Merge pull request #54 from polywrap/rename-evo-researcher

chore: rename evo_researcher to evo_prophet

evo_researcher/app.py → evo_prophet/app.py

@@ -1,12 +1,12 @@
 import os
 from typing import cast
-from evo_researcher.benchmark.agents import _make_prediction
-from evo_researcher.functions.evaluate_question import is_predictable as evaluate_if_predictable
-from evo_researcher.functions.research import research
+from evo_prophet.benchmark.agents import _make_prediction
+from evo_prophet.functions.evaluate_question import is_predictable as evaluate_if_predictable
+from evo_prophet.functions.research import research
 from prediction_market_agent_tooling.benchmark.utils import (
     OutcomePrediction
 )
-from evo_researcher.utils.logger import BaseLogger
+from evo_prophet.utils.logger import BaseLogger
 from prediction_market_agent_tooling.tools.utils import secret_str_from_env
 from pydantic.types import SecretStr
 import streamlit as st
@@ -31,7 +31,7 @@ def log(self, msg: str) -> None:
         st.stop()
 
 st.set_page_config(layout="wide")
-st.title("Evo Predict")
+st.title("Evo Prophet")
 
 with st.form("question_form", clear_on_submit=True):
     question = st.text_input(

evo_researcher/autonolas/research.py → evo_prophet/autonolas/research.py

@@ -27,10 +27,10 @@
 from langchain_openai import OpenAIEmbeddings
 
 from dateutil import parser
-from evo_researcher.functions.utils import check_not_none
+from evo_prophet.functions.utils import check_not_none
 from prediction_market_agent_tooling.tools.utils import secret_str_from_env
-from evo_researcher.functions.cache import persistent_inmemory_cache
-from evo_researcher.functions.parallelism import par_map
+from evo_prophet.functions.cache import persistent_inmemory_cache
+from evo_prophet.functions.parallelism import par_map
 from pydantic.types import SecretStr
 from prediction_market_agent_tooling.gtypes import secretstr_to_v1_secretstr
 

evo_researcher/benchmark/agents.py → evo_prophet/benchmark/agents.py

@@ -9,23 +9,23 @@
     Prediction,
 )
 from datetime import datetime
-from evo_researcher.autonolas.research import EmbeddingModel
-from evo_researcher.autonolas.research import make_prediction, get_urls_from_queries
-from evo_researcher.autonolas.research import research as research_autonolas
-from evo_researcher.functions.evaluate_question import is_predictable
-from evo_researcher.functions.rephrase_question import rephrase_question
-from evo_researcher.functions.research import research as research_evo
-from evo_researcher.functions.search import search
-from evo_researcher.functions.utils import url_is_older_than
-from evo_researcher.models.WebSearchResult import WebSearchResult
+from evo_prophet.autonolas.research import EmbeddingModel
+from evo_prophet.autonolas.research import make_prediction, get_urls_from_queries
+from evo_prophet.autonolas.research import research as research_autonolas
+from evo_prophet.functions.evaluate_question import is_predictable
+from evo_prophet.functions.rephrase_question import rephrase_question
+from evo_prophet.functions.research import research as research_evo
+from evo_prophet.functions.search import search
+from evo_prophet.functions.utils import url_is_older_than
+from evo_prophet.models.WebSearchResult import WebSearchResult
 from unittest.mock import patch
-from evo_researcher.functions.search import search
+from evo_prophet.functions.search import search
 from prediction_market_agent_tooling.benchmark.utils import (
     OutcomePrediction,
     Prediction,
 )
 from pydantic.types import SecretStr
-from evo_researcher.autonolas.research import Prediction as LLMCompletionPredictionDict
+from evo_prophet.autonolas.research import Prediction as LLMCompletionPredictionDict
 
 def _make_prediction(
     market_question: str,
@@ -146,7 +146,7 @@ def side_effect(*args: t.Any, **kwargs: t.Any) -> list[str]:
             ]
             return results_filtered
 
-        with patch('evo_researcher.autonolas.research.get_urls_from_queries', side_effect=side_effect, autospec=True):
+        with patch('evo_prophet.autonolas.research.get_urls_from_queries', side_effect=side_effect, autospec=True):
             return self.predict(market_question)
 
 
@@ -206,7 +206,7 @@ def side_effect(*args: t.Any, **kwargs: t.Any) -> list[tuple[str, WebSearchResul
             ]
             return results_filtered
 
