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Add CAJAL scientific paper agent template (#14641)
### What problem does this PR solve? Closes https://github.com/infiniflow/ragflow/issues/14571. Adds CAJAL as a first-class local scientific-writing option in RAGFlow: - registers `agnuxo/cajal-4b-p2pclaw` as a known Ollama chat model with a 32K context setting - adds a built-in “CAJAL scientific paper agent” template under the existing agent template catalog - preconfigures the agent for grounded scientific writing: retrieval first, citation traceability, LaTeX-ready output, and explicit limitations when evidence is missing - adds unit coverage to ensure the template normalizes through RAGFlow’s production template loader, keeps graph form data in sync, and exposes the Ollama model option Behavior/evidence gathered for the requested model: - Hugging Face model metadata for `Agnuxo/CAJAL-4B-P2PCLAW` reports `pipeline_tag=text-generation` and tags including `gguf`, `llama.cpp`, `vllm`, `scientific-research`, `papers`, `academic-writing`, `latex`, and `license:apache-2.0`. - The model card documents CAJAL as a 4B scientific paper generation model with 32K context, local inference, LaTeX/citation specialization, and CPU-only support around 5 tok/s on Ryzen 7 5800X. - Local CPU generation could not be completed on this machine because the advertised Ollama model name is not currently resolvable from Ollama’s registry: both `https://registry.ollama.ai/v2/agnuxo/cajal-4b-p2pclaw/manifests/latest` and `https://registry.ollama.ai/v2/library/agnuxo/cajal-4b-p2pclaw/manifests/latest` returned `404 Not Found`; the Hugging Face repo tree currently exposes an 8.4 GB `model.safetensors` but no GGUF artifact in `main`. The template therefore targets the documented Ollama model name for users who have the local CAJAL deployment/model file available. Verification run locally: ```bash python3 -m pytest test/test_cajal_template_unit.py -q # 3 passed in 0.34s python3 - <<'PY' import json, glob for f in sorted(glob.glob('agent/templates/*.json') + ['conf/llm_factories.json']): with open(f, encoding='utf-8') as fp: json.load(fp) print('json_ok') PY # json_ok python3 -m ruff check test/test_cajal_template_unit.py # All checks passed! git diff --check ``` `uv run pytest test/testcases/test_web_api/test_agent_app/test_cajal_template_unit.py -q` was also attempted first, but dependency setup failed before test collection while building `ormsgpack==1.5.0` from uv with a package metadata parse error. Clearing uv’s `ormsgpack` cache and retrying reproduced the same build failure, so the focused unit test was run with the system Python environment instead. ### Type of change - [ ] Bug Fix (non-breaking change which fixes an issue) - [x] New Feature (non-breaking change which adds functionality) - [ ] Documentation Update - [ ] Refactoring - [ ] Performance Improvement - [ ] Other (please describe): --------- Co-authored-by: sxxtony <sxxtony@users.noreply.github.com> Co-authored-by: yzc <yzc@users.noreply.github.com> Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
This commit is contained in:
sxxtony
304
agent/templates/cajal_scientific_paper_agent.json
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304
agent/templates/cajal_scientific_paper_agent.json
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{
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"id": "41",
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"title": {
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"en": "CAJAL scientific paper agent",
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"de": "CAJAL-Agent für wissenschaftliche Arbeiten",
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"zh": "CAJAL 科学论文助手"
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},
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"description": {
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"en": "A local-first scientific paper generation agent for RAGFlow. It is preconfigured for Agnuxo/CAJAL-4B-P2PCLAW through Ollama, retrieves knowledge-base evidence, and drafts citation-grounded LaTeX-ready academic sections.",
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"de": "Ein lokal ausgerichteter Agent zur Erstellung wissenschaftlicher Arbeiten in RAGFlow. Er ist für Agnuxo/CAJAL-4B-P2PCLAW über Ollama vorkonfiguriert, ruft Evidenz aus der Wissensdatenbank ab und erstellt zitationsgestützte, LaTeX-fähige akademische Abschnitte.",
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"zh": "面向 RAGFlow 的本地优先科学论文生成助手。该模板预配置 Agnuxo/CAJAL-4B-P2PCLAW（Ollama），可检索知识库证据，并生成带引用依据、适合 LaTeX 的学术章节。"
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},
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"canvas_type": "Agent",
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"canvas_types": [
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"Agent",
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"Recommended"
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],
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"dsl": {
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"components": {
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"Agent:NewPumasLick": {
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"downstream": [
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"Message:OrangeYearsShine"
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],
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"obj": {
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"component_name": "Agent",
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"params": {
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"delay_after_error": 1,
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"description": "",
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"exception_comment": "",
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"exception_default_value": "",
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"exception_goto": [],
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"exception_method": null,
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"frequencyPenaltyEnabled": false,
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"frequency_penalty": 0.5,
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"llm_id": "agnuxo/cajal-4b-p2pclaw@Ollama",
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"maxTokensEnabled": true,
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"max_retries": 3,
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"max_rounds": 3,
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"max_tokens": 32768,
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"mcp": [],
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"message_history_window_size": 12,
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"outputs": {
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"content": {
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"type": "string",
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"value": ""
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}
