add keyword extraction in graph (#1373)

### What problem does this PR solve?
#918

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

api/apps/canvas_app.py

@@ -142,16 +142,19 @@ def run():
 
 
 @manager.route('/reset', methods=['POST'])
-@validate_request("canvas_id")
+@validate_request("id")
 @login_required
 def reset():
     req = request.json
     try:
-        user_canvas = UserCanvasService.get_by_id(req["canvas_id"])
-        canvas = Canvas(user_canvas.dsl, current_user.id)
+        e, user_canvas = UserCanvasService.get_by_id(req["id"])
+        if not e:
+            return server_error_response("canvas not found.")
+
+        canvas = Canvas(json.dumps(user_canvas.dsl), current_user.id)
         canvas.reset()
         req["dsl"] = json.loads(str(canvas))
-        UserCanvasService.update_by_id(req["canvas_id"], dsl=req["dsl"])
+        UserCanvasService.update_by_id(req["id"], {"dsl": req["dsl"]})
         return get_json_result(data=req["dsl"])
     except Exception as e:
         return server_error_response(e)

api/db/init_data.py

@@ -156,7 +156,7 @@ factory_infos = [{
     "tags": "TEXT EMBEDDING, TEXT RE-RANK",
     "status": "1",
 },{
-    "name": "Minimax",
+    "name": "MiniMax",
     "logo": "",
     "tags": "LLM,TEXT EMBEDDING",
     "status": "1",

graph/canvas.py

@@ -102,19 +102,26 @@ class Canvas(ABC):
         self.load()
 
     def load(self):
-        assert self.dsl.get("components", {}).get("begin"), "There have to be a 'Begin' component."
-
         self.components = self.dsl["components"]
+        cpn_nms = set([])
+        for k, cpn in self.components.items():
+            cpn_nms.add(cpn["obj"]["component_name"])
+
+        assert "Begin" in cpn_nms, "There have to be an 'Begin' component."
+        assert "Answer" in cpn_nms, "There have to be an 'Answer' component."
+
         for k, cpn in self.components.items():
+            cpn_nms.add(cpn["obj"]["component_name"])
             param = component_class(cpn["obj"]["component_name"] + "Param")()
             param.update(cpn["obj"]["params"])
             param.check()
             cpn["obj"] = component_class(cpn["obj"]["component_name"])(self, k, param)
             if cpn["obj"].component_name == "Categorize":
-                for _,desc in param.category_description.items():
+                for _, desc in param.category_description.items():
                     if desc["to"] not in cpn["downstream"]:
                         cpn["downstream"].append(desc["to"])
 
+
         self.path = self.dsl["path"]
         self.history = self.dsl["history"]
         self.messages = self.dsl["messages"]
@@ -140,7 +147,8 @@ class Canvas(ABC):
         self.messages = []
         self.answer = []
         self.reference = []
-        self.components = {}
+        for k, cpn in self.components.items():
+            self.components[k]["obj"].reset()
         self._embed_id = ""
 
     def run(self, **kwargs):
@@ -176,7 +184,7 @@ class Canvas(ABC):
                 ran += 1
 
         prepare2run(self.components[self.path[-2][-1]]["downstream"])
-        while ran < len(self.path[-1]):
+        while 0 <= ran < len(self.path[-1]):
             if DEBUG: print(ran, self.path)
             cpn_id = self.path[-1][ran]
             cpn = self.get_component(cpn_id)

graph/component/base.py

@@ -418,6 +418,9 @@ class ComponentBase(ABC):
             o = pd.DataFrame(o)
         return self._param.output_var_name, o
 
+    def reset(self):
+        setattr(self._param, self._param.output_var_name, None)
+
     def set_output(self, v: pd.DataFrame):
         setattr(self._param, self._param.output_var_name, v)
 

