v0.20.0 release notes (#9218)

### What problem does this PR solve?

### Type of change

- [x] Documentation Update

.gitignore

@@ -193,3 +193,5 @@ dist
 # SvelteKit build / generate output
 .svelte-kit
 
+# Default backup dir
+backup

.trivyignore

@@ -0,0 +1,15 @@
+**/*.md
+**/*.min.js
+**/*.min.css
+**/*.svg
+**/*.png
+**/*.jpg
+**/*.jpeg
+**/*.gif
+**/*.woff
+**/*.woff2
+**/*.map
+**/*.webp
+**/*.ico
+**/*.ttf
+**/*.eot

agent/templates/cv_evaluation.json

@@ -170,7 +170,7 @@
                             "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}",
+                                    "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Outline agent output is {Agent:BetterSitesSend@content}",
                                     "role": "user"
                                 }
                             ],
@@ -250,7 +250,7 @@
                             "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}",
+                                    "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Outline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
                                     "role": "user"
                                 }
                             ],
@@ -602,7 +602,7 @@
                                 "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}",
+                                        "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Outline agent output is {Agent:BetterSitesSend@content}",
                                         "role": "user"
                                     }
                                 ],
@@ -715,7 +715,7 @@
                                 "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}",
+                                        "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Outline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
                                         "role": "user"
                                     }
                                 ],

agent/templates/market_generate_seo_blog.json

@@ -169,7 +169,7 @@
                             "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}",
+                                    "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Outline agent output is {Agent:BetterSitesSend@content}",
                                     "role": "user"
                                 }
                             ],
@@ -249,7 +249,7 @@
                             "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}",
+                                    "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Outline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
                                     "role": "user"
                                 }
                             ],
@@ -601,7 +601,7 @@
                                 "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}",
+                                        "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Outline agent output is {Agent:BetterSitesSend@content}",
                                         "role": "user"
                                     }
                                 ],
@@ -714,7 +714,7 @@
                                 "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}",
+                                        "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Outline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
                                         "role": "user"
                                     }
                                 ],
@@ -912,4 +912,4 @@
             "retrieval": []
         },
     "avatar": "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/4gHYSUNDX1BST0ZJTEUAAQEAAAHIAAAAAAQwAABtbnRyUkdCIFhZWiAH4AABAAEAAAAAAABhY3NwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlkZXNjAAAA8AAAACRyWFlaAAABFAAAABRnWFlaAAABKAAAABRiWFlaAAABPAAAABR3dHB0AAABUAAAABRyVFJDAAABZAAAAChnVFJDAAABZAAAAChiVFJDAAABZAAAAChjcHJ0AAABjAAAADxtbHVjAAAAAAAAAAEAAAAMZW5VUwAAAAgAAAAcAHMAUgBHAEJYWVogAAAAAAAAb6IAADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9YWVogAAAAAAAA9tYAAQAAAADTLXBhcmEAAAAAAAQAAAACZmYAAPKnAAANWQAAE9AAAApbAAAAAAAAAABtbHVjAAAAAAAAAAEAAAAMZW5VUwAAACAAAAAcAEcAbwBvAGcAbABlACAASQBuAGMALgAgADIAMAAxADb/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCAAwADADASIAAhEBAxEB/8QAGQAAAwEBAQAAAAAAAAAAAAAABgkKBwUI/8QAMBAAAAYCAQIEBQQCAwAAAAAAAQIDBAUGBxEhCAkAEjFBFFFhcaETFiKRFyOx8PH/xAAaAQACAwEBAAAAAAAAAAAAAAACAwABBgQF/8QALBEAAgIBAgUCBAcAAAAAAAAAAQIDBBEFEgATITFRIkEGIzJhFBUWgaGx8P/aAAwDAQACEQMRAD8AfF2hez9089t7pvxgQMa1Gb6qZ6oQE9m/NEvCIStyPfJSOF/M1epzMugo/qtMqbiRc1mJjoJKCLMNIxKcsLJedfO1Ct9cI63x9fx6CA/19t+oh4LFA5HfuAgP/A8eOIsnsTBrkBHXA7+v53+Q+ficTgJft9gIgA+/P9/1r342O/YA8A8k3/if+IbAN7+2/f8AAiI6H19PGoPyESTMZQPKUAHkQEN+3r9dh78/YPGUTk2wb/qAZZIugH1OHH5DjkdfbnWw2DsOxPj+xjrnx2H39unBopJGBn9s+PHv1HXjPJtH+J+B40O9a16h/wB/92j/ALrPa/wR104UyAobHlXhuo2HrEtK4qy3CwjKOuJLRHJLSkXWrFKs/gVrJVrE8TUiH8bPrP20UEu8m4hNpMJJuTOfnbUw/kUqyZgMHGjAO9+mtDsQ53sdcB6eMhnpEjhNQxRKICAgHy5+/roOdjr7c+J6O4x07dx484/n7nzw1gexBGfIPkZ/3t39uGpqc6+fP5/Ht8vGFZCzJjWpWuBxvO2yPjrtclUUK7BqmUI4fuASeyhG5FzFI0Bw4aQ0iZNoDgzvRW4qtyFkI4XmwyEk2YNnDp0sVBu3IUyy5iqH8gqKERSIRNIii67hddRJs1at01Xbx2sgzZoLu10UFJR+4V1A5cxF3FqNcLvjwcno43uuLrOxZYjujaClcb4QQfxEizpFiQyM9olcueRnjC2ZMt9iY06zL0qytrMSqSOVGsfHMaGhZ3l4lSRI2MqE74zJvRTveNFWWIh3RWw+XCAM5icKQLrCH57T17FhErSlRXnWvyZXKQwWJ3eraD14p5YuZCFgacskK2oGkVuKO5GYTHzf7DaD12cBD3DgPOIDrWw9PnrXPgDkpVsUDGMG+DD6E9gHXIjrYjwUPQTCXYgHPhIV974+F6E1hpC14Yzmzj56YaQEeZhXsayD1zLPW7pygxaMf81Nzu1iJsnIuDIKnaJAkPldqrHaoORZ73tMVEbFdSXT9nVgRQgnBq6j8e/HCIEATpAnH5KlmRVkFRFJwks/bqImSXJ5VFyA3N6Ikh3bCW3YHp5cowOmCfTgA+xJCnrjtwHKcLvJj2ZGcTRFj19kEhckdzgEjKnABGSSzdc1Fe5byXXGNjKdvRcw5NxvLidNZFFCxUa62KrzMaChw8hhYScFJtROAgmuLByq1MsgkZYPaVVuDe0wraRaqAdJwgRQo+YR8xTlAQNx6b49w41vXiJpCalLh1jZhyrTqRM4+jstdRmYryNkydLQRWg1LNGcWd5jIFFvCythlIySa0mNu74sKRQtaWsTmupqPItw0lE52ufpyYzrSkx6cw5bLmBEpkTsz+dt8P5QFuCRtAIkBH9MuwKHICIaDQhnojMs9mKaeGcrMxXlQtAYkdVljimRrE5MqI4zL8oSqQ6wxjodBqK05qdK3Vo3aCSVkBW7bjuC1NFJJBPaqyx6fp6pWkliYLXK2XrukkRu2CCVoSWMgsdMyySKwoLFcIGWSTUMg4IBgTcICoBhRcplMcpFkhIqQp1ClMBTmA0Zfe1zpjvHfXff65bZlzXpB3jjGTgiirmPjAfs16PHqHeQ75Wbj3xxZpOEkV3LRJJSPdomUBZISJLncV2k+8D07dxXp7xsYuTapA9UkJUYWIzNhadnWEZeCXGLQQiJi1ViHfhHL2unWh+mlORsrW0JFpEFnGVfm1mU4kq0FY3eD6corJncv6dr5NLSMNXVaTUksjTiMnaq8uFfSVuDyiJ1iZpy0LOJtpa3YfkcQ5fdozyxI2m5qqcrHN61YYmHsh6v3o9ParYmYJEtlhIx6+gUbjgD23M6oqg92YL0JyF6Bps+qDValVA9h9Lj5SZI3SHXdEQlj1wiQtLLIe6pGzjO3BlBkK1hxpblLVH5wdW0BcFKf/JwRtjsot2z8omaSdxbzzk1iEjsE0AM9rrRZNRIrVyo7dGO6E+oh8axLlJ5H5VaJKx7ePRGFbW6vUeFfHQIWPTI9Tm7HHfuhqY7E6C7JFqUzM6iZXIoncNxX7+bIVdJnTT48x3OQU1krIDW3UeixVhyISzYz6cadY5Xph6TseRNTRsTElzzBn9Vlly0TAERsdgnMYyLROjyFbg5R4ZlsGaMT4yNi2Zlq1GwjZB3jq0PsaJfA3t0jL0W0Y9xf1V41lpWckXMLaZiwxuKYPqc6LlHdkeRF+Qxswx5ASDqBVrsL+2A/N6SiCbYymV2BywJiMZj3GRRMTnL+lVyHCll3R7Szv0vqXMtQ74T+HijljIScLaEpkKCB3rqMBIi0jPs5JeOKTZMZEi5VVnouzy0k3jXjWSMlY6UcVGDxlKMVDqx91SILWSi3D2KdgYy3kP8E9X/AE1SnRXBNdNRMlefT6g7aY6giK+cPLGNg0bY68rcnpsNh9PqIBve/EcPQ3WIq2dR93xpSgk5SAZ9R6MLAOZFUkpLSUDXp6/KPpGUkmTdswlnKnwbl5ITMdGwcXJi7LKsqzUmT5tWYmkXuF9wjBvb76b7dHheazJ9RElUJOCxViuMlUJC0Gtz6PKyjLBY4qMWUe12r1xZ6lOyT6XPEBKN2CkTDOlZd02TBdTMt7Upx2knrkdCv1UKjDKn1A7XBYH6SCOOrWn5Oi/DtRiu+GleRthDL8rXdVjZlcfWrSIxVlGGGCOnH//Z"
-}
+}

agent/templates/seo_blog.json

@@ -169,7 +169,7 @@
                             "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}",
+                                    "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Outline agent output is {Agent:BetterSitesSend@content}",
                                     "role": "user"
                                 }
                             ],
@@ -249,7 +249,7 @@
                             "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}",
+                                    "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Outline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
                                     "role": "user"
                                 }
                             ],
@@ -601,7 +601,7 @@
                                 "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}",
+                                        "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\n\n\nThe Outline agent output is {Agent:BetterSitesSend@content}",
                                         "role": "user"
                                     }
                                 ],
@@ -714,7 +714,7 @@
                                 "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}",
+                                        "content": "The parse and keyword agent output is {Agent:ClearRabbitsScream@content}\n\nThe Outline agent output is {Agent:BetterSitesSend@content}\n\nThe Body agent output is {Agent:EagerNailsRemain@content}",
                                         "role": "user"
                                     }
                                 ],
@@ -912,4 +912,4 @@
             "retrieval": []
         },
     "avatar": "data:image/jpeg;base64,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"
-}
+}

api/apps/document_app.py

@@ -206,6 +206,8 @@ def list_docs():
         desc = False
     else:
         desc = True
+    create_time_from = int(request.args.get("create_time_from", 0))
+    create_time_to = int(request.args.get("create_time_to", 0))
 
     req = request.get_json()
 
