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Added doc embedding support (#41)

Browse source 
* document embedding writer & query
* Added test query for doc embeddings
* Bump version
* Added doc rag prompt
* Document RAG service
This commit is contained in:
cybermaggedon 2024-08-26 23:45:23 +01:00 • committed by GitHub
parent 0159e938a2
commit 669aed0f8a
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52 changed files with 1257 additions and 252 deletions
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2
Makefile
View file

@ -1,6 +1,6 @@
# VERSION=$(shell git describe | sed 's/^v//')
VERSION=0.7.16
VERSION=0.7.17
DOCKER=podman

6
scripts/de-query-milvus Executable file
View file

@ -0,0 +1,6 @@
#!/usr/bin/env python3
from trustgraph.query.doc_embeddings.milvus import run
run()

6
scripts/de-write-milvus Executable file
View file

@ -0,0 +1,6 @@
#!/usr/bin/env python3
from trustgraph.storage.doc_embeddings.milvus import run
run()

6
scripts/document-rag Executable file
View file

@ -0,0 +1,6 @@
#!/usr/bin/env python3
from trustgraph.retrieval.document_rag import run
run()

5
setup.py
View file

@ -4,7 +4,7 @@ import os
with open("README.md", "r") as fh:
long_description = fh.read()
version = "0.7.16"
version = "0.7.17"
setuptools.setup(
name="trustgraph",
@ -55,6 +55,9 @@ setuptools.setup(
"scripts/chunker-recursive",
"scripts/chunker-token",
"scripts/concat-parquet",
"scripts/de-query-milvus",
"scripts/de-write-milvus",
"scripts/document-rag",
"scripts/dump-parquet",
"scripts/embeddings-hf",
"scripts/embeddings-ollama",

53
templates/components/milvus.jsonnet
View file

@ -53,8 +53,59 @@ milvus + {
},
},
/*
// Document embeddings writer & query service. Not currently enabled.
"store-doc-embeddings": base + {
image: images.trustgraph,
command: [
"de-write-milvus",
"-p",
url.pulsar,
"-t",
url.milvus,
],
deploy: {
resources: {
limits: {
cpus: '0.5',
memory: '128M'
},
reservations: {
cpus: '0.1',
memory: '128M'
}
}
},
},
"query-doc-embeddings": base + {
image: images.trustgraph,
command: [
"de-query-milvus",
"-p",
url.pulsar,
"-t",
url.milvus,
],
deploy: {
resources: {
limits: {
cpus: '0.5',
memory: '128M'
},
reservations: {
cpus: '0.1',
memory: '128M'
}
}
},
},
*/
}
}

2
templates/prompts/gemini.jsonnet
View file

@ -60,6 +60,8 @@ local url = import "../components/url.jsonnet";
"<instructions>\nStudy the following text and derive entity relationships. For each\nrelationship, derive the subject, predicate and object of the relationship.\nOutput relationships in JSON format as an arary of objects with fields:\n- subject: the subject of the relationship\n- predicate: the predicate\n- object: the object of the relationship\n- object-entity: false if the object is a simple data type: name, value or date. true if it is an entity.\n</instructions>\n\n<text>\n{text}\n</text>\n\n<requirements>\nYou will respond only with raw JSON format data. Do not provide\nexplanations. Do not use special characters in the abstract text. The\nabstract must be written as plain text. Do not add markdown formatting\nor headers or prefixes.\n</requirements>",
"--knowledge-query-template",
"Study the following set of knowledge statements. The statements are written in Cypher format that has been extracted from a knowledge graph. Use only the provided set of knowledge statements in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere's the knowledge statements:\n{graph}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
"--document-query-template",
"Study the following context. Use only the information provided in the context in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere is the context:\n{documents}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
],
deploy: {
resources: {

2
templates/prompts/mixtral.jsonnet
View file

@ -60,6 +60,8 @@ local url = import "../components/url.jsonnet";
"<instructions>\nStudy the following text and derive entity relationships. For each\nrelationship, derive the subject, predicate and object of the relationship.\nOutput relationships in JSON format as an arary of objects with fields:\n- subject: the subject of the relationship\n- predicate: the predicate\n- object: the object of the relationship\n- object-entity: false if the object is a simple data type: name, value or date. true if it is an entity.\n</instructions>\n\n<text>\n{text}\n</text>\n\n<requirements>\nYou will respond only with raw JSON format data. Do not provide\nexplanations. Do not use special characters in the abstract text. The\nabstract must be written as plain text. Do not add markdown formatting\nor headers or prefixes.\n</requirements>",
"--knowledge-query-template",
"Study the following set of knowledge statements. The statements are written in Cypher format that has been extracted from a knowledge graph. Use only the provided set of knowledge statements in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere's the knowledge statements:\n{graph}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
"--document-query-template",
"Study the following context. Use only the information provided in the context in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere is the context:\n{documents}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
],
deploy: {
resources: {

2
templates/prompts/openai.jsonnet
View file

@ -60,6 +60,8 @@ local url = import "../components/url.jsonnet";
"<instructions>\nStudy the following text and derive entity relationships. For each\nrelationship, derive the subject, predicate and object of the relationship.\nOutput relationships in JSON format as an arary of objects with fields:\n- subject: the subject of the relationship\n- predicate: the predicate\n- object: the object of the relationship\n- object-entity: false if the object is a simple data type: name, value or date. true if it is an entity.\n</instructions>\n\n<text>\n{text}\n</text>\n\n<requirements>\nYou will respond only with raw JSON format data. Do not provide\nexplanations. Do not use special characters in the abstract text. The\nabstract must be written as plain text. Do not add markdown formatting\nor headers or prefixes.\n</requirements>",
"--knowledge-query-template",
"Study the following set of knowledge statements. The statements are written in Cypher format that has been extracted from a knowledge graph. Use only the provided set of knowledge statements in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere's the knowledge statements:\n{graph}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
"--document-query-template",
"Study the following context. Use only the information provided in the context in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere is the context:\n{documents}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
],
deploy: {
resources: {

