pengjunjie/ragflow
1
0
Fork 1
mirror of https://github.com/infiniflow/ragflow.git synced 2025-12-08 20:42:30 +08:00
Code Issues Packages Projects Releases Wiki Activity

Refa: add result to callback for agent tool use. (#9137)

Browse Source 
### What problem does this PR solve?


### Type of change

- [x] Refactoring
This commit is contained in:
Kevin Hu
2025-08-01 21:49:39 +08:00
committed by GitHub
parent c5823a33a3
commit a16cd4f110
26 changed files with 10875 additions and 897 deletions
Download Patch File Download Diff File Expand all files Collapse all files

89
agent/canvas.py
View File

@ -252,15 +252,6 @@ class Canvas:
"created_at": cpn_obj.output("_created_time"), "created_at": cpn_obj.output("_created_time"),
}) })
def _append_path(cpn_id):
if self.path[-1] == cpn_id:
return
self.path.append(cpn_id)
def _extend_path(cpn_ids):
for cpn_id in cpn_ids:
_append_path(cpn_id)
self.error = "" self.error = ""
idx = len(self.path) - 1 idx = len(self.path) - 1
partials = [] partials = []
@ -279,10 +270,11 @@ class Canvas:
# post processing of components invocation # post processing of components invocation
for i in range(idx, to): for i in range(idx, to):
cpn = self.get_component(self.path[i]) cpn = self.get_component(self.path[i])
if cpn["obj"].component_name.lower() == "message": cpn_obj = self.get_component_obj(self.path[i])
if isinstance(cpn["obj"].output("content"), partial): if cpn_obj.component_name.lower() == "message":
if isinstance(cpn_obj.output("content"), partial):
_m = "" _m = ""
for m in cpn["obj"].output("content")(): for m in cpn_obj.output("content")():
if not m: if not m:
continue continue
if m == "<think>": if m == "<think>":
@ -292,48 +284,65 @@ class Canvas:
else: else:
yield decorate("message", {"content": m}) yield decorate("message", {"content": m})
_m += m _m += m
cpn["obj"].set_output("content", _m) cpn_obj.set_output("content", _m)
else: else:
yield decorate("message", {"content": cpn["obj"].output("content")}) yield decorate("message", {"content": cpn_obj.output("content")})
yield decorate("message_end", {"reference": self.get_reference()}) yield decorate("message_end", {"reference": self.get_reference()})
while partials: while partials:
_cpn = self.get_component(partials[0]) _cpn_obj = self.get_component_obj(partials[0])
if isinstance(_cpn["obj"].output("content"), partial): if isinstance(_cpn_obj.output("content"), partial):
break break
yield _node_finished(_cpn["obj"]) yield _node_finished(_cpn_obj)
partials.pop(0) partials.pop(0)
if cpn["obj"].error(): other_branch = False
ex = cpn["obj"].exception_handler() if cpn_obj.error():
if ex and ex["comment"]: ex = cpn_obj.exception_handler()
yield decorate("message", {"content": ex["comment"]})
yield decorate("message_end", {})
if ex and ex["goto"]: if ex and ex["goto"]:
self.path.append(ex["goto"]) self.path.extend(ex["goto"])
elif not ex or not ex["default_value"]: other_branch = True
self.error = cpn["obj"].error() elif ex and ex["default_value"]:
yield decorate("message", {"content": ex["default_value"]})
yield decorate("message_end", {})
else:
self.error = cpn_obj.error()
if cpn["obj"].component_name.lower() != "iteration": if cpn_obj.component_name.lower() != "iteration":
if isinstance(cpn["obj"].output("content"), partial): if isinstance(cpn_obj.output("content"), partial):
if self.error: if self.error:
cpn["obj"].set_output("content", None) cpn_obj.set_output("content", None)
yield _node_finished(cpn["obj"]) yield _node_finished(cpn_obj)
else: else:
partials.append(self.path[i]) partials.append(self.path[i])
else: else:
yield _node_finished(cpn["obj"]) yield _node_finished(cpn_obj)
if cpn["obj"].component_name.lower() == "iterationitem" and cpn["obj"].end(): def _append_path(cpn_id):
iter = cpn["obj"].get_parent() nonlocal other_branch
if other_branch:
return
if self.path[-1] == cpn_id:
return
self.path.append(cpn_id)
def _extend_path(cpn_ids):
nonlocal other_branch
if other_branch:
return
for cpn_id in cpn_ids:
_append_path(cpn_id)
if cpn_obj.component_name.lower() == "iterationitem" and cpn_obj.end():
iter = cpn_obj.get_parent()
yield _node_finished(iter) yield _node_finished(iter)
_extend_path(self.get_component(cpn["parent_id"])["downstream"]) _extend_path(self.get_component(cpn["parent_id"])["downstream"])
elif cpn["obj"].component_name.lower() in ["categorize", "switch"]: elif cpn_obj.component_name.lower() in ["categorize", "switch"]:
_extend_path(cpn["obj"].output("_next")) _extend_path(cpn_obj.output("_next"))
elif cpn["obj"].component_name.lower() == "iteration": elif cpn_obj.component_name.lower() == "iteration":
_append_path(cpn["obj"].get_start()) _append_path(cpn_obj.get_start())
elif not cpn["downstream"] and cpn["obj"].get_parent(): elif not cpn["downstream"] and cpn_obj.get_parent():
_append_path(cpn["obj"].get_parent().get_start()) _append_path(cpn_obj.get_parent().get_start())
else: else:
_extend_path(cpn["downstream"]) _extend_path(cpn["downstream"])
@ -342,13 +351,13 @@ class Canvas:
break break
idx = to idx = to
if any([self.get_component(c)["obj"].component_name.lower() == "userfillup" for c in self.path[idx:]]): if any([self.get_component_obj(c).component_name.lower() == "userfillup" for c in self.path[idx:]]):
path = [c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() == "userfillup"] path = [c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() == "userfillup"]
path.extend([c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() != "userfillup"]) path.extend([c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() != "userfillup"])
another_inputs = {} another_inputs = {}
tips = "" tips = ""
for c in path: for c in path:
o = self.get_component(c)["obj"] o = self.get_component_obj(c)
if o.component_name.lower() == "userfillup": if o.component_name.lower() == "userfillup":
another_inputs.update(o.get_input_elements()) another_inputs.update(o.get_input_elements())
if o.get_param("enable_tips"): if o.get_param("enable_tips"):

23
agent/component/agent_with_tools.py
View File

@ -157,7 +157,8 @@ class Agent(LLM, ToolBase):
prompt, msg = self._prepare_prompt_variables() prompt, msg = self._prepare_prompt_variables()
downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else [] downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not self._param.output_structure: ex = self.exception_handler()
if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not self._param.output_structure and not (ex and ex["goto"]):
self.set_output("content", partial(self.stream_output_with_tools, prompt, msg)) self.set_output("content", partial(self.stream_output_with_tools, prompt, msg))
return return
@ -169,6 +170,9 @@ class Agent(LLM, ToolBase):
if ans.find("**ERROR**") >= 0: if ans.find("**ERROR**") >= 0:
logging.error(f"Agent._chat got error. response: {ans}") logging.error(f"Agent._chat got error. response: {ans}")
if self.get_exception_default_value():
self.set_output("content", self.get_exception_default_value())
else:
self.set_output("_ERROR", ans) self.set_output("_ERROR", ans)
return return
@ -182,6 +186,12 @@ class Agent(LLM, ToolBase):
answer_without_toolcall = "" answer_without_toolcall = ""
use_tools = [] use_tools = []
for delta_ans,_ in self._react_with_tools_streamly(msg, use_tools): for delta_ans,_ in self._react_with_tools_streamly(msg, use_tools):
if delta_ans.find("**ERROR**") >= 0:
if self.get_exception_default_value():
self.set_output("content", self.get_exception_default_value())
yield self.get_exception_default_value()
else:
self.set_output("_ERROR", delta_ans)
answer_without_toolcall += delta_ans answer_without_toolcall += delta_ans
yield delta_ans yield delta_ans
@ -204,8 +214,8 @@ class Agent(LLM, ToolBase):
hist = deepcopy(history) hist = deepcopy(history)
last_calling = "" last_calling = ""
if len(hist) > 3: if len(hist) > 3:
self.callback("Multi-turn conversation optimization", {}, " running ...")
user_request = full_question(messages=history, chat_mdl=self.chat_mdl) user_request = full_question(messages=history, chat_mdl=self.chat_mdl)
self.callback("Multi-turn conversation optimization", {}, user_request)
else: else:
user_request = history[-1]["content"] user_request = history[-1]["content"]
@ -241,9 +251,6 @@ class Agent(LLM, ToolBase):
cited = True cited = True
yield "", token_count yield "", token_count
if not cited and need2cite:
self.callback("gen_citations", {}, " running ...")
_hist = hist _hist = hist
if len(hist) > 12: if len(hist) > 12:
_hist = [hist[0], hist[1], *hist[-10:]] _hist = [hist[0], hist[1], *hist[-10:]]
@ -255,8 +262,12 @@ class Agent(LLM, ToolBase):
if not need2cite or cited: if not need2cite or cited:
return return
txt = ""
for delta_ans in self._gen_citations(entire_txt): for delta_ans in self._gen_citations(entire_txt):
yield delta_ans, 0 yield delta_ans, 0
txt += delta_ans
self.callback("gen_citations", {}, txt)
def append_user_content(hist, content): def append_user_content(hist, content):
if hist[-1]["role"] == "user": if hist[-1]["role"] == "user":
@ -264,8 +275,8 @@ class Agent(LLM, ToolBase):
else: else:
hist.append({"role": "user", "content": content}) hist.append({"role": "user", "content": content})
self.callback("analyze_task", {}, " running ...")
task_desc = analyze_task(self.chat_mdl, user_request, tool_metas) task_desc = analyze_task(self.chat_mdl, user_request, tool_metas)
self.callback("analyze_task", {}, task_desc)
for _ in range(self._param.max_rounds + 1): for _ in range(self._param.max_rounds + 1):
response, tk = next_step(self.chat_mdl, hist, tool_metas, task_desc) response, tk = next_step(self.chat_mdl, hist, tool_metas, task_desc)
# self.callback("next_step", {}, str(response)[:256]+"...") # self.callback("next_step", {}, str(response)[:256]+"...")

