Updated prompt-template

trustgraph/model/prompt/generic/prompts.py

@@ -3,64 +3,90 @@ def to_relationships(text):
 
     prompt = f"""You are a helpful assistant that performs information extraction tasks for a provided text.
 
-Read the provided text. You will model the text as an information network for a RDF knowledge graph.
+Read the provided text. You will model the text as an information network for a RDF knowledge graph in JSON.
 
-Information network rules:
+Information Network Rules:
 - An information network has subjects connected by predicates to objects.
-- A subject can have many predicates and objects.
+- A subject is a named-entity or a conceptual topic.
+- One subject can have many predicates and objects.
+- An object is a property or attribute of a subject.
 - A subject can be connected by a predicate to another subject.
-- Objects shall be either nouns or adjectives.
 
-Here is the provided text: 
+Reading Instructions:
+- Ignore document formatting in the provided text.
+- Study the provided text carefully.
+
+Here is the text: 
 {text}
 
-Instructions:
+Response Instructions:
-- Obey the information network rules.
+- Obey the information network rules. 
-- Ignore document formatting. 
+- Do not return special characters.
-- Do not provide explanations or any additional text. 
+- Respond only with well-formed JSON.
-- Do not use special characters.
+- The JSON response shall be an array of JSON objects with keys "subject", "predicate", "object", and "object-entity".
-- The key "object-entity" is true if it is a Named-Entity.
+- The JSON response shall use the following structure:
-- Respond only with a well-formed JSON using the following example:
 
-JSON example: [{{"subject": string, "predicate": string, "object": string, "object-entity": boolean}}]
+```json
+[{{"subject": string, "predicate": string, "object": string, "object-entity": boolean}}]
+```
+
+- The key "object-entity" is TRUE only if the "object" is a subject.
+- Do not write any additional text or explanations.
 """
     
     return prompt
 
 def to_topics(text):
 
-    prompt = f"""You are a helpful assistant that performs information extraction tasks for a provided text.\nRead the provided text. You will identify topics and their definitions.
+    prompt = f"""You are a helpful assistant that performs information extraction tasks for a provided text.\nRead the provided text. You will identify topics and their definitions in JSON.
 
-Here is the provided text: 
+Reading Instructions:
+- Ignore document formatting in the provided text.
+- Study the provided text carefully.
+
+Here is the text:
 {text}
 
-Instructions:
+Response Instructions: 
-- Ignore document formatting. 
+- Do not respond with special characters.
-- Do not provide explanations or any additional text. 
+- Return only topics that are concepts and unique to the provided text.
-- Do not use special characters.
+- Respond only with well-formed JSON.
-- Identify only topics that are unique to the provided text.
+- The JSON response shall be an array of objects with keys "topic" and "definition". 
-- Respond only with a well-formed JSON using the following example:
+- The JSON response shall use the following structure:
 
-JSON example: [{{"topic": string, "definition": string}}]
+```json
+[{{"topic": string, "definition": string}}]
+```
+
+- Do not write any additional text or explanations.
 """
     
     return prompt
     
 def to_definitions(text):
 
-    prompt = f"""You are a helpful assistant that performs information extraction tasks for a provided text.\nRead the provided text. You will identify named-entities and their definitions.
+    prompt = f"""You are a helpful assistant that performs information extraction tasks for a provided text.\nRead the provided text. You will identify entities and their definitions in JSON.
 
-Here is the provided text: 
+Reading Instructions:
+- Ignore document formatting in the provided text.
+- Study the provided text carefully.
+
+Here is the text:
 {text}
 
-Instructions:
+Response Instructions:
-- Ignore document formatting. 
+- Do not respond with special characters.
-- Do not provide explanations or any additional text. 
+- Return only entities that are named-entities such as: people, organizations, physical objects, locations, animals, products, commodotities, or substances.
-- Do not use special characters.
+- Respond only with well-formed JSON. 
-- Identity only entities that are named-entities.
+- The JSON response shall be an array of objects with keys "entity" and "definition".
-- Respond only with a well-formed JSON using the following example:
+- The JSON response shall use the following structure: 
 
-JSON example: [{{"entity": string, "definition": string}}]"""
+```json
+[{{"entity": string, "definition": string}}]
+```
+
+- Do not write any additional text or explanations.
+"""
     
     return prompt
 

trustgraph/model/prompt/generic/service.py

@@ -3,6 +3,7 @@ Language service abstracts prompt engineering from LLM.
 """
 
 import json
+import re
 
 from .... schema import Definition, Relationship, Triple
 from .... schema import PromptRequest, PromptResponse, Error
@@ -56,12 +57,15 @@ class Processor(ConsumerProducer):
         )
 
     def parse_json(self, text):
-        
+        json_match = re.search(r'```(?:json)?(.*?)```', text, re.DOTALL)
-        # Hacky, workaround temperamental JSON markdown
+    
-        text = text.replace("```json", "")
+        if json_match:
-        text = text.replace("```", "")
+            json_str = json_match.group(1).strip()
+        else:
+            # If no delimiters, assume the entire output is JSON
+            json_str = text.strip()
 