22
tests/test-doc-embeddings Executable file
View file

@ -0,0 +1,22 @@
#!/usr/bin/env python3
import pulsar
from trustgraph.clients.document_embeddings_client import DocumentEmbeddingsClient
from trustgraph.clients.embeddings_client import EmbeddingsClient
ec = EmbeddingsClient(pulsar_host="pulsar://localhost:6650")
vectors = ec.request("What caused the space shuttle to explode?")
print(vectors)
llm = DocumentEmbeddingsClient(pulsar_host="pulsar://localhost:6650")
limit=10
resp = llm.request(vectors, limit)
print("Response...")
for val in resp:
print(val)

25
tests/test-doc-prompt Executable file
View file

@ -0,0 +1,25 @@
#!/usr/bin/env python3
import pulsar
from trustgraph.clients.prompt_client import PromptClient
p = PromptClient(pulsar_host="pulsar://localhost:6650")
docs = [
"In our house there is a big cat and a small cat.",
"The small cat is black.",
"The big cat is called Fred.",
"The orange stripey cat is big.",
"The black cat pounces on the big cat.",
"The black cat is called Hope."
]
query="What is the name of the cat who pounces on Fred? Provide a full explanation."
resp = p.request_document_prompt(
query=query,
documents=docs,
)
print(resp)

15
tests/test-doc-rag Executable file
View file

@ -0,0 +1,15 @@
#!/usr/bin/env python3
import pulsar
from trustgraph.clients.document_rag_client import DocumentRagClient
rag = DocumentRagClient(pulsar_host="pulsar://localhost:6650")
query="""
This knowledge graph describes the Space Shuttle disaster.
Present 20 facts which are present in the knowledge graph."""
resp = rag.request(query)
print(resp)

30
tg-launch-azure-cassandra.yaml
View file

@ -33,7 +33,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -50,7 +50,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -122,7 +122,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -155,7 +155,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -170,7 +170,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -232,7 +232,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -280,7 +280,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -316,7 +316,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -369,7 +369,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -386,7 +386,7 @@
"reservations":
"cpus": "0.1"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -403,7 +403,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -420,7 +420,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -443,7 +443,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion-rag":
"command":
@ -470,7 +470,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"vectorize":
"command":
@ -485,7 +485,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"cassandra": {}

30
tg-launch-azure-neo4j.yaml
View file

@ -16,7 +16,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -33,7 +33,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -105,7 +105,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -138,7 +138,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -153,7 +153,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -233,7 +233,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -281,7 +281,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -317,7 +317,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -370,7 +370,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -387,7 +387,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -404,7 +404,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -421,7 +421,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -444,7 +444,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion-rag":
"command":
@ -471,7 +471,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"vectorize":
"command":
@ -486,7 +486,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"etcd": {}

30
tg-launch-bedrock-cassandra.yaml
View file

@ -33,7 +33,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -50,7 +50,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -122,7 +122,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -155,7 +155,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -170,7 +170,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -232,7 +232,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -280,7 +280,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -316,7 +316,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -369,7 +369,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -386,7 +386,7 @@
"reservations":
"cpus": "0.1"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -403,7 +403,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -420,7 +420,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -447,7 +447,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion-rag":
"command":
@ -478,7 +478,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"vectorize":
"command":
@ -493,7 +493,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"cassandra": {}

30
tg-launch-bedrock-neo4j.yaml
View file

@ -16,7 +16,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -33,7 +33,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -105,7 +105,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -138,7 +138,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -153,7 +153,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -233,7 +233,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -281,7 +281,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -317,7 +317,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -370,7 +370,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -387,7 +387,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -404,7 +404,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -421,7 +421,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -448,7 +448,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion-rag":
"command":
@ -479,7 +479,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"vectorize":
"command":
@ -494,7 +494,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"etcd": {}

30
tg-launch-claude-cassandra.yaml
View file

@ -33,7 +33,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -50,7 +50,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -122,7 +122,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -155,7 +155,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -170,7 +170,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -232,7 +232,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -280,7 +280,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -316,7 +316,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -369,7 +369,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -386,7 +386,7 @@
"reservations":
"cpus": "0.1"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -403,7 +403,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -420,7 +420,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -441,7 +441,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion-rag":
"command":
@ -466,7 +466,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"vectorize":
"command":
@ -481,7 +481,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"cassandra": {}

30
tg-launch-claude-neo4j.yaml
View file

@ -16,7 +16,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -33,7 +33,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -105,7 +105,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -138,7 +138,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -153,7 +153,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -233,7 +233,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -281,7 +281,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -317,7 +317,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -370,7 +370,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -387,7 +387,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -404,7 +404,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -421,7 +421,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -442,7 +442,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion-rag":
"command":
@ -467,7 +467,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"vectorize":
"command":
@ -482,7 +482,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"etcd": {}

30
tg-launch-cohere-cassandra.yaml
View file

@ -33,7 +33,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -50,7 +50,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -122,7 +122,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -155,7 +155,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -170,7 +170,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -232,7 +232,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -280,7 +280,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -316,7 +316,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -369,7 +369,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -386,7 +386,7 @@
"reservations":
"cpus": "0.1"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -403,7 +403,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -420,7 +420,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -439,7 +439,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion-rag":
"command":
@ -462,7 +462,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"vectorize":
"command":
@ -477,7 +477,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"cassandra": {}