@@ -226,6 +228,14 @@ def list_docs():
     try:
         docs, tol = DocumentService.get_by_kb_id(kb_id, page_number, items_per_page, orderby, desc, keywords, run_status, types, suffix)
 
+        if create_time_from or create_time_to:
+            filtered_docs = []
+            for doc in docs:
+                doc_create_time = doc.get("create_time", 0)
+                if (create_time_from == 0 or doc_create_time >= create_time_from) and (create_time_to == 0 or doc_create_time <= create_time_to):
+                    filtered_docs.append(doc)
+            docs = filtered_docs
+
         for doc_item in docs:
             if doc_item["thumbnail"] and not doc_item["thumbnail"].startswith(IMG_BASE64_PREFIX):
                 doc_item["thumbnail"] = f"/v1/document/image/{kb_id}-{doc_item['thumbnail']}"

api/apps/kb_app.py

@@ -247,7 +247,10 @@ def list_tags(kb_id):
             code=settings.RetCode.AUTHENTICATION_ERROR
         )
 
-    tags = settings.retrievaler.all_tags(current_user.id, [kb_id])
+    tenants = UserTenantService.get_tenants_by_user_id(current_user.id)
+    tags = []
+    for tenant in tenants:
+        tags += settings.retrievaler.all_tags(tenant["tenant_id"], [kb_id])
     return get_json_result(data=tags)
 
 
@@ -263,7 +266,10 @@ def list_tags_from_kbs():
                 code=settings.RetCode.AUTHENTICATION_ERROR
             )
 
-    tags = settings.retrievaler.all_tags(current_user.id, kb_ids)
+    tenants = UserTenantService.get_tenants_by_user_id(current_user.id)
+    tags = []
+    for tenant in tenants:
+        tags += settings.retrievaler.all_tags(tenant["tenant_id"], kb_ids)
     return get_json_result(data=tags)
 
 

api/apps/sdk/dify_retrieval.py

@@ -13,6 +13,8 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
+
 from flask import request, jsonify
 
 from api.db import LLMType
@@ -77,7 +79,7 @@ def retrieval(tenant_id):
                 "content": c["content_with_weight"],
                 "score": c["similarity"],
                 "title": c["docnm_kwd"],
-                "metadata": doc.meta_fields
+                "metadata": getattr(doc, 'meta_fields', {})
             })
 
         return jsonify({"records": records})
@@ -87,4 +89,5 @@ def retrieval(tenant_id):
                 message='No chunk found! Check the chunk status please!',
                 code=settings.RetCode.NOT_FOUND
             )
+        logging.exception(e)
         return build_error_result(message=str(e), code=settings.RetCode.SERVER_ERROR)

api/apps/sdk/doc.py

@@ -38,7 +38,7 @@ from api.utils.api_utils import check_duplicate_ids, construct_json_result, get_
 from rag.app.qa import beAdoc, rmPrefix
 from rag.app.tag import label_question
 from rag.nlp import rag_tokenizer, search
-from rag.prompts import keyword_extraction, cross_languages
+from rag.prompts import cross_languages, keyword_extraction
 from rag.utils import rmSpace
 from rag.utils.storage_factory import STORAGE_IMPL
 
@@ -456,6 +456,18 @@ def list_docs(dataset_id, tenant_id):
         required: false
         default: true
         description: Order in descending.
+    - in: query
+        name: create_time_from
+        type: integer
+        required: false
+        default: 0
+        description: Unix timestamp for filtering documents created after this time. 0 means no filter.
+      - in: query
+        name: create_time_to
+        type: integer
+        required: false
+        default: 0
+        description: Unix timestamp for filtering documents created before this time. 0 means no filter.
       - in: header
         name: Authorization
         type: string
@@ -517,6 +529,17 @@ def list_docs(dataset_id, tenant_id):
         desc = True
     docs, tol = DocumentService.get_list(dataset_id, page, page_size, orderby, desc, keywords, id, name)
 
+    create_time_from = int(request.args.get("create_time_from", 0))
+    create_time_to = int(request.args.get("create_time_to", 0))
+
+    if create_time_from or create_time_to:
+        filtered_docs = []
+        for doc in docs:
+            doc_create_time = doc.get("create_time", 0)
+            if (create_time_from == 0 or doc_create_time >= create_time_from) and (create_time_to == 0 or doc_create_time <= create_time_to):
+                filtered_docs.append(doc)
+        docs = filtered_docs
+
     # rename key's name
     renamed_doc_list = []
     key_mapping = {

api/db/services/dialog_service.py

@@ -208,12 +208,14 @@ def chat(dialog, messages, stream=True, **kwargs):
     check_llm_ts = timer()
 
     langfuse_tracer = None
+    trace_context = {}
     langfuse_keys = TenantLangfuseService.filter_by_tenant(tenant_id=dialog.tenant_id)
     if langfuse_keys:
         langfuse = Langfuse(public_key=langfuse_keys.public_key, secret_key=langfuse_keys.secret_key, host=langfuse_keys.host)
         if langfuse.auth_check():
             langfuse_tracer = langfuse
-            langfuse.trace = langfuse_tracer.trace(name=f"{dialog.name}-{llm_model_config['llm_name']}")
+            trace_id = langfuse_tracer.create_trace_id()
+            trace_context = {"trace_id": trace_id}
 
     check_langfuse_tracer_ts = timer()
     kbs, embd_mdl, rerank_mdl, chat_mdl, tts_mdl = get_models(dialog)
@@ -400,17 +402,19 @@ def chat(dialog, messages, stream=True, **kwargs):
             f"  - Token speed: {int(tk_num / (generate_result_time_cost / 1000.0))}/s"
         )
 
-        langfuse_output = "\n" + re.sub(r"^.*?(### Query:.*)", r"\1", prompt, flags=re.DOTALL)
-        langfuse_output = {"time_elapsed:": re.sub(r"\n", "  \n", langfuse_output), "created_at": time.time()}
-
         # Add a condition check to call the end method only if langfuse_tracer exists
         if langfuse_tracer and "langfuse_generation" in locals():
-            langfuse_generation.end(output=langfuse_output)
+            langfuse_output = "\n" + re.sub(r"^.*?(### Query:.*)", r"\1", prompt, flags=re.DOTALL)
+            langfuse_output = {"time_elapsed:": re.sub(r"\n", "  \n", langfuse_output), "created_at": time.time()}
+            langfuse_generation.update(output=langfuse_output)
+            langfuse_generation.end()
 
         return {"answer": think + answer, "reference": refs, "prompt": re.sub(r"\n", "  \n", prompt), "created_at": time.time()}
 
     if langfuse_tracer:
-        langfuse_generation = langfuse_tracer.trace.generation(name="chat", model=llm_model_config["llm_name"], input={"prompt": prompt, "prompt4citation": prompt4citation, "messages": msg})
+        langfuse_generation = langfuse_tracer.start_generation(
+            trace_context=trace_context, name="chat", model=llm_model_config["llm_name"], input={"prompt": prompt, "prompt4citation": prompt4citation, "messages": msg}
+        )
 
     if stream:
         last_ans = ""

api/db/services/llm_service.py

@@ -217,7 +217,7 @@ class TenantLLMService(CommonService):
         return list(objs)
 
     @staticmethod
-    def llm_id2llm_type(llm_id: str) ->str|None:
+    def llm_id2llm_type(llm_id: str) -> str | None:
         llm_id, *_ = TenantLLMService.split_model_name_and_factory(llm_id)
         llm_factories = settings.FACTORY_LLM_INFOS
         for llm_factory in llm_factories:
@@ -240,13 +240,13 @@ class LLMBundle:
         self.verbose_tool_use = kwargs.get("verbose_tool_use")
 
         langfuse_keys = TenantLangfuseService.filter_by_tenant(tenant_id=tenant_id)
+        self.langfuse = None
         if langfuse_keys:
             langfuse = Langfuse(public_key=langfuse_keys.public_key, secret_key=langfuse_keys.secret_key, host=langfuse_keys.host)
             if langfuse.auth_check():
                 self.langfuse = langfuse
-                self.trace = self.langfuse.trace(name=f"{self.llm_type}-{self.llm_name}")
-        else:
-            self.langfuse = None
+                trace_id = self.langfuse.create_trace_id()
+                self.trace_context = {"trace_id": trace_id}
 
     def bind_tools(self, toolcall_session, tools):
         if not self.is_tools:
@@ -256,7 +256,7 @@ class LLMBundle:
 
     def encode(self, texts: list):
         if self.langfuse:
-            generation = self.trace.generation(name="encode", model=self.llm_name, input={"texts": texts})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="encode", model=self.llm_name, input={"texts": texts})
 
         embeddings, used_tokens = self.mdl.encode(texts)
         llm_name = getattr(self, "llm_name", None)
@@ -264,13 +264,14 @@ class LLMBundle:
             logging.error("LLMBundle.encode can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens))
 
         if self.langfuse:
-            generation.end(usage_details={"total_tokens": used_tokens})
+            generation.update(usage_details={"total_tokens": used_tokens})
+            generation.end()
 
         return embeddings, used_tokens
 
     def encode_queries(self, query: str):
         if self.langfuse:
-            generation = self.trace.generation(name="encode_queries", model=self.llm_name, input={"query": query})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="encode_queries", model=self.llm_name, input={"query": query})
 
         emd, used_tokens = self.mdl.encode_queries(query)
         llm_name = getattr(self, "llm_name", None)
@@ -278,65 +279,70 @@ class LLMBundle:
             logging.error("LLMBundle.encode_queries can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens))
 
         if self.langfuse:
-            generation.end(usage_details={"total_tokens": used_tokens})
+            generation.update(usage_details={"total_tokens": used_tokens})
+            generation.end()
 