-        with patch('evo_researcher.functions.research.search', side_effect=side_effect, autospec=True):
+        with patch('evo_prophet.functions.research.search', side_effect=side_effect, autospec=True):
             return self.predict(market_question)
 
 class RephrasingOlasAgent(OlasAgent):

evo_researcher/deployment/models.py → evo_prophet/deployment/models.py

@@ -1,7 +1,7 @@
 import pytz
 from decimal import Decimal
 from datetime import datetime, timedelta
-from evo_researcher.benchmark.agents import EvoAgent, OlasAgent, EmbeddingModel
+from evo_prophet.benchmark.agents import EvoAgent, OlasAgent, EmbeddingModel
 from prediction_market_agent_tooling.benchmark.agents import AbstractBenchmarkedAgent
 from prediction_market_agent_tooling.markets.agent_market import AgentMarket
 from prediction_market_agent_tooling.markets.manifold.manifold import ManifoldAgentMarket

evo_researcher/functions/create_embeddings_from_results.py → evo_prophet/functions/create_embeddings_from_results.py

@@ -9,7 +9,7 @@
 import os
 from langchain_openai import OpenAIEmbeddings
 from langchain.vectorstores.chroma import Chroma
-from evo_researcher.models.WebScrapeResult import WebScrapeResult
+from evo_prophet.models.WebScrapeResult import WebScrapeResult
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from pydantic.types import SecretStr
 from prediction_market_agent_tooling.tools.utils import secret_str_from_env

evo_researcher/functions/evaluate_question.py → evo_prophet/functions/evaluate_question.py

@@ -1,9 +1,9 @@
 import json
 import os
-from evo_researcher.autonolas.research import clean_completion_json
+from evo_prophet.autonolas.research import clean_completion_json
 from langchain_openai import ChatOpenAI
 from langchain.prompts import ChatPromptTemplate
-from evo_researcher.functions.cache import persistent_inmemory_cache
+from evo_prophet.functions.cache import persistent_inmemory_cache
 from pydantic.types import SecretStr
 from prediction_market_agent_tooling.tools.utils import secret_str_from_env
 from prediction_market_agent_tooling.gtypes import secretstr_to_v1_secretstr

evo_researcher/functions/prepare_report.py → evo_prophet/functions/prepare_report.py

@@ -4,8 +4,8 @@
 from langchain_openai import ChatOpenAI
 from langchain.prompts import ChatPromptTemplate
 from langchain.schema.output_parser import StrOutputParser
-from evo_researcher.functions.cache import persistent_inmemory_cache
-from evo_researcher.functions.utils import trim_to_n_tokens
+from evo_prophet.functions.cache import persistent_inmemory_cache
+from evo_prophet.functions.utils import trim_to_n_tokens
 from prediction_market_agent_tooling.tools.utils import secret_str_from_env
 from prediction_market_agent_tooling.gtypes import secretstr_to_v1_secretstr
 from pydantic.types import SecretStr

evo_researcher/functions/rephrase_question.py → evo_prophet/functions/rephrase_question.py

@@ -2,7 +2,7 @@
 import tiktoken
 from pydantic import BaseModel
 from langchain_openai import ChatOpenAI
-from evo_researcher.autonolas.research import clean_completion_json
+from evo_prophet.autonolas.research import clean_completion_json
 from langchain.prompts import ChatPromptTemplate
 
 

evo_researcher/functions/research.py → evo_prophet/functions/research.py

@@ -1,13 +1,13 @@
-from evo_researcher.utils.logger import BaseLogger
+from evo_prophet.utils.logger import BaseLogger
 
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from evo_researcher.functions.create_embeddings_from_results import create_embeddings_from_results
-from evo_researcher.functions.generate_subqueries import generate_subqueries
-from evo_researcher.functions.prepare_report import prepare_report, prepare_summary
-from evo_researcher.models.WebScrapeResult import WebScrapeResult
-from evo_researcher.functions.rerank_subqueries import rerank_subqueries
-from evo_researcher.functions.scrape_results import scrape_results
-from evo_researcher.functions.search import search
+from evo_prophet.functions.create_embeddings_from_results import create_embeddings_from_results
+from evo_prophet.functions.generate_subqueries import generate_subqueries
+from evo_prophet.functions.prepare_report import prepare_report, prepare_summary
+from evo_prophet.models.WebScrapeResult import WebScrapeResult
+from evo_prophet.functions.rerank_subqueries import rerank_subqueries
+from evo_prophet.functions.scrape_results import scrape_results
+from evo_prophet.functions.search import search
 from pydantic.types import SecretStr
 
 def research(

evo_researcher/functions/scrape_results.py → evo_prophet/functions/scrape_results.py

