Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fixes #4103: Separate docs GenAI and RAG #4112

Merged
merged 1 commit into from
Jun 26, 2024
Merged

Fixes #4103: Separate docs GenAI and RAG #4112

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions docs/asciidoc/modules/ROOT/nav.adoc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -68,6 +68,8 @@ include::partial$generated-documentation/nav.adoc[]
** xref:ml/bedrock.adoc[]
** xref:ml/watsonai.adoc[]
** xref:ml/mixedbread.adoc[]
** xref:ml/genai.adoc[]
** xref:ml/rag.adoc[]

* xref:background-operations/index.adoc[]
** xref::background-operations/apoc-load-directory-async.adoc[]
Expand Down
342 changes: 342 additions & 0 deletions docs/asciidoc/modules/ROOT/pages/ml/genai.adoc
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,342 @@
[[genai-assistant]]
= GenAI Assistant Procedures
:description: This section describes procedures that can be used to access the GenAI Assistant.

== Query with natural language

This procedure `apoc.ml.query` takes a question in natural language and returns the results of that query.

It uses the `chat/completions` API which is https://platform.openai.com/docs/api-reference/chat/create[documented here^].

.Query call
[source,cypher]
----
CALL apoc.ml.query("What movies did Tom Hanks play in?") yield value, query
RETURN *
----

.Example response
[source, bash]
----
+------------------------------------------------------------------------------------------------------------------------------+
| value | query |
+------------------------------------------------------------------------------------------------------------------------------+
| {m.title -> "You've Got Mail"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "Apollo 13"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "Joe Versus the Volcano"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "That Thing You Do"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "Cloud Atlas"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "The Da Vinci Code"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "Sleepless in Seattle"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "A League of Their Own"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "The Green Mile"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "Charlie Wilson's War"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "Cast Away"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
| {m.title -> "The Polar Express"} | "cypher
MATCH (m:Movie)<-[:ACTED_IN]-(p:Person {name: 'Tom Hanks'})
RETURN m.title
" |
+------------------------------------------------------------------------------------------------------------------------------+
12 rows
----

.Input Parameters
[%autowidth, opts=header]
|===
| name | description
| question | The question in the natural language
| conf | An optional configuration map, please check the next section | no
|===

.Configuration map
[%autowidth, opts=header]
|===
| name | description | mandatory
| retries | The number of retries in case of API call failures | no, default `3`
| retryWithError | If true, in case of error retry the api adding the following messages to the body request:
{`"role":"user", "content": "The previous Cypher Statement throws the following error, consider it to return the correct statement: `<errorMessage>`"}, {"role":"assistant", "content":"Cypher Statement (in backticks):"}` | no, default `false`
| apiKey | OpenAI API key | in case `apoc.openai.key` is not defined
| model | The Open AI model | no, default `gpt-3.5-turbo`
| sample | The number of nodes to skip, e.g. a sample of 1000 will read every 1000th node. It's used as a parameter to `apoc.meta.data` procedure that computes the schema | no, default is a random number
|===

.Results
[%autowidth, opts=header]
|===
| name | description
| value | the result of the query
| cypher | the query used to compute the result
|===


== Describe the graph model with natural language

This procedure `apoc.ml.schema` returns a description, in natural language, of the underlying dataset.

It uses the `chat/completions` API which is https://platform.openai.com/docs/api-reference/chat/create[documented here^].

.Query call
[source,cypher]
----
CALL apoc.ml.schema() yield value
RETURN *
----

.Example response
[source, bash]
----
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| value |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| "The graph database schema represents a system where users can follow other users and review movies. Users (:Person) can either follow other users (:Person) or review movies (:Movie). The relationships allow users to express their preferences and opinions about movies. This schema can be compared to social media platforms where users can follow each other and leave reviews or ratings for movies they have watched. It can also be related to movie recommendation systems where user preferences and reviews play a crucial role in generating personalized recommendations." |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row
----

.Input Parameters
[%autowidth, opts=header]
|===
| name | description
| conf | An optional configuration map, please check the next section
|===

.Configuration map
[%autowidth, opts=header]
|===
| name | description | mandatory
| apiKey | OpenAI API key | in case `apoc.openai.key` is not defined
| model | The Open AI model | no, default `gpt-3.5-turbo`
| sample | The number of nodes to skip, e.g. a sample of 1000 will read every 1000th node. It's used as a parameter to `apoc.meta.data` procedure that computes the schema | no, default is a random number
|===

.Results
[%autowidth, opts=header]
|===
| name | description
| value | the description of the dataset
|===


== Create cypher queries from a natural language query

This procedure `apoc.ml.cypher` takes a natural language question and transforms it into a number of requested cypher queries.

It uses the `chat/completions` API which is https://platform.openai.com/docs/api-reference/chat/create[documented here^].