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},
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"parameter": "Precise",
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"presencePenaltyEnabled": false,
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"presence_penalty": 0.5,
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"prompts": [
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{
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"role": "user",
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"content": "# Research request\n{sys.query}\n\nUse the configured knowledge base retrieval tool before drafting. If no evidence is retrieved, state that limitation clearly."
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}
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],
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"sys_prompt": "## Role & Task\nYou are **CAJAL**, a local-first scientific writing agent specialized in citation-grounded paper generation.\n\nUse RAGFlow retrieval results as the source of truth. Write precise academic content that can be pasted into a paper draft, technical report, or LaTeX manuscript. You are optimized for the local GGUF model `Agnuxo/CAJAL-4B-P2PCLAW` served through Ollama as `agnuxo/cajal-4b-p2pclaw`.\n\n## Operating Rules\n1. Decompose the user request into research goals, target section type, expected citation style, and missing evidence.\n2. Retrieve relevant knowledge-base passages before drafting factual claims.\n3. Ground every substantive claim in retrieved evidence. If evidence is missing, mark it as a limitation instead of inventing a citation.\n4. Prefer structured scientific writing: abstract, introduction, related work, methodology, experiments, results, limitations, and conclusion.\n5. Use LaTeX formatting for equations, symbols, algorithms, tables, and section headings when it helps the manuscript.\n6. Preserve traceability: cite source titles, document names, page numbers, or chunk identifiers when available in retrieved context.\n7. Keep language technical, concise, and reproducible. Avoid marketing language and vague generalizations.\n\n## Output Contract\nReturn one of the following, depending on the user request:\n- A complete paper section with citation markers and a short evidence map.\n- A literature review organized by themes, methods, findings, and gaps.\n- A methodology or experiment section with reproducible steps, assumptions, and limitations.\n- A LaTeX-ready abstract, introduction, or conclusion.\n\nAlways include:\n- **Draft**: the requested scientific content.\n- **Evidence used**: concise bullets mapping claims to retrieved sources.\n- **Limitations**: missing evidence, weak support, or assumptions that require verification.\n",
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"temperature": 0.2,
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"temperatureEnabled": true,
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"tools": [
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{
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"component_name": "Retrieval",
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"name": "Retrieval",
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"params": {
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"cross_languages": [],
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"description": "Retrieve papers, reports, datasets, and notes that ground CAJAL scientific writing outputs.",
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"empty_response": "",
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"kb_ids": [],
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"keywords_similarity_weight": 0.7,
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"outputs": {
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"formalized_content": {
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"type": "string",
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"value": ""
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}
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},
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"rerank_id": "",
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"similarity_threshold": 0.2,
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"top_k": 1024,
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"top_n": 10,
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"use_kg": false
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}
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}
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],
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"topPEnabled": false,
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"top_p": 0.75,
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"user_prompt": "",
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"visual_files_var": ""
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}
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},
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"upstream": [
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"begin"
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]
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},
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"Message:OrangeYearsShine": {
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"downstream": [],
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"obj": {
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"component_name": "Message",
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"params": {
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"content": [
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"{Agent:NewPumasLick@content}"
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]
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}
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},
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"upstream": [
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"Agent:NewPumasLick"
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]
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},
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"begin": {
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"downstream": [
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"Agent:NewPumasLick"
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],
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"obj": {
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"component_name": "Begin",
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"params": {
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"enablePrologue": true,
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"inputs": {},
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"mode": "conversational",
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"prologue": "Hi, I am CAJAL in RAGFlow. Add research papers or datasets to your knowledge base, then ask me to draft a citation-grounded paper section, literature review, methodology, or LaTeX-ready abstract."