         return emd, used_tokens
 
     def similarity(self, query: str, texts: list):
         if self.langfuse:
-            generation = self.trace.generation(name="similarity", model=self.llm_name, input={"query": query, "texts": texts})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="similarity", model=self.llm_name, input={"query": query, "texts": texts})
 
         sim, used_tokens = self.mdl.similarity(query, texts)
         if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens):
             logging.error("LLMBundle.similarity can't update token usage for {}/RERANK used_tokens: {}".format(self.tenant_id, used_tokens))
 
         if self.langfuse:
-            generation.end(usage_details={"total_tokens": used_tokens})
+            generation.update(usage_details={"total_tokens": used_tokens})
+            generation.end()
 
         return sim, used_tokens
 
     def describe(self, image, max_tokens=300):
         if self.langfuse:
-            generation = self.trace.generation(name="describe", metadata={"model": self.llm_name})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="describe", metadata={"model": self.llm_name})
 
         txt, used_tokens = self.mdl.describe(image)
         if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens):
             logging.error("LLMBundle.describe can't update token usage for {}/IMAGE2TEXT used_tokens: {}".format(self.tenant_id, used_tokens))
 
         if self.langfuse:
-            generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.update(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.end()
 
         return txt
 
     def describe_with_prompt(self, image, prompt):
         if self.langfuse:
-            generation = self.trace.generation(name="describe_with_prompt", metadata={"model": self.llm_name, "prompt": prompt})
+            generation = self.language.start_generation(trace_context=self.trace_context, name="describe_with_prompt", metadata={"model": self.llm_name, "prompt": prompt})
 
         txt, used_tokens = self.mdl.describe_with_prompt(image, prompt)
         if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens):
             logging.error("LLMBundle.describe can't update token usage for {}/IMAGE2TEXT used_tokens: {}".format(self.tenant_id, used_tokens))
 
         if self.langfuse:
-            generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.update(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.end()
 
         return txt
 
     def transcription(self, audio):
         if self.langfuse:
-            generation = self.trace.generation(name="transcription", metadata={"model": self.llm_name})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="transcription", metadata={"model": self.llm_name})
 
         txt, used_tokens = self.mdl.transcription(audio)
         if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens):
             logging.error("LLMBundle.transcription can't update token usage for {}/SEQUENCE2TXT used_tokens: {}".format(self.tenant_id, used_tokens))
 
         if self.langfuse:
-            generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.update(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.end()
 
         return txt
 
     def tts(self, text: str) -> Generator[bytes, None, None]:
         if self.langfuse:
-            span = self.trace.span(name="tts", input={"text": text})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="tts", input={"text": text})
 
         for chunk in self.mdl.tts(text):
             if isinstance(chunk, int):
@@ -346,7 +352,7 @@ class LLMBundle:
             yield chunk
 
         if self.langfuse:
-            span.end()
+            generation.end()
 
     def _remove_reasoning_content(self, txt: str) -> str:
         first_think_start = txt.find("<think>")
@@ -362,9 +368,9 @@ class LLMBundle:
 
         return txt[last_think_end + len("</think>") :]
 
-    def chat(self, system: str, history: list, gen_conf: dict={}, **kwargs) -> str:
+    def chat(self, system: str, history: list, gen_conf: dict = {}, **kwargs) -> str:
         if self.langfuse:
-            generation = self.trace.generation(name="chat", model=self.llm_name, input={"system": system, "history": history})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="chat", model=self.llm_name, input={"system": system, "history": history})
 
         chat_partial = partial(self.mdl.chat, system, history, gen_conf)
         if self.is_tools and self.mdl.is_tools:
@@ -380,13 +386,14 @@ class LLMBundle:
             logging.error("LLMBundle.chat can't update token usage for {}/CHAT llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, used_tokens))
 
         if self.langfuse:
-            generation.end(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.update(output={"output": txt}, usage_details={"total_tokens": used_tokens})
+            generation.end()
 
         return txt
 
-    def chat_streamly(self, system: str, history: list, gen_conf: dict={}, **kwargs):
+    def chat_streamly(self, system: str, history: list, gen_conf: dict = {}, **kwargs):
         if self.langfuse:
-            generation = self.trace.generation(name="chat_streamly", model=self.llm_name, input={"system": system, "history": history})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="chat_streamly", model=self.llm_name, input={"system": system, "history": history})
 
         ans = ""
         chat_partial = partial(self.mdl.chat_streamly, system, history, gen_conf)
@@ -398,7 +405,8 @@ class LLMBundle:
             if isinstance(txt, int):
                 total_tokens = txt
                 if self.langfuse:
-                    generation.end(output={"output": ans})
+                    generation.update(output={"output": ans})
+                    generation.end()
                 break
 
             if txt.endswith("</think>"):

api/settings.py

@@ -70,6 +70,7 @@ REGISTER_ENABLED = 1
 # sandbox-executor-manager
 SANDBOX_ENABLED = 0
 SANDBOX_HOST = None
+STRONG_TEST_COUNT = int(os.environ.get("STRONG_TEST_COUNT", "32"))
 
 BUILTIN_EMBEDDING_MODELS = ["BAAI/bge-large-zh-v1.5@BAAI", "maidalun1020/bce-embedding-base_v1@Youdao"]
 

api/utils/api_utils.py

@@ -687,7 +687,13 @@ def timeout(seconds: float | int = None, attempts: int = 2, *, exception: Option
 
 
 async def is_strong_enough(chat_model, embedding_model):
-    @timeout(30, 2)
+    count = settings.STRONG_TEST_COUNT
+    if not chat_model or not embedding_model:
+        return
+    if isinstance(count, int) and count <= 0:
+        return
+
+    @timeout(60, 2)
     async def _is_strong_enough():
         nonlocal chat_model, embedding_model
         if embedding_model:
@@ -701,5 +707,5 @@ async def is_strong_enough(chat_model, embedding_model):
 
     # Pressure test for GraphRAG task
     async with trio.open_nursery() as nursery:
-        for _ in range(32):
+        for _ in range(count):
             nursery.start_soon(_is_strong_enough)

deepdoc/parser/ppt_parser.py

@@ -87,7 +87,7 @@ class RAGFlowPptParser:
                 break
             texts = []
             for shape in sorted(
-                    slide.shapes, key=lambda x: ((x.top if x.top is not None else 0) // 10, x.left)):
+                    slide.shapes, key=lambda x: ((x.top if x.top is not None else 0) // 10, x.left if x.left is not None else 0)):
                 try:
                     txt = self.__extract(shape)
                     if txt:
@@ -96,4 +96,4 @@ class RAGFlowPptParser:
                     logging.exception(e)
             txts.append("\n".join(texts))
 