30
tg-launch-cohere-neo4j.yaml
View file

@ -16,7 +16,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -33,7 +33,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -105,7 +105,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -138,7 +138,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -153,7 +153,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -233,7 +233,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -281,7 +281,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -317,7 +317,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -370,7 +370,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -387,7 +387,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -404,7 +404,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -421,7 +421,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -440,7 +440,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
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@ -463,7 +463,7 @@
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@ -478,7 +478,7 @@
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"restart": "on-failure:100"
"volumes":
"etcd": {}

30
tg-launch-ollama-cassandra.yaml
View file

@ -33,7 +33,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
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@ -50,7 +50,7 @@
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@ -122,7 +122,7 @@
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@ -155,7 +155,7 @@
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@ -170,7 +170,7 @@
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@ -232,7 +232,7 @@
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@ -267,7 +267,7 @@
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@ -290,7 +290,7 @@
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@ -343,7 +343,7 @@
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@ -360,7 +360,7 @@
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@ -377,7 +377,7 @@
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@ -394,7 +394,7 @@
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@ -413,7 +413,7 @@
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@ -436,7 +436,7 @@
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@ -451,7 +451,7 @@
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"volumes":
"cassandra": {}

30
tg-launch-ollama-neo4j.yaml
View file

@ -16,7 +16,7 @@
"reservations":
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@ -33,7 +33,7 @@
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@ -105,7 +105,7 @@
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@ -138,7 +138,7 @@
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@ -153,7 +153,7 @@
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@ -233,7 +233,7 @@
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@ -268,7 +268,7 @@
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@ -291,7 +291,7 @@
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@ -344,7 +344,7 @@
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@ -361,7 +361,7 @@
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@ -378,7 +378,7 @@
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@ -395,7 +395,7 @@
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@ -414,7 +414,7 @@
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@ -437,7 +437,7 @@
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@ -452,7 +452,7 @@
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"volumes":
"etcd": {}

30
tg-launch-openai-cassandra.yaml
View file

@ -33,7 +33,7 @@
"reservations":
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"memory": "128M"
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@ -50,7 +50,7 @@
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@ -122,7 +122,7 @@
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@ -155,7 +155,7 @@
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@ -170,7 +170,7 @@
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@ -232,7 +232,7 @@
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@ -280,7 +280,7 @@
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@ -316,7 +316,7 @@
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@ -369,7 +369,7 @@
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@ -386,7 +386,7 @@
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@ -403,7 +403,7 @@
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@ -420,7 +420,7 @@
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@ -441,7 +441,7 @@
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@ -466,7 +466,7 @@
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@ -481,7 +481,7 @@
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"restart": "on-failure:100"
"volumes":
"cassandra": {}

30
tg-launch-openai-neo4j.yaml
View file

@ -16,7 +16,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
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"embeddings":
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@ -33,7 +33,7 @@
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@ -105,7 +105,7 @@
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@ -138,7 +138,7 @@
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@ -153,7 +153,7 @@
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@ -233,7 +233,7 @@
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@ -281,7 +281,7 @@
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@ -317,7 +317,7 @@
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@ -370,7 +370,7 @@
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@ -387,7 +387,7 @@
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@ -404,7 +404,7 @@
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@ -421,7 +421,7 @@
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@ -442,7 +442,7 @@
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@ -467,7 +467,7 @@
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@ -482,7 +482,7 @@
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"volumes":
"etcd": {}

30
tg-launch-vertexai-cassandra.yaml
View file

@ -33,7 +33,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
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"embeddings":
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@ -50,7 +50,7 @@
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@ -122,7 +122,7 @@
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@ -155,7 +155,7 @@
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@ -170,7 +170,7 @@
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@ -232,7 +232,7 @@
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"prometheus":
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@ -280,7 +280,7 @@
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@ -316,7 +316,7 @@
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@ -369,7 +369,7 @@
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"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -386,7 +386,7 @@
"reservations":
"cpus": "0.1"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -403,7 +403,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -420,7 +420,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -443,7 +443,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
- "./vertexai:/vertexai"
@ -472,7 +472,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
- "./vertexai:/vertexai"
@ -489,7 +489,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"cassandra": {}

30
tg-launch-vertexai-neo4j.yaml
View file

@ -16,7 +16,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"embeddings":
"command":
@ -33,7 +33,7 @@
"reservations":
"cpus": "0.5"
"memory": "256M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"etcd":
"command":
@ -105,7 +105,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"init-pulsar":
"command":
@ -138,7 +138,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"kg-extract-relationships":
"command":
@ -153,7 +153,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"milvus":
"command":
@ -233,7 +233,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prometheus":
"deploy":
@ -281,7 +281,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"prompt-rag":
"command":
@ -317,7 +317,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"pulsar":
"command": "bin/pulsar standalone"
@ -370,7 +370,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -387,7 +387,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -404,7 +404,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -421,7 +421,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"text-completion":
"command":
@ -444,7 +444,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
- "./vertexai:/vertexai"
@ -473,7 +473,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
- "./vertexai:/vertexai"
@ -490,7 +490,7 @@
"reservations":
"cpus": "0.5"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"etcd": {}

8
tg-storage-cassandra.yaml
View file

@ -195,7 +195,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -212,7 +212,7 @@
"reservations":
"cpus": "0.1"
"memory": "512M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -229,7 +229,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -246,7 +246,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"cassandra": {}

8
tg-storage-neo4j.yaml
View file

@ -196,7 +196,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"query-triples":
"command":
@ -213,7 +213,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-graph-embeddings":
"command":
@ -230,7 +230,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"store-triples":
"command":
@ -247,7 +247,7 @@
"reservations":
"cpus": "0.1"
"memory": "128M"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.16"
"image": "docker.io/trustgraph/trustgraph-flow:0.7.17"
"restart": "on-failure:100"
"volumes":
"etcd": {}