26
agent/component/base.py
View File

@ -44,7 +44,6 @@ class ComponentParamBase(ABC):
self.delay_after_error = 2.0 self.delay_after_error = 2.0
self.exception_method = None self.exception_method = None
self.exception_default_value = None self.exception_default_value = None
self.exception_comment = None
self.exception_goto = None self.exception_goto = None
self.debug_inputs = {} self.debug_inputs = {}
@ -97,6 +96,14 @@ class ComponentParamBase(ABC):
def as_dict(self): def as_dict(self):
def _recursive_convert_obj_to_dict(obj): def _recursive_convert_obj_to_dict(obj):
ret_dict = {} ret_dict = {}
if isinstance(obj, dict):
for k,v in obj.items():
if isinstance(v, dict) or (v and type(v).__name__ not in dir(builtins)):
ret_dict[k] = _recursive_convert_obj_to_dict(v)
else:
ret_dict[k] = v
return ret_dict
for attr_name in list(obj.__dict__): for attr_name in list(obj.__dict__):
if attr_name in [_FEEDED_DEPRECATED_PARAMS, _DEPRECATED_PARAMS, _USER_FEEDED_PARAMS, _IS_RAW_CONF]: if attr_name in [_FEEDED_DEPRECATED_PARAMS, _DEPRECATED_PARAMS, _USER_FEEDED_PARAMS, _IS_RAW_CONF]:
continue continue
@ -105,7 +112,7 @@ class ComponentParamBase(ABC):
if isinstance(attr, pd.DataFrame): if isinstance(attr, pd.DataFrame):
ret_dict[attr_name] = attr.to_dict() ret_dict[attr_name] = attr.to_dict()
continue continue
if attr and type(attr).__name__ not in dir(builtins): if isinstance(attr, dict) or (attr and type(attr).__name__ not in dir(builtins)):
ret_dict[attr_name] = _recursive_convert_obj_to_dict(attr) ret_dict[attr_name] = _recursive_convert_obj_to_dict(attr)
else: else:
ret_dict[attr_name] = attr ret_dict[attr_name] = attr
@ -415,7 +422,10 @@ class ComponentBase(ABC):
try: try:
self._invoke(**kwargs) self._invoke(**kwargs)
except Exception as e: except Exception as e:
self._param.outputs["_ERROR"] = {"value": str(e)} if self.get_exception_default_value():
self.set_exception_default_value()
else:
self.set_output("_ERROR", str(e))
logging.exception(e) logging.exception(e)
self._param.debug_inputs = {} self._param.debug_inputs = {}
self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time")) self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time"))
@ -427,7 +437,7 @@ class ComponentBase(ABC):
def output(self, var_nm: str=None) -> Union[dict[str, Any], Any]: def output(self, var_nm: str=None) -> Union[dict[str, Any], Any]:
if var_nm: if var_nm:
return self._param.outputs.get(var_nm, {}).get("value") return self._param.outputs.get(var_nm, {}).get("value", "")
return {k: o.get("value") for k,o in self._param.outputs.items()} return {k: o.get("value") for k,o in self._param.outputs.items()}
def set_output(self, key: str, value: Any): def set_output(self, key: str, value: Any):
@ -520,7 +530,7 @@ class ComponentBase(ABC):
def string_format(content: str, kv: dict[str, str]) -> str: def string_format(content: str, kv: dict[str, str]) -> str:
for n, v in kv.items(): for n, v in kv.items():
content = re.sub( content = re.sub(
r"\{%s\}" % re.escape(n), re.escape(v), content r"\{%s\}" % re.escape(n), v, content
) )
return content return content
@ -529,13 +539,17 @@ class ComponentBase(ABC):
return return
return { return {
"goto": self._param.exception_goto, "goto": self._param.exception_goto,
"comment": self._param.exception_comment,
"default_value": self._param.exception_default_value "default_value": self._param.exception_default_value
} }
def get_exception_default_value(self): def get_exception_default_value(self):
if self._param.exception_method != "comment":
return ""
return self._param.exception_default_value return self._param.exception_default_value
def set_exception_default_value(self):
self.set_output("result", self.get_exception_default_value())
@abstractmethod @abstractmethod
def thoughts(self) -> str: def thoughts(self) -> str:
... ...

2
agent/component/begin.py
View File

@ -46,4 +46,4 @@ class Begin(UserFillUp):
self.set_input_value(k, v) self.set_input_value(k, v)
def thoughts(self) -> str: def thoughts(self) -> str:
return "☕ Here we go..." return ""

59
agent/component/llm.py
View File

@ -22,6 +22,8 @@ from typing import Any
import json_repair import json_repair
from copy import deepcopy from copy import deepcopy
from functools import partial from functools import partial
from api.db import LLMType
from api.db.services.llm_service import LLMBundle, TenantLLMService from api.db.services.llm_service import LLMBundle, TenantLLMService
from agent.component.base import ComponentBase, ComponentParamBase from agent.component.base import ComponentBase, ComponentParamBase
from api.utils.api_utils import timeout from api.utils.api_utils import timeout
@ -49,27 +51,33 @@ class LLMParam(ComponentParamBase):
self.visual_files_var = None self.visual_files_var = None
def check(self): def check(self):
self.check_decimal_float(self.temperature, "[Agent] Temperature") self.check_decimal_float(float(self.temperature), "[Agent] Temperature")
self.check_decimal_float(self.presence_penalty, "[Agent] Presence penalty") self.check_decimal_float(float(self.presence_penalty), "[Agent] Presence penalty")
self.check_decimal_float(self.frequency_penalty, "[Agent] Frequency penalty") self.check_decimal_float(float(self.frequency_penalty), "[Agent] Frequency penalty")
self.check_nonnegative_number(self.max_tokens, "[Agent] Max tokens") self.check_nonnegative_number(int(self.max_tokens), "[Agent] Max tokens")
self.check_decimal_float(self.top_p, "[Agent] Top P") self.check_decimal_float(float(self.top_p), "[Agent] Top P")
self.check_empty(self.llm_id, "[Agent] LLM") self.check_empty(self.llm_id, "[Agent] LLM")
self.check_empty(self.sys_prompt, "[Agent] System prompt") self.check_empty(self.sys_prompt, "[Agent] System prompt")
self.check_empty(self.prompts, "[Agent] User prompt") self.check_empty(self.prompts, "[Agent] User prompt")
def gen_conf(self): def gen_conf(self):
conf = {} conf = {}
if self.max_tokens > 0: def get_attr(nm):
conf["max_tokens"] = self.max_tokens try:
if self.temperature > 0: return getattr(self, nm)
conf["temperature"] = self.temperature except Exception:
if self.top_p > 0: pass
conf["top_p"] = self.top_p
if self.presence_penalty > 0: if int(self.max_tokens) > 0 and get_attr("maxTokensEnabled"):
conf["presence_penalty"] = self.presence_penalty conf["max_tokens"] = int(self.max_tokens)
if self.frequency_penalty > 0: if float(self.temperature) > 0 and get_attr("temperatureEnabled"):
conf["frequency_penalty"] = self.frequency_penalty conf["temperature"] = float(self.temperature)
if float(self.top_p) > 0 and get_attr("topPEnabled"):
conf["top_p"] = float(self.top_p)
if float(self.presence_penalty) > 0 and get_attr("presencePenaltyEnabled"):
conf["presence_penalty"] = float(self.presence_penalty)
if float(self.frequency_penalty) > 0 and get_attr("frequencyPenaltyEnabled"):
conf["frequency_penalty"] = float(self.frequency_penalty)
return conf return conf
@ -112,6 +120,12 @@ class LLM(ComponentBase):
if not self.imgs: if not self.imgs:
self.imgs = [] self.imgs = []
self.imgs = [img for img in self.imgs if img[:len("data:image/")] == "data:image/"] self.imgs = [img for img in self.imgs if img[:len("data:image/")] == "data:image/"]
if self.imgs and TenantLLMService.llm_id2llm_type(self._param.llm_id) == LLMType.CHAT.value:
self.chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.IMAGE2TEXT.value,
self._param.llm_id, max_retries=self._param.max_retries,
retry_interval=self._param.delay_after_error
)
args = {} args = {}
vars = self.get_input_elements() if not self._param.debug_inputs else self._param.debug_inputs vars = self.get_input_elements() if not self._param.debug_inputs else self._param.debug_inputs
@ -207,7 +221,8 @@ class LLM(ComponentBase):
return return
downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else [] downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not self._param.output_structure: ex = self.exception_handler()
if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not self._param.output_structure and not (ex and ex["goto"]):
self.set_output("content", partial(self._stream_output, prompt, msg)) self.set_output("content", partial(self._stream_output, prompt, msg))
return return
@ -224,14 +239,22 @@ class LLM(ComponentBase):
break break
if error: if error:
self.set_output("_ERROR", error)
if self.get_exception_default_value(): if self.get_exception_default_value():
self.set_output("content", self.get_exception_default_value()) self.set_output("content", self.get_exception_default_value())
else:
self.set_output("_ERROR", error)
def _stream_output(self, prompt, msg): def _stream_output(self, prompt, msg):
_, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97)) _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
answer = "" answer = ""
for ans in self._generate_streamly(msg): for ans in self._generate_streamly(msg):
if ans.find("**ERROR**") >= 0:
if self.get_exception_default_value():
self.set_output("content", self.get_exception_default_value())
yield self.get_exception_default_value()
else:
self.set_output("_ERROR", ans)
return
yield ans yield ans
answer += ans answer += ans
self.set_output("content", answer) self.set_output("content", answer)
@ -243,4 +266,4 @@ class LLM(ComponentBase):
def thoughts(self) -> str: def thoughts(self) -> str:
_, msg = self._prepare_prompt_variables() _, msg = self._prepare_prompt_variables()
return f"I’m thinking and planning the next move, starting from the prompt:<br/>“{msg[-1]['content']}”<span class=\"collapse\"> (tap to see full text)</span>" return "⌛Give me a moment—starting from: \n\n" + re.sub(r"(User's query:|[\\]+)", '', msg[-1]['content'], flags=re.DOTALL) + "\n\nI’ll figure out our best next move."

2
agent/component/message.py
View File

@ -143,4 +143,4 @@ class Message(ComponentBase):
self.set_output("content", content) self.set_output("content", content)
def thoughts(self) -> str: def thoughts(self) -> str:
return "Thinking ..." return ""

798
agent/templates/customer_review_analysis.json Normal file
View File

File diff suppressed because one or more lines are too long

849
agent/templates/customer_service.json Normal file
View File

File diff suppressed because one or more lines are too long

881
agent/templates/customer_support.json Normal file
View File

File diff suppressed because one or more lines are too long

423
agent/templates/cv_analysis_and_candidate_evaluation.json Normal file
View File