graph/component/keyword.py

@@ -0,0 +1,68 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import re
+from abc import ABC
+from api.db import LLMType
+from api.db.services.llm_service import LLMBundle
+from graph.component import GenerateParam, Generate
+from graph.settings import DEBUG
+
+
+class KeywordExtractParam(GenerateParam):
+
+    """
+    Define the KeywordExtract component parameters.
+    """
+    def __init__(self):
+        super().__init__()
+        self.temperature = 0.5
+        self.prompt = ""
+        self.topn = 1
+
+    def check(self):
+        super().check()
+
+    def get_prompt(self):
+        self.prompt = """
+- Role: You're a question analyzer. 
+- Requirements: 
+  - Summarize user's question, and give top %s important keyword/phrase.
+  - Use comma as a delimiter to separate keywords/phrases.
+- Answer format: (in language of user's question)
+  - keyword: 
+"""%self.topn
+        return self.prompt
+
+
+class KeywordExtract(Generate, ABC):
+    component_name = "RewriteQuestion"
+
+    def _run(self, history, **kwargs):
+        q = ""
+        for r, c in self._canvas.history[::-1]:
+            if r == "user":
+                q += c
+                break
+
+        chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
+        ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": q}],
+                            self._param.gen_conf())
+
+        ans = re.sub(r".*keyword:", "", ans).strip()
+        if DEBUG: print(ans, ":::::::::::::::::::::::::::::::::")
+        return KeywordExtract.be_output(ans)
+
+

graph/templates/HR_callout_zh.json

@@ -1,5 +1,5 @@
 {
-    "id": 0,
+    "id": 1,
     "title": "HR call-out assistant(Chinese)",
     "description": "A HR call-out assistant. It will introduce the given job, answer the candidates' question about this job. And the most important thing is that it will try to obtain the contact information of the candidates. What you need to do is to link a knowledgebase which contains job description in 'Retrieval' component.",
     "canvas_type": "chatbot",

graph/templates/customer_service.json

@@ -1,5 +1,5 @@
 {
-  "id": 1,
+  "id": 2,
   "title": "Customer service",
   "description": "A call-in customer service chat bot. It will provide useful information about the products, answer customers' questions and soothe the customers' bad emotions.",
   "canvas_type": "chatbot",
@@ -106,7 +106,7 @@
           "upstream": ["categorize:0"]
         },
         "generate:complain": {
-          "downstream": [],
+          "downstream": ["answer:0"],
           "obj": {
             "component_name": "Generate",
             "params": {
@@ -116,7 +116,7 @@
               "prompt": "You are a customer support. the Customers complain even curse about the products but not specific enough. You need to ask him/her what's the specific problem with the product. Be nice, patient and concern to soothe your customers’ emotions at first place."
             }
           },
-          "upstream": ["categorize:0", "answer:0"]
+          "upstream": ["categorize:0"]
         },
         "message:get_contact": {
           "downstream": ["answer:0"],
@@ -286,13 +286,13 @@
           {
             "id": "reactflow__edge-answer:0a-generate:complaind",
             "markerEnd": "logo",
-            "source": "answer:0",
+            "source": "generate:complain",
             "sourceHandle": "a",
             "style": {
               "stroke": "rgb(202 197 245)",
               "strokeWidth": 2
             },
-            "target": "generate:complain",
+            "target": "answer:0",
             "targetHandle": "d",
             "type": "buttonEdge"
           },

