chunkerNode" @@ -421,7 +471,7 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:StrongCoatsTalk", + "id": "Tokenizer:LegalReadersDecide", "measured": { "height": 114, "width": 200 @@ -442,5 +492,5 @@ "retrieval": [], "variables": [] }, - "avatar": 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" } diff --git a/agent/templates/ingestion_pipeline_Laws.json b/agent/templates/ingestion_pipeline_Laws.json index b2b86f6f04..bc389724bc 100644 --- a/agent/templates/ingestion_pipeline_Laws.json +++ b/agent/templates/ingestion_pipeline_Laws.json @@ -26,7 +26,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TitleChunker:SlimyPapayasAttend" + "TitleChunker:SpicyKeysKick" ], "obj": { "component_name": "Parser", @@ -52,18 +52,15 @@ "setups": { "doc": { "output_format": "json", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "doc" ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "docx" ], @@ -81,9 +78,7 @@ "attachments" ], "output_format": "text", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "eml", "msg" @@ -91,9 +86,7 @@ }, "html": { "output_format": "json", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "htm", "html" @@ -102,21 +95,19 @@ "image": { "output_format": "text", "parse_method": "ocr", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "jpg", "jpeg", "png", "gif" - ] + ], + "system_prompt": "" }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "md", "markdown", @@ -125,11 +116,10 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "pdf" ], @@ -138,20 +128,17 @@ "slides": { "output_format": "json", "parse_method": "DeepDOC", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "pptx", "ppt" ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "xls", "xlsx", @@ -161,9 +148,7 @@ }, "text&code": { "output_format": "json", - "preprocess": [ - "main_content" - ], + "preprocess": "main_content", "suffix": [ "txt", "py", @@ -188,9 +173,9 @@ "File" ] }, - "TitleChunker:SlimyPapayasAttend": { + "TitleChunker:SpicyKeysKick": { "downstream": [ - "Tokenizer:RipeSchoolsFetch" + "Tokenizer:PublicJobsTake" ], "obj": { "component_name": "TitleChunker", @@ -239,7 +224,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:RipeSchoolsFetch": { + "Tokenizer:PublicJobsTake": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -254,7 +239,7 @@ } }, "upstream": [ - "TitleChunker:SlimyPapayasAttend" + "TitleChunker:SpicyKeysKick" ] } }, @@ -264,6 +249,9 @@ "graph": { "edges": [ { + "data": { + "isHovered": false + }, "id": "xy-edge__Filestart-Parser:HipSignsRhymeend", "source": "File", "sourceHandle": "start", @@ -271,23 +259,20 @@ "targetHandle": "end" }, { - "data": { - "isHovered": false - }, - "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:SlimyPapayasAttendend", + "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:SpicyKeysKickend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TitleChunker:SlimyPapayasAttend", + "target": "TitleChunker:SpicyKeysKick", "targetHandle": "end" }, { "data": { "isHovered": false }, - "id": "xy-edge__TitleChunker:SlimyPapayasAttendstart-Tokenizer:RipeSchoolsFetchend", - "source": "TitleChunker:SlimyPapayasAttend", + "id": "xy-edge__TitleChunker:SpicyKeysKickstart-Tokenizer:PublicJobsTakeend", + "source": "TitleChunker:SpicyKeysKick", "sourceHandle": "start", - "target": "Tokenizer:RipeSchoolsFetch", + "target": "Tokenizer:PublicJobsTake", "targetHandle": "end" } ], @@ -299,7 +284,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -334,29 +319,24 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", - "preprocess": [ - "main_content" - ], - "vlm": {} + "preprocess": "main_content" }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", - "preprocess": [ - "main_content" - ], - "vlm": {} + "preprocess": "main_content" }, { "fileFormat": "image", "output_format": "text", "parse_method": "ocr", - "preprocess": [ - "main_content" - ] + "preprocess": "main_content", + "system_prompt": "" }, { "fields": [ @@ -371,54 +351,40 @@ ], "fileFormat": "email", "output_format": "text", - "preprocess": [ - "main_content" - ] + "preprocess": "main_content" }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", - "preprocess": [ - "main_content" - ], - "vlm": {} + "preprocess": "main_content" }, { "fileFormat": "text&code", "output_format": "json", - "preprocess": [ - "main_content" - ] + "preprocess": "main_content" }, { "fileFormat": "html", "output_format": "json", - "preprocess": [ - "main_content" - ] + "preprocess": "main_content" }, { "fileFormat": "doc", "output_format": "json", - "preprocess": [ - "main_content" - ] + "preprocess": "main_content" }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", - "preprocess": [ - "main_content" - ], - "vlm": {} + "preprocess": "main_content" }, { "fileFormat": "slides", "output_format": "json", "parse_method": "DeepDOC", - "preprocess": [ - "main_content" - ] + "preprocess": "main_content" } ] }, @@ -435,7 +401,7 @@ "x": 316.99524094206413, "y": 195.39629819663406 }, - "selected": true, + "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "parserNode" @@ -547,7 +513,7 @@ "label": "TitleChunker", "name": "Title Chunker_0" }, - "id": "TitleChunker:SlimyPapayasAttend", + "id": "TitleChunker:SpicyKeysKick", "measured": { "height": 74, "width": 200 @@ -575,7 +541,7 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:RipeSchoolsFetch", + "id": "Tokenizer:PublicJobsTake", "measured": { "height": 114, "width": 200 @@ -584,6 +550,7 @@ "x": 916.9952409420641, "y": 195.39629819663406 }, + "selected": true, "sourcePosition": "right", "targetPosition": "left", "type": "tokenizerNode" @@ -596,5 +563,5 @@ "retrieval": [], "variables": [] }, - "avatar": 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+ "avatar": 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" } diff --git a/agent/templates/ingestion_pipeline_Manual.json b/agent/templates/ingestion_pipeline_Manual.json index 46bc02ba6d..cfe1137226 100644 --- a/agent/templates/ingestion_pipeline_Manual.json +++ b/agent/templates/ingestion_pipeline_Manual.json @@ -26,7 +26,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TitleChunker:WideSwansSmoke" + "TitleChunker:NineInsectsFind" ], "obj": { "component_name": "Parser", @@ -58,6 +58,7 @@ ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -104,6 +105,7 @@ "system_prompt": "" }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -114,6 +116,7 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -132,6 +135,7 @@ ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -169,9 +173,9 @@ "File" ] }, - "TitleChunker:WideSwansSmoke": { + "TitleChunker:NineInsectsFind": { "downstream": [ - "Tokenizer:FloppyCrewsRelax" + "Tokenizer:FunnyBalloonsGrin" ], "obj": { "component_name": "TitleChunker", @@ -220,7 +224,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:FloppyCrewsRelax": { + "Tokenizer:FunnyBalloonsGrin": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -235,7 +239,7 @@ } }, "upstream": [ - "TitleChunker:WideSwansSmoke" + "TitleChunker:NineInsectsFind" ] } }, @@ -252,17 +256,17 @@ "targetHandle": "end" }, { - "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:WideSwansSmokeend", + "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:NineInsectsFindend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TitleChunker:WideSwansSmoke", + "target": "TitleChunker:NineInsectsFind", "targetHandle": "end" }, { - "id": "xy-edge__TitleChunker:WideSwansSmokestart-Tokenizer:FloppyCrewsRelaxend", - "source": "TitleChunker:WideSwansSmoke", + "id": "xy-edge__TitleChunker:NineInsectsFindstart-Tokenizer:FunnyBalloonsGrinend", + "source": "TitleChunker:NineInsectsFind", "sourceHandle": "start", - "target": "Tokenizer:FloppyCrewsRelax", + "target": "Tokenizer:FunnyBalloonsGrin", "targetHandle": "end" } ], @@ -274,7 +278,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -309,12 +313,14 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content" }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content" @@ -343,6 +349,7 @@ }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -363,6 +370,7 @@ }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -499,16 +507,16 @@ "label": "TitleChunker", "name": "Title Chunker_0" }, - "id": "TitleChunker:WideSwansSmoke", + "id": "TitleChunker:NineInsectsFind", "measured": { - "height": 73, + "height": 74, "width": 200 }, "position": { "x": 616.9952409420641, "y": 195.39629819663406 }, - "selected": false, + "selected": true, "sourcePosition": "right", "targetPosition": "left", "type": "chunkerNode" @@ -527,9 +535,9 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:FloppyCrewsRelax", + "id": "Tokenizer:FunnyBalloonsGrin", "measured": { - "height": 113, + "height": 114, "width": 200 }, "position": { @@ -548,5 +556,5 @@ "retrieval": [], "variables": [] }, - "avatar": 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" } diff --git a/agent/templates/ingestion_pipeline_One.json b/agent/templates/ingestion_pipeline_One.json index 0e6a1599bc..9700e37248 100644 --- a/agent/templates/ingestion_pipeline_One.json +++ b/agent/templates/ingestion_pipeline_One.json @@ -26,7 +26,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TokenChunker:LongRadiosNotice" + "TokenChunker:DryDrinksVisit" ], "obj": { "component_name": "Parser", @@ -58,6 +58,7 @@ ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -104,6 +105,7 @@ "system_prompt": "" }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -114,6 +116,7 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -132,6 +135,7 @@ ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -169,9 +173,9 @@ "File" ] }, - "TokenChunker:LongRadiosNotice": { + "TokenChunker:DryDrinksVisit": { "downstream": [ - "Tokenizer:SixtyChickenSell" + "Tokenizer:FrankWeeksListen" ], "obj": { "component_name": "TokenChunker", @@ -195,7 +199,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:SixtyChickenSell": { + "Tokenizer:FrankWeeksListen": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -210,7 +214,7 @@ } }, "upstream": [ - "TokenChunker:LongRadiosNotice" + "TokenChunker:DryDrinksVisit" ] } }, @@ -227,17 +231,17 @@ "targetHandle": "end" }, { - "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:LongRadiosNoticeend", + "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:DryDrinksVisitend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TokenChunker:LongRadiosNotice", + "target": "TokenChunker:DryDrinksVisit", "targetHandle": "end" }, { - "id": "xy-edge__TokenChunker:LongRadiosNoticestart-Tokenizer:SixtyChickenSellend", - "source": "TokenChunker:LongRadiosNotice", + "id": "xy-edge__TokenChunker:DryDrinksVisitstart-Tokenizer:FrankWeeksListenend", + "source": "TokenChunker:DryDrinksVisit", "sourceHandle": "start", - "target": "Tokenizer:SixtyChickenSell", + "target": "Tokenizer:FrankWeeksListen", "targetHandle": "end" } ], @@ -249,7 +253,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -284,12 +288,14 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content" }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content" @@ -318,6 +324,7 @@ }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -338,6 +345,7 @@ }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -355,7 +363,7 @@ "dragging": false, "id": "Parser:HipSignsRhyme", "measured": { - "height": 197, + "height": 57, "width": 200 }, "position": { @@ -390,16 +398,16 @@ "label": "TokenChunker", "name": "Token