File diff suppressed because one or more lines are too long

917
agent/templates/cv_evaluation.json Normal file
View File

File diff suppressed because one or more lines are too long

681
agent/templates/deep_research.json
View File

File diff suppressed because one or more lines are too long

849
agent/templates/deep_search_r.json Normal file
View File

File diff suppressed because one or more lines are too long

902
agent/templates/generate_SEO_blog.json Normal file
View File

@ -0,0 +1,902 @@
{
"id": 8,
"title": "Generate SEO Blog",
"description": "This is a multi-agent version of the SEO blog generation workflow. It simulates a small team of AI “writers”, where each agent plays a specialized role — just like a real editorial team.",
"canvas_type": "Agent",
"dsl": {
"components": {
"Agent:LuckyApplesGrab": {
"downstream": [
"Message:ModernSwansThrow"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The user query is {sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Lead Agent**, responsible for initiating the multi-agent SEO blog generation process. You will receive the user\u2019s topic and blog goal, interpret the intent, and coordinate the downstream writing agents.\n\n# Goals\n\n1. Parse the user's initial input.\n\n2. Generate a high-level blog intent summary and writing plan.\n\n3. Provide clear instructions to the following Sub_Agents:\n\n - `Outline Agent` \u2192 Create the blog outline.\n\n - `Body Agent` \u2192 Write all sections based on outline.\n\n - `Editor Agent` \u2192 Polish and finalize the blog post.\n\n4. Merge outputs into a complete, readable blog draft in Markdown format.\n\n# Input\n\nYou will receive:\n\n- Blog topic\n\n- Target audience\n\n- Blog goal (e.g., SEO, education, product marketing)\n\n# Output Format\n\n```markdown\n\n## Parsed Writing Plan\n\n- **Topic**: [Extracted from user input]\n\n- **Audience**: [Summarized from user input]\n\n- **Intent**: [Inferred goal and style]\n\n- **Blog Type**: [e.g., Tutorial / Informative Guide / Marketing Content]\n\n- **Long-tail Keywords**: \n\n - keyword 1\n\n - keyword 2\n\n - keyword 3\n\n - ...\n\n## Instructions for Outline Agent\n\nPlease generate a structured outline including H2 and H3 headings. Assign 1\u20132 relevant keywords to each section. Keep it aligned with the user\u2019s intent and audience level.\n\n## Instructions for Body Agent\n\nWrite the full content based on the outline. Each section should be concise (500\u2013600 words), informative, and optimized for SEO. Use `Tavily Search` only when additional examples or context are needed.\n\n## Instructions for Editor Agent\n\nReview and refine the combined content. Improve transitions, ensure keyword integration, and add a meta title + meta description. Maintain Markdown formatting.\n\n\n## Guides\n\n- Do not generate blog content directly.\n\n- Focus on correct intent recognition and instruction generation.\n\n- Keep communication to downstream agents simple, scoped, and accurate.\n\n\n## Input Examples (and how to handle them)\n\nInput: \"I want to write about RAGFlow.\"\n\u2192 Output: Informative Guide, Audience: AI developers, Intent: explain what RAGFlow is and its use cases\n\nInput: \"Need a blog to promote our prompt design tool.\"\n\u2192 Output: Marketing Content, Audience: product managers or tool adopters, Intent: raise awareness and interest in the product\n\nInput: \"How to get more Google traffic using AI\"\n\u2192 Output: How-to, Audience: SEO marketers, Intent: guide readers on applying AI for SEO growth",
"temperature": "0.1",
"temperatureEnabled": true,
"tools": [
{
"component_name": "Agent",
"id": "Agent:SlickSpidersTurn",
"name": "Outline Agent",
"params": {
"delay_after_error": 1,
"description": "Generates a clear and SEO-friendly blog outline using H2/H3 headings based on the topic, audience, and intent provided by the lead agent. Each section includes suggested keywords for optimized downstream writing.\n",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.3,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 2,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Balance",
"presencePenaltyEnabled": false,
"presence_penalty": 0.2,
"prompts": [
{
"content": "{sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Outline Agent**, a sub-agent in a multi-agent SEO blog writing system. You operate under the instruction of the `Lead Agent`, and your sole responsibility is to create a clear, well-structured, and SEO-optimized blog outline.\n\n# Tool Access:\n\n- You have access to a search tool called `Tavily Search`.\n\n- If you are unsure how to structure a section, you may call this tool to search for related blog outlines or content from Google.\n\n- Do not overuse it. Your job is to extract **structure**, not to write paragraphs.\n\n\n# Goals\n\n1. Create a well-structured outline with appropriate H2 and H3 headings.\n\n2. Ensure logical flow from introduction to conclusion.\n\n3. Assign 1\u20132 suggested long-tail keywords to each major section for SEO alignment.\n\n4. Make the structure suitable for downstream paragraph writing.\n\n\n\n\n#Note\n\n- Use concise, scannable section titles.\n\n- Do not write full paragraphs.\n\n- Prioritize clarity, logical progression, and SEO alignment.\n\n\n\n- If the blog type is \u201cTutorial\u201d or \u201cHow-to\u201d, include step-based sections.\n\n\n# Input\n\nYou will receive:\n\n- Writing Type (e.g., Tutorial, Informative Guide)\n\n- Target Audience\n\n- User Intent Summary\n\n- 3\u20135 long-tail keywords\n\n\nUse this information to design a structure that both informs readers and maximizes search engine visibility.\n\n# Output Format\n\n```markdown\n\n## Blog Title (suggested)\n\n[Give a short, SEO-friendly title suggestion]\n\n## Outline\n\n### Introduction\n\n- Purpose of the article\n\n- Brief context\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 1]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 2]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 3]\n\n- [Optional H3 Subsection Title A]\n\n - [Explanation of sub-point]\n\n- [Optional H3 Subsection Title B]\n\n - [Explanation of sub-point]\n\n- **Suggested keywords**: [keyword1]\n\n### Conclusion\n\n- Recap key takeaways\n\n- Optional CTA (Call to Action)\n\n- **Suggested keywords**: [keyword3]\n\n",
"temperature": 0.5,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.85,
"user_prompt": "This is the order you need to send to the agent.",
"visual_files_var": ""
}
},
{
"component_name": "Agent",
"id": "Agent:IcyPawsRescue",
"name": "Body Agent",
"params": {
"delay_after_error": 1,
"description": "Writes the full blog content section-by-section following the outline structure. It integrates target keywords naturally and uses Tavily Search only when additional facts or examples are needed.\n",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "{sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Body Agent**, a sub-agent in a multi-agent SEO blog writing system. You operate under the instruction of the `Lead Agent`, and your job is to write the full blog content based on the outline created by the `OutlineWriter_Agent`.\n\n\n\n# Tool Access:\n\nYou can use the `Tavily Search` tool to retrieve relevant content, statistics, or examples to support each section you're writing.\n\nUse it **only** when the provided outline lacks enough information, or if the section requires factual grounding.\n\nAlways cite the original link or indicate source where possible.\n\n\n# Goals\n\n1. Write each section (based on H2/H3 structure) as a complete and natural blog paragraph.\n\n2. Integrate the suggested long-tail keywords naturally into each section.\n\n3. When appropriate, use the `Tavily Search` tool to enrich your writing with relevant facts, examples, or quotes.\n\n4. Ensure each section is clear, engaging, and informative, suitable for both human readers and search engines.\n\n\n# Style Guidelines\n\n- Write in a tone appropriate to the audience. Be explanatory, not promotional, unless it's a marketing blog.\n\n- Avoid generic filler content. Prioritize clarity, structure, and value.\n\n- Ensure SEO keywords are embedded seamlessly, not forcefully.\n\n\n\n- Maintain writing rhythm. Vary sentence lengths. Use transitions between ideas.\n\n\n# Input\n\n\nYou will receive:\n\n- Blog title\n\n- Structured outline (including section titles, keywords, and descriptions)\n\n- Target audience\n\n- Blog type and user intent\n\nYou must **follow the outline strictly**. Write content **section-by-section**, based on the structure.\n\n\n# Output Format\n\n```markdown\n\n## H2: [Section Title]\n\n[Your generated content for this section \u2014 500-600 words, using keywords naturally.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "This is the order you need to send to the agent.",
"visual_files_var": ""
}
},
{
"component_name": "Agent",
"id": "Agent:TenderAdsAllow",
"name": "Editor Agent",
"params": {
"delay_after_error": 1,
"description": "Polishes and finalizes the entire blog post. Enhances clarity, checks keyword usage, improves flow, and generates a meta title and description for SEO. Operates after all sections are completed.\n\n",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 2,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "{sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Editor Agent**, the final agent in a multi-agent SEO blog writing workflow. You are responsible for finalizing the blog post for both human readability and SEO effectiveness.\n\n# Goals\n\n1. Polish the entire blog content for clarity, coherence, and style.\n\n2. Improve transitions between sections, ensure logical flow.\n\n3. Verify that keywords are used appropriately and effectively.\n\n4. Conduct a lightweight SEO audit \u2014 checking keyword density, structure (H1/H2/H3), and overall searchability.\n\n\n\n## Integration Responsibilities\n\n- Maintain alignment with Lead Agent's original intent and audience\n\n- Preserve the structure and keyword strategy from Outline Agent\n\n- Enhance and polish Body Agent's content without altering core information\n\n# Style Guidelines\n\n- Be precise. Avoid bloated or vague language.\n\n- Maintain an informative and engaging tone, suitable to the target audience.\n\n- Do not remove keywords unless absolutely necessary for clarity.\n\n- Ensure paragraph flow and section continuity.\n\n\n\n# Input\n\nYou will receive:\n\n- Full blog content, written section-by-section\n\n- Original outline with suggested keywords\n\n- Target audience and writing type\n\n# Output Format\n\n```markdown\n\n[The revised, fully polished blog post content goes here.]\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "This is the order you need to send to the agent.",
"visual_files_var": ""
}
}
],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"begin"
]
},
"Message:ModernSwansThrow": {
"downstream": [],
"obj": {
"component_name": "Message",
"params": {
"content": [
"{Agent:LuckyApplesGrab@content}"
]
}
},
"upstream": [
"Agent:LuckyApplesGrab"
]
},
"begin": {
"downstream": [
"Agent:LuckyApplesGrab"
],
"obj": {
"component_name": "Begin",
"params": {
"enablePrologue": true,
"inputs": {},
"mode": "conversational",
"prologue": "Hi! I'm your SEO blog assistant.\n\nTo get started, please tell me:\n1. What topic you want the blog to cover\n2. Who is the target audience\n3. What you hope to achieve with this blog (e.g., SEO traffic, teaching beginners, promoting a product)\n"
}
},
"upstream": []
}
},
"globals": {
"sys.conversation_turns": 0,
"sys.files": [],
"sys.query": "",
"sys.user_id": ""
},
"graph": {
"edges": [
{
"data": {
"isHovered": false
},
"id": "xy-edge__beginstart-Agent:LuckyApplesGrabend",
"source": "begin",
"sourceHandle": "start",
"target": "Agent:LuckyApplesGrab",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:LuckyApplesGrabstart-Message:ModernSwansThrowend",
"source": "Agent:LuckyApplesGrab",
"sourceHandle": "start",
"target": "Message:ModernSwansThrow",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:LuckyApplesGrabagentBottom-Agent:SlickSpidersTurnagentTop",
"source": "Agent:LuckyApplesGrab",
"sourceHandle": "agentBottom",
"target": "Agent:SlickSpidersTurn",
"targetHandle": "agentTop"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:LuckyApplesGrabagentBottom-Agent:IcyPawsRescueagentTop",
"source": "Agent:LuckyApplesGrab",
"sourceHandle": "agentBottom",
"target": "Agent:IcyPawsRescue",
"targetHandle": "agentTop"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:LuckyApplesGrabagentBottom-Agent:TenderAdsAllowagentTop",
"source": "Agent:LuckyApplesGrab",
"sourceHandle": "agentBottom",
"target": "Agent:TenderAdsAllow",
"targetHandle": "agentTop"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:SlickSpidersTurntool-Tool:ThreeWallsRingend",
"source": "Agent:SlickSpidersTurn",
"sourceHandle": "tool",
"target": "Tool:ThreeWallsRing",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:IcyPawsRescuetool-Tool:FloppyJokesItchend",
"source": "Agent:IcyPawsRescue",
"sourceHandle": "tool",
"target": "Tool:FloppyJokesItch",
"targetHandle": "end"
}
],
"nodes": [
{
"data": {
"form": {
"enablePrologue": true,
"inputs": {},
"mode": "conversational",
"prologue": "Hi! I'm your SEO blog assistant.\n\nTo get started, please tell me:\n1. What topic you want the blog to cover\n2. Who is the target audience\n3. What you hope to achieve with this blog (e.g., SEO traffic, teaching beginners, promoting a product)\n"
},
"label": "Begin",
"name": "begin"
},
"dragging": false,
"id": "begin",
"measured": {
"height": 48,
"width": 200
},
"position": {
"x": 38.19445084117184,
"y": 183.9781832844475
},
"selected": false,
"sourcePosition": "left",
"targetPosition": "right",