2
trustgraph/base/consumer.py
View file

@ -65,7 +65,7 @@ class Consumer(BaseProcessor):
self.consumer.negative_acknowledge(msg)
print("TooManyRequests: will retry")
__class__.processing_metric.labels(status="rate-limit").inc()
time.sleep(5)
time.sleep(2)
continue
except Exception as e:

2
trustgraph/base/consumer_producer.py
View file

@ -84,7 +84,7 @@ class ConsumerProducer(BaseProcessor):
self.consumer.negative_acknowledge(msg)
print("TooManyRequests: will retry")
__class__.processing_metric.labels(status="rate-limit").inc()
time.sleep(5)
time.sleep(2)
continue
except Exception as e:

45
trustgraph/clients/document_embeddings_client.py Normal file
View file

@ -0,0 +1,45 @@
import _pulsar
from .. schema import DocumentEmbeddingsRequest, DocumentEmbeddingsResponse
from .. schema import document_embeddings_request_queue
from .. schema import document_embeddings_response_queue
from . base import BaseClient
# Ugly
ERROR=_pulsar.LoggerLevel.Error
WARN=_pulsar.LoggerLevel.Warn
INFO=_pulsar.LoggerLevel.Info
DEBUG=_pulsar.LoggerLevel.Debug
class DocumentEmbeddingsClient(BaseClient):
def __init__(
self, log_level=ERROR,
subscriber=None,
input_queue=None,
output_queue=None,
pulsar_host="pulsar://pulsar:6650",
):
if input_queue == None:
input_queue = document_embeddings_request_queue
if output_queue == None:
output_queue = document_embeddings_response_queue
super(DocumentEmbeddingsClient, self).__init__(
log_level=log_level,
subscriber=subscriber,
input_queue=input_queue,
output_queue=output_queue,
pulsar_host=pulsar_host,
input_schema=DocumentEmbeddingsRequest,
output_schema=DocumentEmbeddingsResponse,
)
def request(self, vectors, limit=10, timeout=300):
return self.call(
vectors=vectors, limit=limit, timeout=timeout
).documents

46
trustgraph/clients/document_rag_client.py Normal file
View file

@ -0,0 +1,46 @@
import _pulsar
from .. schema import DocumentRagQuery, DocumentRagResponse
from .. schema import document_rag_request_queue, document_rag_response_queue
from . base import BaseClient
# Ugly
ERROR=_pulsar.LoggerLevel.Error
WARN=_pulsar.LoggerLevel.Warn
INFO=_pulsar.LoggerLevel.Info
DEBUG=_pulsar.LoggerLevel.Debug
class DocumentRagClient(BaseClient):
def __init__(
self,
log_level=ERROR,
subscriber=None,
input_queue=None,
output_queue=None,
pulsar_host="pulsar://pulsar:6650",
):
if input_queue == None:
input_queue = document_rag_request_queue
if output_queue == None:
output_queue = document_rag_response_queue
super(DocumentRagClient, self).__init__(
log_level=log_level,
subscriber=subscriber,
input_queue=input_queue,
output_queue=output_queue,
pulsar_host=pulsar_host,
input_schema=DocumentRagQuery,
output_schema=DocumentRagResponse,
)
def request(self, query, timeout=500):
return self.call(
query=query, timeout=timeout
).response

9
trustgraph/clients/prompt_client.py
View file

@ -64,3 +64,12 @@ class PromptClient(BaseClient):
timeout=timeout
).answer
def request_document_prompt(self, query, documents, timeout=300):
return self.call(
kind="document-prompt",
query=query,
documents=documents,
timeout=timeout
).answer

138
trustgraph/direct/milvus_doc_embeddings.py Normal file
View file

@ -0,0 +1,138 @@
from pymilvus import MilvusClient, CollectionSchema, FieldSchema, DataType
import time
class DocVectors:
def __init__(self, uri="http://localhost:19530", prefix='doc'):
self.client = MilvusClient(uri=uri)
# Strategy is to create collections per dimension. Probably only
# going to be using 1 anyway, but that means we don't need to
# hard-code the dimension anywhere, and no big deal if more than
# one are created.
self.collections = {}
self.prefix = prefix
# Time between reloads
self.reload_time = 90
# Next time to reload - this forces a reload at next window
self.next_reload = time.time() + self.reload_time
print("Reload at", self.next_reload)
def init_collection(self, dimension):
collection_name = self.prefix + "_" + str(dimension)
pkey_field = FieldSchema(
name="id",
dtype=DataType.INT64,
is_primary=True,
auto_id=True,
)
vec_field = FieldSchema(
name="vector",
dtype=DataType.FLOAT_VECTOR,
dim=dimension,
)
doc_field = FieldSchema(
name="doc",
dtype=DataType.VARCHAR,
max_length=65535,
)
schema = CollectionSchema(
fields = [pkey_field, vec_field, doc_field],
description = "Document embedding schema",
)
self.client.create_collection(
collection_name=collection_name,
schema=schema,
metric_type="COSINE",
)
index_params = MilvusClient.prepare_index_params()
index_params.add_index(
field_name="vector",
metric_type="COSINE",
index_type="IVF_SQ8",
index_name="vector_index",
params={ "nlist": 128 }
)
self.client.create_index(
collection_name=collection_name,
index_params=index_params
)
self.collections[dimension] = collection_name
def insert(self, embeds, doc):
dim = len(embeds)
if dim not in self.collections:
self.init_collection(dim)
data = [
{
"vector": embeds,
"doc": doc,
}
]
self.client.insert(
collection_name=self.collections[dim],
data=data
)
def search(self, embeds, fields=["doc"], limit=10):
dim = len(embeds)
if dim not in self.collections:
self.init_collection(dim)
coll = self.collections[dim]
search_params = {
"metric_type": "COSINE",
"params": {
"radius": 0.1,
"range_filter": 0.8
}
}
print("Loading...")
self.client.load_collection(
collection_name=coll,
)
print("Searching...")
res = self.client.search(
collection_name=coll,
data=[embeds],
limit=limit,
output_fields=fields,
search_params=search_params,
)[0]
# If reload time has passed, unload collection
if time.time() > self.next_reload:
print("Unloading, reload at", self.next_reload)
self.client.release_collection(
collection_name=coll,
)
self.next_reload = time.time() + self.reload_time
return res