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}
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},
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"upstream": []
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}
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},
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"globals": {
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"sys.conversation_turns": 0,
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"sys.files": [],
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"sys.query": "",
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"sys.user_id": ""
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},
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"graph": {
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"edges": [
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{
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"data": {
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"isHovered": false
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},
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"id": "xy-edge__beginstart-Agent:NewPumasLickend",
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"source": "begin",
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"sourceHandle": "start",
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"target": "Agent:NewPumasLick",
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"targetHandle": "end"
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},
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{
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"data": {
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"isHovered": false
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},
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"id": "xy-edge__Agent:NewPumasLickstart-Message:OrangeYearsShineend",
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"markerEnd": "logo",
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"source": "Agent:NewPumasLick",
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"sourceHandle": "start",
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"style": {
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"stroke": "rgba(91, 93, 106, 1)",
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"strokeWidth": 1
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},
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"target": "Message:OrangeYearsShine",
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"targetHandle": "end",
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"type": "buttonEdge",
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"zIndex": 1001
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}
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],
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"nodes": [
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{
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"data": {
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"form": {
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"enablePrologue": true,
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"inputs": {},
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"mode": "conversational",
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"prologue": "Hi, I am CAJAL in RAGFlow. Add research papers or datasets to your knowledge base, then ask me to draft a citation-grounded paper section, literature review, methodology, or LaTeX-ready abstract."
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},
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"label": "Begin",
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"name": "begin"
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},
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"dragging": false,
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"id": "begin",
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"measured": {
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"height": 48,
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"width": 200
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},
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"position": {
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"x": -9.569875358221438,
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"y": 205.84018385864917
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},
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"selected": false,
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"sourcePosition": "left",
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"targetPosition": "right",
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"type": "beginNode"
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},
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{
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"data": {
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"form": {
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"content": [
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"{Agent:NewPumasLick@content}"
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]
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},
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"label": "Scientific Draft",
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"name": "Response"
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},
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"dragging": false,
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"id": "Message:OrangeYearsShine",
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"measured": {
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"height": 56,
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"width": 200
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"position": {
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"x": 734.4061285881053,
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"y": 199.9706031723009
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},
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"selected": false,
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"sourcePosition": "right",
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"targetPosition": "left",
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"type": "messageNode"
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},
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{
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"data": {
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"form": {
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"delay_after_error": 1,
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"description": "",
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"exception_comment": "",
|
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"exception_default_value": "",
|
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"exception_goto": [],
|
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"exception_method": null,
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"frequencyPenaltyEnabled": false,
|
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"frequency_penalty": 0.5,
|
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"llm_id": "agnuxo/cajal-4b-p2pclaw@Ollama",
|
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"maxTokensEnabled": true,
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"max_retries": 3,
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"max_rounds": 3,
|
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"max_tokens": 32768,
|
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"mcp": [],
|
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"message_history_window_size": 12,
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"outputs": {
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"content": {
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"type": "string",
|
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"value": ""
|
||||
}
|
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},
|
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"parameter": "Precise",
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"presencePenaltyEnabled": false,
|
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"presence_penalty": 0.5,
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"prompts": [
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{
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"role": "user",
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"content": "# Research request\n{sys.query}\n\nUse the configured knowledge base retrieval tool before drafting. If no evidence is retrieved, state that limitation clearly."