"type": "beginNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The user query is {sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Lead Agent**, responsible for initiating the multi-agent SEO blog generation process. You will receive the user\u2019s topic and blog goal, interpret the intent, and coordinate the downstream writing agents.\n\n# Goals\n\n1. Parse the user's initial input.\n\n2. Generate a high-level blog intent summary and writing plan.\n\n3. Provide clear instructions to the following Sub_Agents:\n\n - `Outline Agent` \u2192 Create the blog outline.\n\n - `Body Agent` \u2192 Write all sections based on outline.\n\n - `Editor Agent` \u2192 Polish and finalize the blog post.\n\n4. Merge outputs into a complete, readable blog draft in Markdown format.\n\n# Input\n\nYou will receive:\n\n- Blog topic\n\n- Target audience\n\n- Blog goal (e.g., SEO, education, product marketing)\n\n# Output Format\n\n```markdown\n\n## Parsed Writing Plan\n\n- **Topic**: [Extracted from user input]\n\n- **Audience**: [Summarized from user input]\n\n- **Intent**: [Inferred goal and style]\n\n- **Blog Type**: [e.g., Tutorial / Informative Guide / Marketing Content]\n\n- **Long-tail Keywords**: \n\n - keyword 1\n\n - keyword 2\n\n - keyword 3\n\n - ...\n\n## Instructions for Outline Agent\n\nPlease generate a structured outline including H2 and H3 headings. Assign 1\u20132 relevant keywords to each section. Keep it aligned with the user\u2019s intent and audience level.\n\n## Instructions for Body Agent\n\nWrite the full content based on the outline. Each section should be concise (500\u2013600 words), informative, and optimized for SEO. Use `Tavily Search` only when additional examples or context are needed.\n\n## Instructions for Editor Agent\n\nReview and refine the combined content. Improve transitions, ensure keyword integration, and add a meta title + meta description. Maintain Markdown formatting.\n\n\n## Guides\n\n- Do not generate blog content directly.\n\n- Focus on correct intent recognition and instruction generation.\n\n- Keep communication to downstream agents simple, scoped, and accurate.\n\n\n## Input Examples (and how to handle them)\n\nInput: \"I want to write about RAGFlow.\"\n\u2192 Output: Informative Guide, Audience: AI developers, Intent: explain what RAGFlow is and its use cases\n\nInput: \"Need a blog to promote our prompt design tool.\"\n\u2192 Output: Marketing Content, Audience: product managers or tool adopters, Intent: raise awareness and interest in the product\n\nInput: \"How to get more Google traffic using AI\"\n\u2192 Output: How-to, Audience: SEO marketers, Intent: guide readers on applying AI for SEO growth",
"temperature": "0.1",
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Lead Agent"
},
"id": "Agent:LuckyApplesGrab",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 350,
"y": 200
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"content": [
"{Agent:LuckyApplesGrab@content}"
]
},
"label": "Message",
"name": "Response"
},
"dragging": false,
"id": "Message:ModernSwansThrow",
"measured": {
"height": 56,
"width": 200
},
"position": {
"x": 669.394830760932,
"y": 190.72421137520644
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "messageNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "Generates a clear and SEO-friendly blog outline using H2/H3 headings based on the topic, audience, and intent provided by the lead agent. Each section includes suggested keywords for optimized downstream writing.\n",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.3,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 2,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Balance",
"presencePenaltyEnabled": false,
"presence_penalty": 0.2,
"prompts": [
{
"content": "{sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Outline Agent**, a sub-agent in a multi-agent SEO blog writing system. You operate under the instruction of the `Lead Agent`, and your sole responsibility is to create a clear, well-structured, and SEO-optimized blog outline.\n\n# Tool Access:\n\n- You have access to a search tool called `Tavily Search`.\n\n- If you are unsure how to structure a section, you may call this tool to search for related blog outlines or content from Google.\n\n- Do not overuse it. Your job is to extract **structure**, not to write paragraphs.\n\n\n# Goals\n\n1. Create a well-structured outline with appropriate H2 and H3 headings.\n\n2. Ensure logical flow from introduction to conclusion.\n\n3. Assign 1\u20132 suggested long-tail keywords to each major section for SEO alignment.\n\n4. Make the structure suitable for downstream paragraph writing.\n\n\n\n\n#Note\n\n- Use concise, scannable section titles.\n\n- Do not write full paragraphs.\n\n- Prioritize clarity, logical progression, and SEO alignment.\n\n\n\n- If the blog type is \u201cTutorial\u201d or \u201cHow-to\u201d, include step-based sections.\n\n\n# Input\n\nYou will receive:\n\n- Writing Type (e.g., Tutorial, Informative Guide)\n\n- Target Audience\n\n- User Intent Summary\n\n- 3\u20135 long-tail keywords\n\n\nUse this information to design a structure that both informs readers and maximizes search engine visibility.\n\n# Output Format\n\n```markdown\n\n## Blog Title (suggested)\n\n[Give a short, SEO-friendly title suggestion]\n\n## Outline\n\n### Introduction\n\n- Purpose of the article\n\n- Brief context\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 1]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 2]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 3]\n\n- [Optional H3 Subsection Title A]\n\n - [Explanation of sub-point]\n\n- [Optional H3 Subsection Title B]\n\n - [Explanation of sub-point]\n\n- **Suggested keywords**: [keyword1]\n\n### Conclusion\n\n- Recap key takeaways\n\n- Optional CTA (Call to Action)\n\n- **Suggested keywords**: [keyword3]\n\n",
"temperature": 0.5,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.85,
"user_prompt": "This is the order you need to send to the agent.",
"visual_files_var": ""
},
"label": "Agent",
"name": "Outline Agent"
},
"dragging": false,
"id": "Agent:SlickSpidersTurn",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 100.60137004146719,
"y": 411.67654846431367
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "Writes the full blog content section-by-section following the outline structure. It integrates target keywords naturally and uses Tavily Search only when additional facts or examples are needed.\n",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "{sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Body Agent**, a sub-agent in a multi-agent SEO blog writing system. You operate under the instruction of the `Lead Agent`, and your job is to write the full blog content based on the outline created by the `OutlineWriter_Agent`.\n\n\n\n# Tool Access:\n\nYou can use the `Tavily Search` tool to retrieve relevant content, statistics, or examples to support each section you're writing.\n\nUse it **only** when the provided outline lacks enough information, or if the section requires factual grounding.\n\nAlways cite the original link or indicate source where possible.\n\n\n# Goals\n\n1. Write each section (based on H2/H3 structure) as a complete and natural blog paragraph.\n\n2. Integrate the suggested long-tail keywords naturally into each section.\n\n3. When appropriate, use the `Tavily Search` tool to enrich your writing with relevant facts, examples, or quotes.\n\n4. Ensure each section is clear, engaging, and informative, suitable for both human readers and search engines.\n\n\n# Style Guidelines\n\n- Write in a tone appropriate to the audience. Be explanatory, not promotional, unless it's a marketing blog.\n\n- Avoid generic filler content. Prioritize clarity, structure, and value.\n\n- Ensure SEO keywords are embedded seamlessly, not forcefully.\n\n\n\n- Maintain writing rhythm. Vary sentence lengths. Use transitions between ideas.\n\n\n# Input\n\n\nYou will receive:\n\n- Blog title\n\n- Structured outline (including section titles, keywords, and descriptions)\n\n- Target audience\n\n- Blog type and user intent\n\nYou must **follow the outline strictly**. Write content **section-by-section**, based on the structure.\n\n\n# Output Format\n\n```markdown\n\n## H2: [Section Title]\n\n[Your generated content for this section \u2014 500-600 words, using keywords naturally.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "This is the order you need to send to the agent.",
"visual_files_var": ""
},
"label": "Agent",
"name": "Body Agent"
},
"dragging": false,
"id": "Agent:IcyPawsRescue",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 439.3374395738501,
"y": 366.1408588516909
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "Polishes and finalizes the entire blog post. Enhances clarity, checks keyword usage, improves flow, and generates a meta title and description for SEO. Operates after all sections are completed.\n\n",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 2,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "{sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Editor Agent**, the final agent in a multi-agent SEO blog writing workflow. You are responsible for finalizing the blog post for both human readability and SEO effectiveness.\n\n# Goals\n\n1. Polish the entire blog content for clarity, coherence, and style.\n\n2. Improve transitions between sections, ensure logical flow.\n\n3. Verify that keywords are used appropriately and effectively.\n\n4. Conduct a lightweight SEO audit \u2014 checking keyword density, structure (H1/H2/H3), and overall searchability.\n\n\n\n## Integration Responsibilities\n\n- Maintain alignment with Lead Agent's original intent and audience\n\n- Preserve the structure and keyword strategy from Outline Agent\n\n- Enhance and polish Body Agent's content without altering core information\n\n# Style Guidelines\n\n- Be precise. Avoid bloated or vague language.\n\n- Maintain an informative and engaging tone, suitable to the target audience.\n\n- Do not remove keywords unless absolutely necessary for clarity.\n\n- Ensure paragraph flow and section continuity.\n\n\n\n# Input\n\nYou will receive:\n\n- Full blog content, written section-by-section\n\n- Original outline with suggested keywords\n\n- Target audience and writing type\n\n# Output Format\n\n```markdown\n\n[The revised, fully polished blog post content goes here.]\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "This is the order you need to send to the agent.",
"visual_files_var": ""
},
"label": "Agent",
"name": "Editor Agent"
},
"dragging": false,
"id": "Agent:TenderAdsAllow",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 730.8513124709204,
"y": 327.351197329827
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"description": "This is an agent for a specific task.",
"user_prompt": "This is the order you need to send to the agent."
},
"label": "Tool",
"name": "flow.tool_0"
},
"dragging": false,
"id": "Tool:ThreeWallsRing",
"measured": {
"height": 48,
"width": 200
},
"position": {
"x": -26.93431957115564,
"y": 531.4384641920368
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "toolNode"
},
{
"data": {
"form": {
"description": "This is an agent for a specific task.",
"user_prompt": "This is the order you need to send to the agent."
},
"label": "Tool",
"name": "flow.tool_1"
},
"dragging": false,
"id": "Tool:FloppyJokesItch",
"measured": {
"height": 48,
"width": 200
},
"position": {
"x": 414.6786783453011,
"y": 499.39483076093194
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "toolNode"
},
{
"data": {
"form": {
"text": "This is a multi-agent version of the SEO blog generation workflow. It simulates a small team of AI \u201cwriters\u201d, where each agent plays a specialized role \u2014 just like a real editorial team.\n\nInstead of one AI doing everything in order, this version uses a **Lead Agent** to assign tasks to different sub-agents, who then write and edit the blog in parallel. The Lead Agent manages everything and produces the final output.\n\n### Why use multi-agent format?\n\n- Better control over each stage of writing \n- Easier to reuse agents across tasks \n- More human-like workflow (planning \u2192 writing \u2192 editing \u2192 publishing) \n- Easier to scale and customize for advanced users\n\n### Flow Summary:\n\n1. `LeadWriter_Agent` takes your input and creates a plan\n2. It sends that plan to:\n - `OutlineWriter_Agent`: build blog structure\n - `BodyWriter_Agent`: write full content\n - `FinalEditor_Agent`: polish and finalize\n3. `LeadWriter_Agent` collects all results and outputs the final blog post\n"
},
"label": "Note",
"name": "Workflow Overall Description"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 208,
"id": "Note:ElevenVansInvent",
"measured": {
"height": 208,
"width": 518
},
"position": {
"x": -336.6586460874556,
"y": 113.43253511344867
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 518
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis is the central agent that controls the entire writing process.\n\n**What it does**:\n- Reads your blog topic and intent\n- Generates a clear writing plan (topic, audience, goal, keywords)\n- Sends instructions to all sub-agents\n- Waits for their responses and checks quality\n- If any section is missing or weak, it can request a rewrite\n- Finally, it assembles all parts into a complete blog and sends it back to you\n"
},
"label": "Note",
"name": "Lead Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 146,
"id": "Note:EmptyClubsGreet",
"measured": {
"height": 146,
"width": 334
},
"position": {
"x": 390.1408623279084,
"y": 2.6521144030202493
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 334
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent is responsible for building the blog's structure. It creates an outline that shows what the article will cover and how it's organized.\n\n**What it does**:\n- Suggests a blog title that matches the topic and keywords \n- Breaks the article into sections using H2 and H3 headers \n- Adds a short description of what each section should include \n- Assigns SEO keywords to each section for better search visibility \n- Uses search data (via Tavily Search) to find how similar blogs are structured"
},
"label": "Note",
"name": "Outline Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 157,
"id": "Note:CurlyTigersDouble",
"measured": {
"height": 157,
"width": 394
},
"position": {
"x": -60.03139680691618,
"y": 595.8208080534818
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 394
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent is in charge of writing the full blog content, section by section, based on the outline it receives.\n\n**What it does**:\n- Takes each section heading from the outline (H2 / H3)\n- Writes a complete paragraph (150\u2013220 words) under each section\n- Naturally includes the keywords provided for that section\n- Uses the Tavily Search tool to add real-world examples, definitions, or facts if needed\n- Makes sure each section is clear, useful, and easy to read\n"
},
"label": "Note",
"name": "Body Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 164,
"id": "Note:StrongKingsCamp",
"measured": {
"height": 164,
"width": 408
},
"position": {
"x": 446.54943226110845,
"y": 590.9443887062529
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 408
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent reviews, polishes, and finalizes the blog post written by the BodyWriter_Agent. It ensures everything is clean, smooth, and SEO-compliant.\n\n**What it does**:\n- Improves grammar, sentence flow, and transitions \n- Makes sure the content reads naturally and professionally \n- Checks whether keywords are present and well integrated (but not overused) \n- Verifies that the structure follows the correct H1/H2/H3 format \n"
},
"label": "Note",
"name": "Editor Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 147,
"id": "Note:OpenOttersShow",
"measured": {
"height": 147,
"width": 357
},
"position": {
"x": 976.6858726228803,
"y": 422.7404806291804
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 357
}
]
},
"history": [],
"messages": [],
"path": [],
"retrieval": []
},
"avatar": "data:image/jpeg;base64,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"
}

