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""" |
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Create a pitch for this project. |
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PROMPT> python -m src.pitch.create_pitch |
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""" |
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import os |
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import json |
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import time |
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from math import ceil |
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from typing import List, Optional |
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from uuid import uuid4 |
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from dataclasses import dataclass |
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from pydantic import BaseModel, Field |
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from llama_index.core.llms.llm import LLM |
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from src.format_json_for_use_in_query import format_json_for_use_in_query |
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class ProjectPitch(BaseModel): |
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pitch: str = Field( |
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description="A compelling pitch for this project." |
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) |
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why_this_pitch_works: str = Field( |
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description="Explanation why this pitch works." |
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) |
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target_audience: str = Field( |
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description="Who this pitch is aimed at, such as investors, stakeholders, or the general public." |
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) |
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call_to_action: str = Field( |
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description="A clear next step for the audience to engage with the project." |
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) |
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risks_and_mitigation: str = Field( |
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description="Address potential challenges and demonstrate readiness to handle them." |
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) |
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metrics_for_success: str = Field( |
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description="Define how the success of the project will be measured beyond its goals." |
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) |
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stakeholder_benefits: str = Field( |
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description="Explicitly state what stakeholders gain from supporting or being involved in the project." |
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) |
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ethical_considerations: str = Field( |
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description="Build trust by showing a commitment to ethical practices." |
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) |
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collaboration_opportunities: str = Field( |
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description="Highlight ways other organizations or individuals can partner with the project." |
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) |
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long_term_vision: str = Field( |
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description="Show the broader impact and sustainability of the project." |
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) |
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QUERY_PREAMBLE = f""" |
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Craft a compelling pitch for this project that starts with an attention-grabbing hook, |
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presents its purpose clearly, and highlights the benefits or value it brings. Use a tone |
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that conveys enthusiasm and aligns with the goals and values of the intended audience, |
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emphasizing why this project matters and how it stands out. |
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""" |
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@dataclass |
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class CreatePitch: |
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query: str |
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response: dict |
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metadata: dict |
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@classmethod |
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def format_query(cls, plan_json: dict, wbs_level1_json: dict, wbs_level2_json: list) -> str: |
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""" |
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Format the query for creating project pitch. |
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""" |
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if not isinstance(plan_json, dict): |
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raise ValueError("Invalid plan_json.") |
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if not isinstance(wbs_level1_json, dict): |
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raise ValueError("Invalid wbs_level1_json.") |
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if not isinstance(wbs_level2_json, list): |
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raise ValueError("Invalid wbs_level2_json.") |
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query = f""" |
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The project plan: |
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{format_json_for_use_in_query(plan_json)} |
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WBS Level 1: |
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{format_json_for_use_in_query(wbs_level1_json)} |
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WBS Level 2: |
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{format_json_for_use_in_query(wbs_level2_json)} |
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""" |
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return query |
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@classmethod |
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def execute(cls, llm: LLM, query: str) -> 'CreatePitch': |
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""" |
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Invoke LLM to create a project pitch. |
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""" |
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if not isinstance(llm, LLM): |
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raise ValueError("Invalid LLM instance.") |
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if not isinstance(query, str): |
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raise ValueError("Invalid query.") |
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start_time = time.perf_counter() |
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sllm = llm.as_structured_llm(ProjectPitch) |
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response = sllm.complete(QUERY_PREAMBLE + query) |
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json_response = json.loads(response.text) |
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end_time = time.perf_counter() |
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duration = int(ceil(end_time - start_time)) |
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metadata = dict(llm.metadata) |
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metadata["llm_classname"] = llm.class_name() |
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metadata["duration"] = duration |
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result = CreatePitch( |
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query=query, |
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response=json_response, |
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metadata=metadata, |
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) |
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return result |
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def raw_response_dict(self, include_metadata=True, include_query=True) -> dict: |
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d = self.response.copy() |
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if include_metadata: |
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d['metadata'] = self.metadata |
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if include_query: |
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d['query'] = self.query |
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return d |
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if __name__ == "__main__": |
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from llama_index.llms.ollama import Ollama |
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basepath = os.path.join(os.path.dirname(__file__), 'test_data') |
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def load_json(relative_path: str) -> dict: |
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path = os.path.join(basepath, relative_path) |
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print(f"loading file: {path}") |
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with open(path, 'r', encoding='utf-8') as f: |
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the_json = json.load(f) |
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return the_json |
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plan_json = load_json('lunar_base-project_plan.json') |
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wbs_level1_json = load_json('lunar_base-wbs_level1.json') |
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wbs_level2_json = load_json('lunar_base-wbs_level2.json') |
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model_name = "llama3.1:latest" |
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llm = Ollama(model=model_name, request_timeout=120.0, temperature=0.5, is_function_calling_model=False) |
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query = CreatePitch.format_query(plan_json, wbs_level1_json, wbs_level2_json) |
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print(f"Query: {query}") |
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result = CreatePitch.execute(llm, query) |
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print("\nResponse:") |
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json_response = result.raw_response_dict(include_query=False) |
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print(json.dumps(json_response, indent=2)) |
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