-        return txts
+        return txts

docker/migration.sh

@@ -0,0 +1,298 @@
+#!/bin/bash
+
+# RAGFlow Data Migration Script
+# Usage: ./migration.sh [backup|restore] [backup_folder]
+# 
+# This script helps you backup and restore RAGFlow Docker volumes
+# including MySQL, MinIO, Redis, and Elasticsearch data.
+
+set -e  # Exit on any error
+# Instead, we'll handle errors manually for better debugging experience
+
+# Default values
+DEFAULT_BACKUP_FOLDER="backup"
+VOLUMES=("docker_mysql_data" "docker_minio_data" "docker_redis_data" "docker_esdata01")
+BACKUP_FILES=("mysql_backup.tar.gz" "minio_backup.tar.gz" "redis_backup.tar.gz" "es_backup.tar.gz")
+
+# Function to display help information
+show_help() {
+    echo "RAGFlow Data Migration Tool"
+    echo ""
+    echo "USAGE:"
+    echo "  $0 <operation> [backup_folder]"
+    echo ""
+    echo "OPERATIONS:"
+    echo "  backup   - Create backup of all RAGFlow data volumes"
+    echo "  restore  - Restore RAGFlow data volumes from backup"
+    echo "  help     - Show this help message"
+    echo ""
+    echo "PARAMETERS:"
+    echo "  backup_folder  - Name of backup folder (default: '$DEFAULT_BACKUP_FOLDER')"
+    echo ""
+    echo "EXAMPLES:"
+    echo "  $0 backup                    # Backup to './backup' folder"
+    echo "  $0 backup my_backup          # Backup to './my_backup' folder"
+    echo "  $0 restore                   # Restore from './backup' folder"
+    echo "  $0 restore my_backup         # Restore from './my_backup' folder"
+    echo ""
+    echo "DOCKER VOLUMES:"
+    echo "  - docker_mysql_data     (MySQL database)"
+    echo "  - docker_minio_data     (MinIO object storage)"
+    echo "  - docker_redis_data     (Redis cache)"
+    echo "  - docker_esdata01       (Elasticsearch indices)"
+}
+
+# Function to check if Docker is running
+check_docker() {
+    if ! docker info >/dev/null 2>&1; then
+        echo "❌ Error: Docker is not running or not accessible"
+        echo "Please start Docker and try again"
+        exit 1
+    fi
+}
+
+# Function to check if volume exists
+volume_exists() {
+    local volume_name=$1
+    docker volume inspect "$volume_name" >/dev/null 2>&1
+}
+
+# Function to check if any containers are using the target volumes
+check_containers_using_volumes() {
+    echo "🔍 Checking for running containers that might be using target volumes..."
+    
+    # Get all running containers
+    local running_containers=$(docker ps --format "{{.Names}}")
+    
+    if [ -z "$running_containers" ]; then
+        echo "✅ No running containers found"
+        return 0
+    fi
+    
+    # Check each running container for volume usage
+    local containers_using_volumes=()
+    local volume_usage_details=()
+    
+    for container in $running_containers; do
+        # Get container's mount information
+        local mounts=$(docker inspect "$container" --format '{{range .Mounts}}{{.Source}}{{"|"}}{{end}}' 2>/dev/null || echo "")
+        
+        # Check if any of our target volumes are used by this container
+        for volume in "${VOLUMES[@]}"; do
+            if echo "$mounts" | grep -q "$volume"; then
+                containers_using_volumes+=("$container")
+                volume_usage_details+=("$container -> $volume")
+                break
+            fi
+        done
+    done
+    
+    # If any containers are using our volumes, show error and exit
+    if [ ${#containers_using_volumes[@]} -gt 0 ]; then
+        echo ""
+        echo "❌ ERROR: Found running containers using target volumes!"
+        echo ""
+        echo "📋 Running containers status:"
+        docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Image}}"
+        echo ""
+        echo "🔗 Volume usage details:"
+        for detail in "${volume_usage_details[@]}"; do
+            echo "  - $detail"
+        done
+        echo ""
+        echo "🛑 SOLUTION: Stop the containers before performing backup/restore operations:"
+        echo "   docker-compose -f docker/<your-docker-compose-file>.yml down"
+        echo ""
+        echo "💡 After backup/restore, you can restart with:"
+        echo "   docker-compose -f docker/<your-docker-compose-file>.yml up -d"
+        echo ""
+        exit 1
+    fi
+    
+    echo "✅ No containers are using target volumes, safe to proceed"
+    return 0
+}
+
+# Function to confirm user action
+confirm_action() {
+    local message=$1
+    echo -n "$message (y/N): "
+    read -r response
+    case "$response" in
+        [yY]|[yY][eE][sS]) return 0 ;;
+        *) return 1 ;;
+    esac
+}
+
+# Function to perform backup
+perform_backup() {
+    local backup_folder=$1
+    
+    echo "🚀 Starting RAGFlow data backup..."
+    echo "📁 Backup folder: $backup_folder"
+    echo ""
+    
+    # Check if any containers are using the volumes
+    check_containers_using_volumes
+    
+    # Create backup folder if it doesn't exist
+    mkdir -p "$backup_folder"
+    
+    # Backup each volume
+    for i in "${!VOLUMES[@]}"; do
+        local volume="${VOLUMES[$i]}"
+        local backup_file="${BACKUP_FILES[$i]}"
+        local step=$((i + 1))
+        
+        echo "📦 Step $step/4: Backing up $volume..."
+        
+        if volume_exists "$volume"; then
+            docker run --rm \
+                -v "$volume":/source \
+                -v "$(pwd)/$backup_folder":/backup \
+                alpine tar czf "/backup/$backup_file" -C /source .
+            echo "✅ Successfully backed up $volume to $backup_folder/$backup_file"
+        else
+            echo "⚠️  Warning: Volume $volume does not exist, skipping..."
+        fi
+        echo ""
+    done
+    
+    echo "🎉 Backup completed successfully!"
+    echo "📍 Backup location: $(pwd)/$backup_folder"
+    
+    # List backup files with sizes
+    echo ""
+    echo "📋 Backup files created:"
+    for backup_file in "${BACKUP_FILES[@]}"; do
+        if [ -f "$backup_folder/$backup_file" ]; then
+            local size=$(ls -lh "$backup_folder/$backup_file" | awk '{print $5}')
+            echo "  - $backup_file ($size)"
+        fi
+    done
+}
+
+# Function to perform restore
+perform_restore() {
+    local backup_folder=$1
+    
+    echo "🔄 Starting RAGFlow data restore..."
+    echo "📁 Backup folder: $backup_folder"
+    echo ""
+    
+    # Check if any containers are using the volumes
+    check_containers_using_volumes
+    
+    # Check if backup folder exists
+    if [ ! -d "$backup_folder" ]; then
+        echo "❌ Error: Backup folder '$backup_folder' does not exist"
+        exit 1
+    fi
+    
+    # Check if all backup files exist
+    local missing_files=()
+    for backup_file in "${BACKUP_FILES[@]}"; do
+        if [ ! -f "$backup_folder/$backup_file" ]; then
+            missing_files+=("$backup_file")
+        fi
+    done
+    
+    if [ ${#missing_files[@]} -gt 0 ]; then
+        echo "❌ Error: Missing backup files:"
+        for file in "${missing_files[@]}"; do
+            echo "  - $file"
+        done
+        echo "Please ensure all backup files are present in '$backup_folder'"
+        exit 1
+    fi
+    
+    # Check for existing volumes and warn user
+    local existing_volumes=()
+    for volume in "${VOLUMES[@]}"; do
+        if volume_exists "$volume"; then
+            existing_volumes+=("$volume")
+        fi
+    done
+    
+    if [ ${#existing_volumes[@]} -gt 0 ]; then
+        echo "⚠️  WARNING: The following Docker volumes already exist:"
+        for volume in "${existing_volumes[@]}"; do
+            echo "  - $volume"
+        done
+        echo ""
+        echo "🔴 IMPORTANT: Restoring will OVERWRITE existing data!"
+        echo "💡 Recommendation: Create a backup of your current data first:"
+        echo "   $0 backup current_backup_$(date +%Y%m%d_%H%M%S)"
+        echo ""
+        
+        if ! confirm_action "Do you want to continue with the restore operation?"; then
+            echo "❌ Restore operation cancelled by user"
+            exit 0
+        fi
+    fi
+    
+    # Create volumes and restore data
+    for i in "${!VOLUMES[@]}"; do
+        local volume="${VOLUMES[$i]}"
+        local backup_file="${BACKUP_FILES[$i]}"
+        local step=$((i + 1))
+        
+        echo "🔧 Step $step/4: Restoring $volume..."
+        
+        # Create volume if it doesn't exist
+        if ! volume_exists "$volume"; then
+            echo "  📋 Creating Docker volume: $volume"
+            docker volume create "$volume"
+        else
+            echo "  📋 Using existing Docker volume: $volume"
+        fi
+        
+        # Restore data
+        echo "  📥 Restoring data from $backup_file..."
+        docker run --rm \
+            -v "$volume":/target \
+            -v "$(pwd)/$backup_folder":/backup \
+            alpine tar xzf "/backup/$backup_file" -C /target
+        
+        echo "✅ Successfully restored $volume"
+        echo ""
+    done
+    
+    echo "🎉 Restore completed successfully!"
+    echo "💡 You can now start your RAGFlow services"
+}
+
+# Main script logic
+main() {
+    # Check if Docker is available
+    check_docker
+    
+    # Parse command line arguments
+    local operation=${1:-}
+    local backup_folder=${2:-$DEFAULT_BACKUP_FOLDER}
+    
+    # Handle help or no arguments
+    if [ -z "$operation" ] || [ "$operation" = "help" ] || [ "$operation" = "-h" ] || [ "$operation" = "--help" ]; then
+        show_help
+        exit 0
+    fi
+    
+    # Validate operation
+    case "$operation" in
+        backup)
+            perform_backup "$backup_folder"
+            ;;
+        restore)
+            perform_restore "$backup_folder"
+            ;;
+        *)
+            echo "❌ Error: Invalid operation '$operation'"
+            echo ""
+            show_help
+            exit 1
+            ;;
+    esac
+}
+
+# Run main function with all arguments
+main "$@"

docs/guides/migration/migrate_from_docker_compose.md

@@ -0,0 +1,108 @@
+# Data Migration Guide
+
+A common scenario is processing large datasets on a powerful instance (e.g., with a GPU) and then migrating the entire RAGFlow service to a different production environment (e.g., a CPU-only server). This guide explains how to safely back up and restore your data using our provided migration script.
+
+## Identifying Your Data
+
+By default, RAGFlow uses Docker volumes to store all persistent data, including your database, uploaded files, and search indexes. You can see these volumes by running:
+
+```bash
+docker volume ls
+```
+
+The output will look similar to this:
+
+```text
+DRIVER    VOLUME NAME
+local     docker_esdata01
+local     docker_minio_data
+local     docker_mysql_data
+local     docker_redis_data
+```
+
+These volumes contain all the data you need to migrate.
+
+## Step 1: Stop RAGFlow Services
+
+Before starting the migration, you must stop all running RAGFlow services on the **source machine**. Navigate to the project's root directory and run:
+
+```bash
+docker-compose -f docker/docker-compose.yml down
+```
+
+**Important:** Do **not** use the `-v` flag (e.g., `docker-compose down -v`), as this will delete all your data volumes. The migration script includes a check and will prevent you from running it if services are active.
+
+## Step 2: Back Up Your Data
+
+We provide a convenient script to package all your data volumes into a single backup folder.
+
+For a quick reference of the script's commands and options, you can run:
+```bash
+bash docker/migration.sh help
+```
+
+To create a backup, run the following command from the project's root directory:
+
+```bash
+bash docker/migration.sh backup
+```
+
+This will create a `backup/` folder in your project root containing compressed archives of your data volumes.
+
+You can also specify a custom name for your backup folder:
+
+```bash
+bash docker/migration.sh backup my_ragflow_backup
+```
+
+This will create a folder named `my_ragflow_backup/` instead.
+
+## Step 3: Transfer the Backup Folder
+
+Copy the entire backup folder (e.g., `backup/` or `my_ragflow_backup/`) from your source machine to the RAGFlow project directory on your **target machine**. You can use tools like `scp`, `rsync`, or a physical drive for the transfer.
+
+## Step 4: Restore Your Data
+
+On the **target machine**, ensure that RAGFlow services are not running. Then, use the migration script to restore your data from the backup folder.
+
+If your backup folder is named `backup/`, run:
+
+```bash
+bash docker/migration.sh restore
+```
+
+If you used a custom name, specify it in the command:
+
+```bash
+bash docker/migration.sh restore my_ragflow_backup
+```
+
+The script will automatically create the necessary Docker volumes and unpack the data.
+
+**Note:** If the script detects that Docker volumes with the same names already exist on the target machine, it will warn you that restoring will overwrite the existing data and ask for confirmation before proceeding.
+
+## Step 5: Start RAGFlow Services
+
+Once the restore process is complete, you can start the RAGFlow services on your new machine:
+
+```bash
+docker-compose -f docker/docker-compose.yml up -d
+```
+
+**Note:** If you already have build an service by docker-compose before, you may need to backup your data for target machine like this guide above and run like:
+
+```bash
+# Please backup by `sh docker/migration.sh backup backup_dir_name` before you do the following line.
+# !!! this line -v flag will delete the original docker volume
+docker-compose -f docker/docker-compose.yml down -v
+docker-compose -f docker/docker-compose.yml up -d
+```
+
+Your RAGFlow instance is now running with all the data from your original machine.
+
+
+
+
+
+
+

docs/references/http_api_reference.md

@@ -1118,14 +1118,14 @@ Failure:
 
 ### List documents
 
-**GET** `/api/v1/datasets/{dataset_id}/documents?page={page}&page_size={page_size}&orderby={orderby}&desc={desc}&keywords={keywords}&id={document_id}&name={document_name}`
+**GET** `/api/v1/datasets/{dataset_id}/documents?page={page}&page_size={page_size}&orderby={orderby}&desc={desc}&keywords={keywords}&id={document_id}&name={document_name}&create_time_from={timestamp}&create_time_to={timestamp}`
 
 Lists documents in a specified dataset.
 