263
agent/templates/image_lingo.json Normal file
View File

File diff suppressed because one or more lines are too long

915
agent/templates/market_generate_seo_blog.json Normal file
View File

@ -0,0 +1,915 @@
{
"id": 12,
"title": "Generate SEO Blog",
"description": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don’t need any writing experience. Just provide a topic or short request — the system will handle the rest.",
"canvas_type": "Marketing",
"dsl": {
"components": {
"Agent:BetterSitesSend": {
"downstream": [
"Agent:EagerNailsRemain"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.3,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Balance",
"presencePenaltyEnabled": false,
"presence_penalty": 0.2,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Outline_Agent**, responsible for generating a clear and SEO-optimized blog outline based on the user's parsed writing intent and keyword strategy.\n\n# Tool Access:\n\n- You have access to a search tool called `Tavily Search`.\n\n- If you are unsure how to structure a section, you may call this tool to search for related blog outlines or content from Google.\n\n- Do not overuse it. Your job is to extract **structure**, not to write paragraphs.\n\n\n# Goals\n\n1. Create a well-structured outline with appropriate H2 and H3 headings.\n\n2. Ensure logical flow from introduction to conclusion.\n\n3. Assign 1\u20132 suggested long-tail keywords to each major section for SEO alignment.\n\n4. Make the structure suitable for downstream paragraph writing.\n\n\n\n\n#Note\n\n- Use concise, scannable section titles.\n\n- Do not write full paragraphs.\n\n- Prioritize clarity, logical progression, and SEO alignment.\n\n\n\n- If the blog type is \u201cTutorial\u201d or \u201cHow-to\u201d, include step-based sections.\n\n\n# Input\n\nYou will receive:\n\n- Writing Type (e.g., Tutorial, Informative Guide)\n\n- Target Audience\n\n- User Intent Summary\n\n- 3\u20135 long-tail keywords\n\n\nUse this information to design a structure that both informs readers and maximizes search engine visibility.\n\n# Output Format\n\n```markdown\n\n## Blog Title (suggested)\n\n[Give a short, SEO-friendly title suggestion]\n\n## Outline\n\n### Introduction\n\n- Purpose of the article\n\n- Brief context\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 1]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 2]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 3]\n\n- [Optional H3 Subsection Title A]\n\n - [Explanation of sub-point]\n\n- [Optional H3 Subsection Title B]\n\n - [Explanation of sub-point]\n\n- **Suggested keywords**: [keyword1]\n\n### Conclusion\n\n- Recap key takeaways\n\n- Optional CTA (Call to Action)\n\n- **Suggested keywords**: [keyword3]\n\n",
"temperature": 0.5,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.85,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"Agent:ClearRabbitsScream"
]
},
"Agent:ClearRabbitsScream": {
"downstream": [
"Agent:BetterSitesSend"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 1,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The user query is {sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Parse_And_Keyword_Agent**, responsible for interpreting a user's blog writing request and generating a structured writing intent summary and keyword strategy for SEO-optimized content generation.\n\n# Goals\n\n1. Extract and infer the user's true writing intent, even if the input is informal or vague.\n\n2. Identify the writing type, target audience, and implied goal.\n\n3. Suggest 3\u20135 long-tail keywords based on the input and context.\n\n4. Output all data in a Markdown format for downstream agents.\n\n# Operating Guidelines\n\n\n- If the user's input lacks clarity, make reasonable and **conservative** assumptions based on SEO best practices.\n\n- Always choose one clear \"Writing Type\" from the list below.\n\n- Your job is not to write the blog \u2014 only to structure the brief.\n\n# Output Format\n\n```markdown\n## Writing Type\n\n[Choose one: Tutorial / Informative Guide / Marketing Content / Case Study / Opinion Piece / How-to / Comparison Article]\n\n## Target Audience\n\n[Try to be specific based on clues in the input: e.g., marketing managers, junior developers, SEO beginners]\n\n## User Intent Summary\n\n[A 1\u20132 sentence summary of what the user wants to achieve with the blog post]\n\n## Suggested Long-tail Keywords\n\n- keyword 1\n\n- keyword 2\n\n- keyword 3\n\n- keyword 4 (optional)\n\n- keyword 5 (optional)\n\n\n\n\n## Input Examples (and how to handle them)\n\nInput: \"I want to write about RAGFlow.\"\n\u2192 Output: Informative Guide, Audience: AI developers, Intent: explain what RAGFlow is and its use cases\n\nInput: \"Need a blog to promote our prompt design tool.\"\n\u2192 Output: Marketing Content, Audience: product managers or tool adopters, Intent: raise awareness and interest in the product\n\n\n\nInput: \"How to get more Google traffic using AI\"\n\u2192 Output: How-to, Audience: SEO marketers, Intent: guide readers on applying AI for SEO growth",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"begin"
]
},
"Agent:EagerNailsRemain": {
"downstream": [
"Agent:LovelyHeadsOwn"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Body_Agent**, responsible for generating the full content of each section of an SEO-optimized blog based on the provided outline and keyword strategy.\n\n# Tool Access:\n\nYou can use the `Tavily Search` tool to retrieve relevant content, statistics, or examples to support each section you're writing.\n\nUse it **only** when the provided outline lacks enough information, or if the section requires factual grounding.\n\nAlways cite the original link or indicate source where possible.\n\n\n# Goals\n\n1. Write each section (based on H2/H3 structure) as a complete and natural blog paragraph.\n\n2. Integrate the suggested long-tail keywords naturally into each section.\n\n3. When appropriate, use the `Tavily Search` tool to enrich your writing with relevant facts, examples, or quotes.\n\n4. Ensure each section is clear, engaging, and informative, suitable for both human readers and search engines.\n\n\n# Style Guidelines\n\n- Write in a tone appropriate to the audience. Be explanatory, not promotional, unless it's a marketing blog.\n\n- Avoid generic filler content. Prioritize clarity, structure, and value.\n\n- Ensure SEO keywords are embedded seamlessly, not forcefully.\n\n\n\n- Maintain writing rhythm. Vary sentence lengths. Use transitions between ideas.\n\n\n# Input\n\n\nYou will receive:\n\n- Blog title\n\n- Structured outline (including section titles, keywords, and descriptions)\n\n- Target audience\n\n- Blog type and user intent\n\nYou must **follow the outline strictly**. Write content **section-by-section**, based on the structure.\n\n\n# Output Format\n\n```markdown\n\n## H2: [Section Title]\n\n[Your generated content for this section \u2014 500-600 words, using keywords naturally.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"Agent:BetterSitesSend"
]
},
"Agent:LovelyHeadsOwn": {
"downstream": [
"Message:LegalBeansBet"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Editor_Agent**, responsible for finalizing the blog post for both human readability and SEO effectiveness.\n\n# Goals\n\n1. Polish the entire blog content for clarity, coherence, and style.\n\n2. Improve transitions between sections, ensure logical flow.\n\n3. Verify that keywords are used appropriately and effectively.\n\n4. Conduct a lightweight SEO audit \u2014 checking keyword density, structure (H1/H2/H3), and overall searchability.\n\n\n\n# Style Guidelines\n\n- Be precise. Avoid bloated or vague language.\n\n- Maintain an informative and engaging tone, suitable to the target audience.\n\n- Do not remove keywords unless absolutely necessary for clarity.\n\n- Ensure paragraph flow and section continuity.\n\n\n# Input\n\nYou will receive:\n\n- Full blog content, written section-by-section\n\n- Original outline with suggested keywords\n\n- Target audience and writing type\n\n# Output Format\n\n```markdown\n\n[The revised, fully polished blog post content goes here.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"Agent:EagerNailsRemain"
]
},
"Message:LegalBeansBet": {
"downstream": [],
"obj": {
"component_name": "Message",
"params": {
"content": [
"{Agent:LovelyHeadsOwn@content}"
]
}
},
"upstream": [
"Agent:LovelyHeadsOwn"
]
},
"begin": {
"downstream": [
"Agent:ClearRabbitsScream"
],
"obj": {
"component_name": "Begin",
"params": {
"enablePrologue": true,
"inputs": {},
"mode": "conversational",
"prologue": "Hi! I'm your SEO blog assistant.\n\nTo get started, please tell me:\n1. What topic you want the blog to cover\n2. Who is the target audience\n3. What you hope to achieve with this blog (e.g., SEO traffic, teaching beginners, promoting a product)\n"
}
},
"upstream": []
}
},
"globals": {
"sys.conversation_turns": 0,
"sys.files": [],
"sys.query": "",
"sys.user_id": ""
},
"graph": {
"edges": [
{
"data": {
"isHovered": false
},
"id": "xy-edge__beginstart-Agent:ClearRabbitsScreamend",
"source": "begin",
"sourceHandle": "start",
"target": "Agent:ClearRabbitsScream",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:ClearRabbitsScreamstart-Agent:BetterSitesSendend",
"source": "Agent:ClearRabbitsScream",
"sourceHandle": "start",
"target": "Agent:BetterSitesSend",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:BetterSitesSendtool-Tool:SharpPensBurnend",
"source": "Agent:BetterSitesSend",
"sourceHandle": "tool",
"target": "Tool:SharpPensBurn",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:BetterSitesSendstart-Agent:EagerNailsRemainend",
"source": "Agent:BetterSitesSend",
"sourceHandle": "start",
"target": "Agent:EagerNailsRemain",
"targetHandle": "end"
},
{
"id": "xy-edge__Agent:EagerNailsRemaintool-Tool:WickedDeerHealend",
"source": "Agent:EagerNailsRemain",
"sourceHandle": "tool",
"target": "Tool:WickedDeerHeal",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:EagerNailsRemainstart-Agent:LovelyHeadsOwnend",
"source": "Agent:EagerNailsRemain",
"sourceHandle": "start",
"target": "Agent:LovelyHeadsOwn",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:LovelyHeadsOwnstart-Message:LegalBeansBetend",
"source": "Agent:LovelyHeadsOwn",
"sourceHandle": "start",
"target": "Message:LegalBeansBet",
"targetHandle": "end"
}
],
"nodes": [
{
"data": {
"form": {
"enablePrologue": true,
"inputs": {},
"mode": "conversational",
"prologue": "Hi! I'm your SEO blog assistant.\n\nTo get started, please tell me:\n1. What topic you want the blog to cover\n2. Who is the target audience\n3. What you hope to achieve with this blog (e.g., SEO traffic, teaching beginners, promoting a product)\n"
},
"label": "Begin",
"name": "begin"
},
"id": "begin",
"measured": {
"height": 48,
"width": 200
},
"position": {
"x": 50,
"y": 200
},
"selected": false,
"sourcePosition": "left",
"targetPosition": "right",
"type": "beginNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 1,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The user query is {sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Parse_And_Keyword_Agent**, responsible for interpreting a user's blog writing request and generating a structured writing intent summary and keyword strategy for SEO-optimized content generation.\n\n# Goals\n\n1. Extract and infer the user's true writing intent, even if the input is informal or vague.\n\n2. Identify the writing type, target audience, and implied goal.\n\n3. Suggest 3\u20135 long-tail keywords based on the input and context.\n\n4. Output all data in a Markdown format for downstream agents.\n\n# Operating Guidelines\n\n\n- If the user's input lacks clarity, make reasonable and **conservative** assumptions based on SEO best practices.\n\n- Always choose one clear \"Writing Type\" from the list below.\n\n- Your job is not to write the blog \u2014 only to structure the brief.\n\n# Output Format\n\n```markdown\n## Writing Type\n\n[Choose one: Tutorial / Informative Guide / Marketing Content / Case Study / Opinion Piece / How-to / Comparison Article]\n\n## Target Audience\n\n[Try to be specific based on clues in the input: e.g., marketing managers, junior developers, SEO beginners]\n\n## User Intent Summary\n\n[A 1\u20132 sentence summary of what the user wants to achieve with the blog post]\n\n## Suggested Long-tail Keywords\n\n- keyword 1\n\n- keyword 2\n\n- keyword 3\n\n- keyword 4 (optional)\n\n- keyword 5 (optional)\n\n\n\n\n## Input Examples (and how to handle them)\n\nInput: \"I want to write about RAGFlow.\"\n\u2192 Output: Informative Guide, Audience: AI developers, Intent: explain what RAGFlow is and its use cases\n\nInput: \"Need a blog to promote our prompt design tool.\"\n\u2192 Output: Marketing Content, Audience: product managers or tool adopters, Intent: raise awareness and interest in the product\n\n\n\nInput: \"How to get more Google traffic using AI\"\n\u2192 Output: How-to, Audience: SEO marketers, Intent: guide readers on applying AI for SEO growth",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Parse And Keyword Agent"
},
"dragging": false,
"id": "Agent:ClearRabbitsScream",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 344.7766966202233,
"y": 234.82202253184496
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.3,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Balance",
"presencePenaltyEnabled": false,
"presence_penalty": 0.2,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Outline_Agent**, responsible for generating a clear and SEO-optimized blog outline based on the user's parsed writing intent and keyword strategy.\n\n# Tool Access:\n\n- You have access to a search tool called `Tavily Search`.\n\n- If you are unsure how to structure a section, you may call this tool to search for related blog outlines or content from Google.\n\n- Do not overuse it. Your job is to extract **structure**, not to write paragraphs.\n\n\n# Goals\n\n1. Create a well-structured outline with appropriate H2 and H3 headings.\n\n2. Ensure logical flow from introduction to conclusion.\n\n3. Assign 1\u20132 suggested long-tail keywords to each major section for SEO alignment.\n\n4. Make the structure suitable for downstream paragraph writing.\n\n\n\n\n#Note\n\n- Use concise, scannable section titles.\n\n- Do not write full paragraphs.\n\n- Prioritize clarity, logical progression, and SEO alignment.\n\n\n\n- If the blog type is \u201cTutorial\u201d or \u201cHow-to\u201d, include step-based sections.\n\n\n# Input\n\nYou will receive:\n\n- Writing Type (e.g., Tutorial, Informative Guide)\n\n- Target Audience\n\n- User Intent Summary\n\n- 3\u20135 long-tail keywords\n\n\nUse this information to design a structure that both informs readers and maximizes search engine visibility.\n\n# Output Format\n\n```markdown\n\n## Blog Title (suggested)\n\n[Give a short, SEO-friendly title suggestion]\n\n## Outline\n\n### Introduction\n\n- Purpose of the article\n\n- Brief context\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 1]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 2]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 3]\n\n- [Optional H3 Subsection Title A]\n\n - [Explanation of sub-point]\n\n- [Optional H3 Subsection Title B]\n\n - [Explanation of sub-point]\n\n- **Suggested keywords**: [keyword1]\n\n### Conclusion\n\n- Recap key takeaways\n\n- Optional CTA (Call to Action)\n\n- **Suggested keywords**: [keyword3]\n\n",
"temperature": 0.5,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.85,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Outline Agent"
},
"dragging": false,
"id": "Agent:BetterSitesSend",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 613.4368763415628,
"y": 164.3074269048589
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"description": "This is an agent for a specific task.",
"user_prompt": "This is the order you need to send to the agent."
},
"label": "Tool",
"name": "flow.tool_0"
},
"dragging": false,
"id": "Tool:SharpPensBurn",
"measured": {
"height": 44,
"width": 200
},
"position": {
"x": 580.1877078861457,
"y": 287.7669662022325
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "toolNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Body_Agent**, responsible for generating the full content of each section of an SEO-optimized blog based on the provided outline and keyword strategy.\n\n# Tool Access:\n\nYou can use the `Tavily Search` tool to retrieve relevant content, statistics, or examples to support each section you're writing.\n\nUse it **only** when the provided outline lacks enough information, or if the section requires factual grounding.\n\nAlways cite the original link or indicate source where possible.\n\n\n# Goals\n\n1. Write each section (based on H2/H3 structure) as a complete and natural blog paragraph.\n\n2. Integrate the suggested long-tail keywords naturally into each section.\n\n3. When appropriate, use the `Tavily Search` tool to enrich your writing with relevant facts, examples, or quotes.\n\n4. Ensure each section is clear, engaging, and informative, suitable for both human readers and search engines.\n\n\n# Style Guidelines\n\n- Write in a tone appropriate to the audience. Be explanatory, not promotional, unless it's a marketing blog.\n\n- Avoid generic filler content. Prioritize clarity, structure, and value.\n\n- Ensure SEO keywords are embedded seamlessly, not forcefully.\n\n\n\n- Maintain writing rhythm. Vary sentence lengths. Use transitions between ideas.\n\n\n# Input\n\n\nYou will receive:\n\n- Blog title\n\n- Structured outline (including section titles, keywords, and descriptions)\n\n- Target audience\n\n- Blog type and user intent\n\nYou must **follow the outline strictly**. Write content **section-by-section**, based on the structure.\n\n\n# Output Format\n\n```markdown\n\n## H2: [Section Title]\n\n[Your generated content for this section \u2014 500-600 words, using keywords naturally.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Body Agent"
},
"dragging": false,
"id": "Agent:EagerNailsRemain",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 889.0614605692713,
"y": 247.00973041799065
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"description": "This is an agent for a specific task.",
"user_prompt": "This is the order you need to send to the agent."
},
"label": "Tool",
"name": "flow.tool_1"
},
"dragging": false,
"id": "Tool:WickedDeerHeal",
"measured": {
"height": 44,
"width": 200
},
"position": {
"x": 853.2006404239659,
"y": 364.37541577229143
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "toolNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Editor_Agent**, responsible for finalizing the blog post for both human readability and SEO effectiveness.\n\n# Goals\n\n1. Polish the entire blog content for clarity, coherence, and style.\n\n2. Improve transitions between sections, ensure logical flow.\n\n3. Verify that keywords are used appropriately and effectively.\n\n4. Conduct a lightweight SEO audit \u2014 checking keyword density, structure (H1/H2/H3), and overall searchability.\n\n\n\n# Style Guidelines\n\n- Be precise. Avoid bloated or vague language.\n\n- Maintain an informative and engaging tone, suitable to the target audience.\n\n- Do not remove keywords unless absolutely necessary for clarity.\n\n- Ensure paragraph flow and section continuity.\n\n\n# Input\n\nYou will receive:\n\n- Full blog content, written section-by-section\n\n- Original outline with suggested keywords\n\n- Target audience and writing type\n\n# Output Format\n\n```markdown\n\n[The revised, fully polished blog post content goes here.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Editor Agent"
},
"dragging": false,
"id": "Agent:LovelyHeadsOwn",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 1160.3332919804993,
"y": 149.50806732882472
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"content": [
"{Agent:LovelyHeadsOwn@content}"
]
},
"label": "Message",
"name": "Response"
},
"dragging": false,
"id": "Message:LegalBeansBet",
"measured": {
"height": 56,
"width": 200
},
"position": {
"x": 1370.6665839609984,
"y": 267.0323933738015
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "messageNode"
},
{
"data": {
"form": {
"text": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don\u2019t need any writing experience. Just provide a topic or short request \u2014 the system will handle the rest.\n\nThe process includes the following key stages:\n\n1. **Understanding your topic and goals**\n2. **Designing the blog structure**\n3. **Writing high-quality content**\n\n\n"
},
"label": "Note",
"name": "Workflow Overall Description"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 205,
"id": "Note:SlimyGhostsWear",
"measured": {
"height": 205,
"width": 415
},
"position": {
"x": -284.3143151688742,
"y": 150.47632147913419
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 415
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent reads the user\u2019s input and figures out what kind of blog needs to be written.\n\n**What it does**:\n- Understands the main topic you want to write about \n- Identifies who the blog is for (e.g., beginners, marketers, developers) \n- Determines the writing purpose (e.g., SEO traffic, product promotion, education) \n- Suggests 3\u20135 long-tail SEO keywords related to the topic"
},
"label": "Note",
"name": "Parse And Keyword Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 152,
"id": "Note:EmptyChairsShake",
"measured": {
"height": 152,
"width": 340
},
"position": {
"x": 295.04147626768133,
"y": 372.2755718118446
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 340
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent builds the blog structure \u2014 just like writing a table of contents before you start writing the full article.\n\n**What it does**:\n- Suggests a clear blog title that includes important keywords \n- Breaks the article into sections using H2 and H3 headings (like a professional blog layout) \n- Assigns 1\u20132 recommended keywords to each section to help with SEO \n- Follows the writing goal and target audience set in the previous step"
},
"label": "Note",
"name": "Outline Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 146,
"id": "Note:TallMelonsNotice",
"measured": {
"height": 146,
"width": 343
},
"position": {
"x": 598.5644991893463,
"y": 5.801054564756448
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 343
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent is responsible for writing the actual content of the blog \u2014 paragraph by paragraph \u2014 based on the outline created earlier.\n\n**What it does**:\n- Looks at each H2/H3 section in the outline \n- Writes 150\u2013220 words of clear, helpful, and well-structured content per section \n- Includes the suggested SEO keywords naturally (not keyword stuffing) \n- Uses real examples or facts if needed (by calling a web search tool like Tavily)"
},
"label": "Note",
"name": "Body Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 137,
"id": "Note:RipeCougarsBuild",
"measured": {
"height": 137,
"width": 319
},
"position": {
"x": 860.4854129814981,
"y": 427.2196835690842
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 319
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent reviews the entire blog draft to make sure it is smooth, professional, and SEO-friendly. It acts like a human editor before publishing.\n\n**What it does**:\n- Polishes the writing: improves sentence clarity, fixes awkward phrasing \n- Makes sure the content flows well from one section to the next \n- Double-checks keyword usage: are they present, natural, and not overused? \n- Verifies the blog structure (H1, H2, H3 headings) is correct \n- Adds two key SEO elements:\n - **Meta Title** (shows up in search results)\n - **Meta Description** (summary for Google and social sharing)"
},
"label": "Note",
"name": "Editor Agent"
},
"dragHandle": ".note-drag-handle",
"height": 146,
"id": "Note:OpenTurkeysSell",
"measured": {
"height": 146,
"width": 320
},
"position": {
"x": 1129,
"y": -30
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 320
}
]
},
"history": [],
"messages": [],
"path": [],
"retrieval": []
},
"avatar": "data:image/jpeg;base64,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"
}