10
trustgraph/direct/milvus.py → trustgraph/direct/milvus_graph_embeddings.py
View file

@ -2,9 +2,9 @@
from pymilvus import MilvusClient, CollectionSchema, FieldSchema, DataType
import time
class TripleVectors:
class EntityVectors:
def __init__(self, uri="http://localhost:19530"):
def __init__(self, uri="http://localhost:19530", prefix='entity'):
self.client = MilvusClient(uri=uri)
@ -14,6 +14,8 @@ class TripleVectors:
# one are created.
self.collections = {}
self.prefix = prefix
# Time between reloads
self.reload_time = 90
@ -23,7 +25,7 @@ class TripleVectors:
def init_collection(self, dimension):
collection_name = "triples_" + str(dimension)
collection_name = self.prefix + "_" + str(dimension)
pkey_field = FieldSchema(
name="id",
@ -46,7 +48,7 @@ class TripleVectors:
schema = CollectionSchema(
fields = [pkey_field, vec_field, entity_field],
description = "Edge map schema",
description = "Graph embedding schema",
)
self.client.create_collection(

132
trustgraph/document_rag.py Normal file
View file

@ -0,0 +1,132 @@
from . clients.document_embeddings_client import DocumentEmbeddingsClient
from . clients.triples_query_client import TriplesQueryClient
from . clients.embeddings_client import EmbeddingsClient
from . clients.prompt_client import PromptClient
from . schema import DocumentEmbeddingsRequest, DocumentEmbeddingsResponse
from . schema import TriplesQueryRequest, TriplesQueryResponse
from . schema import prompt_request_queue
from . schema import prompt_response_queue
from . schema import embeddings_request_queue
from . schema import embeddings_response_queue
from . schema import document_embeddings_request_queue
from . schema import document_embeddings_response_queue
LABEL="http://www.w3.org/2000/01/rdf-schema#label"
DEFINITION="http://www.w3.org/2004/02/skos/core#definition"
class DocumentRag:
def __init__(
self,
pulsar_host="pulsar://pulsar:6650",
pr_request_queue=None,
pr_response_queue=None,
emb_request_queue=None,
emb_response_queue=None,
de_request_queue=None,
de_response_queue=None,
verbose=False,
module="test",
):
self.verbose=verbose
if pr_request_queue is None:
pr_request_queue = prompt_request_queue
if pr_response_queue is None:
pr_response_queue = prompt_response_queue
if emb_request_queue is None:
emb_request_queue = embeddings_request_queue
if emb_response_queue is None:
emb_response_queue = embeddings_response_queue
if de_request_queue is None:
de_request_queue = document_embeddings_request_queue
if de_response_queue is None:
de_response_queue = document_embeddings_response_queue
if self.verbose:
print("Initialising...", flush=True)
# FIXME: Configurable
self.entity_limit = 20
self.de_client = DocumentEmbeddingsClient(
pulsar_host=pulsar_host,
subscriber=module + "-de",
input_queue=de_request_queue,
output_queue=de_response_queue,
)
self.embeddings = EmbeddingsClient(
pulsar_host=pulsar_host,
input_queue=emb_request_queue,
output_queue=emb_response_queue,
subscriber=module + "-emb",
)
self.lang = PromptClient(
pulsar_host=pulsar_host,
input_queue=prompt_request_queue,
output_queue=prompt_response_queue,
subscriber=module + "-de-prompt",
)
if self.verbose:
print("Initialised", flush=True)
def get_vector(self, query):
if self.verbose:
print("Compute embeddings...", flush=True)
qembeds = self.embeddings.request(query)
if self.verbose:
print("Done.", flush=True)
return qembeds
def get_docs(self, query):
vectors = self.get_vector(query)
if self.verbose:
print("Get entities...", flush=True)
docs = self.de_client.request(
vectors, self.entity_limit
)
if self.verbose:
print("Docs:", flush=True)
for doc in docs:
print(doc, flush=True)
return docs
def query(self, query):
if self.verbose:
print("Construct prompt...", flush=True)
docs = self.get_docs(query)
if self.verbose:
print("Invoke LLM...", flush=True)
print(docs)
print(query)
resp = self.lang.request_document_prompt(query, docs)
if self.verbose:
print("Done", flush=True)
return resp

15
trustgraph/model/prompt/generic/prompts.py
View file

@ -79,3 +79,18 @@ Use only the provided knowledge statements to respond to the following:
"""
return prompt
def to_document_query(query, documents):
documents = "\n\n".join(documents)
prompt=f"""Study the following context. Use only the information provided in the context in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.
Here is the context:
{documents}
Use only the provided knowledge statements to respond to the following:
{query}
"""
return prompt