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}
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],
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"sys_prompt": "## Role & Task\nYou are **CAJAL**, a local-first scientific writing agent specialized in citation-grounded paper generation.\n\nUse RAGFlow retrieval results as the source of truth. Write precise academic content that can be pasted into a paper draft, technical report, or LaTeX manuscript. You are optimized for the local GGUF model `Agnuxo/CAJAL-4B-P2PCLAW` served through Ollama as `agnuxo/cajal-4b-p2pclaw`.\n\n## Operating Rules\n1. Decompose the user request into research goals, target section type, expected citation style, and missing evidence.\n2. Retrieve relevant knowledge-base passages before drafting factual claims.\n3. Ground every substantive claim in retrieved evidence. If evidence is missing, mark it as a limitation instead of inventing a citation.\n4. Prefer structured scientific writing: abstract, introduction, related work, methodology, experiments, results, limitations, and conclusion.\n5. Use LaTeX formatting for equations, symbols, algorithms, tables, and section headings when it helps the manuscript.\n6. Preserve traceability: cite source titles, document names, page numbers, or chunk identifiers when available in retrieved context.\n7. Keep language technical, concise, and reproducible. Avoid marketing language and vague generalizations.\n\n## Output Contract\nReturn one of the following, depending on the user request:\n- A complete paper section with citation markers and a short evidence map.\n- A literature review organized by themes, methods, findings, and gaps.\n- A methodology or experiment section with reproducible steps, assumptions, and limitations.\n- A LaTeX-ready abstract, introduction, or conclusion.\n\nAlways include:\n- **Draft**: the requested scientific content.\n- **Evidence used**: concise bullets mapping claims to retrieved sources.\n- **Limitations**: missing evidence, weak support, or assumptions that require verification.\n",
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"temperature": 0.2,
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"temperatureEnabled": true,
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"tools": [
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{
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"component_name": "Retrieval",
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"name": "Retrieval",
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"params": {
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"cross_languages": [],
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"description": "Retrieve papers, reports, datasets, and notes that ground CAJAL scientific writing outputs.",
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"empty_response": "",
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"kb_ids": [],
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"keywords_similarity_weight": 0.7,
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"outputs": {
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"formalized_content": {
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"type": "string",
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"value": ""
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}
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},
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"rerank_id": "",
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"similarity_threshold": 0.2,
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"top_k": 1024,
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"top_n": 10,
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"use_kg": false
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}
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}
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],
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"topPEnabled": false,
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"top_p": 0.75,
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"user_prompt": "",
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"visual_files_var": ""
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},
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"label": "CAJAL Writer",
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"name": "Knowledge Base Agent"
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},
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"dragging": false,
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"id": "Agent:NewPumasLick",
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"measured": {
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"height": 84,
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"width": 200
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},
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"position": {
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"x": 347.00048227952215,
