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214 lines
6.3 KiB
Python
214 lines
6.3 KiB
Python
# flake8: noqa
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from langchain import PromptTemplate
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SONG_DATA_SOURCE = """\
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```json
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{
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"content": "Lyrics of a song",
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"attributes": {
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"artist": {
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"type": "string",
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"description": "Name of the song artist"
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},
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"length": {
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"type": "integer",
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"description": "Length of the song in seconds"
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},
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"genre": {
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"type": "string",
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"description": "The song genre, one of \"pop\", \"rock\" or \"rap\""
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}
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}
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}
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```\
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""".replace(
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"{", "{{"
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).replace(
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"}", "}}"
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)
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FULL_ANSWER = """\
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```json
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{{
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"query": "teenager love",
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"filter": "and(or(eq(\\"artist\\", \\"Taylor Swift\\"), eq(\\"artist\\", \\"Katy Perry\\")), \
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lt(\\"length\\", 180), eq(\\"genre\\", \\"pop\\"))"
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}}
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```\
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"""
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NO_FILTER_ANSWER = """\
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```json
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{{
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"query": "",
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"filter": "NO_FILTER"
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}}
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```\
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"""
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WITH_LIMIT_ANSWER = """\
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```json
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{{
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"query": "love",
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"filter": "NO_FILTER",
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"limit": 2
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}}
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```\
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"""
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DEFAULT_EXAMPLES = [
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{
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"i": 1,
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"data_source": SONG_DATA_SOURCE,
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"user_query": "What are songs by Taylor Swift or Katy Perry about teenage romance under 3 minutes long in the dance pop genre",
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"structured_request": FULL_ANSWER,
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},
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{
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"i": 2,
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"data_source": SONG_DATA_SOURCE,
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"user_query": "What are songs that were not published on Spotify",
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"structured_request": NO_FILTER_ANSWER,
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},
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]
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EXAMPLES_WITH_LIMIT = [
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{
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"i": 1,
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"data_source": SONG_DATA_SOURCE,
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"user_query": "What are songs by Taylor Swift or Katy Perry about teenage romance under 3 minutes long in the dance pop genre",
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"structured_request": FULL_ANSWER,
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},
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{
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"i": 2,
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"data_source": SONG_DATA_SOURCE,
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"user_query": "What are songs that were not published on Spotify",
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"structured_request": NO_FILTER_ANSWER,
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},
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{
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"i": 3,
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"data_source": SONG_DATA_SOURCE,
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"user_query": "What are three songs about love",
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"structured_request": WITH_LIMIT_ANSWER,
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},
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]
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EXAMPLE_PROMPT_TEMPLATE = """\
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<< Example {i}. >>
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Data Source:
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{data_source}
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User Query:
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{user_query}
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Structured Request:
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{structured_request}
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"""
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EXAMPLE_PROMPT = PromptTemplate(
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input_variables=["i", "data_source", "user_query", "structured_request"],
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template=EXAMPLE_PROMPT_TEMPLATE,
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)
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DEFAULT_SCHEMA = """\
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<< Structured Request Schema >>
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When responding use a markdown code snippet with a JSON object formatted in the \
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following schema:
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```json
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{{{{
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"query": string \\ text string to compare to document contents
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"filter": string \\ logical condition statement for filtering documents
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}}}}
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```
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The query string should contain only text that is expected to match the contents of \
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documents. Any conditions in the filter should not be mentioned in the query as well.
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A logical condition statement is composed of one or more comparison and logical \
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operation statements.
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A comparison statement takes the form: `comp(attr, val)`:
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- `comp` ({allowed_comparators}): comparator
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- `attr` (string): name of attribute to apply the comparison to
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- `val` (string): is the comparison value
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A logical operation statement takes the form `op(statement1, statement2, ...)`:
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- `op` ({allowed_operators}): logical operator
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- `statement1`, `statement2`, ... (comparison statements or logical operation \
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statements): one or more statements to apply the operation to
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Make sure that you only use the comparators and logical operators listed above and \
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no others.
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Make sure that filters only refer to attributes that exist in the data source.
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Make sure that filters only use the attributed names with its function names if there are functions applied on them.
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Make sure that filters only use format `YYYY-MM-DD` when handling timestamp data typed values.
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Make sure that filters take into account the descriptions of attributes and only make \
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comparisons that are feasible given the type of data being stored.
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Make sure that filters are only used as needed. If there are no filters that should be \
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applied return "NO_FILTER" for the filter value.\
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"""
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SCHEMA_WITH_LIMIT = """\
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<< Structured Request Schema >>
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When responding use a markdown code snippet with a JSON object formatted in the \
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following schema:
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```json
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{{{{
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"query": string \\ text string to compare to document contents
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"filter": string \\ logical condition statement for filtering documents
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"limit": int \\ the number of documents to retrieve
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}}}}
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```
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The query string should contain only text that is expected to match the contents of \
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documents. Any conditions in the filter should not be mentioned in the query as well.
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A logical condition statement is composed of one or more comparison and logical \
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operation statements.
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|
A comparison statement takes the form: `comp(attr, val)`:
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- `comp` ({allowed_comparators}): comparator
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- `attr` (string): name of attribute to apply the comparison to
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- `val` (string): is the comparison value
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A logical operation statement takes the form `op(statement1, statement2, ...)`:
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- `op` ({allowed_operators}): logical operator
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- `statement1`, `statement2`, ... (comparison statements or logical operation \
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statements): one or more statements to apply the operation to
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Make sure that you only use the comparators and logical operators listed above and \
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no others.
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Make sure that filters only refer to attributes that exist in the data source.
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Make sure that filters only use the attributed names with its function names if there are functions applied on them.
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Make sure that filters only use format `YYYY-MM-DD` when handling timestamp data typed values.
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Make sure that filters take into account the descriptions of attributes and only make \
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comparisons that are feasible given the type of data being stored.
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Make sure that filters are only used as needed. If there are no filters that should be \
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applied return "NO_FILTER" for the filter value.
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Make sure the `limit` is always an int value. It is an optional parameter so leave it blank if it is does not make sense.
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"""
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DEFAULT_PREFIX = """\
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Your goal is to structure the user's query to match the request schema provided below.
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{schema}\
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"""
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DEFAULT_SUFFIX = """\
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<< Example {i}. >>
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Data Source:
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```json
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{{{{
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"content": "{content}",
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"attributes": {attributes}
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}}}}
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```
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User Query:
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{{query}}
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Structured Request:
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"""
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