graph/templates/general_chat_bot.json

@@ -0,0 +1,335 @@
+{
+  "id": 0,
+  "title": "Chat bot",
+  "description": "A general chat bot. It is based on Self-RAG mechanism. What you need to do is setting up knowleage base in 'Retrieval'",
+  "canvas_type": "chatbot",
+  "dsl": {
+      "answer": [],
+      "components": {
+        "answer:0": {
+          "downstream": ["retrieval:0"],
+          "obj": {
+            "component_name": "Answer",
+            "params": {}
+          },
+          "upstream": ["begin", "generate:0"]
+        },
+        "begin": {
+          "downstream": ["answer:0"],
+          "obj": {
+            "component_name": "Begin",
+            "params": {
+              "prologue": "Hi there!"
+            }
+          },
+          "upstream": []
+        },
+        "generate:0": {
+          "downstream": ["answer:0"],
+          "obj": {
+            "component_name": "Generate",
+            "params": {
+              "llm_id": "deepseek-chat",
+              "prompt": "You are an intelligent assistant. Please answer the question based on content of knowledge base. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\". Answers need to consider chat history.\n      Knowledge base content is as following:\n      {input}\n      The above is the content of knowledge base."
+            }
+          },
+          "upstream": ["relevant:0"]
+        },
+        "relevant:0": {
+          "downstream": ["rewrite:0", "generate:0"],
+          "obj": {
+            "component_name": "Relevant",
+            "params": {
+              "llm_id": "deepseek-chat",
+              "no": "rewrite:0",
+              "temperature": 0.02,
+              "yes": "generate:0"
+            }
+          },
+          "upstream": ["retrieval:0"]
+        },
+        "retrieval:0": {
+          "downstream": ["relevant:0"],
+          "obj": {
+            "component_name": "Retrieval",
+            "params": {
+              "empty_response": "Sorry, knowledge base has noting related information.",
+              "kb_ids": ["869a236818b811ef91dffa163e197198"],
+              "keywords_similarity_weight": 0.3,
+              "rerank_id": "BAAI/bge-reranker-v2-m3",
+              "similarity_threshold": 0.2,
+              "top_k": 1024,
+              "top_n": 6
+            }
+          },
+          "upstream": ["answer:0", "rewrite:0"]
+        },
+        "rewrite:0": {
+          "downstream": ["retrieval:0"],
+          "obj": {
+            "component_name": "RewriteQuestion",
+            "params": {
+              "llm_id": "deepseek-chat",
+              "temperature": 0.8
+            }
+          },
+          "upstream": ["relevant:0"]
+        }
+      },
+      "graph": {
+        "edges": [
+          {
+            "id": "81de838d-a541-4b3f-9d68-9172ffd7c6b4",
+            "label": "",
+            "source": "begin",
+            "target": "answer:0"
+          },
+          {
+            "id": "reactflow__edge-answer:0b-retrieval:0c",
+            "markerEnd": "logo",
+            "source": "answer:0",
+            "sourceHandle": "b",
+            "style": {
+              "stroke": "rgb(202 197 245)",
+              "strokeWidth": 2
+            },
+            "target": "retrieval:0",
+            "targetHandle": "c",
+            "type": "buttonEdge"
+          },
+          {
+            "id": "reactflow__edge-generate:0d-answer:0a",
+            "markerEnd": "logo",
+            "source": "generate:0",
+            "sourceHandle": "d",
+            "style": {
+              "stroke": "rgb(202 197 245)",
+              "strokeWidth": 2
+            },
+            "target": "answer:0",
+            "targetHandle": "a",
+            "type": "buttonEdge"
+          },
+          {
+            "id": "reactflow__edge-retrieval:0a-relevant:0b",
+            "markerEnd": "logo",
+            "source": "retrieval:0",
+            "sourceHandle": "a",
+            "style": {
+              "stroke": "rgb(202 197 245)",
+              "strokeWidth": 2
+            },
+            "target": "relevant:0",
+            "targetHandle": "b",
+            "type": "buttonEdge"
+          },
+          {
+            "id": "reactflow__edge-rewrite:0d-retrieval:0b",
+            "markerEnd": "logo",
+            "source": "rewrite:0",
+            "sourceHandle": "d",
+            "style": {
+              "stroke": "rgb(202 197 245)",
+              "strokeWidth": 2
+            },
+            "target": "retrieval:0",
+            "targetHandle": "b",
+            "type": "buttonEdge"
+          },
+          {
+            "id": "reactflow__edge-relevant:0no-rewrite:0a",
+            "markerEnd": "logo",
+            "source": "relevant:0",
+            "sourceHandle": "no",
+            "style": {
+              "stroke": "rgb(202 197 245)",
+              "strokeWidth": 2
+            },
+            "target": "rewrite:0",
+            "targetHandle": "a",
+            "type": "buttonEdge"
+          },
+          {
+            "id": "reactflow__edge-relevant:0yes-generate:0b",
+            "markerEnd": "logo",
+            "source": "relevant:0",
+            "sourceHandle": "yes",
+            "style": {
+              "stroke": "rgb(202 197 245)",
+              "strokeWidth": 2
+            },
+            "target": "generate:0",
+            "targetHandle": "b",
+            "type": "buttonEdge"
+          }