.Query call
[source,cypher]
----
CALL apoc.ml.cypher("Who are the actors which also directed a movie?", {count: 4}) yield cypher
RETURN *
----

.Example response
[source, bash]
----
+----------------------------------------------------------------------------------------------------------------+
| query |
+----------------------------------------------------------------------------------------------------------------+
| "
MATCH (a:Person)-[:ACTED_IN]->(m:Movie)<-[:DIRECTED]-(d:Person)
RETURN a.name as actor, d.name as director
" |
| "cypher
MATCH (a:Person)-[:ACTED_IN]->(m:Movie)<-[:DIRECTED]-(a)
RETURN a.name
" |
| "
MATCH (a:Person)-[:ACTED_IN]->(m:Movie)<-[:DIRECTED]-(d:Person)
RETURN a.name
" |
| "cypher
MATCH (a:Person)-[:ACTED_IN]->(:Movie)<-[:DIRECTED]-(a)
RETURN DISTINCT a.name
" |
+----------------------------------------------------------------------------------------------------------------+
4 rows
----

.Input Parameters
[%autowidth, opts=header]
|===
| name | description | mandatory
| question | The question in the natural language | yes
| conf | An optional configuration map, please check the next section | no
|===

.Configuration map
[%autowidth, opts=header]
|===
| name | description | mandatory
| count | The number of queries to retrieve | no, default `1`
| apiKey | OpenAI API key | in case `apoc.openai.key` is not defined
| model | The Open AI model | no, default `gpt-3.5-turbo`
| sample | The number of nodes to skip, e.g. a sample of 1000 will read every 1000th node. It's used as a parameter to `apoc.meta.data` procedure that computes the schema | no, default is a random number
|===

.Results
[%autowidth, opts=header]
|===
| name | description
| value | the description of the dataset
|===

== Create a natural language query explanation from a cypher query

This procedure `apoc.ml.fromCypher` takes a natural language question and transforms it into natural language query explanation.

It uses the `chat/completions` API which is https://platform.openai.com/docs/api-reference/chat/create[documented here^].

.Query call
[source,cypher]
----
CALL apoc.ml.cypher("MATCH (p:Person {name: "Tom Hanks"})-[:ACTED_IN]->(m:Movie) RETURN m", {}) yield value
RETURN *
----

.Example response
[opts="header"]
|===
| value
| this database schema represents a simplified version of a common movie database model. the `movie` node represents a movie entity with attributes such as the year it was released, a tagline, and the movie title. the `person` node represents a person involved in the movie industry, with attributes for the person's year of birth and name. the relationship `directed` connects a `person` node to a `movie` node, indicating that the person directed the movie.
in terms of domains, this schema can be related to the entertainment industry, specifically the movie industry. movies and people involved in creating those movies are fundamental entities in this domain. the `directed` relationship captures the directed-by relationship between a person and a movie. this type of model can be extended to include other relationships like `acted_in`, `produced`, `wrote`, etc., to capture more complex connections within the movie industry.
overall, this graph database schema provides a simple yet powerful representation of entities and relationships in the movie domain, allowing for querying and analysis of connections within the industry.
|===

.Input Parameters
[%autowidth, opts=header]
|===
| name | description | mandatory
| cypher | The question in the natural language | yes
| conf | An optional configuration map, please check the next section | no
|===

.Configuration map
[%autowidth, opts=header]
|===
| name | description | mandatory
| retries | The number of retries in case of API call failures | no, default `3`
| apiKey | OpenAI API key | in case `apoc.openai.key` is not defined
| model | The Open AI model | no, default `gpt-3.5-turbo`
| sample | The number of nodes to skip, e.g. a sample of 1000 will read every 1000th node. It's used as a parameter to `apoc.meta.data` procedure that computes the schema | no, default is a random number
|===


.Results
[%autowidth, opts=header]
|===
| name | description
| value | the description of the dataset
|===


== Create explanation of the subgraph from a set of queries

This procedure `apoc.ml.fromQueries` returns an explanation, in natural language, of the given set of queries.

It uses the `chat/completions` API which is https://platform.openai.com/docs/api-reference/chat/create[documented here^].

.Query call
[source,cypher]
----
CALL apoc.ml.fromQueries(['MATCH (n:Movie) RETURN n', 'MATCH (n:Person) RETURN n'],
{apiKey: <apiKey>})
YIELD value
RETURN *
----

.Example response
[source, bash]
----
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| value |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| "The database represents movies and people, like in a movie database or social network.
There are no defined relationships between nodes, allowing flexibility for future connections.
The Movie node includes properties like title, tagline, and release year." |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row
----

.Query call with path
[source,cypher]
----
CALL apoc.ml.fromQueries(['MATCH (n:Movie) RETURN n', 'MATCH p=(n:Movie)--() RETURN p'],
{apiKey: <apiKey>})
YIELD value
RETURN *
----

.Example response
[source, bash]
----
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| value |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| "models relationships in the movie industry, connecting :Person nodes to :Movie nodes.
It represents actors, directors, writers, producers, and reviewers connected to movies they are involved with.
Similar to a social network graph but specialized for the entertainment industry.
Each relationship type corresponds to common roles in movie production and reviewing.
Allows for querying and analyzing connections and collaborations within the movie business." |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row
----


.Input Parameters
[%autowidth, opts=header]
|===
| name | description
| queries | The list of queries
| conf | An optional configuration map, please check the next section
|===

.Configuration map
[%autowidth, opts=header]
|===
| name | description | mandatory
| apiKey | OpenAI API key | in case `apoc.openai.key` is not defined
| model | The Open AI model | no, default `gpt-3.5-turbo`
| sample | The number of nodes to skip, e.g. a sample of 1000 will read every 1000th node. It's used as a parameter to `apoc.meta.data` procedure that computes the schema | no, default is a random number
|===

.Results
[%autowidth, opts=header]
|===
| name | description
| value | the description of the dataset
|===

2 changes: 2 additions & 0 deletions docs/asciidoc/modules/ROOT/pages/ml/index.adoc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,3 +12,5 @@ This section includes:
* xref::ml/bedrock.adoc[]
* xref::ml/watsonai.adoc[]
* xref::ml/mixedbread.adoc[]
* xref::ml/genai.adoc[]
* xref::ml/rag.adoc[]
Loading
Loading