 #### Request
 
 - Method: GET
-- URL: `/api/v1/datasets/{dataset_id}/documents?page={page}&page_size={page_size}&orderby={orderby}&desc={desc}&keywords={keywords}&id={document_id}&name={document_name}`
+- URL: `/api/v1/datasets/{dataset_id}/documents?page={page}&page_size={page_size}&orderby={orderby}&desc={desc}&keywords={keywords}&id={document_id}&name={document_name}&create_time_from={timestamp}&create_time_to={timestamp}`
 - Headers:
   - `'content-Type: application/json'`
   - `'Authorization: Bearer <YOUR_API_KEY>'`
@@ -1134,7 +1134,7 @@ Lists documents in a specified dataset.
 
 ```bash
 curl --request GET \
-     --url http://{address}/api/v1/datasets/{dataset_id}/documents?page={page}&page_size={page_size}&orderby={orderby}&desc={desc}&keywords={keywords}&id={document_id}&name={document_name} \
+     --url http://{address}/api/v1/datasets/{dataset_id}/documents?page={page}&page_size={page_size}&orderby={orderby}&desc={desc}&keywords={keywords}&id={document_id}&name={document_name}&create_time_from={timestamp}&create_time_to={timestamp} \
      --header 'Authorization: Bearer <YOUR_API_KEY>'
 ```
 
@@ -1156,6 +1156,10 @@ curl --request GET \
   Indicates whether the retrieved documents should be sorted in descending order. Defaults to `true`.
 - `id`: (*Filter parameter*), `string`  
   The ID of the document to retrieve.
+- `create_time_from`: (*Filter parameter*), `integer`
+  Unix timestamp for filtering documents created after this time. 0 means no filter. Defaults to `0`.
+- `create_time_to`: (*Filter parameter*), `integer`
+  Unix timestamp for filtering documents created before this time. 0 means no filter. Defaults to `0`.
 
 #### Response
 

docs/references/python_api_reference.md

@@ -507,7 +507,16 @@ print(doc)
 ### List documents
 
 ```python
-Dataset.list_documents(id:str =None, keywords: str=None, page: int=1, page_size:int = 30, order_by:str = "create_time", desc: bool = True) -> list[Document]
+Dataset.list_documents(
+    id: str = None,
+    keywords: str = None,
+    page: int = 1,
+    page_size: int = 30,
+    order_by: str = "create_time",
+    desc: bool = True,
+    create_time_from: int = 0,
+    create_time_to: int = 0
+) -> list[Document]
 ```
 
 Lists documents in the current dataset.
@@ -541,6 +550,12 @@ The field by which documents should be sorted. Available options:
 
 Indicates whether the retrieved documents should be sorted in descending order. Defaults to `True`.
 
+##### create_time_from: `int`
+Unix timestamp for filtering documents created after this time. 0 means no filter. Defaults to 0.
+
+##### create_time_to: `int`
+Unix timestamp for filtering documents created before this time. 0 means no filter. Defaults to 0.
+
 #### Returns
 
 - Success: A list of `Document` objects.

docs/release_notes.md

@@ -22,6 +22,39 @@ The embedding models included in a full edition are:
 These two embedding models are optimized specifically for English and Chinese, so performance may be compromised if you use them to embed documents in other languages.
 :::
 
+## v0.20.0
+
+Released on August 4, 2025.
+
+### Compatibility changes
+
+From v0.20.0 onwards, Agents are no longer compatible with earlier versions, and all existing Agents from previous versions must be rebuilt following the upgrade.
+
+### New features
+
+- Unified orchestration of both Agents and Workflows.
+- A comprehensive refactor of the Agent, greatly enhancing its capabilities and usability, with support for Multi-Agent configurations, planning and reflection, and visual functionalities.
+- Fully realized MCP functionality, allowing for MCP Server import, Agents functioning as MCP Clients, and RAGFlow itself operating as an MCP Server.
+- Access to runtime logs for Agents.
+- Chat histories with Agents available through the management panel.
+- Integration of a new, more robust version of Infinity, enabling the auto-tagging functionality with Infinity as the underlying document engine.
+- An OpenAI-compatible API that supports file reference information.
+- Support for new embedding models, including Kimi K2, Grok 4, and Voyage.
+- RAGFlow’s codebase is now mirrored on Gitee.
+- Introduction of a new model provider, Gitee AI.
+
+### New agent templates
+
+- Multi-Agent based Deep Research: Collaborative Agent teamwork led by a Lead Agent with multiple Subagents, distinct from traditional workflow orchestration.
+- An intelligent Q&A chatbot leveraging internal knowledge bases, designed for customer service and training scenarios.
+- A resume analysis template used by the RAGFlow team to screen, analyze, and record candidate information.
+- A blog generation workflow that transforms raw ideas into SEO-friendly blog content.
+- An intelligent customer service workflow.
+- A user feedback analysis template that directs user feedback to appropriate teams through semantic analysis.
+- Trip Planner: Uses web search and map MCP servers to assist with travel planning.
+- Image Lingo: Translates content from uploaded photos.
+- An information search assistant that retrieves answers from both internal knowledge bases and the web.
+
 ## v0.19.1
 
 Released on June 23, 2025.

graphrag/general/extractor.py

@@ -47,7 +47,7 @@ class Extractor:
         self._language = language
         self._entity_types = entity_types or DEFAULT_ENTITY_TYPES
 
-    @timeout(60*3)
+    @timeout(60*5)
     def _chat(self, system, history, gen_conf={}):
         hist = deepcopy(history)
         conf = deepcopy(gen_conf)

rag/app/presentation.py

@@ -42,7 +42,7 @@ class Ppt(PptParser):
                 try:
                     with BytesIO() as buffered:
                         slide.get_thumbnail(
-                            0.5, 0.5).save(
+                            0.1, 0.1).save(
                             buffered, drawing.imaging.ImageFormat.jpeg)
                         buffered.seek(0)
                         imgs.append(Image.open(buffered).copy())

rag/llm/chat_model.py

@@ -1075,6 +1075,9 @@ class GeminiChat(Base):
         for k in list(gen_conf.keys()):
             if k not in ["temperature", "top_p", "max_tokens"]:
                 del gen_conf[k]
+            # if max_tokens exists, rename it to max_output_tokens to match Gemini's API
+            if k == "max_tokens":
+                gen_conf["max_output_tokens"] = gen_conf.pop("max_tokens")
         return gen_conf
 
     def _chat(self, history, gen_conf={}, **kwargs):

rag/nlp/__init__.py

@@ -634,6 +634,17 @@ def concat_img(img1, img2):
         return img2
     if not img1 and not img2:
         return None
+    
+    if img1 is img2:
+        return img1
+    
+    if isinstance(img1, Image.Image) and isinstance(img2, Image.Image):
+        pixel_data1 = img1.tobytes()
+        pixel_data2 = img2.tobytes()
+        if pixel_data1 == pixel_data2:
+            img2.close()
+            return img1
+
     width1, height1 = img1.size
     width2, height2 = img2.size
 
@@ -643,7 +654,8 @@ def concat_img(img1, img2):
 
     new_image.paste(img1, (0, 0))
     new_image.paste(img2, (0, height1))
-
+    img1.close()
+    img2.close()
     return new_image
 
 

sdk/python/ragflow_sdk/modules/dataset.py

@@ -63,8 +63,30 @@ class DataSet(Base):
             return doc_list
         raise Exception(res.get("message"))
 
-    def list_documents(self, id: str | None = None, name: str | None = None, keywords: str | None = None, page: int = 1, page_size: int = 30, orderby: str = "create_time", desc: bool = True):
-        res = self.get(f"/datasets/{self.id}/documents", params={"id": id, "name": name, "keywords": keywords, "page": page, "page_size": page_size, "orderby": orderby, "desc": desc})
+    def list_documents(
+        self,
+        id: str | None = None,
+        name: str | None = None,
+        keywords: str | None = None,
+        page: int = 1,
+        page_size: int = 30,
+        orderby: str = "create_time",
+        desc: bool = True,
+        create_time_from: int = 0,
+        create_time_to: int = 0,
+    ):
+        params = {
+            "id": id,
+            "name": name,
+            "keywords": keywords,
+            "page": page,
+            "page_size": page_size,
+            "orderby": orderby,
+            "desc": desc,
+            "create_time_from": create_time_from,
+            "create_time_to": create_time_to,
+        }
+        res = self.get(f"/datasets/{self.id}/documents", params=params)
         res = res.json()
         documents = []
         if res.get("code") == 0:

web/src/components/knowledge-base-item.tsx

@@ -1,9 +1,13 @@
 import { DocumentParserType } from '@/constants/knowledge';
 import { useTranslate } from '@/hooks/common-hooks';
 import { useFetchKnowledgeList } from '@/hooks/knowledge-hooks';
+import { useBuildQueryVariableOptions } from '@/pages/agent/hooks/use-get-begin-query';
 import { UserOutlined } from '@ant-design/icons';
 import { Avatar as AntAvatar, Form, Select, Space } from 'antd';
+import { toLower } from 'lodash';
+import { useMemo } from 'react';
 import { useFormContext } from 'react-hook-form';
+import { useTranslation } from 'react-i18next';
 import { RAGFlowAvatar } from './ragflow-avatar';
 import { FormControl, FormField, FormItem, FormLabel } from './ui/form';
 import { MultiSelect } from './ui/multi-select';
@@ -66,9 +70,13 @@ const KnowledgeBaseItem = ({
 
 export default KnowledgeBaseItem;
 
-export function KnowledgeBaseFormField() {
+export function KnowledgeBaseFormField({
+  showVariable = false,
+}: {
+  showVariable?: boolean;
+}) {
   const form = useFormContext();
-  const { t } = useTranslate('chat');
+  const { t } = useTranslation();
 
   const { list: knowledgeList } = useFetchKnowledgeList(true);
 
@@ -76,6 +84,8 @@ export function KnowledgeBaseFormField() {
     (x) => x.parser_id !== DocumentParserType.Tag,
   );
 
+  const nextOptions = useBuildQueryVariableOptions();
+
   const knowledgeOptions = filteredKnowledgeList.map((x) => ({
     label: x.name,
     value: x.id,
@@ -84,18 +94,48 @@ export function KnowledgeBaseFormField() {
     ),
   }));
 