+        ],
+        "nodes": [
+          {
+            "data": {
+              "form": {
+                "prologue": "Hi there!"
+              },
+              "label": "Begin",
+              "name": "Opening"
+            },
+            "dragging": false,
+            "height": 50,
+            "id": "begin",
+            "position": {
+              "x": -304.50000000000006,
+              "y": -2.9994670375766646
+            },
+            "positionAbsolute": {
+              "x": -304.50000000000006,
+              "y": -2.9994670375766646
+            },
+            "selected": false,
+            "sourcePosition": "left",
+            "targetPosition": "right",
+            "type": "beginNode",
+            "width": 50
+          },
+          {
+            "data": {
+              "form": {},
+              "label": "Answer",
+              "name": "Interface"
+            },
+            "dragging": false,
+            "height": 100,
+            "id": "answer:0",
+            "position": {
+              "x": -89.78929141627594,
+              "y": -29.530900170597448
+            },
+            "positionAbsolute": {
+              "x": -89.78929141627594,
+              "y": -29.530900170597448
+            },
+            "selected": false,
+            "sourcePosition": "left",
+            "targetPosition": "right",
+            "type": "ragNode",
+            "width": 100
+          },
+          {
+            "data": {
+              "form": {
+                "empty_response": "Sorry, knowledge base has noting related information.",
+                "kb_ids": ["869a236818b811ef91dffa163e197198"],
+                "keywords_similarity_weight": 0.3,
+                "rerank_id": "BAAI/bge-reranker-v2-m3",
+                "similarity_threshold": 0.2,
+                "top_k": 1024,
+                "top_n": 6
+              },
+              "label": "Retrieval",
+              "name": "Search KB"
+            },
+            "dragging": false,
+            "height": 100,
+            "id": "retrieval:0",
+            "position": {
+              "x": 225.1100159655728,
+              "y": -28.569259485130402
+            },
+            "positionAbsolute": {
+              "x": 225.1100159655728,
+              "y": -28.569259485130402
+            },
+            "selected": true,
+            "sourcePosition": "left",
+            "targetPosition": "right",
+            "type": "ragNode",
+            "width": 100
+          },
+          {
+            "data": {
+              "form": {
+                "llm_id": "deepseek-chat",
+                "no": "rewrite:0",
+                "temperature": 0.02,
+                "yes": "generate:0"
+              },
+              "label": "Relevant",
+              "name": "Relevant?"
+            },
+            "dragging": false,
+            "height": 70,
+            "id": "relevant:0",
+            "position": {
+              "x": 225.36494412049518,
+              "y": 307.7194989687223
+            },
+            "positionAbsolute": {
+              "x": 225.36494412049518,
+              "y": 307.7194989687223
+            },
+            "selected": false,
+            "sourcePosition": "left",
+            "targetPosition": "right",
+            "type": "relevantNode",
+            "width": 70
+          },
+          {
+            "data": {
+              "form": {
+                "llm_id": "deepseek-chat",
+                "prompt": "You are an intelligent assistant. Please answer the question based on content of knowledge base. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\". Answers need to consider chat history.\n      Knowledge base content is as following:\n      {input}\n      The above is the content of knowledge base.",
+                "temperature": 0.02
+              },
+              "label": "Generate",
+              "name": "LLM"
+            },
+            "dragging": false,
+            "height": 150,
+            "id": "generate:0",
+            "position": {
+              "x": -90.09669656497177,
+              "y": 192.12280240375043
+            },
+            "positionAbsolute": {
+              "x": -90.09669656497177,
+              "y": 192.12280240375043
+            },
+            "selected": false,
+            "sourcePosition": "left",
+            "targetPosition": "right",
+            "type": "ragNode",
+            "width": 150
+          },
+          {
+            "data": {
+              "form": {
+                "llm_id": "deepseek-chat",
+                "temperature": 0.8
+              },
+              "label": "RewriteQuestion",
+              "name": "Refine Ques"
+            },
+            "dragging": false,
+            "height": 70,
+            "id": "rewrite:0",
+            "position": {
+              "x": 416.0628662660416,
+              "y": 144.09722952739514
+            },
+            "positionAbsolute": {
+              "x": 416.0628662660416,
+              "y": 144.09722952739514
+            },
+            "selected": false,
+            "sourcePosition": "left",
+            "targetPosition": "right",
+            "type": "ragNode",
+            "width": 70
+          }
+        ]
+      },
+      "history": [],
+      "messages": [],
+      "path": [],
+      "reference": []
+    },
+  "avatar": 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"
+}