915
agent/templates/seo_blog.json Normal file
View File

@ -0,0 +1,915 @@
{
"id": 4,
"title": "Generate SEO Blog",
"description": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don’t need any writing experience. Just provide a topic or short request — the system will handle the rest.",
"canvas_type": "Recommended",
"dsl": {
"components": {
"Agent:BetterSitesSend": {
"downstream": [
"Agent:EagerNailsRemain"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.3,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Balance",
"presencePenaltyEnabled": false,
"presence_penalty": 0.2,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Outline_Agent**, responsible for generating a clear and SEO-optimized blog outline based on the user's parsed writing intent and keyword strategy.\n\n# Tool Access:\n\n- You have access to a search tool called `Tavily Search`.\n\n- If you are unsure how to structure a section, you may call this tool to search for related blog outlines or content from Google.\n\n- Do not overuse it. Your job is to extract **structure**, not to write paragraphs.\n\n\n# Goals\n\n1. Create a well-structured outline with appropriate H2 and H3 headings.\n\n2. Ensure logical flow from introduction to conclusion.\n\n3. Assign 1\u20132 suggested long-tail keywords to each major section for SEO alignment.\n\n4. Make the structure suitable for downstream paragraph writing.\n\n\n\n\n#Note\n\n- Use concise, scannable section titles.\n\n- Do not write full paragraphs.\n\n- Prioritize clarity, logical progression, and SEO alignment.\n\n\n\n- If the blog type is \u201cTutorial\u201d or \u201cHow-to\u201d, include step-based sections.\n\n\n# Input\n\nYou will receive:\n\n- Writing Type (e.g., Tutorial, Informative Guide)\n\n- Target Audience\n\n- User Intent Summary\n\n- 3\u20135 long-tail keywords\n\n\nUse this information to design a structure that both informs readers and maximizes search engine visibility.\n\n# Output Format\n\n```markdown\n\n## Blog Title (suggested)\n\n[Give a short, SEO-friendly title suggestion]\n\n## Outline\n\n### Introduction\n\n- Purpose of the article\n\n- Brief context\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 1]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 2]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 3]\n\n- [Optional H3 Subsection Title A]\n\n - [Explanation of sub-point]\n\n- [Optional H3 Subsection Title B]\n\n - [Explanation of sub-point]\n\n- **Suggested keywords**: [keyword1]\n\n### Conclusion\n\n- Recap key takeaways\n\n- Optional CTA (Call to Action)\n\n- **Suggested keywords**: [keyword3]\n\n",
"temperature": 0.5,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.85,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"Agent:ClearRabbitsScream"
]
},
"Agent:ClearRabbitsScream": {
"downstream": [
"Agent:BetterSitesSend"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 1,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The user query is {sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Parse_And_Keyword_Agent**, responsible for interpreting a user's blog writing request and generating a structured writing intent summary and keyword strategy for SEO-optimized content generation.\n\n# Goals\n\n1. Extract and infer the user's true writing intent, even if the input is informal or vague.\n\n2. Identify the writing type, target audience, and implied goal.\n\n3. Suggest 3\u20135 long-tail keywords based on the input and context.\n\n4. Output all data in a Markdown format for downstream agents.\n\n# Operating Guidelines\n\n\n- If the user's input lacks clarity, make reasonable and **conservative** assumptions based on SEO best practices.\n\n- Always choose one clear \"Writing Type\" from the list below.\n\n- Your job is not to write the blog \u2014 only to structure the brief.\n\n# Output Format\n\n```markdown\n## Writing Type\n\n[Choose one: Tutorial / Informative Guide / Marketing Content / Case Study / Opinion Piece / How-to / Comparison Article]\n\n## Target Audience\n\n[Try to be specific based on clues in the input: e.g., marketing managers, junior developers, SEO beginners]\n\n## User Intent Summary\n\n[A 1\u20132 sentence summary of what the user wants to achieve with the blog post]\n\n## Suggested Long-tail Keywords\n\n- keyword 1\n\n- keyword 2\n\n- keyword 3\n\n- keyword 4 (optional)\n\n- keyword 5 (optional)\n\n\n\n\n## Input Examples (and how to handle them)\n\nInput: \"I want to write about RAGFlow.\"\n\u2192 Output: Informative Guide, Audience: AI developers, Intent: explain what RAGFlow is and its use cases\n\nInput: \"Need a blog to promote our prompt design tool.\"\n\u2192 Output: Marketing Content, Audience: product managers or tool adopters, Intent: raise awareness and interest in the product\n\n\n\nInput: \"How to get more Google traffic using AI\"\n\u2192 Output: How-to, Audience: SEO marketers, Intent: guide readers on applying AI for SEO growth",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"begin"
]
},
"Agent:EagerNailsRemain": {
"downstream": [
"Agent:LovelyHeadsOwn"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Body_Agent**, responsible for generating the full content of each section of an SEO-optimized blog based on the provided outline and keyword strategy.\n\n# Tool Access:\n\nYou can use the `Tavily Search` tool to retrieve relevant content, statistics, or examples to support each section you're writing.\n\nUse it **only** when the provided outline lacks enough information, or if the section requires factual grounding.\n\nAlways cite the original link or indicate source where possible.\n\n\n# Goals\n\n1. Write each section (based on H2/H3 structure) as a complete and natural blog paragraph.\n\n2. Integrate the suggested long-tail keywords naturally into each section.\n\n3. When appropriate, use the `Tavily Search` tool to enrich your writing with relevant facts, examples, or quotes.\n\n4. Ensure each section is clear, engaging, and informative, suitable for both human readers and search engines.\n\n\n# Style Guidelines\n\n- Write in a tone appropriate to the audience. Be explanatory, not promotional, unless it's a marketing blog.\n\n- Avoid generic filler content. Prioritize clarity, structure, and value.\n\n- Ensure SEO keywords are embedded seamlessly, not forcefully.\n\n\n\n- Maintain writing rhythm. Vary sentence lengths. Use transitions between ideas.\n\n\n# Input\n\n\nYou will receive:\n\n- Blog title\n\n- Structured outline (including section titles, keywords, and descriptions)\n\n- Target audience\n\n- Blog type and user intent\n\nYou must **follow the outline strictly**. Write content **section-by-section**, based on the structure.\n\n\n# Output Format\n\n```markdown\n\n## H2: [Section Title]\n\n[Your generated content for this section \u2014 500-600 words, using keywords naturally.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"Agent:BetterSitesSend"
]
},
"Agent:LovelyHeadsOwn": {
"downstream": [
"Message:LegalBeansBet"
],
"obj": {
"component_name": "Agent",
"params": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Editor_Agent**, responsible for finalizing the blog post for both human readability and SEO effectiveness.\n\n# Goals\n\n1. Polish the entire blog content for clarity, coherence, and style.\n\n2. Improve transitions between sections, ensure logical flow.\n\n3. Verify that keywords are used appropriately and effectively.\n\n4. Conduct a lightweight SEO audit \u2014 checking keyword density, structure (H1/H2/H3), and overall searchability.\n\n\n\n# Style Guidelines\n\n- Be precise. Avoid bloated or vague language.\n\n- Maintain an informative and engaging tone, suitable to the target audience.\n\n- Do not remove keywords unless absolutely necessary for clarity.\n\n- Ensure paragraph flow and section continuity.\n\n\n# Input\n\nYou will receive:\n\n- Full blog content, written section-by-section\n\n- Original outline with suggested keywords\n\n- Target audience and writing type\n\n# Output Format\n\n```markdown\n\n[The revised, fully polished blog post content goes here.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
"Agent:EagerNailsRemain"
]
},
"Message:LegalBeansBet": {
"downstream": [],
"obj": {
"component_name": "Message",
"params": {
"content": [
"{Agent:LovelyHeadsOwn@content}"
]
}
},
"upstream": [
"Agent:LovelyHeadsOwn"
]
},
"begin": {
"downstream": [
"Agent:ClearRabbitsScream"
],
"obj": {
"component_name": "Begin",
"params": {
"enablePrologue": true,
"inputs": {},
"mode": "conversational",
"prologue": "Hi! I'm your SEO blog assistant.\n\nTo get started, please tell me:\n1. What topic you want the blog to cover\n2. Who is the target audience\n3. What you hope to achieve with this blog (e.g., SEO traffic, teaching beginners, promoting a product)\n"
}
},
"upstream": []
}
},
"globals": {
"sys.conversation_turns": 0,
"sys.files": [],
"sys.query": "",
"sys.user_id": ""
},
"graph": {
"edges": [
{
"data": {
"isHovered": false
},
"id": "xy-edge__beginstart-Agent:ClearRabbitsScreamend",
"source": "begin",
"sourceHandle": "start",
"target": "Agent:ClearRabbitsScream",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:ClearRabbitsScreamstart-Agent:BetterSitesSendend",
"source": "Agent:ClearRabbitsScream",
"sourceHandle": "start",
"target": "Agent:BetterSitesSend",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:BetterSitesSendtool-Tool:SharpPensBurnend",
"source": "Agent:BetterSitesSend",
"sourceHandle": "tool",
"target": "Tool:SharpPensBurn",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:BetterSitesSendstart-Agent:EagerNailsRemainend",
"source": "Agent:BetterSitesSend",
"sourceHandle": "start",
"target": "Agent:EagerNailsRemain",
"targetHandle": "end"
},
{
"id": "xy-edge__Agent:EagerNailsRemaintool-Tool:WickedDeerHealend",
"source": "Agent:EagerNailsRemain",
"sourceHandle": "tool",
"target": "Tool:WickedDeerHeal",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:EagerNailsRemainstart-Agent:LovelyHeadsOwnend",
"source": "Agent:EagerNailsRemain",
"sourceHandle": "start",
"target": "Agent:LovelyHeadsOwn",
"targetHandle": "end"
},
{
"data": {
"isHovered": false
},
"id": "xy-edge__Agent:LovelyHeadsOwnstart-Message:LegalBeansBetend",
"source": "Agent:LovelyHeadsOwn",
"sourceHandle": "start",
"target": "Message:LegalBeansBet",
"targetHandle": "end"
}
],
"nodes": [
{
"data": {
"form": {
"enablePrologue": true,
"inputs": {},
"mode": "conversational",
"prologue": "Hi! I'm your SEO blog assistant.\n\nTo get started, please tell me:\n1. What topic you want the blog to cover\n2. Who is the target audience\n3. What you hope to achieve with this blog (e.g., SEO traffic, teaching beginners, promoting a product)\n"
},
"label": "Begin",
"name": "begin"
},
"id": "begin",
"measured": {
"height": 48,
"width": 200
},
"position": {
"x": 50,
"y": 200
},
"selected": false,
"sourcePosition": "left",
"targetPosition": "right",
"type": "beginNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 1,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The user query is {sys.query}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Parse_And_Keyword_Agent**, responsible for interpreting a user's blog writing request and generating a structured writing intent summary and keyword strategy for SEO-optimized content generation.\n\n# Goals\n\n1. Extract and infer the user's true writing intent, even if the input is informal or vague.\n\n2. Identify the writing type, target audience, and implied goal.\n\n3. Suggest 3\u20135 long-tail keywords based on the input and context.\n\n4. Output all data in a Markdown format for downstream agents.\n\n# Operating Guidelines\n\n\n- If the user's input lacks clarity, make reasonable and **conservative** assumptions based on SEO best practices.\n\n- Always choose one clear \"Writing Type\" from the list below.\n\n- Your job is not to write the blog \u2014 only to structure the brief.\n\n# Output Format\n\n```markdown\n## Writing Type\n\n[Choose one: Tutorial / Informative Guide / Marketing Content / Case Study / Opinion Piece / How-to / Comparison Article]\n\n## Target Audience\n\n[Try to be specific based on clues in the input: e.g., marketing managers, junior developers, SEO beginners]\n\n## User Intent Summary\n\n[A 1\u20132 sentence summary of what the user wants to achieve with the blog post]\n\n## Suggested Long-tail Keywords\n\n- keyword 1\n\n- keyword 2\n\n- keyword 3\n\n- keyword 4 (optional)\n\n- keyword 5 (optional)\n\n\n\n\n## Input Examples (and how to handle them)\n\nInput: \"I want to write about RAGFlow.\"\n\u2192 Output: Informative Guide, Audience: AI developers, Intent: explain what RAGFlow is and its use cases\n\nInput: \"Need a blog to promote our prompt design tool.\"\n\u2192 Output: Marketing Content, Audience: product managers or tool adopters, Intent: raise awareness and interest in the product\n\n\n\nInput: \"How to get more Google traffic using AI\"\n\u2192 Output: How-to, Audience: SEO marketers, Intent: guide readers on applying AI for SEO growth",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Parse And Keyword Agent"