-        return json.loads(text)
+        return json.loads(json_str)
 
     def handle(self, msg):
 

trustgraph/model/prompt/template/prompts.py

@@ -5,6 +5,9 @@ def to_relationships(template, text):
 def to_definitions(template, text):
     return template.format(text=text)
 
+def to_topics(template, text):
+    return template.format(text=text)
+
 def to_rows(template, schema, text):
 
     field_schema = [

trustgraph/model/prompt/template/service.py

@@ -4,6 +4,7 @@ Language service abstracts prompt engineering from LLM.
 """
 
 import json
+import re
 
 from .... schema import Definition, Relationship, Triple
 from .... schema import PromptRequest, PromptResponse, Error
@@ -15,7 +16,7 @@ from .... base import ConsumerProducer
 from .... clients.llm_client import LlmClient
 
 from . prompts import to_definitions, to_relationships, to_rows
-from . prompts import to_kg_query, to_document_query
+from . prompts import to_kg_query, to_document_query, to_topics
 
 module = ".".join(__name__.split(".")[1:-1])
 
@@ -38,6 +39,7 @@ class Processor(ConsumerProducer):
         )
         definition_template = params.get("definition_template")
         relationship_template = params.get("relationship_template")
+        topic_template = params.get("topic_template")
         rows_template = params.get("rows_template")
         knowledge_query_template = params.get("knowledge_query_template")
         document_query_template = params.get("document_query_template")
@@ -62,18 +64,22 @@ class Processor(ConsumerProducer):
         )
 
         self.definition_template = definition_template
+        self.topic_template = topic_template
         self.relationship_template = relationship_template
         self.rows_template = rows_template
         self.knowledge_query_template = knowledge_query_template
         self.document_query_template = document_query_template
 
     def parse_json(self, text):
-        
+        json_match = re.search(r'```(?:json)?(.*?)```', text, re.DOTALL)
-        # Hacky, workaround temperamental JSON markdown
+    
-        text = text.replace("```json", "")
+        if json_match:
-        text = text.replace("```", "")
+            json_str = json_match.group(1).strip()
+        else:
+            # If no delimiters, assume the entire output is JSON
+            json_str = text.strip()
 
-        return json.loads(text)
+        return json.loads(json_str)
 
     def handle(self, msg):
 
@@ -92,6 +98,11 @@ class Processor(ConsumerProducer):
             self.handle_extract_definitions(id, v)
             return
 
+        elif kind == "extract-topics":
+
+            self.handle_extract_topics(id, v)
+            return
+
         elif kind == "extract-relationships":
 
             self.handle_extract_relationships(id, v)
@@ -176,6 +187,66 @@ class Processor(ConsumerProducer):
 
             self.producer.send(r, properties={"id": id})
 
+    def handle_extract_topics(self, id, v):
+
+        try:
+
+            prompt = to_topics(self.topic_template, v.chunk)
+
+            ans = self.llm.request(prompt)
+
+            # Silently ignore JSON parse error
+            try:
+                defs = self.parse_json(ans)
+            except:
+                print("JSON parse error, ignored", flush=True)
+                defs = []
+
+            output = []
+
+            for defn in defs:
+
+                try:
+                    e = defn["topic"]
+                    d = defn["definition"]
+
+                    if e == "": continue
+                    if e is None: continue
+                    if d == "": continue
+                    if d is None: continue
+
+                    output.append(
+                        Definition(
+                            name=e, definition=d
+                        )
+                    )
+
+                except:
+                    print("definition fields missing, ignored", flush=True)
+
+            print("Send response...", flush=True)
+            r = PromptResponse(topics=output, error=None)
+            self.producer.send(r, properties={"id": id})
+
+            print("Done.", flush=True)
+        
+        except Exception as e:
+
+            print(f"Exception: {e}")
+
+            print("Send error response...", flush=True)
+
+            r = PromptResponse(
+                error=Error(
+                    type = "llm-error",
+                    message = str(e),
+                ),
+                response=None,
+            )
+
+            self.producer.send(r, properties={"id": id})
+
+
     def handle_extract_relationships(self, id, v):
 
         try:
@@ -415,6 +486,12 @@ class Processor(ConsumerProducer):
             help=f'Definition extraction template',
         )
 
+        parser.add_argument(
+            '--topic-template',
+            required=True,
+            help=f'Topic extraction template',
+        )
+
         parser.add_argument(
             '--rows-template',
             required=True,