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"y": 186.49109364794631
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},
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"selected": false,
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"sourcePosition": "right",
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"targetPosition": "left",
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"type": "agentNode"
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}
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]
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},
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"history": [],
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"memory": [],
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"messages": [],
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"path": [],
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"retrieval": []
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},
|
||||
"avatar": "data:image/png;base64,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"
|
||||
}
|
||||
@@ -1759,8 +1759,16 @@
|
||||
"logo": "",
|
||||
"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
|
||||
"status": "1",
|
||||
"rank": "988",
|
||||
"llm": []
|
||||
"rank": "830",
|
||||
"llm": [
|
||||
{
|
||||
"llm_name": "agnuxo/cajal-4b-p2pclaw",
|
||||
"tags": "LLM,CHAT,32K,SCIENTIFIC_WRITING",
|
||||
"max_tokens": 32768,
|
||||
"model_type": "chat",
|
||||
"is_tools": false
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "ModelScope",
|
||||
|
||||
79
test/test_cajal_template_unit.py
Normal file
79
test/test_cajal_template_unit.py
Normal file
@@ -0,0 +1,79 @@
|
||||
#
|
||||
# Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
#
|
||||
import json
|
||||
import importlib.util
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def _load_template_utils():
|
||||
repo_root = Path(__file__).resolve().parents[1]
|
||||
module_path = repo_root / "api" / "db" / "template_utils.py"
|
||||
spec = importlib.util.spec_from_file_location("template_utils", module_path)
|
||||
module = importlib.util.module_from_spec(spec)
|
||||
spec.loader.exec_module(module)
|
||||
return module
|
||||
|
||||
|
||||
def _load_cajal_template():
|
||||
repo_root = Path(__file__).resolve().parents[1]
|
||||
template_path = repo_root / "agent" / "templates" / "cajal_scientific_paper_agent.json"
|
||||
with template_path.open(encoding="utf-8") as template_file:
|
||||
return _load_template_utils().normalize_canvas_template_categories(json.load(template_file))
|
||||
|
||||
|
||||
def test_cajal_template_exposes_local_ollama_model_and_agent_categories():
|
||||
template = _load_cajal_template()
|
||||
|
||||
assert template["id"] == "41"
|
||||
assert template["title"]["en"] == "CAJAL scientific paper agent"
|
||||
assert template["canvas_type"] == "Agent"
|
||||
assert template["canvas_types"] == ["Agent", "Recommended"]
|
||||
|
||||
agent_params = template["dsl"]["components"]["Agent:NewPumasLick"]["obj"]["params"]
|
||||
assert agent_params["llm_id"] == "agnuxo/cajal-4b-p2pclaw@Ollama"
|
||||
assert agent_params["max_tokens"] == 32768
|
||||
assert "Agnuxo/CAJAL-4B-P2PCLAW" in agent_params["sys_prompt"]
|
||||
assert "LaTeX" in agent_params["sys_prompt"]
|
||||
|
||||
|
||||
def test_cajal_template_keeps_retrieval_grounding_and_graph_form_in_sync():
|
||||
template = _load_cajal_template()
|
||||
agent_params = template["dsl"]["components"]["Agent:NewPumasLick"]["obj"]["params"]
|
||||
retrieval_tools = [tool for tool in agent_params["tools"] if tool["component_name"] == "Retrieval"]
|
||||
|
||||
assert len(retrieval_tools) == 1
|
||||
assert retrieval_tools[0]["params"]["top_n"] == 10
|
||||
assert "ground" in retrieval_tools[0]["params"]["description"].lower()
|
||||
assert "{sys.query}" in agent_params["prompts"][0]["content"]
|
||||
|
||||
agent_node = next(node for node in template["dsl"]["graph"]["nodes"] if node["id"] == "Agent:NewPumasLick")
|
||||
begin_node = next(node for node in template["dsl"]["graph"]["nodes"] if node["id"] == "begin")
|
||||
|
||||
assert agent_node["data"]["form"]["llm_id"] == agent_params["llm_id"]
|
||||
assert agent_node["data"]["form"]["sys_prompt"] == agent_params["sys_prompt"]
|
||||
assert "CAJAL" in begin_node["data"]["form"]["prologue"]
|
||||
|
||||
|
||||
def test_cajal_is_registered_as_a_known_ollama_chat_model():
|
||||
repo_root = Path(__file__).resolve().parents[1]
|
||||
factories_path = repo_root / "conf" / "llm_factories.json"
|
||||
factories = json.loads(factories_path.read_text(encoding="utf-8"))
|
||||
ollama = next(factory for factory in factories["factory_llm_infos"] if factory["name"] == "Ollama")
|
||||
cajal = next(model for model in ollama["llm"] if model["llm_name"] == "agnuxo/cajal-4b-p2pclaw")
|
||||
|
||||
assert cajal["model_type"] == "chat"
|
||||
assert cajal["max_tokens"] == 32768
|
||||
assert "SCIENTIFIC_WRITING" in cajal["tags"]
|
||||
Reference in New Issue
Block a user