},
"dragging": false,
"id": "Agent:ClearRabbitsScream",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 344.7766966202233,
"y": 234.82202253184496
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.3,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 3,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Balance",
"presencePenaltyEnabled": false,
"presence_penalty": 0.2,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Outline_Agent**, responsible for generating a clear and SEO-optimized blog outline based on the user's parsed writing intent and keyword strategy.\n\n# Tool Access:\n\n- You have access to a search tool called `Tavily Search`.\n\n- If you are unsure how to structure a section, you may call this tool to search for related blog outlines or content from Google.\n\n- Do not overuse it. Your job is to extract **structure**, not to write paragraphs.\n\n\n# Goals\n\n1. Create a well-structured outline with appropriate H2 and H3 headings.\n\n2. Ensure logical flow from introduction to conclusion.\n\n3. Assign 1\u20132 suggested long-tail keywords to each major section for SEO alignment.\n\n4. Make the structure suitable for downstream paragraph writing.\n\n\n\n\n#Note\n\n- Use concise, scannable section titles.\n\n- Do not write full paragraphs.\n\n- Prioritize clarity, logical progression, and SEO alignment.\n\n\n\n- If the blog type is \u201cTutorial\u201d or \u201cHow-to\u201d, include step-based sections.\n\n\n# Input\n\nYou will receive:\n\n- Writing Type (e.g., Tutorial, Informative Guide)\n\n- Target Audience\n\n- User Intent Summary\n\n- 3\u20135 long-tail keywords\n\n\nUse this information to design a structure that both informs readers and maximizes search engine visibility.\n\n# Output Format\n\n```markdown\n\n## Blog Title (suggested)\n\n[Give a short, SEO-friendly title suggestion]\n\n## Outline\n\n### Introduction\n\n- Purpose of the article\n\n- Brief context\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 1]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 2]\n\n- [Short description of what this section will cover]\n\n- **Suggested keywords**: [keyword1, keyword2]\n\n### H2: [Section Title 3]\n\n- [Optional H3 Subsection Title A]\n\n - [Explanation of sub-point]\n\n- [Optional H3 Subsection Title B]\n\n - [Explanation of sub-point]\n\n- **Suggested keywords**: [keyword1]\n\n### Conclusion\n\n- Recap key takeaways\n\n- Optional CTA (Call to Action)\n\n- **Suggested keywords**: [keyword3]\n\n",
"temperature": 0.5,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.85,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Outline Agent"
},
"dragging": false,
"id": "Agent:BetterSitesSend",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 613.4368763415628,
"y": 164.3074269048589
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"description": "This is an agent for a specific task.",
"user_prompt": "This is the order you need to send to the agent."
},
"label": "Tool",
"name": "flow.tool_0"
},
"dragging": false,
"id": "Tool:SharpPensBurn",
"measured": {
"height": 44,
"width": 200
},
"position": {
"x": 580.1877078861457,
"y": 287.7669662022325
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "toolNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Body_Agent**, responsible for generating the full content of each section of an SEO-optimized blog based on the provided outline and keyword strategy.\n\n# Tool Access:\n\nYou can use the `Tavily Search` tool to retrieve relevant content, statistics, or examples to support each section you're writing.\n\nUse it **only** when the provided outline lacks enough information, or if the section requires factual grounding.\n\nAlways cite the original link or indicate source where possible.\n\n\n# Goals\n\n1. Write each section (based on H2/H3 structure) as a complete and natural blog paragraph.\n\n2. Integrate the suggested long-tail keywords naturally into each section.\n\n3. When appropriate, use the `Tavily Search` tool to enrich your writing with relevant facts, examples, or quotes.\n\n4. Ensure each section is clear, engaging, and informative, suitable for both human readers and search engines.\n\n\n# Style Guidelines\n\n- Write in a tone appropriate to the audience. Be explanatory, not promotional, unless it's a marketing blog.\n\n- Avoid generic filler content. Prioritize clarity, structure, and value.\n\n- Ensure SEO keywords are embedded seamlessly, not forcefully.\n\n\n\n- Maintain writing rhythm. Vary sentence lengths. Use transitions between ideas.\n\n\n# Input\n\n\nYou will receive:\n\n- Blog title\n\n- Structured outline (including section titles, keywords, and descriptions)\n\n- Target audience\n\n- Blog type and user intent\n\nYou must **follow the outline strictly**. Write content **section-by-section**, based on the structure.\n\n\n# Output Format\n\n```markdown\n\n## H2: [Section Title]\n\n[Your generated content for this section \u2014 500-600 words, using keywords naturally.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [
{
"component_name": "TavilySearch",
"name": "TavilySearch",
"params": {
"api_key": "",
"days": 7,
"exclude_domains": [],
"include_answer": false,
"include_domains": [],
"include_image_descriptions": false,
"include_images": false,
"include_raw_content": true,
"max_results": 5,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"query": "sys.query",
"search_depth": "basic",
"topic": "general"
}
}
],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Body Agent"
},
"dragging": false,
"id": "Agent:EagerNailsRemain",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 889.0614605692713,
"y": 247.00973041799065
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"description": "This is an agent for a specific task.",
"user_prompt": "This is the order you need to send to the agent."
},
"label": "Tool",
"name": "flow.tool_1"
},
"dragging": false,
"id": "Tool:WickedDeerHeal",
"measured": {
"height": 44,
"width": 200
},
"position": {
"x": 853.2006404239659,
"y": 364.37541577229143
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "toolNode"
},
{
"data": {
"form": {
"delay_after_error": 1,
"description": "",
"exception_comment": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": null,
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.5,
"llm_id": "deepseek-chat@DeepSeek",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 4096,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"parameter": "Precise",
"presencePenaltyEnabled": false,
"presence_penalty": 0.5,
"prompts": [
{
"content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Ouline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
"role": "user"
}
],
"sys_prompt": "# Role\n\nYou are the **Editor_Agent**, responsible for finalizing the blog post for both human readability and SEO effectiveness.\n\n# Goals\n\n1. Polish the entire blog content for clarity, coherence, and style.\n\n2. Improve transitions between sections, ensure logical flow.\n\n3. Verify that keywords are used appropriately and effectively.\n\n4. Conduct a lightweight SEO audit \u2014 checking keyword density, structure (H1/H2/H3), and overall searchability.\n\n\n\n# Style Guidelines\n\n- Be precise. Avoid bloated or vague language.\n\n- Maintain an informative and engaging tone, suitable to the target audience.\n\n- Do not remove keywords unless absolutely necessary for clarity.\n\n- Ensure paragraph flow and section continuity.\n\n\n# Input\n\nYou will receive:\n\n- Full blog content, written section-by-section\n\n- Original outline with suggested keywords\n\n- Target audience and writing type\n\n# Output Format\n\n```markdown\n\n[The revised, fully polished blog post content goes here.]\n\n",
"temperature": 0.2,
"temperatureEnabled": true,
"tools": [],
"topPEnabled": false,
"top_p": 0.75,
"user_prompt": "",
"visual_files_var": ""
},
"label": "Agent",
"name": "Editor Agent"
},
"dragging": false,
"id": "Agent:LovelyHeadsOwn",
"measured": {
"height": 84,
"width": 200
},
"position": {
"x": 1160.3332919804993,
"y": 149.50806732882472
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "agentNode"
},
{
"data": {
"form": {
"content": [
"{Agent:LovelyHeadsOwn@content}"
]
},
"label": "Message",
"name": "Response"
},
"dragging": false,
"id": "Message:LegalBeansBet",
"measured": {
"height": 56,
"width": 200
},
"position": {
"x": 1370.6665839609984,
"y": 267.0323933738015
},
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "messageNode"
},
{
"data": {
"form": {
"text": "This workflow automatically generates a complete SEO-optimized blog article based on a simple user input. You don\u2019t need any writing experience. Just provide a topic or short request \u2014 the system will handle the rest.\n\nThe process includes the following key stages:\n\n1. **Understanding your topic and goals**\n2. **Designing the blog structure**\n3. **Writing high-quality content**\n\n\n"
},
"label": "Note",
"name": "Workflow Overall Description"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 205,
"id": "Note:SlimyGhostsWear",
"measured": {
"height": 205,
"width": 415
},
"position": {
"x": -284.3143151688742,
"y": 150.47632147913419
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 415
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent reads the user\u2019s input and figures out what kind of blog needs to be written.\n\n**What it does**:\n- Understands the main topic you want to write about \n- Identifies who the blog is for (e.g., beginners, marketers, developers) \n- Determines the writing purpose (e.g., SEO traffic, product promotion, education) \n- Suggests 3\u20135 long-tail SEO keywords related to the topic"
},
"label": "Note",
"name": "Parse And Keyword Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 152,
"id": "Note:EmptyChairsShake",
"measured": {
"height": 152,
"width": 340
},
"position": {
"x": 295.04147626768133,
"y": 372.2755718118446
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 340
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent builds the blog structure \u2014 just like writing a table of contents before you start writing the full article.\n\n**What it does**:\n- Suggests a clear blog title that includes important keywords \n- Breaks the article into sections using H2 and H3 headings (like a professional blog layout) \n- Assigns 1\u20132 recommended keywords to each section to help with SEO \n- Follows the writing goal and target audience set in the previous step"
},
"label": "Note",
"name": "Outline Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 146,
"id": "Note:TallMelonsNotice",
"measured": {
"height": 146,
"width": 343
},
"position": {
"x": 598.5644991893463,
"y": 5.801054564756448
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 343
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent is responsible for writing the actual content of the blog \u2014 paragraph by paragraph \u2014 based on the outline created earlier.\n\n**What it does**:\n- Looks at each H2/H3 section in the outline \n- Writes 150\u2013220 words of clear, helpful, and well-structured content per section \n- Includes the suggested SEO keywords naturally (not keyword stuffing) \n- Uses real examples or facts if needed (by calling a web search tool like Tavily)"
},
"label": "Note",
"name": "Body Agent"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"height": 137,
"id": "Note:RipeCougarsBuild",
"measured": {
"height": 137,
"width": 319
},
"position": {
"x": 860.4854129814981,
"y": 427.2196835690842
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 319
},
{
"data": {
"form": {
"text": "**Purpose**: \nThis agent reviews the entire blog draft to make sure it is smooth, professional, and SEO-friendly. It acts like a human editor before publishing.\n\n**What it does**:\n- Polishes the writing: improves sentence clarity, fixes awkward phrasing \n- Makes sure the content flows well from one section to the next \n- Double-checks keyword usage: are they present, natural, and not overused? \n- Verifies the blog structure (H1, H2, H3 headings) is correct \n- Adds two key SEO elements:\n - **Meta Title** (shows up in search results)\n - **Meta Description** (summary for Google and social sharing)"
},
"label": "Note",
"name": "Editor Agent"
},
"dragHandle": ".note-drag-handle",
"height": 146,
"id": "Note:OpenTurkeysSell",
"measured": {
"height": 146,
"width": 320
},
"position": {
"x": 1129,
"y": -30
},
"resizing": false,
"selected": false,
"sourcePosition": "right",
"targetPosition": "left",
"type": "noteNode",
"width": 320
}
]
},
"history": [],
"messages": [],
"path": [],
"retrieval": []
},
"avatar": "data:image/jpeg;base64,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"
}