+  const options = useMemo(() => {
+    if (showVariable) {
+      return [
+        {
+          label: t('knowledgeDetails.dataset'),
+          options: knowledgeOptions,
+        },
+        ...nextOptions.map((x) => {
+          return {
+            ...x,
+            options: x.options
+              .filter((y) => toLower(y.type).includes('string'))
+              .map((x) => ({
+                ...x,
+                icon: () => (
+                  <RAGFlowAvatar
+                    className="size-4 mr-2"
+                    avatar={x.label}
+                    name={x.label}
+                  />
+                ),
+              })),
+          };
+        }),
+      ];
+    }
+
+    return knowledgeOptions;
+  }, [knowledgeOptions, nextOptions, showVariable, t]);
+
   return (
     <FormField
       control={form.control}
       name="kb_ids"
       render={({ field }) => (
         <FormItem>
-          <FormLabel>{t('knowledgeBases')}</FormLabel>
+          <FormLabel>{t('chat.knowledgeBases')}</FormLabel>
           <FormControl>
             <MultiSelect
-              options={knowledgeOptions}
+              options={options}
               onValueChange={field.onChange}
-              placeholder={t('knowledgeBasesMessage')}
+              placeholder={t('chat.knowledgeBasesMessage')}
               variant="inverted"
               maxCount={100}
               defaultValue={field.value}

web/src/components/ui/accordion.tsx

@@ -28,8 +28,11 @@ function AccordionItem({
 function AccordionTrigger({
   className,
   children,
+  hideDownIcon = false,
   ...props
-}: React.ComponentProps<typeof AccordionPrimitive.Trigger>) {
+}: React.ComponentProps<typeof AccordionPrimitive.Trigger> & {
+  hideDownIcon?: boolean;
+}) {
   return (
     <AccordionPrimitive.Header className="flex">
       <AccordionPrimitive.Trigger
@@ -41,7 +44,9 @@ function AccordionTrigger({
         {...props}
       >
         {children}
-        <ChevronDownIcon className="text-muted-foreground pointer-events-none size-4 shrink-0 translate-y-0.5 transition-transform duration-200" />
+        {!hideDownIcon && (
+          <ChevronDownIcon className="text-muted-foreground pointer-events-none size-4 shrink-0 translate-y-0.5 transition-transform duration-200" />
+        )}
       </AccordionPrimitive.Trigger>
     </AccordionPrimitive.Header>
   );

web/src/components/ui/multi-select.tsx

@@ -1,3 +1,4 @@
+// https://github.com/sersavan/shadcn-multi-select-component
 // src/components/multi-select.tsx
 
 import { cva, type VariantProps } from 'class-variance-authority';
@@ -29,6 +30,51 @@ import {
 import { Separator } from '@/components/ui/separator';
 import { cn } from '@/lib/utils';
 
+export type MultiSelectOptionType = {
+  label: React.ReactNode;
+  value: string;
+  disabled?: boolean;
+  icon?: React.ComponentType<{ className?: string }>;
+};
+
+export type MultiSelectGroupOptionType = {
+  label: React.ReactNode;
+  options: MultiSelectOptionType[];
+};
+
+function MultiCommandItem({
+  option,
+  isSelected,
+  toggleOption,
+}: {
+  option: MultiSelectOptionType;
+  isSelected: boolean;
+  toggleOption(value: string): void;
+}) {
+  return (
+    <CommandItem
+      key={option.value}
+      onSelect={() => toggleOption(option.value)}
+      className="cursor-pointer"
+    >
+      <div
+        className={cn(
+          'mr-2 flex h-4 w-4 items-center justify-center rounded-sm border border-primary',
+          isSelected
+            ? 'bg-primary text-primary-foreground'
+            : 'opacity-50 [&_svg]:invisible',
+        )}
+      >
+        <CheckIcon className="h-4 w-4" />
+      </div>
+      {option.icon && (
+        <option.icon className="mr-2 h-4 w-4 text-muted-foreground" />
+      )}
+      <span>{option.label}</span>
+    </CommandItem>
+  );
+}
+
 /**
  * Variants for the multi-select component to handle different styles.
  * Uses class-variance-authority (cva) to define different styles based on "variant" prop.
@@ -63,14 +109,7 @@ interface MultiSelectProps
    * An array of option objects to be displayed in the multi-select component.
    * Each option object has a label, value, and an optional icon.
    */
-  options: {
-    /** The text to display for the option. */
-    label: string;
-    /** The unique value associated with the option. */
-    value: string;
-    /** Optional icon component to display alongside the option. */
-    icon?: React.ComponentType<{ className?: string }>;
-  }[];
+  options: (MultiSelectGroupOptionType | MultiSelectOptionType)[];
 
   /**
    * Callback function triggered when the selected values change.
@@ -144,6 +183,11 @@ export const MultiSelect = React.forwardRef<
     const [isPopoverOpen, setIsPopoverOpen] = React.useState(false);
     const [isAnimating, setIsAnimating] = React.useState(false);
 
+    const flatOptions = React.useMemo(() => {
+      return options.flatMap((option) =>
+        'options' in option ? option.options : [option],
+      );
+    }, [options]);
     const handleInputKeyDown = (
       event: React.KeyboardEvent<HTMLInputElement>,
     ) => {
@@ -181,10 +225,10 @@ export const MultiSelect = React.forwardRef<
     };
 
     const toggleAll = () => {
-      if (selectedValues.length === options.length) {
+      if (selectedValues.length === flatOptions.length) {
         handleClear();
       } else {
-        const allValues = options.map((option) => option.value);
+        const allValues = flatOptions.map((option) => option.value);
         setSelectedValues(allValues);
         onValueChange(allValues);
       }
@@ -210,7 +254,7 @@ export const MultiSelect = React.forwardRef<
               <div className="flex justify-between items-center w-full">
                 <div className="flex flex-wrap items-center">
                   {selectedValues?.slice(0, maxCount)?.map((value) => {
-                    const option = options.find((o) => o.value === value);
+                    const option = flatOptions.find((o) => o.value === value);
                     const IconComponent = option?.icon;
                     return (
                       <Badge
@@ -304,7 +348,7 @@ export const MultiSelect = React.forwardRef<
                   <div
                     className={cn(
                       'mr-2 flex h-4 w-4 items-center justify-center rounded-sm border border-primary',
-                      selectedValues.length === options.length
+                      selectedValues.length === flatOptions.length
                         ? 'bg-primary text-primary-foreground'
                         : 'opacity-50 [&_svg]:invisible',
                     )}
@@ -313,32 +357,38 @@ export const MultiSelect = React.forwardRef<
                   </div>
                   <span>(Select All)</span>
                 </CommandItem>
-                {options.map((option) => {
-                  const isSelected = selectedValues.includes(option.value);
-                  return (
-                    <CommandItem
-                      key={option.value}
-                      onSelect={() => toggleOption(option.value)}
-                      className="cursor-pointer"
-                    >
-                      <div
-                        className={cn(
-                          'mr-2 flex h-4 w-4 items-center justify-center rounded-sm border border-primary',
-                          isSelected
-                            ? 'bg-primary text-primary-foreground'
-                            : 'opacity-50 [&_svg]:invisible',
-                        )}
-                      >
-                        <CheckIcon className="h-4 w-4" />
-                      </div>
-                      {option.icon && (
-                        <option.icon className="mr-2 h-4 w-4 text-muted-foreground" />
-                      )}
-                      <span>{option.label}</span>
-                    </CommandItem>
-                  );
-                })}
+                {!options.some((x) => 'options' in x) &&
+                  (options as unknown as MultiSelectOptionType[]).map(
+                    (option) => {
+                      const isSelected = selectedValues.includes(option.value);
+                      return (
+                        <MultiCommandItem
+                          option={option}
+                          key={option.value}
+                          isSelected={isSelected}
+                          toggleOption={toggleOption}
+                        ></MultiCommandItem>
+                      );
+                    },
+                  )}
               </CommandGroup>
+              {options.every((x) => 'options' in x) &&
+                options.map((x, idx) => (
+                  <CommandGroup heading={x.label} key={idx}>
+                    {x.options.map((option) => {
+                      const isSelected = selectedValues.includes(option.value);
+
+                      return (
+                        <MultiCommandItem
+                          option={option}
+                          key={option.value}
+                          isSelected={isSelected}
+                          toggleOption={toggleOption}
+                        ></MultiCommandItem>
+                      );
+                    })}
+                  </CommandGroup>
+                ))}
               <CommandSeparator />
               <CommandGroup>
                 <div className="flex items-center justify-between">

web/src/locales/en.ts

@@ -1322,6 +1322,7 @@ This delimiter is used to split the input text into several text pieces echo of
       logTimeline: {
         begin: 'Ready to begin',
         agent: 'Agent is thinking',
+        userFillUp: 'Waiting for you',
         retrieval: 'Looking up knowledge',
         message: 'Agent says',
         awaitResponse: 'Waiting for you',

web/src/locales/zh.ts

@@ -1265,6 +1265,7 @@ General：实体和关系提取提示来自 GitHub - microsoft/graphrag：基于
       subject: '主题',
       logTimeline: {
         begin: '准备开始',
+        userFillUp: '等你输入',
         agent: '智能体正在思考',
         retrieval: '查找知识',
         message: '回复',

web/src/pages/agent/canvas/node/dropdown/next-step-dropdown.tsx

@@ -11,6 +11,11 @@ import {
   DropdownMenuLabel,
   DropdownMenuTrigger,
 } from '@/components/ui/dropdown-menu';
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipTrigger,
+} from '@/components/ui/tooltip';
 import { IModalProps } from '@/interfaces/common';
 import { Operator } from '@/pages/agent/constant';
 import { AgentInstanceContext, HandleContext } from '@/pages/agent/context';
@@ -33,19 +38,26 @@ function OperatorItemList({ operators }: OperatorItemProps) {
     <ul className="space-y-2">
       {operators.map((x) => {
         return (
-          <DropdownMenuItem
-            key={x}
-            className="hover:bg-background-card py-1 px-3 cursor-pointer rounded-sm flex gap-2 items-center justify-start"
-            onClick={addCanvasNode(x, {
-              nodeId,
-              id,
-              position,
-            })}
-            onSelect={() => hideModal?.()}
-          >
-            <OperatorIcon name={x}></OperatorIcon>
-            {t(`flow.${lowerFirst(x)}`)}
-          </DropdownMenuItem>
+          <Tooltip key={x}>
+            <TooltipTrigger asChild>
+              <DropdownMenuItem
+                key={x}
+                className="hover:bg-background-card py-1 px-3 cursor-pointer rounded-sm flex gap-2 items-center justify-start"
+                onClick={addCanvasNode(x, {
+                  nodeId,
+                  id,
+                  position,
+                })}
+                onSelect={() => hideModal?.()}
+              >
+                <OperatorIcon name={x}></OperatorIcon>
+                {t(`flow.${lowerFirst(x)}`)}
+              </DropdownMenuItem>
+            </TooltipTrigger>
+            <TooltipContent side="right">
+              <p>{t(`flow.${lowerFirst(x)}Description`)}</p>
+            </TooltipContent>
+          </Tooltip>
         );
       })}
     </ul>