46
trustgraph/model/prompt/generic/service.py
View file

@ -1,4 +1,3 @@
"""
Language service abstracts prompt engineering from LLM.
"""
@ -14,7 +13,8 @@ from .... schema import prompt_request_queue, prompt_response_queue
from .... base import ConsumerProducer
from .... clients.llm_client import LlmClient
from . prompts import to_definitions, to_relationships, to_kg_query
from . prompts import to_definitions, to_relationships
from . prompts import to_kg_query, to_document_query
module = ".".join(__name__.split(".")[1:-1])
@ -82,6 +82,11 @@ class Processor(ConsumerProducer):
self.handle_kg_prompt(id, v)
return
elif kind == "document-prompt":
self.handle_document_prompt(id, v)
return
else:
print("Invalid kind.", flush=True)
@ -252,6 +257,43 @@ class Processor(ConsumerProducer):
self.producer.send(r, properties={"id": id})
def handle_document_prompt(self, id, v):
try:
prompt = to_document_query(v.query, v.documents)
print("prompt")
print(prompt)
print("Call LLM...")
ans = self.llm.request(prompt)
print(ans)
print("Send response...", flush=True)
r = PromptResponse(answer=ans, 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})
@staticmethod
def add_args(parser):

4
trustgraph/model/prompt/template/prompts.py
View file

@ -17,3 +17,7 @@ def to_kg_query(template, query, kg):
cypher = get_cypher(kg)
return template.format(query=query, graph=cypher)
def to_document_query(template, query, docs):
docs = "\n\n".join(docs)
return template.format(query=query, documents=docs)

86
trustgraph/model/prompt/template/service.py
View file

@ -14,7 +14,8 @@ from .... schema import prompt_request_queue, prompt_response_queue
from .... base import ConsumerProducer
from .... clients.llm_client import LlmClient
from . prompts import to_definitions, to_relationships, to_kg_query
from . prompts import to_definitions, to_relationships
from . prompts import to_kg_query, to_document_query
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")
knowledge_query_template = params.get("knowledge_query_template")
document_query_template = params.get("document_query_template")
super(Processor, self).__init__(
**params | {
@ -48,9 +50,6 @@ class Processor(ConsumerProducer):
"output_schema": PromptResponse,
"text_completion_request_queue": tc_request_queue,
"text_completion_response_queue": tc_response_queue,
"definition_template": definition_template,
"relationship_template": relationship_template,
"knowledge_query_template": knowledge_query_template,
}
)
@ -64,6 +63,7 @@ class Processor(ConsumerProducer):
self.definition_template = definition_template
self.relationship_template = relationship_template
self.knowledge_query_template = knowledge_query_template
self.document_query_template = document_query_template
def handle(self, msg):
@ -92,6 +92,11 @@ class Processor(ConsumerProducer):
self.handle_kg_prompt(id, v)
return
elif kind == "document-prompt":
self.handle_document_prompt(id, v)
return
else:
print("Invalid kind.", flush=True)
@ -120,6 +125,11 @@ class Processor(ConsumerProducer):
e = defn["entity"]
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
@ -171,12 +181,30 @@ class Processor(ConsumerProducer):
for defn in defs:
try:
s = defn["subject"]
p = defn["predicate"]
o = defn["object"]
o_entity = defn["object-entity"]
if s == "": continue
if s is None: continue
if p == "": continue
if p is None: continue
if o == "": continue
if o is None: continue
if o_entity == "" or o_entity is None:
o_entity = False
output.append(
Relationship(
s = defn["subject"],
p = defn["predicate"],
o = defn["object"],
o_entity = defn["object-entity"],
s = s,
p = p,
o = o,
o_entity = o_entity,
)
)
@ -239,6 +267,42 @@ class Processor(ConsumerProducer):
self.producer.send(r, properties={"id": id})
def handle_document_prompt(self, id, v):
try:
prompt = to_document_query(
self.document_query_template, v.query, v.documents
)
print(prompt)
ans = self.llm.request(prompt)
print(ans)
print("Send response...", flush=True)
r = PromptResponse(answer=ans, 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})
@staticmethod
def add_args(parser):
@ -277,6 +341,12 @@ class Processor(ConsumerProducer):
help=f'Knowledge query template',
)
parser.add_argument(
'--document-query-template',
required=True,
help=f'Document query template',
)
def run():
Processor.start(module, __doc__)

0
trustgraph/query/doc_embeddings/__init__.py Normal file
View file

3
trustgraph/query/doc_embeddings/milvus/__init__.py Normal file
View file

@ -0,0 +1,3 @@
from . service import *

7
trustgraph/query/doc_embeddings/milvus/__main__.py Executable file
View file

@ -0,0 +1,7 @@
#!/usr/bin/env python3
from . hf import run
if __name__ == '__main__':
run()

