567a8ab74a
* implement so * bug fixes and typing * inject schema for non-openai clients * correct datetime format * remove List keyword * Refactor node_operations.py to use updated prompt_library functions * update example
114 lines
3.2 KiB
Python
114 lines
3.2 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 pydantic import BaseModel, Field
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from .models import Message, PromptFunction, PromptVersion
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class Summary(BaseModel):
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summary: str = Field(
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..., description='Summary containing the important information from both summaries'
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)
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class SummaryDescription(BaseModel):
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description: str = Field(..., description='One sentence description of the provided summary')
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class Prompt(Protocol):
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summarize_pair: PromptVersion
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summarize_context: PromptVersion
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summary_description: PromptVersion
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class Versions(TypedDict):
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summarize_pair: PromptFunction
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summarize_context: PromptFunction
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summary_description: PromptFunction
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def summarize_pair(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 combines summaries.',
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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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Synthesize the information from the following two summaries into a single succinct summary.
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Summaries:
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{json.dumps(context['node_summaries'], indent=2)}
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""",
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),
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]
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def summarize_context(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 combines summaries with new conversation context.',
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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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<MESSAGES>
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{json.dumps(context['previous_episodes'], indent=2)}
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{json.dumps(context['episode_content'], indent=2)}
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</MESSAGES>
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Given the above MESSAGES and the following ENTITY name, create a summary for the ENTITY. Your summary must only use
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information from the provided MESSAGES. Your summary should also only contain information relevant to the
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provided ENTITY.
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<ENTITY>
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{context['node_name']}
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</ENTITY>
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""",
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),
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]
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def summary_description(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 describes provided contents in a single sentence.',
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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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Create a short one sentence description of the summary that explains what kind of information is summarized.
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Summary:
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{json.dumps(context['summary'], indent=2)}
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""",
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),
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]
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versions: Versions = {
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'summarize_pair': summarize_pair,
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'summarize_context': summarize_context,
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'summary_description': summary_description,
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}
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