@@ -1,7 +1,7 @@
-from evo_researcher.models.WebScrapeResult import WebScrapeResult
-from evo_researcher.functions.web_search import WebSearchResult
-from evo_researcher.functions.web_scrape import web_scrape
-from evo_researcher.functions.parallelism import par_map
+from evo_prophet.models.WebScrapeResult import WebScrapeResult
+from evo_prophet.functions.web_search import WebSearchResult
+from evo_prophet.functions.web_scrape import web_scrape
+from evo_prophet.functions.parallelism import par_map
 
 
 def scrape_results(results: list[WebSearchResult]) -> list[WebScrapeResult]:

evo_researcher/functions/search.py → evo_prophet/functions/search.py

@@ -1,6 +1,6 @@
 import requests
 import typing as t
-from evo_researcher.functions.web_search import WebSearchResult, web_search
+from evo_prophet.functions.web_search import WebSearchResult, web_search
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from pydantic.types import SecretStr
 

evo_researcher/functions/utils.py → evo_prophet/functions/utils.py

@@ -3,7 +3,7 @@
 from datetime import datetime
 from typing import NoReturn, Type, TypeVar, Optional
 from googleapiclient.discovery import build
-from evo_researcher.functions.cache import persistent_inmemory_cache
+from evo_prophet.functions.cache import persistent_inmemory_cache
 
 T = TypeVar("T")
 

evo_researcher/functions/web_scrape.py → evo_prophet/functions/web_scrape.py

@@ -4,7 +4,7 @@
 from bs4 import BeautifulSoup
 from requests import Response
 import tenacity
-from evo_researcher.functions.cache import persistent_inmemory_cache
+from evo_prophet.functions.cache import persistent_inmemory_cache
 
 
 @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_fixed(1), reraise=True)

evo_researcher/functions/web_search.py → evo_prophet/functions/web_search.py

@@ -4,8 +4,8 @@
 from pydantic.types import SecretStr
 
 from prediction_market_agent_tooling.tools.utils import secret_str_from_env
-from evo_researcher.models.WebSearchResult import WebSearchResult
-from evo_researcher.functions.cache import persistent_inmemory_cache
+from evo_prophet.models.WebSearchResult import WebSearchResult
+from evo_prophet.functions.cache import persistent_inmemory_cache
 
 
 @tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_fixed(1), reraise=True)

evo_researcher/main.py → evo_prophet/main.py

@@ -1,9 +1,9 @@
 import click
 import time
 from dotenv import load_dotenv
-from evo_researcher.benchmark.agents import _make_prediction
+from evo_prophet.benchmark.agents import _make_prediction
 from langchain_community.callbacks import get_openai_callback
-from evo_researcher.functions.research import research as evo_research
+from evo_prophet.functions.research import research as evo_research
 
 load_dotenv()
 

mypy.ini

@@ -1,6 +1,6 @@
 [mypy]
 python_version = 3.10
-files = evo_researcher/, scripts/, tests/
+files = evo_prophet/, scripts/, tests/
 plugins = pydantic.mypy
 warn_redundant_casts = True
 warn_unused_ignores = True

pyproject.toml

@@ -1,5 +1,5 @@
 [tool.poetry]
-name = "evo_researcher"
+name = "evo_prophet"
 version = "0.1.10"
 description = ""
 authors = ["Nestor Amesty <[email protected]>"]
@@ -38,8 +38,8 @@ langchain-community = "^0.0.21"
 mypy = "^1.8.0"
 
 [tool.poetry.scripts]
-research= "evo_researcher.main:research"
-predict= "evo_researcher.main:predict"
+research= "evo_prophet.main:research"
+predict= "evo_prophet.main:predict"
 