106
trustgraph/query/doc_embeddings/milvus/service.py Executable file
View file

@ -0,0 +1,106 @@
"""
Document embeddings query service. Input is vector, output is an array
of chunks
"""
from .... direct.milvus_doc_embeddings import DocVectors
from .... schema import DocumentEmbeddingsRequest, DocumentEmbeddingsResponse
from .... schema import Error, Value
from .... schema import document_embeddings_request_queue
from .... schema import document_embeddings_response_queue
from .... base import ConsumerProducer
module = ".".join(__name__.split(".")[1:-1])
default_input_queue = document_embeddings_request_queue
default_output_queue = document_embeddings_response_queue
default_subscriber = module
default_store_uri = 'http://localhost:19530'
class Processor(ConsumerProducer):
def __init__(self, **params):
input_queue = params.get("input_queue", default_input_queue)
output_queue = params.get("output_queue", default_output_queue)
subscriber = params.get("subscriber", default_subscriber)
store_uri = params.get("store_uri", default_store_uri)
super(Processor, self).__init__(
**params | {
"input_queue": input_queue,
"output_queue": output_queue,
"subscriber": subscriber,
"input_schema": DocumentEmbeddingsRequest,
"output_schema": DocumentEmbeddingsResponse,
"store_uri": store_uri,
}
)
self.vecstore = DocVectors(store_uri)
def handle(self, msg):
try:
v = msg.value()
# Sender-produced ID
id = msg.properties()["id"]
print(f"Handling input {id}...", flush=True)
chunks = []
for vec in v.vectors:
resp = self.vecstore.search(vec, limit=v.limit)
for r in resp:
chunk = r["entity"]["doc"]
chunk = chunk.encode("utf-8")
chunks.append(chunk)
print("Send response...", flush=True)
r = DocumentEmbeddingsResponse(documents=chunks, 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 = DocumentEmbeddingsResponse(
error=Error(
type = "llm-error",
message = str(e),
),
documents=None,
)
self.producer.send(r, properties={"id": id})
self.consumer.acknowledge(msg)
@staticmethod
def add_args(parser):
ConsumerProducer.add_args(
parser, default_input_queue, default_subscriber,
default_output_queue,
)
parser.add_argument(
'-t', '--store-uri',
default=default_store_uri,
help=f'Milvus store URI (default: {default_store_uri})'
)
def run():
Processor.start(module, __doc__)

6
trustgraph/query/graph_embeddings/milvus/service.py
View file

@ -4,7 +4,7 @@ Graph embeddings query service. Input is vector, output is list of
entities
"""
from .... direct.milvus import TripleVectors
from .... direct.milvus_graph_embeddings import EntityVectors
from .... schema import GraphEmbeddingsRequest, GraphEmbeddingsResponse
from .... schema import Error, Value
from .... schema import graph_embeddings_request_queue
@ -38,7 +38,7 @@ class Processor(ConsumerProducer):
}
)
self.vecstore = TripleVectors(store_uri)
self.vecstore = EntityVectors(store_uri)
def create_value(self, ent):
if ent.startswith("http://") or ent.startswith("https://"):
@ -94,7 +94,7 @@ class Processor(ConsumerProducer):
type = "llm-error",
message = str(e),
),
response=None,
entities=None,
)
self.producer.send(r, properties={"id": id})

3
trustgraph/retrieval/document_rag/__init__.py Normal file
View file

@ -0,0 +1,3 @@
from . rag import *

7
trustgraph/retrieval/document_rag/__main__.py Executable file
View file

@ -0,0 +1,7 @@
#!/usr/bin/env python3
from . rag import run
if __name__ == '__main__':
run()

194
trustgraph/retrieval/document_rag/rag.py Executable file
View file

@ -0,0 +1,194 @@
"""
Simple RAG service, performs query using document RAG an LLM.
Input is query, output is response.
"""
from ... schema import DocumentRagQuery, DocumentRagResponse, Error
from ... schema import document_rag_request_queue, document_rag_response_queue
from ... schema import prompt_request_queue
from ... schema import prompt_response_queue
from ... schema import embeddings_request_queue
from ... schema import embeddings_response_queue
from ... schema import document_embeddings_request_queue
from ... schema import document_embeddings_response_queue
from ... log_level import LogLevel
from ... document_rag import DocumentRag
from ... base import ConsumerProducer
module = ".".join(__name__.split(".")[1:-1])
default_input_queue = document_rag_request_queue
default_output_queue = document_rag_response_queue
default_subscriber = module
class Processor(ConsumerProducer):
def __init__(self, **params):
input_queue = params.get("input_queue", default_input_queue)
output_queue = params.get("output_queue", default_output_queue)
subscriber = params.get("subscriber", default_subscriber)
entity_limit = params.get("entity_limit", 50)
triple_limit = params.get("triple_limit", 30)
pr_request_queue = params.get(
"prompt_request_queue", prompt_request_queue
)
pr_response_queue = params.get(
"prompt_response_queue", prompt_response_queue
)
emb_request_queue = params.get(
"embeddings_request_queue", embeddings_request_queue
)
emb_response_queue = params.get(
"embeddings_response_queue", embeddings_response_queue
)
de_request_queue = params.get(
"document_embeddings_request_queue",
document_embeddings_request_queue
)
de_response_queue = params.get(
"document_embeddings_response_queue",
document_embeddings_response_queue
)
super(Processor, self).__init__(
**params | {
"input_queue": input_queue,
"output_queue": output_queue,
"subscriber": subscriber,
"input_schema": DocumentRagQuery,
"output_schema": DocumentRagResponse,
"prompt_request_queue": pr_request_queue,
"prompt_response_queue": pr_response_queue,
"embeddings_request_queue": emb_request_queue,
"embeddings_response_queue": emb_response_queue,
"document_embeddings_request_queue": de_request_queue,
"document_embeddings_response_queue": de_response_queue,
}
)
self.rag = DocumentRag(
pulsar_host=self.pulsar_host,
pr_request_queue=pr_request_queue,
pr_response_queue=pr_response_queue,
emb_request_queue=emb_request_queue,
emb_response_queue=emb_response_queue,
de_request_queue=de_request_queue,
de_response_queue=de_response_queue,
verbose=True,
module=module,
)
def handle(self, msg):
try:
v = msg.value()
# Sender-produced ID
id = msg.properties()["id"]
print(f"Handling input {id}...", flush=True)
response = self.rag.query(v.query)
print("Send response...", flush=True)
r = DocumentRagResponse(response = response, 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 = GraphRagResponse(
error=Error(
type = "llm-error",
message = str(e),
),
response=None,
)
self.producer.send(r, properties={"id": id})
self.consumer.acknowledge(msg)
@staticmethod
def add_args(parser):
ConsumerProducer.add_args(
parser, default_input_queue, default_subscriber,
default_output_queue,
)
parser.add_argument(
'-v', '--vector-store',
default='http://milvus:19530',
help=f'Vector host (default: http://milvus:19530)'
)
parser.add_argument(
'-e', '--entity-limit',
type=int,
default=50,
help=f'Entity vector fetch limit (default: 50)'
)
parser.add_argument(
'-t', '--triple-limit',
type=int,
default=30,
help=f'Triple query limit, per query (default: 30)'
)
parser.add_argument(
'-u', '--max-subgraph-size',
type=int,
default=3000,
help=f'Max subgraph size (default: 3000)'
)
parser.add_argument(
'--prompt-request-queue',
default=prompt_request_queue,
help=f'Prompt request queue (default: {prompt_request_queue})',
)
parser.add_argument(
'--prompt-response-queue',
default=prompt_response_queue,
help=f'Prompt response queue (default: {prompt_response_queue})',
)
parser.add_argument(
'--embeddings-request-queue',
default=embeddings_request_queue,
help=f'Embeddings request queue (default: {embeddings_request_queue})',
)
parser.add_argument(
'--embeddings-response-queue',
default=embeddings_response_queue,
help=f'Embeddings response queue (default: {embeddings_response_queue})',
)
parser.add_argument(
'--document-embeddings-request-queue',
default=document_embeddings_request_queue,
help=f'Document embeddings request queue (default: {document_embeddings_request_queue})',
)
parser.add_argument(
'--document-embeddings-response-queue',
default=document_embeddings_response_queue,
help=f'Document embeddings response queue (default: {document_embeddings_response_queue})',
)
def run():
Processor.start(module, __doc__)