web/src/pages/agent/canvas/node/retrieval-node.tsx

@@ -2,11 +2,11 @@ import { RAGFlowAvatar } from '@/components/ragflow-avatar';
 import { useFetchKnowledgeList } from '@/hooks/knowledge-hooks';
 import { IRetrievalNode } from '@/interfaces/database/flow';
 import { NodeProps, Position } from '@xyflow/react';
-import { Flex } from 'antd';
 import classNames from 'classnames';
 import { get } from 'lodash';
 import { memo, useMemo } from 'react';
 import { NodeHandleId } from '../../constant';
+import { useGetVariableLabelByValue } from '../../hooks/use-get-begin-query';
 import { CommonHandle } from './handle';
 import { LeftHandleStyle, RightHandleStyle } from './handle-icon';
 import styles from './index.less';
@@ -21,6 +21,7 @@ function InnerRetrievalNode({
   selected,
 }: NodeProps<IRetrievalNode>) {
   const knowledgeBaseIds: string[] = get(data, 'form.kb_ids', []);
+  console.log('🚀 ~ InnerRetrievalNode ~ knowledgeBaseIds:', knowledgeBaseIds);
   const { list: knowledgeList } = useFetchKnowledgeList(true);
   const knowledgeBases = useMemo(() => {
     return knowledgeBaseIds.map((x) => {
@@ -33,6 +34,8 @@ function InnerRetrievalNode({
     });
   }, [knowledgeList, knowledgeBaseIds]);
 
+  const getLabel = useGetVariableLabelByValue(id);
+
   return (
     <ToolBar selected={selected} id={id} label={data.label}>
       <NodeWrapper selected={selected}>
@@ -63,25 +66,27 @@ function InnerRetrievalNode({
             [styles.nodeHeader]: knowledgeBaseIds.length > 0,
           })}
         ></NodeHeader>
-        <Flex vertical gap={8}>
-          {knowledgeBases.map((knowledge) => {
+        <section className="flex flex-col gap-2">
+          {knowledgeBaseIds.map((id) => {
+            const item = knowledgeList.find((y) => id === y.id);
+            const label = getLabel(id);
+
             return (
-              <div className={styles.nodeText} key={knowledge.id}>
-                <Flex align={'center'} gap={6}>
+              <div className={styles.nodeText} key={id}>
+                <div className="flex items-center gap-1.5">
                   <RAGFlowAvatar
                     className="size-6 rounded-lg"
-                    avatar={knowledge.avatar}
-                    name={knowledge.name || 'CN'}
+                    avatar={id}
+                    name={item?.name || (label as string) || 'CN'}
                     isPerson={true}
                   />
-                  <Flex className={styles.knowledgeNodeName} flex={1}>
-                    {knowledge.name}
-                  </Flex>
-                </Flex>
+
+                  <div className={'truncate flex-1'}>{label || item?.name}</div>
+                </div>
               </div>
             );
           })}
-        </Flex>
+        </section>
       </NodeWrapper>
     </ToolBar>
   );

web/src/pages/agent/chat/box.tsx

@@ -13,14 +13,11 @@ import {
   useUploadCanvasFileWithProgress,
 } from '@/hooks/use-agent-request';
 import { useFetchUserInfo } from '@/hooks/user-setting-hooks';
-import { Message } from '@/interfaces/database/chat';
 import { buildMessageUuidWithRole } from '@/utils/chat';
-import { get } from 'lodash';
-import { memo, useCallback, useMemo } from 'react';
+import { memo, useCallback } from 'react';
 import { useParams } from 'umi';
 import DebugContent from '../debug-content';
-import { BeginQuery } from '../interface';
-import { buildBeginQueryWithObject } from '../utils';
+import { useAwaitCompentData } from '../hooks/use-chat-logic';
 
 function AgentChatBox() {
   const {
@@ -43,33 +40,12 @@ function AgentChatBox() {
   const { data: canvasInfo } = useFetchAgent();
   const { id: canvasId } = useParams();
   const { uploadCanvasFile, loading } = useUploadCanvasFileWithProgress();
-  const getInputs = useCallback((message: Message) => {
-    return get(message, 'data.inputs', {}) as Record<string, BeginQuery>;
-  }, []);
 
-  const buildInputList = useCallback(
-    (message: Message) => {
-      return Object.entries(getInputs(message)).map(([key, val]) => {
-        return {
-          ...val,
-          key,
-        };
-      });
-    },
-    [getInputs],
-  );
-
-  const handleOk = useCallback(
-    (message: Message) => (values: BeginQuery[]) => {
-      const inputs = getInputs(message);
-      const nextInputs = buildBeginQueryWithObject(inputs, values);
-      sendFormMessage({
-        inputs: nextInputs,
-        id: canvasId,
-      });
-    },
-    [canvasId, getInputs, sendFormMessage],
-  );
+  const { buildInputList, handleOk, isWaitting } = useAwaitCompentData({
+    derivedMessages,
+    sendFormMessage,
+    canvasId: canvasId as string,
+  });
 
   const handleUploadFile: NonNullable<FileUploadProps['onUpload']> =
     useCallback(
@@ -79,16 +55,7 @@ function AgentChatBox() {
       },
       [appendUploadResponseList, uploadCanvasFile],
     );
-  const isWaitting = useMemo(() => {
-    const temp = derivedMessages?.some((message, i) => {
-      const flag =
-        message.role === MessageType.Assistant &&
-        derivedMessages.length - 1 === i &&
-        message.data;
-      return flag;
-    });
-    return temp;
-  }, [derivedMessages]);
+
   return (
     <>
       <section className="flex flex-1 flex-col px-5 h-[90vh]">

web/src/pages/agent/chat/use-send-agent-message.ts

@@ -269,7 +269,7 @@ export const useSendAgentMessage = (
 
   const sendFormMessage = useCallback(
     (body: { id?: string; inputs: Record<string, BeginQuery> }) => {
-      send(body);
+      send({ ...body, session_id: sessionId });
       addNewestOneQuestion({
         content: Object.entries(body.inputs)
           .map(([key, val]) => `${key}: ${val.value}`)
@@ -277,7 +277,7 @@ export const useSendAgentMessage = (
         role: MessageType.User,
       });
     },
-    [addNewestOneQuestion, send],
+    [addNewestOneQuestion, send, sessionId],
   );
 
   // reset session

web/src/pages/agent/form/components/prompt-editor/index.tsx

@@ -103,9 +103,12 @@ function PromptContent({
         </div>
       )}
       <ContentEditable
-        className={cn('relative px-2 py-1 focus-visible:outline-none', {
-          'min-h-40': multiLine,
-        })}
+        className={cn(
+          'relative px-2 py-1 focus-visible:outline-none max-h-[50vh] overflow-auto',
+          {
+            'min-h-40': multiLine,
+          },
+        )}
         onBlur={handleBlur}
         onFocus={handleFocus}
       />

web/src/pages/agent/form/retrieval-form/next.tsx

@@ -97,7 +97,7 @@ function RetrievalForm({ node }: INextOperatorForm) {
       <FormWrapper>
         <FormContainer>
           <QueryVariable></QueryVariable>
-          <KnowledgeBaseFormField></KnowledgeBaseFormField>
+          <KnowledgeBaseFormField showVariable></KnowledgeBaseFormField>
         </FormContainer>
         <Collapse title={<div>Advanced Settings</div>}>
           <FormContainer>

web/src/pages/agent/form/tool-form/retrieval-form/index.tsx

@@ -43,7 +43,7 @@ const RetrievalForm = () => {
       >
         <FormContainer>
           <DescriptionField></DescriptionField>
-          <KnowledgeBaseFormField></KnowledgeBaseFormField>
+          <KnowledgeBaseFormField showVariable></KnowledgeBaseFormField>
         </FormContainer>
         <Collapse title={<div>Advanced Settings</div>}>
           <FormContainer>

web/src/pages/agent/hooks/use-chat-logic.ts

@@ -0,0 +1,60 @@
+import { MessageType } from '@/constants/chat';
+import { Message } from '@/interfaces/database/chat';
+import { IMessage } from '@/pages/chat/interface';
+import { get } from 'lodash';
+import { useCallback, useMemo } from 'react';
+import { BeginQuery } from '../interface';
+import { buildBeginQueryWithObject } from '../utils';
+type IAwaitCompentData = {
+  derivedMessages: IMessage[];
+  sendFormMessage: (params: {
+    inputs: Record<string, BeginQuery>;
+    id: string;
+  }) => void;
+  canvasId: string;
+};
+const useAwaitCompentData = (props: IAwaitCompentData) => {
+  const { derivedMessages, sendFormMessage, canvasId } = props;
+
+  const getInputs = useCallback((message: Message) => {
+    return get(message, 'data.inputs', {}) as Record<string, BeginQuery>;
+  }, []);
+
+  const buildInputList = useCallback(
+    (message: Message) => {
+      return Object.entries(getInputs(message)).map(([key, val]) => {
+        return {
+          ...val,
+          key,
+        };
+      });
+    },
+    [getInputs],
+  );
+
+  const handleOk = useCallback(
+    (message: Message) => (values: BeginQuery[]) => {
+      const inputs = getInputs(message);
+      const nextInputs = buildBeginQueryWithObject(inputs, values);
+      sendFormMessage({
+        inputs: nextInputs,
+        id: canvasId,
+      });
+    },
+    [getInputs, sendFormMessage, canvasId],
+  );
+
+  const isWaitting = useMemo(() => {
+    const temp = derivedMessages?.some((message, i) => {
+      const flag =
+        message.role === MessageType.Assistant &&
+        derivedMessages.length - 1 === i &&
+        message.data;
+      return flag;
+    });
+    return temp;
+  }, [derivedMessages]);
+  return { getInputs, buildInputList, handleOk, isWaitting };
+};
+
+export { useAwaitCompentData };

web/src/pages/agent/log-sheet/toolTimelineItem.tsx

@@ -14,24 +14,37 @@ import {
 import { cn } from '@/lib/utils';
 import { isEmpty } from 'lodash';
 import { Operator } from '../constant';
-import OperatorIcon from '../operator-icon';
+import OperatorIcon, { SVGIconMap } from '../operator-icon';
 import {
   JsonViewer,
   toLowerCaseStringAndDeleteChar,
   typeMap,
 } from './workFlowTimeline';
-const capitalizeWords = (str: string, separator: string = '_'): string => {
-  if (!str) return '';
+type IToolIcon =
+  | Operator.ArXiv
+  | Operator.GitHub
+  | Operator.Bing
+  | Operator.DuckDuckGo
+  | Operator.Google
+  | Operator.GoogleScholar
+  | Operator.PubMed
+  | Operator.TavilyExtract
+  | Operator.TavilySearch
+  | Operator.Wikipedia
+  | Operator.YahooFinance
+  | Operator.WenCai
+  | Operator.Crawler;
 