 [build-system]
 requires = ["poetry-core"]

scripts/agent_app.py

@@ -9,7 +9,7 @@
 from enum import Enum 
 from prediction_market_agent_tooling.benchmark.utils import get_markets, MarketSource
 from prediction_market_agent_tooling.benchmark.agents import AbstractBenchmarkedAgent
-from evo_researcher.benchmark.agents import AGENTS
+from evo_prophet.benchmark.agents import AGENTS
 
 SENTINTEL = object()
 

scripts/benchmark.py

@@ -5,9 +5,9 @@
 from prediction_market_agent_tooling.benchmark.benchmark import Benchmarker
 from prediction_market_agent_tooling.benchmark.utils import MarketSource, get_markets, MarketFilter, MarketSort
 
-from evo_researcher.autonolas.research import EmbeddingModel
-from evo_researcher.benchmark.agents import EvoAgent, OlasAgent, QuestionOnlyAgent
-from evo_researcher.functions.cache import ENABLE_CACHE
+from evo_prophet.autonolas.research import EmbeddingModel
+from evo_prophet.benchmark.agents import EvoAgent, OlasAgent, QuestionOnlyAgent
+from evo_prophet.functions.cache import ENABLE_CACHE
 
 
 def main(

scripts/compare_manual_scrap_vs_tavily_raw_content.py

@@ -1,7 +1,7 @@
 import streamlit as st
 from dotenv import load_dotenv
-from evo_researcher.functions.web_search import web_search
-from evo_researcher.functions.scrape_results import scrape_results
+from evo_prophet.functions.web_search import web_search
+from evo_prophet.functions.scrape_results import scrape_results
 
 load_dotenv()
 st.set_page_config(layout="wide")

scripts/compare_search_results.py

@@ -7,8 +7,8 @@
 from urllib.parse import urlparse
 from collections import defaultdict
 from prediction_market_agent_tooling.benchmark.utils import get_markets, MarketSource
-from evo_researcher.functions.web_search import web_search
-from evo_researcher.autonolas.research import safe_get_urls_from_query
+from evo_prophet.functions.web_search import web_search
+from evo_prophet.autonolas.research import safe_get_urls_from_query
 
 ENGINES: dict[str, t.Callable[[str, int], list[str]]] = {
     "tavily": lambda q, limit: [x.url for x in web_search(q, max_results=limit)],

scripts/deploy.py

@@ -4,7 +4,7 @@
 from git import Repo
 from datetime import datetime
 from prediction_market_agent_tooling.markets.markets import MarketType
-from evo_researcher.deployment.models import DeployableAgentER, DeployableAgentER_EvoGPT3, DeployableAgentER_OlasEmbeddingOA
+from evo_prophet.deployment.models import DeployableAgentER, DeployableAgentER_EvoGPT3, DeployableAgentER_OlasEmbeddingOA
 from prediction_market_agent_tooling.config import APIKeys
 from prediction_market_agent_tooling.gtypes import private_key_type, DatetimeWithTimezone
 from prediction_market_agent_tooling.tools.web3_utils import verify_address
@@ -40,7 +40,7 @@ def deploy(
     chosen_agent_class: t.Type[DeployableAgentER] = [agent for agent in DEPLOYABLE_AGENTS if agent.__name__ == deployable_agent_name][0]
 
     chosen_agent_class().deploy_gcp(
-        repository=f"git+https://github.com/polywrap/evo.researcher.git@{Repo('.').active_branch.name}",
+        repository=f"git+https://github.com/polywrap/evo.prophet.git@{Repo('.').active_branch.name}",
         market_type=market_type,
         api_keys=APIKeys(
             BET_FROM_ADDRESS=verify_address(bet_from_address),

tests/test_benchmark.py

@@ -1,8 +1,8 @@
 import json
 
 import prediction_market_agent_tooling.benchmark.benchmark as bm
-from evo_researcher.autonolas.research import clean_completion_json
-from evo_researcher.benchmark.agents import completion_prediction_json_to_pydantic_model
+from evo_prophet.autonolas.research import clean_completion_json
+from evo_prophet.benchmark.agents import completion_prediction_json_to_pydantic_model
 
 
 def test_parse_result_str_to_json() -> None:

tests/test_evaluate_question.py

@@ -1,5 +1,5 @@
 import pytest
-from evo_researcher.functions.evaluate_question import is_predictable
+from evo_prophet.functions.evaluate_question import is_predictable
 
 
 @pytest.mark.parametrize("question, answerable", [