2
trustgraph/retrieval/graph_rag/rag.py
View file

@ -206,7 +206,7 @@ class Processor(ConsumerProducer):
)
parser.add_argument(
'--graph_embeddings-response-queue',
'--graph-embeddings-response-queue',
default=graph_embeddings_response_queue,
help=f'Graph embeddings response queue (default: {graph_embeddings_response_queue})',
)

42
trustgraph/schema.py
View file

@ -96,6 +96,25 @@ graph_embeddings_response_queue = topic(
############################################################################
# Doc embeddings query
class DocumentEmbeddingsRequest(Record):
vectors = Array(Array(Double()))
limit = Integer()
class DocumentEmbeddingsResponse(Record):
error = Error()
documents = Array(Bytes())
document_embeddings_request_queue = topic(
'doc-embeddings', kind='non-persistent', namespace='request'
)
document_embeddings_response_queue = topic(
'doc-embeddings-response', kind='non-persistent', namespace='response',
)
############################################################################
# Graph triples
class Triple(Record):
@ -187,6 +206,24 @@ graph_rag_response_queue = topic(
############################################################################
# Document RAG text retrieval
class DocumentRagQuery(Record):
query = String()
class DocumentRagResponse(Record):
error = Error()
response = String()
document_rag_request_queue = topic(
'doc-rag', kind='non-persistent', namespace='request'
)
document_rag_response_queue = topic(
'doc-rag-response', kind='non-persistent', namespace='response'
)
############################################################################
# Prompt services, abstract the prompt generation
class Definition(Record):
@ -208,14 +245,17 @@ class Fact(Record):
# chunk -> definitions
# extract-relationships:
# chunk -> relationships
# prompt-rag:
# kg-prompt:
# query, triples -> answer
# document-prompt:
# query, documents -> answer
class PromptRequest(Record):
kind = String()
chunk = String()
query = String()
kg = Array(Fact())
documents = Array(Bytes())
class PromptResponse(Record):
error = Error()

18
trustgraph/storage/doc_embeddings/milvus/write.py
View file

@ -3,15 +3,15 @@
Accepts entity/vector pairs and writes them to a Milvus store.
"""
from .... schema import GraphEmbeddings
from .... schema import graph_embeddings_store_queue
from .... schema import ChunkEmbeddings
from .... schema import chunk_embeddings_ingest_queue
from .... log_level import LogLevel
from .... direct.milvus import TripleVectors
from .... direct.milvus_doc_embeddings import DocVectors
from .... base import Consumer
module = ".".join(__name__.split(".")[1:-1])
default_input_queue = graph_embeddings_store_queue
default_input_queue = chunk_embeddings_ingest_queue
default_subscriber = module
default_store_uri = 'http://localhost:19530'
@ -27,20 +27,22 @@ class Processor(Consumer):
**params | {
"input_queue": input_queue,
"subscriber": subscriber,
"input_schema": GraphEmbeddings,
"input_schema": ChunkEmbeddings,
"store_uri": store_uri,
}
)
self.vecstore = TripleVectors(store_uri)
self.vecstore = DocVectors(store_uri)
def handle(self, msg):
v = msg.value()
if v.entity.value != "":
chunk = v.chunk.decode("utf-8")
if v.chunk != "" and v.chunk is not None:
for vec in v.vectors:
self.vecstore.insert(vec, v.entity.value)
self.vecstore.insert(vec, chunk)
@staticmethod
def add_args(parser):

4
trustgraph/storage/graph_embeddings/milvus/write.py
View file

@ -6,7 +6,7 @@ Accepts entity/vector pairs and writes them to a Milvus store.
from .... schema import GraphEmbeddings
from .... schema import graph_embeddings_store_queue
from .... log_level import LogLevel
from .... direct.milvus import TripleVectors
from .... direct.milvus_graph_embeddings import EntityVectors
from .... base import Consumer
module = ".".join(__name__.split(".")[1:-1])
@ -32,7 +32,7 @@ class Processor(Consumer):
}
)
self.vecstore = TripleVectors(store_uri)
self.vecstore = EntityVectors(store_uri)
def handle(self, msg):