graph/templates/interpreter.json

@@ -1,5 +1,5 @@
 {
-  "id": 2,
+  "id": 3,
   "title": "Interpreter",
   "description": "An interpreter. Type the content you want to translate and the object language like: Hi there => Spanish. Hava a try!",
   "canvas_type": "chatbot",

graph/test/dsl_examples/retrieval_relevant_rewrite_and_generate.json

@@ -1,79 +1,79 @@
 {
   "components": {
-    "begin": {
-      "obj": {
-        "component_name": "Begin",
-        "params": {
-          "prologue": "Hi there!"
-        }
-      },
-      "downstream": ["answer:0"],
-      "upstream": []
-    },
-    "answer:0": {
-      "obj": {
-        "component_name": "Answer",
-        "params": {}
-      },
-      "downstream": ["retrieval:0"],
-      "upstream": ["begin", "generate:0"]
-    },
-    "retrieval:0": {
-      "obj": {
-        "component_name": "Retrieval",
-        "params": {
-          "similarity_threshold": 0.2,
-          "keywords_similarity_weight": 0.3,
-          "top_n": 6,
-          "top_k": 1024,
-          "rerank_id": "BAAI/bge-reranker-v2-m3",
-          "kb_ids": ["869a236818b811ef91dffa163e197198"],
-          "empty_response": "Sorry, knowledge base has noting related information."
-        }
-      },
-      "downstream": ["relevant:0"],
-      "upstream": ["answer:0", "rewrite:0"]
-    },
-    "relevant:0": {
-      "obj": {
-        "component_name": "Relevant",
-        "params": {
-          "llm_id": "deepseek-chat",
-          "temperature": 0.02,
-          "yes": "generate:0",
-          "no": "rewrite:0"
-        }
-      },
-      "downstream": ["generate:0", "rewrite:0"],
-      "upstream": ["retrieval:0"]
-    },
-    "generate:0": {
-      "obj": {
-        "component_name": "Generate",
-        "params": {
-          "llm_id": "deepseek-chat",
-          "prompt": "You are an intelligent assistant. Please answer the question based on content of knowledge base. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\". Answers need to consider chat history.\n      Knowledge base content is as following:\n      {input}\n      The above is the content of knowledge base.",
-          "temperature": 0.02
-        }
-      },
-      "downstream": ["answer:0"],
-      "upstream": ["relevant:0"]
-    },
-    "rewrite:0": {
-      "obj": {
-        "component_name": "RewriteQuestion",
-        "params": {
-          "llm_id": "deepseek-chat",
-          "temperature": 0.8
-        }
-      },
-      "downstream": ["retrieval:0"],
-      "upstream": ["relevant:0"]
-    }
+            "begin": {
+                "obj":{
+                    "component_name": "Begin",
+                    "params": {
+                      "prologue": "Hi there!"
+                    }
+                },
+                "downstream": ["answer:0"],
+                "upstream": []
+            },
+            "answer:0": {
+                "obj": {
+                    "component_name": "Answer",
+                    "params": {}
+                },
+                "downstream": ["retrieval:0"],
+                "upstream": ["begin", "generate:0", "switch:0"]
+            },
+            "retrieval:0": {
+                "obj": {
+                    "component_name": "Retrieval",
+                    "params": {
+                      "similarity_threshold": 0.2,
+                      "keywords_similarity_weight": 0.3,
+                      "top_n": 6,
+                      "top_k": 1024,
+                      "rerank_id": "BAAI/bge-reranker-v2-m3",
+                      "kb_ids": ["869a236818b811ef91dffa163e197198"],
+                      "empty_response": "Sorry, knowledge base has noting related information."
+                    }
+                },
+                "downstream": ["relevant:0"],
+                "upstream": ["answer:0", "rewrite:0"]
+            },
+            "relevant:0": {
+                "obj": {
+                    "component_name": "Relevant",
+                    "params": {
+                      "llm_id": "deepseek-chat",
+                      "temperature": 0.02,
+                      "yes": "generate:0",
+                      "no": "rewrite:0"
+                    }
+                },
+                "downstream": ["generate:0", "rewrite:0"],
+                "upstream": ["retrieval:0"]
+            },
+            "generate:0": {
+                "obj": {
+                    "component_name": "Generate",
+                    "params": {
+                      "llm_id": "deepseek-chat",
+                      "prompt": "You are an intelligent assistant. Please answer the question based on content of knowledge base. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\". Answers need to consider chat history.\n      Knowledge base content is as following:\n      {input}\n      The above is the content of knowledge base.",
+                      "temperature": 0.02
+                    }
+                },
+                "downstream": ["answer:0"],
+                "upstream": ["relevant:0"]
+            },
+            "rewrite:0": {
+                "obj":{
+                    "component_name": "RewriteQuestion",
+                    "params": {
+                      "llm_id": "deepseek-chat",
+                      "temperature": 0.8
+                    }
+                },
+                "downstream": ["retrieval:0"],
+                "upstream": ["relevant:0"]
+            }
   },
   "history": [],
   "messages": [],
   "path": [],
   "reference": [],
   "answer": []
-}
+}

rag/llm/chat_model.py

@@ -95,6 +95,7 @@ class DeepSeekChat(Base):
         if not base_url: base_url="https://api.deepseek.com/v1"
         super().__init__(key, model_name, base_url)
 
+
 class AzureChat(Base):
     def __init__(self, key, model_name, **kwargs):
         self.client = AzureOpenAI(api_key=key, azure_endpoint=kwargs["base_url"], api_version="2024-02-01")