Chunker_0" }, - "id": "TokenChunker:LongRadiosNotice", + "id": "TokenChunker:DryDrinksVisit", "measured": { - "height": 73, + "height": 74, "width": 200 }, "position": { "x": 616.9952409420641, "y": 195.39629819663406 }, - "selected": false, + "selected": true, "sourcePosition": "right", "targetPosition": "left", "type": "chunkerNode" @@ -418,9 +426,9 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:SixtyChickenSell", + "id": "Tokenizer:FrankWeeksListen", "measured": { - "height": 113, + "height": 114, "width": 200 }, "position": { @@ -439,5 +447,5 @@ "retrieval": [], "variables": [] }, - "avatar": 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" } diff --git a/agent/templates/ingestion_pipeline_Paper.json b/agent/templates/ingestion_pipeline_Paper.json index 31c78067af..004f524462 100644 --- a/agent/templates/ingestion_pipeline_Paper.json +++ b/agent/templates/ingestion_pipeline_Paper.json @@ -26,7 +26,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TitleChunker:BeigeSheepTravel" + "TitleChunker:SparklySchoolsTravel" ], "obj": { "component_name": "Parser", @@ -52,14 +52,19 @@ "setups": { "doc": { "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "doc" ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "docx" ], @@ -77,7 +82,9 @@ "attachments" ], "output_format": "text", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "eml", "msg" @@ -85,7 +92,9 @@ }, "html": { "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "htm", "html" @@ -94,18 +103,22 @@ "image": { "output_format": "text", "parse_method": "ocr", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "jpg", "jpeg", "png", "gif" - ], - "system_prompt": "" + ] }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "md", "markdown", @@ -114,9 +127,13 @@ "vlm": {} }, "pdf": { + "enable_multi_column": true, + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "pdf" ], @@ -125,16 +142,21 @@ "slides": { "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "pptx", "ppt" ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "xls", "xlsx", @@ -144,7 +166,9 @@ }, "text&code": { "output_format": "json", - "preprocess": "main_content", + "preprocess": [ + "main_content" + ], "suffix": [ "txt", "py", @@ -169,9 +193,9 @@ "File" ] }, - "TitleChunker:BeigeSheepTravel": { + "TitleChunker:SparklySchoolsTravel": { "downstream": [ - "Tokenizer:EveryBushesStop" + "Tokenizer:GreatCarsWash" ], "obj": { "component_name": "TitleChunker", @@ -220,7 +244,7 @@ "Parser:HipSignsRhyme" ] }, - "Tokenizer:EveryBushesStop": { + "Tokenizer:GreatCarsWash": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -235,7 +259,7 @@ } }, "upstream": [ - "TitleChunker:BeigeSheepTravel" + "TitleChunker:SparklySchoolsTravel" ] } }, @@ -245,6 +269,9 @@ "graph": { "edges": [ { + "data": { + "isHovered": false + }, "id": "xy-edge__Filestart-Parser:HipSignsRhymeend", "source": "File", "sourceHandle": "start", @@ -252,20 +279,20 @@ "targetHandle": "end" }, { - "data": { - "isHovered": false - }, - "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:BeigeSheepTravelend", + "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:SparklySchoolsTravelend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TitleChunker:BeigeSheepTravel", + "target": "TitleChunker:SparklySchoolsTravel", "targetHandle": "end" }, { - "id": "xy-edge__TitleChunker:BeigeSheepTravelstart-Tokenizer:EveryBushesStopend", - "source": "TitleChunker:BeigeSheepTravel", + "data": { + "isHovered": false + }, + "id": "xy-edge__TitleChunker:SparklySchoolsTravelstart-Tokenizer:GreatCarsWashend", + "source": "TitleChunker:SparklySchoolsTravel", "sourceHandle": "start", - "target": "Tokenizer:EveryBushesStop", + "target": "Tokenizer:GreatCarsWash", "targetHandle": "end" } ], @@ -277,7 +304,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -311,23 +338,33 @@ }, "setups": [ { + "enable_multi_column": true, "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "image", "output_format": "text", "parse_method": "ocr", - "preprocess": "main_content", - "system_prompt": "" + "preprocess": [ + "main_content" + ] }, { "fields": [ @@ -342,38 +379,56 @@ ], "fileFormat": "email", "output_format": "text", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "text&code", "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "html", "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "doc", "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ], + "vlm": {} }, { "fileFormat": "slides", "output_format": "json", "parse_method": "DeepDOC", - "preprocess": "main_content" + "preprocess": [ + "main_content" + ] } ] }, @@ -383,7 +438,7 @@ "dragging": false, "id": "Parser:HipSignsRhyme", "measured": { - "height": 57, + "height": 198, "width": 200 }, "position": { @@ -502,9 +557,9 @@ "label": "TitleChunker", "name": "Title Chunker_0" }, - "id": "TitleChunker:BeigeSheepTravel", + "id": "TitleChunker:SparklySchoolsTravel", "measured": { - "height": 73, + "height": 74, "width": 200 }, "position": { @@ -530,15 +585,16 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:EveryBushesStop", + "id": "Tokenizer:GreatCarsWash", "measured": { - "height": 113, + "height": 114, "width": 200 }, "position": { "x": 916.9952409420641, "y": 195.39629819663406 }, + "selected": false, "sourcePosition": "right", "targetPosition": "left", "type": "tokenizerNode" @@ -551,5 +607,5 @@ "retrieval": [], "variables": [] }, - "avatar": 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" } diff --git a/agent/templates/ingestion_pipeline_Resume.json b/agent/templates/ingestion_pipeline_Resume.json new file mode 100644 index 0000000000..7eab1d3a78 --- /dev/null +++ b/agent/templates/ingestion_pipeline_Resume.json @@ -0,0 +1,604 @@ +{ + "id": 40, + "title": { + "en": "Resume", + "de": "Lebenslauf", + "zh": "简历" + }, + "description": { + "en": "This template segments parsed files based on the structure of a resume. It is suitable for documents with clearly defined sections such as personal information, education, work experience, projects, skills, certifications, and other career-related content.", + "de": "Diese Vorlage segmentiert die geparste Datei anhand der Struktur eines Lebenslaufs. Sie eignet sich für Dokumente mit klar definierten Abschnitten wie persönlichen Informationen, Ausbildung, Berufserfahrung, Projekten, Fähigkeiten, Zertifikaten und anderen karrierebezogenen Inhalten.", + "zh": "此模板将解析后的文件按简历结构进行切片,适用于具有清晰分节的文档类型,如个人信息、教育背景、工作经历、项目经历、技能、证书及其他职业相关内容。" + }, + "canvas_type": "Ingestion Pipeline", + "canvas_category": "dataflow_canvas", + "dsl": { + "components": { + "Extractor:ThreeDrinksAct": { + "downstream": [ + "Tokenizer:KindHandsWin" + ], + "obj": { + "component_name": "Extractor", + "params": { + "field_name": "metadata", + "frequencyPenaltyEnabled": true, + "frequency_penalty": 0.7, + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", + "maxTokensEnabled": false, + "max_tokens": 256, + "outputs": { + "chunks": { + "type": "Array", + "value": [] + } + }, + "presencePenaltyEnabled": true, + "presence_penalty": 0.4, + "prompts": [ + { + "content": "Content: {TitleChunker:FlatMiceFix@chunks}", + "role": "user" + } + ], + "sys_prompt": "Act as a precise resume metadata extractor. 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Extract stable, chunk-supported metadata from the provided resume content.\n\nRules:\n1. Use only information explicitly stated in the content. Do not infer, guess, normalize, or add missing facts.\n2. The input may be only one chunk of a resume. Extract only what this content directly supports.