331
agent/templates/technical_docs.json Normal file
View File

File diff suppressed because one or more lines are too long

331
agent/templates/technical_docs_qa.json Normal file
View File

File diff suppressed because one or more lines are too long

685
agent/templates/trip_planner.json Normal file
View File

File diff suppressed because one or more lines are too long

871
agent/templates/web_search_assistant.json Normal file
View File

File diff suppressed because one or more lines are too long

3
agent/tools/base.py
View File

@ -49,11 +49,12 @@ class LLMToolPluginCallSession(ToolCallSession):
def tool_call(self, name: str, arguments: dict[str, Any]) -> Any: def tool_call(self, name: str, arguments: dict[str, Any]) -> Any:
assert name in self.tools_map, f"LLM tool {name} does not exist" assert name in self.tools_map, f"LLM tool {name} does not exist"
self.callback(name, arguments, " running ...")
if isinstance(self.tools_map[name], MCPToolCallSession): if isinstance(self.tools_map[name], MCPToolCallSession):
resp = self.tools_map[name].tool_call(name, arguments, 60) resp = self.tools_map[name].tool_call(name, arguments, 60)
else: else:
resp = self.tools_map[name].invoke(**arguments) resp = self.tools_map[name].invoke(**arguments)
self.callback(name, arguments, resp)
return resp return resp
def get_tool_obj(self, name): def get_tool_obj(self, name):

6
api/apps/sdk/session.py
View File

@ -848,6 +848,10 @@ def begin_inputs(agent_id):
return get_error_data_result(f"Can't find agent by ID: {agent_id}") return get_error_data_result(f"Can't find agent by ID: {agent_id}")
canvas = Canvas(json.dumps(cvs.dsl), objs[0].tenant_id) canvas = Canvas(json.dumps(cvs.dsl), objs[0].tenant_id)
return get_result(data=canvas.get_component_input_form("begin")) return get_result(data={
"title": cvs.title,
"avatar": cvs.avatar,
"inputs": canvas.get_component_input_form("begin")
})

7
api/db/services/canvas_service.py
View File

@ -134,7 +134,9 @@ def completion(tenant_id, agent_id, session_id=None, **kwargs):
assert e, "Session not found!" assert e, "Session not found!"
if not conv.message: if not conv.message:
conv.message = [] conv.message = []
canvas = Canvas(json.dumps(conv.dsl), tenant_id, session_id) if not isinstance(conv.dsl, str):
conv.dsl = json.dumps(conv.dsl, ensure_ascii=False)
canvas = Canvas(conv.dsl, tenant_id, agent_id)
else: else:
e, cvs = UserCanvasService.get_by_id(agent_id) e, cvs = UserCanvasService.get_by_id(agent_id)
assert e, "Agent not found." assert e, "Agent not found."
@ -142,7 +144,8 @@ def completion(tenant_id, agent_id, session_id=None, **kwargs):
if not isinstance(cvs.dsl, str): if not isinstance(cvs.dsl, str):
cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False) cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
session_id=get_uuid() session_id=get_uuid()
canvas = Canvas(cvs.dsl, tenant_id, session_id) canvas = Canvas(cvs.dsl, tenant_id, agent_id)
canvas.reset()
conv = { conv = {
"id": session_id, "id": session_id,
"dialog_id": cvs.id, "dialog_id": cvs.id,

1
deepdoc/parser/html_parser.py
View File

@ -29,7 +29,6 @@ def get_encoding(file):
class RAGFlowHtmlParser: class RAGFlowHtmlParser:
def __call__(self, fnm, binary=None): def __call__(self, fnm, binary=None):
txt = ""
if binary: if binary:
encoding = find_codec(binary) encoding = find_codec(binary)
txt = binary.decode(encoding, errors="ignore") txt = binary.decode(encoding, errors="ignore")

7
rag/res/synonym.json
View File

@ -10535,5 +10535,12 @@
"q2": "二季度", "q2": "二季度",
"q3": "三季度", "q3": "三季度",
"q4": "四季度", "q4": "四季度",
"周一": ["礼拜一", "星期一"],
"周二": ["礼拜二", "星期二"],
"周三": ["礼拜三", "星期三"],
"周四": ["礼拜四", "星期四"],
"周五": ["礼拜五", "星期五"],
"周六": ["礼拜六", "星期六"],
"周日": ["礼拜日", "星期日", "星期天", "礼拜天"],
"上班": "办公" "上班": "办公"
} }