* WIP * updates * use uuid for node dedupe * pret-testing * parallelized node resolution * working add_episode * revert to 4o * format * mypy update * update types
199 lines
7.1 KiB
Python
199 lines
7.1 KiB
Python
"""
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Copyright 2024, Zep Software, Inc.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import json
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from typing import Any, Protocol, TypedDict
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from .models import Message, PromptFunction, PromptVersion
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class Prompt(Protocol):
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v1: PromptVersion
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v2: PromptVersion
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v3: PromptVersion
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node_list: PromptVersion
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class Versions(TypedDict):
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v1: PromptFunction
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v2: PromptFunction
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v3: PromptFunction
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node_list: PromptFunction
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def v1(context: dict[str, Any]) -> list[Message]:
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return [
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Message(
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role='system',
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content='You are a helpful assistant that de-duplicates nodes from node lists.',
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),
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Message(
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role='user',
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content=f"""
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Given the following context, deduplicate nodes from a list of new nodes given a list of existing nodes:
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Existing Nodes:
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{json.dumps(context['existing_nodes'], indent=2)}
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New Nodes:
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{json.dumps(context['extracted_nodes'], indent=2)}
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Task:
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1. start with the list of nodes from New Nodes
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2. If any node in New Nodes is a duplicate of a node in Existing Nodes, replace the new node with the existing
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node in the list
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3. when deduplicating nodes, synthesize their summaries into a short new summary that contains the relevant information
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of the summaries of the new and existing nodes
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4. Respond with the resulting list of nodes
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Guidelines:
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1. Use both the name and summary of nodes to determine if they are duplicates,
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duplicate nodes may have different names
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Respond with a JSON object in the following format:
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{{
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"new_nodes": [
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{{
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"name": "Unique identifier for the node",
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"summary": "Brief summary of the node's role or significance"
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}}
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]
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}}
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""",
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),
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]
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def v2(context: dict[str, Any]) -> list[Message]:
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return [
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Message(
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role='system',
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content='You are a helpful assistant that de-duplicates nodes from node lists.',
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),
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Message(
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role='user',
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content=f"""
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Given the following context, deduplicate nodes from a list of new nodes given a list of existing nodes:
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Existing Nodes:
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{json.dumps(context['existing_nodes'], indent=2)}
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New Nodes:
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{json.dumps(context['extracted_nodes'], indent=2)}
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Important:
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If a node in the new nodes is describing the same entity as a node in the existing nodes, mark it as a duplicate!!!
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Task:
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If any node in New Nodes is a duplicate of a node in Existing Nodes, add their uuids to the output list
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When finding duplicates nodes, synthesize their summaries into a short new summary that contains the
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relevant information of the summaries of the new and existing nodes.
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Guidelines:
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1. Use both the name and summary of nodes to determine if they are duplicates,
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duplicate nodes may have different names
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2. In the output, uuid should always be the uuid of the New Node that is a duplicate. duplicate_of should be
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the uuid of the Existing Node.
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Respond with a JSON object in the following format:
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{{
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"duplicates": [
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{{
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"uuid": "uuid of the new node like 5d643020624c42fa9de13f97b1b3fa39",
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"duplicate_of": "uuid of the existing node",
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"summary": "Brief summary of the node's role or significance. Takes information from the new and existing nodes"
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}}
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]
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}}
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""",
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),
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]
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def v3(context: dict[str, Any]) -> list[Message]:
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return [
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Message(
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role='system',
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content='You are a helpful assistant that de-duplicates nodes from node lists.',
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),
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Message(
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role='user',
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content=f"""
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Given the following context, determine whether the New Node represents any of the entities in the list of Existing Nodes.
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Existing Nodes:
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{json.dumps(context['existing_nodes'], indent=2)}
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New Node:
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{json.dumps(context['extracted_nodes'], indent=2)}
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Task:
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1. If the New Node represents the same entity as any node in Existing Nodes, return 'is_duplicate: true' in the
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response. Otherwise, return 'is_duplicate: false'
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2. If is_duplicate is true, also return the uuid of the existing node in the response
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3. If is_duplicate is true, return a summary that synthesizes the information in the New Node summary and the
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summary of the Existing Node it is a duplicate of.
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Guidelines:
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1. Use both the name and summary of nodes to determine if the entities are duplicates,
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duplicate nodes may have different names
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Respond with a JSON object in the following format:
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{{
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"is_duplicate": true or false,
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"uuid": "uuid of the existing node like 5d643020624c42fa9de13f97b1b3fa39 or null",
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"summary": "Brief summary of the node's role or significance. Takes information from the new and existing node"
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}}
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""",
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),
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]
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def node_list(context: dict[str, Any]) -> list[Message]:
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return [
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Message(
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role='system',
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content='You are a helpful assistant that de-duplicates nodes from node lists.',
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),
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Message(
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role='user',
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content=f"""
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Given the following context, deduplicate a list of nodes:
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Nodes:
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{json.dumps(context['nodes'], indent=2)}
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Task:
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1. Group nodes together such that all duplicate nodes are in the same list of uuids
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2. All duplicate uuids should be grouped together in the same list
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3. Also return a new summary that synthesizes the summary into a new short summary
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Guidelines:
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1. Each uuid from the list of nodes should appear EXACTLY once in your response
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2. If a node has no duplicates, it should appear in the response in a list of only one uuid
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Respond with a JSON object in the following format:
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{{
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"nodes": [
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{{
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"uuids": ["5d643020624c42fa9de13f97b1b3fa39", "node that is a duplicate of 5d643020624c42fa9de13f97b1b3fa39"],
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"summary": "Brief summary of the node summaries that appear in the list of names."
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}}
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]
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}}
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""",
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),
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]
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versions: Versions = {'v1': v1, 'v2': v2, 'v3': v3, 'node_list': node_list}
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