\n3. Use only these field names:\ncandidate_name, gender, phone, email, city, location, nationality, linkedin, github, website, highest_degree, degree_levels, school_names, majors, graduation_years, work_experience_years, current_job_title, job_titles, company_names, job_experience, industries, target_job_titles, target_locations, employment_types, skills, certificates, awards, summary_tags\n4. Ignore detailed responsibilities, project descriptions, achievement narratives, self-evaluation, and other low-value local details.\n5. Keep values in the same language as the source text whenever possible.\n6. Remove duplicates and keep only concise, high-value metadata.\n7. Return only fields that are explicitly supported by the content. Do not return empty or unsupported fields.\n\nField guidance:\n- highest_degree: highest explicit degree level mentioned\n- degree_levels: all explicit degree levels mentioned\n- school_names: explicit school, college, or university names\n- majors: explicit fields of study\n- graduation_years: explicit graduation years only\n- work_experience_years: only if explicitly stated\n- current_job_title: only if explicitly current or most recent\n- job_titles: explicit role titles\n- company_names: explicit employer names\n- job_experience: concise structured work entries explicitly supported by the content, preferably including title, company, and time information when available\n- industries: explicit industry names only\n- target_job_titles: explicit desired roles only\n- target_locations: explicit desired work locations only\n- skills: concise, core, search-useful skills explicitly mentioned\n- certificates: explicit certificate names only\n- awards: explicit award names only\n- summary_tags: short, high-value tags strictly supported by the content\n\nReturn only the extracted metadata. Do not output explanatory text.", + "temperature": 0.1, + "temperatureEnabled": true, + "tenant_llm_id": 29, + "topPEnabled": true, + "top_p": 0.3 + }, + "label": "Extractor", + "name": "Auto Metadata" + }, + "dragging": false, + "id": "Extractor:ThreeDrinksAct", + "measured": { + "height": 90, + "width": 200 + }, + "position": { + "x": 583.3659219536569, + "y": 274.7600100230409 + }, + "selected": false, + "sourcePosition": "right", + "targetPosition": "left", + "type": "contextNode" + } + ] + }, + "history": [], + "messages": [], + "path": [], + "retrieval": [], + "variables": [] + }, + "avatar": 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" +} diff --git a/agent/templates/title_chunker.json b/agent/templates/title_chunker.json index 6c81ff0615..91e574e05c 100644 --- a/agent/templates/title_chunker.json +++ b/agent/templates/title_chunker.json @@ -14,9 +14,9 @@ "canvas_category": "dataflow_canvas", "dsl": { "components": { - "Extractor:PublicPlumsKiss": { + "Extractor:DryRatsGive": { "downstream": [ - "Tokenizer:FullBottlesDeny" + "Tokenizer:WackyOnionsFly" ], "obj": { "component_name": "Extractor", @@ -24,7 +24,7 @@ "field_name": "summary", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -37,20 +37,20 @@ "presence_penalty": 0.4, "prompts": [ { - "content": "Text to Summarize:\n[Insert text here]", + "content": "Text to Summarize:\n{TitleChunker:WideResultsTeach@chunks}", "role": "user" } ], "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 } }, "upstream": [ - "TokenChunker:FancyCitiesStick" + "TitleChunker:WideResultsTeach" ] }, "File": { @@ -65,7 +65,7 @@ }, "Parser:HipSignsRhyme": { "downstream": [ - "TokenChunker:FancyCitiesStick" + "TitleChunker:WideResultsTeach" ], "obj": { "component_name": "Parser", @@ -97,6 +97,7 @@ ] }, "docx": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -143,6 +144,7 @@ "system_prompt": "" }, "markdown": { + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content", "suffix": [ @@ -153,6 +155,7 @@ "vlm": {} }, "pdf": { + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -171,6 +174,7 @@ ] }, "spreadsheet": { + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content", @@ -208,33 +212,58 @@ "File" ] }, - "TokenChunker:FancyCitiesStick": { + "TitleChunker:WideResultsTeach": { "downstream": [ - "Extractor:PublicPlumsKiss" + "Extractor:DryRatsGive" ], "obj": { - "component_name": "TokenChunker", + "component_name": "TitleChunker", "params": { - "children_delimiters": [], - "chunk_token_size": 512, - "delimiter_mode": "token_size", - "delimiters": [], - "image_context_size": 0, - "outputs": { - "chunks": { - "type": "Array", - "value": [] - } - }, - "overlapped_percent": 0, - "table_context_size": 0 + "hierarchy": 3, + "include_heading_content": false, + "levels": [ + [ + "^#[^#]", + "^##[^#]", + "^###[^#]", + "^####[^#]" + ], + [ + "\u7b2c[\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e0-9]+(\u5206?\u7f16|\u90e8\u5206)", + "\u7b2c[\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e0-9]+\u7ae0", + "\u7b2c[\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e0-9]+\u8282", + "\u7b2c[\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e0-9]+\u6761", + "[\\(\uff08][\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e]+[\\)\uff09]" + ], + [ + "\u7b2c[0-9]+\u7ae0", + "\u7b2c[0-9]+\u8282", + "[0-9]{1,2}[\\. \u3001]", + "[0-9]{1,2}\\.[0-9]{1,2}($|[^a-zA-Z/%~.-])", + "[0-9]{1,2}\\.[0-9]{1,2}\\.[0-9]{1,2}" + ], + [ + "\u7b2c[\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e0-9]+\u7ae0", + "\u7b2c[\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e0-9]+\u8282", + "[\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e]+[ \u3001]", + "[\\(\uff08][\u96f6\u4e00\u4e8c\u4e09\u56db\u4e94\u516d\u4e03\u516b\u4e5d\u5341\u767e]+[\\)\uff09]", + "[\\(\uff08][0-9]{,2}[\\)\uff09]" + ], + [ + "PART (ONE|TWO|THREE|FOUR|FIVE|SIX|SEVEN|EIGHT|NINE|TEN)", + "Chapter (I+V?|VI*|XI|IX|X)", + "Section [0-9]+", + "Article [0-9]+" + ] + ], + "method": "hierarchy" } }, "upstream": [ "Parser:HipSignsRhyme" ] }, - "Tokenizer:FullBottlesDeny": { + "Tokenizer:WackyOnionsFly": { "downstream": [], "obj": { "component_name": "Tokenizer", @@ -249,17 +278,12 @@ } }, "upstream": [ - "Extractor:PublicPlumsKiss" + "Extractor:DryRatsGive" ] } }, "globals": { - "sys.conversation_turns": 0, - "sys.date": "", - "sys.files": [], - "sys.history": [], - "sys.query": "", - "sys.user_id": "" + "sys.history": [] }, "graph": { "edges": [ @@ -271,27 +295,24 @@ "targetHandle": "end" }, { - "id": "xy-edge__Parser:HipSignsRhymestart-TokenChunker:FancyCitiesStickend", + "id": "xy-edge__Parser:HipSignsRhymestart-TitleChunker:WideResultsTeachend", "source": "Parser:HipSignsRhyme", "sourceHandle": "start", - "target": "TokenChunker:FancyCitiesStick", + "target": "TitleChunker:WideResultsTeach", "targetHandle": "end" }, { - "data": { - "isHovered": false - }, - "id": "xy-edge__TokenChunker:FancyCitiesStickstart-Extractor:PublicPlumsKissend", - "source": "TokenChunker:FancyCitiesStick", + "id": "xy-edge__TitleChunker:WideResultsTeachstart-Extractor:DryRatsGiveend", + "source": "TitleChunker:WideResultsTeach", "sourceHandle": "start", - "target": "Extractor:PublicPlumsKiss", + "target": "Extractor:DryRatsGive", "targetHandle": "end" }, { - "id": "xy-edge__Extractor:PublicPlumsKissstart-Tokenizer:FullBottlesDenyend", - "source": "Extractor:PublicPlumsKiss", + "id": "xy-edge__Extractor:DryRatsGivestart-Tokenizer:WackyOnionsFlyend", + "source": "Extractor:DryRatsGive", "sourceHandle": "start", - "target": "Tokenizer:FullBottlesDeny", + "target": "Tokenizer:WackyOnionsFly", "targetHandle": "end" } ], @@ -303,7 +324,7 @@ }, "id": "File", "measured": { - "height": 49, + "height": 50, "width": 200 }, "position": { @@ -338,12 +359,14 @@ "setups": [ { "fileFormat": "pdf", + "flatten_media_to_text": false, "output_format": "json", "parse_method": "DeepDOC", "preprocess": "main_content" }, { "fileFormat": "spreadsheet", + "flatten_media_to_text": false, "output_format": "html", "parse_method": "DeepDOC", "preprocess": "main_content" @@ -372,6 +395,7 @@ }, { "fileFormat": "markdown", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -392,6 +416,7 @@ }, { "fileFormat": "docx", + "flatten_media_to_text": false, "output_format": "json", "preprocess": "main_content" }, @@ -424,28 +449,113 @@ { "data": { "form": { - 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"label": "TokenChunker", - "name": "Token Chunker_0" + "label": "TitleChunker", + "name": "Title Chunker_0" }, - "id": "TokenChunker:FancyCitiesStick", + "id": "TitleChunker:WideResultsTeach", "measured": { - "height": 73, + "height": 74, "width": 200 }, "position": { @@ -462,7 +572,7 @@ "field_name": "summary", "frequencyPenaltyEnabled": true, "frequency_penalty": 0.7, - "llm_id": "Qwen/Qwen3-8B@SILICONFLOW", + "llm_id": "THUDM/GLM-4.1V-9B-Thinking@SILICONFLOW", "maxTokensEnabled": false, "max_tokens": 256, "outputs": { @@ -473,27 +583,27 @@ }, "presencePenaltyEnabled": true, "presence_penalty": 0.4, - "prompts": "Text to Summarize:\n[Insert text here]", + "prompts": "Text to Summarize:\n{TitleChunker:WideResultsTeach@chunks}", "sys_prompt": "Act as a precise summarizer. Your task is to create a summary of the provided content that is both concise and faithful to the original.\n\nKey Instructions:\n1. Accuracy: Strictly base the summary on the information given. Do not introduce any new facts, conclusions, or interpretations that are not explicitly stated.\n2. Language: Write the summary in the same language as the source text.\n3. Objectivity: Present the key points without bias, preserving the original intent and tone of the content. Do not editorialize.\n4. Conciseness: Focus on the most important ideas, omitting minor details and fluff.", "temperature": 0.1, "temperatureEnabled": true, - "tenant_llm_id": 54, + "tenant_llm_id": 63, "topPEnabled": true, "top_p": 0.3 }, "label": "Extractor", - "name": "Summarizer" + "name": "Transformer_0" }, - "id": "Extractor:PublicPlumsKiss", + "id": "Extractor:DryRatsGive", "measured": { - "height": 89, + "height": 90, "width": 200 }, "position": { "x": 916.9952409420641, "y": 195.39629819663406 }, - "selected": false, + "selected": true, "sourcePosition": "right", "targetPosition": "left", "type": "contextNode" @@ -512,9 +622,9 @@ "label": "Tokenizer", "name": "Indexer_0" }, - "id": "Tokenizer:FullBottlesDeny", + "id": "Tokenizer:WackyOnionsFly", "measured": { - "height": 113, + "height": 114, "width": 200 }, "position": { @@ -524,34 +634,11 @@ "sourcePosition": "right", "targetPosition": "left", "type": "tokenizerNode" - }, - { - "data": { - "form": { - "text": "Using summary to build both text and vector indexes." - }, - "label": "Note", - "name": "Index Summary" - }, - "dragHandle": ".note-drag-handle", - "dragging": false, - "id": "Note:ElevenKingsPick", - "measured": { - "height": 127, - "width": 267 - }, - "position": { - "x": 735.9586746349814, - "y": 315.614230763182 - }, - "selected": true, - "sourcePosition": "right", - "targetPosition": "left", - "type": "noteNode" } ] }, "history": [], + "messages": [], "path": [], "retrieval": [], "variables": [] diff --git a/rag/flow/chunker/title_chunker/common.py b/rag/flow/chunker/title_chunker/common.py index e3f3a2642a..e02389aa87 100644 --- a/rag/flow/chunker/title_chunker/common.py +++ b/rag/flow/chunker/title_chunker/common.py @@ -222,7 +222,7 @@ class BaseTitleChunker(ABC): if level < BODY_LEVEL: most_level = level break - + return { "levels": levels, "most_level": most_level,