-  return str
-    .split(separator)
-    .map((word) => {
-      return word.charAt(0).toUpperCase() + word.slice(1).toLowerCase();
-    })
-    .join(' ');
+const capitalizeWords = (str: string, separator: string = '_'): string[] => {
+  if (!str) return [''];
+
+  const resultStrArr = str.split(separator).map((word) => {
+    return word.charAt(0).toUpperCase() + word.slice(1).toLowerCase();
+  });
+  return resultStrArr;
 };
 const changeToolName = (toolName: any) => {
-  const name = 'Agent ' + capitalizeWords(toolName);
+  const name = 'Agent ' + capitalizeWords(toolName).join(' ');
   return name;
 };
 const ToolTimelineItem = ({
@@ -61,6 +74,8 @@ const ToolTimelineItem = ({
   return (
     <>
       {filteredTools?.map((tool, idx) => {
+        const toolName = capitalizeWords(tool.tool_name, '_').join('');
+
         return (
           <TimelineItem
             key={'tool_' + idx}
@@ -105,7 +120,11 @@ const ToolTimelineItem = ({
                   <div className="size-6 flex items-center justify-center">
                     <OperatorIcon
                       className="size-4"
-                      name={'Agent' as Operator}
+                      name={
+                        (SVGIconMap[toolName as IToolIcon]
+                          ? toolName
+                          : 'Agent') as Operator
+                      }
                     ></OperatorIcon>
                   </div>
                 </div>
@@ -119,12 +138,14 @@ const ToolTimelineItem = ({
                   className="bg-background-card px-3"
                 >
                   <AccordionItem value={idx.toString()}>
-                    <AccordionTrigger>
+                    <AccordionTrigger
+                      hideDownIcon={isShare && isEmpty(tool.arguments)}
+                    >
                       <div className="flex gap-2 items-center">
                         {!isShare && (
                           <span>
                             {parentName(tool.path) + ' '}
-                            {capitalizeWords(tool.tool_name, '_')}
+                            {capitalizeWords(tool.tool_name, '_').join(' ')}
                           </span>
                         )}
                         {isShare && (
@@ -142,7 +163,7 @@ const ToolTimelineItem = ({
                         </span>
                         <span
                           className={cn(
-                            'border-background  -end-1 -top-1 size-2 rounded-full border-2 bg-dot-green',
+                            'border-background  -end-1 -top-1 size-2 rounded-full bg-dot-green',
                           )}
                         >
                           <span className="sr-only">Online</span>
@@ -161,7 +182,7 @@ const ToolTimelineItem = ({
                     )}
                     {isShare && !isEmpty(tool.arguments) && (
                       <AccordionContent>
-                        <div className="space-y-2">
+                        <div className="space-y-2 bg-muted p-2">
                           {tool &&
                             tool.arguments &&
                             Object.entries(tool.arguments).length &&
@@ -171,8 +192,8 @@ const ToolTimelineItem = ({
                                   <div className="text-sm font-medium leading-none">
                                     {key}
                                   </div>
-                                  <div className="text-sm text-muted-foreground">
-                                    {val || ''}
+                                  <div className="text-sm text-muted-foreground mt-1">
+                                    {val as string}
                                   </div>
                                 </div>
                               );

web/src/pages/agent/log-sheet/workFlowTimeline.tsx

@@ -51,7 +51,7 @@ export function JsonViewer({
         src={data}
         displaySize
         collapseStringsAfterLength={100000000000}
-        className="w-full h-[200px] break-words overflow-auto scrollbar-auto p-2 bg-slate-800"
+        className="w-full h-[200px] break-words overflow-auto scrollbar-auto p-2 bg-muted"
       />
     </section>
   );
@@ -81,11 +81,21 @@ export const typeMap = {
   httpRequest: t('flow.logTimeline.httpRequest'),
   wenCai: t('flow.logTimeline.wenCai'),
   yahooFinance: t('flow.logTimeline.yahooFinance'),
+  userFillUp: t('flow.logTimeline.userFillUp'),
 };
 export const toLowerCaseStringAndDeleteChar = (
   str: string,
   char: string = '_',
 ) => str.toLowerCase().replace(/ /g, '').replaceAll(char, '');
+
+// Convert all keys in typeMap to lowercase and output the new typeMap
+export const typeMapLowerCase = Object.fromEntries(
+  Object.entries(typeMap).map(([key, value]) => [
+    toLowerCaseStringAndDeleteChar(key),
+    value,
+  ]),
+);
+
 function getInputsOrOutputs(
   nodeEventList: INodeData[],
   field: 'inputs' | 'outputs',
@@ -247,16 +257,19 @@ export const WorkFlowTimeline = ({
                     className="bg-background-card px-3"
                   >
                     <AccordionItem value={idx.toString()}>
-                      <AccordionTrigger>
+                      <AccordionTrigger
+                        hideDownIcon={isShare && !x.data?.thoughts}
+                      >
                         <div className="flex gap-2 items-center">
                           <span>
                             {!isShare && getNodeName(x.data?.component_name)}
                             {isShare &&
-                              typeMap[
+                              (typeMapLowerCase[
                                 toLowerCaseStringAndDeleteChar(
                                   nodeLabel,
                                 ) as keyof typeof typeMap
-                              ]}
+                              ] ??
+                                nodeLabel)}
                           </span>
                           <span className="text-text-sub-title text-xs">
                             {x.data.elapsed_time?.toString().slice(0, 6)}
@@ -294,7 +307,7 @@ export const WorkFlowTimeline = ({
                       {isShare && x.data?.thoughts && (
                         <AccordionContent>
                           <div className="space-y-2">
-                            <div className="w-full h-[200px] break-words overflow-auto scrollbar-auto p-2 bg-slate-800">
+                            <div className="w-full h-[200px] break-words overflow-auto scrollbar-auto p-2 bg-muted">
                               <HightLightMarkdown>
                                 {x.data.thoughts || ''}
                               </HightLightMarkdown>

web/src/pages/agent/operator-icon.tsx

@@ -38,7 +38,7 @@ export const OperatorIconMap = {
   [Operator.Email]: 'sendemail-0',
 };
 
-const SVGIconMap = {
+export const SVGIconMap = {
   [Operator.ArXiv]: ArxivIcon,
   [Operator.GitHub]: GithubIcon,
   [Operator.Bing]: BingIcon,

web/src/pages/agents/agent-log-page.tsx

@@ -231,7 +231,7 @@ const AgentLogPage: React.FC = () => {
         <div className="flex justify-between items-center">
           <h1 className="text-2xl font-bold mb-4">Log</h1>
 
-          <div className="flex justify-end space-x-2 mb-4">
+          <div className="flex justify-end space-x-2 mb-4 text-foreground">
             <div className="flex items-center space-x-2">
               <span>ID/Title</span>
               <SearchInput

web/src/pages/next-chats/share/index.tsx

@@ -13,7 +13,9 @@ import {
 } from '@/hooks/use-agent-request';
 import { cn } from '@/lib/utils';
 import i18n from '@/locales/config';
+import DebugContent from '@/pages/agent/debug-content';
 import { useCacheChatLog } from '@/pages/agent/hooks/use-cache-chat-log';
+import { useAwaitCompentData } from '@/pages/agent/hooks/use-chat-logic';
 import { IInputs } from '@/pages/agent/interface';
 import { useSendButtonDisabled } from '@/pages/chat/hooks';
 import { buildMessageUuidWithRole } from '@/utils/chat';
@@ -56,10 +58,15 @@ const ChatContainer = () => {
     appendUploadResponseList,
     parameterDialogVisible,
     showParameterDialog,
+    sendFormMessage,
     ok,
     resetSession,
   } = useSendNextSharedMessage(addEventList);
-
+  const { buildInputList, handleOk, isWaitting } = useAwaitCompentData({
+    derivedMessages,
+    sendFormMessage,
+    canvasId: conversationId as string,
+  });
   const sendDisabled = useSendButtonDisabled(value);
   const appConf = useFetchAppConf();
   const { data: inputsData } = useFetchExternalAgentInputs();
@@ -171,26 +178,47 @@ const ChatContainer = () => {
                     showLoudspeaker={false}
                     showLog={false}
                     sendLoading={sendLoading}
-                  ></MessageItem>
+                  >
+                    {message.role === MessageType.Assistant &&
+                      derivedMessages.length - 1 === i && (
+                        <DebugContent
+                          parameters={buildInputList(message)}
+                          message={message}
+                          ok={handleOk(message)}
+                          isNext={false}
+                          btnText={'Submit'}
+                        ></DebugContent>
+                      )}
+                    {message.role === MessageType.Assistant &&
+                      derivedMessages.length - 1 !== i && (
+                        <div>
+                          <div>{message?.data?.tips}</div>
+
+                          <div>
+                            {buildInputList(message)?.map((item) => item.value)}
+                          </div>
+                        </div>
+                      )}
+                  </MessageItem>
                 );
               })}
             </div>
-            <div ref={ref} />
+            <div ref={ref.scrollRef} />
           </div>
           <div className="flex w-full justify-center mb-8">
             <div className="w-5/6">
               <NextMessageInput
                 isShared
                 value={value}
-                disabled={hasError}
-                sendDisabled={sendDisabled}
+                disabled={hasError || isWaitting}
+                sendDisabled={sendDisabled || isWaitting}
                 conversationId={conversationId}
                 onInputChange={handleInputChange}
                 onPressEnter={handlePressEnter}
                 sendLoading={sendLoading}
                 stopOutputMessage={stopOutputMessage}
                 onUpload={handleUploadFile}
-                isUploading={loading}
+                isUploading={loading || isWaitting}
               ></NextMessageInput>
             </div>
           </div>

web/tailwind.css

@@ -246,7 +246,7 @@
 @layer utilities {
   .scrollbar-auto {
     /* hide scrollbar */
-    scrollbar-width: thin;
+    scrollbar-width: none;
     scrollbar-color: transparent transparent;
   }