Updated database explanations

This commit is contained in:
NunoSempere 2021-04-14 18:49:05 +02:00
parent 025c983374
commit f092c800ab
4 changed files with 53 additions and 45 deletions

2
.gitignore vendored
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possiblenewsources.md possiblenewsources.md
herokulocation.md herokulocation.md
**/manualDownloadFromMongo.js

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This is a set of libraries and a command line interface that fetches probabilities/forecasts from prediction markets and forecasting platforms. This is a set of libraries and a command line interface that fetches probabilities/forecasts from prediction markets and forecasting platforms.
These forecasts are then used to power a search engine for probabilities, which can be found [here](https://metaforecast.org/) (try searching "Trump", "China" or "Semiconductors") (source code [here](https://github.com/QURIresearch/metaforecast-website-nextjs)). A json endpoint can be found [here](https://metaforecast.org/data/metaforecasts.json). These forecasts are then used to power a search engine for probabilities, which can be found [here](https://metaforecast.org/) (try searching "Trump", "China" or "Semiconductors") (source code [here](https://github.com/QURIresearch/metaforecast-website-nextjs)). I also provide a datatabase, which can be accessed with a script similar to [this one](https://github.com/QURIresearch/metaforecasts/blob/master/src/utils/manualDownloadFromMongo.js).
I also created a search engine using Elicit's IDE, which uses GPT-3 to deliver vastly superior semantic search (as opposed to fuzzy word matching). If you have access to the Elicit IDE, you can use the action "Search Metaforecast database". I also created a search engine using Elicit's IDE, which uses GPT-3 to deliver vastly superior semantic search (as opposed to fuzzy word matching). If you have access to the Elicit IDE, you can use the action "Search Metaforecast database". However, I'm not currently updating it regularly.
![](./metaforecasts.png) ![](./metaforecasts.png)
@ -15,16 +15,14 @@ I also created a search engine using Elicit's IDE, which uses GPT-3 to deliver v
``git clone https://github.com/QURIresearch/metaforecasts`` ``git clone https://github.com/QURIresearch/metaforecasts``
### 2. Enter your own process.env variables ### 2. Enter your own process.env variables
The following environment variables are currently needed to run the `master` branch: The following variables are currently needed to run the `master` branch:
- `MONGODB_URL`, a string in the format `"mongodb+srv://<username>:<password>@<mongodburl>/?retryWrites=true&w=majority&useNewUrlParser=true&useUnifiedTopology=true"` - `MONGODB_URL`, a string in the format `"mongodb+srv://<username>:<password>@<mongodburl>/?retryWrites=true&w=majority&useNewUrlParser=true&useUnifiedTopology=true"`
- `REBUIDNETLIFYHOOKURL`, a string in the format `"https://api.netlify.com/build_hooks/someprivatestring"` - `REBUIDNETLIFYHOOKURL`, a string in the format `"https://api.netlify.com/build_hooks/someprivatestring"`
- `CSETFORETELL_COOKIE` - `CSETFORETELL_COOKIE`
- `GOODJUDGMENTOPENCOOKIE` - `GOODJUDGMENTOPENCOOKIE`
- `HYPERMINDCOOKIE` - `HYPERMINDCOOKIE`
The cookie formats can be found in `src/input/privatekeys_example.json`; these session cookies are necessary to query CSET-foretell, Good Judgment Open and Hypermind. You can get these cookies by creating an account in said platforms and then making and inspecting a request (e.g., by making a prediction, or browsing questions). After doing this, you should create the environment variables. They can either be stored as process variables (e.g., something that can be accessed as `process.env.<variable name>`), or as text in `src/input/privatekeys.json`, in the same format as `src/input/privatekeys_example.json`. These session cookies are necessary to query CSET-foretell, Good Judgment Open and Hypermind, and to access the MongoDB database I'm using to save data and history. You can get these cookies by creating an account in said platforms and then making and inspecting a request (e.g., by making a prediction, or browsing questions). After doing this, you should create the environment variables.
Alternatively, for fewer complications, have a look at the `commandlineinterface` branch, which instead of requiring environment variables only requires a `src/privatekeys.json`, in the same format as its `src/privatekeys_example.json`. Its disadvantages are that the command line tool in the `commandlineinterface` is more difficult to integrate with other services.
### 3. Actually run ### 3. Actually run

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import fs from "fs"
import { mongoReadWithReadCredentials } from "./mongo-wrapper.js"
let main = async () => {
let json = await mongoReadWithReadCredentials("metaforecasts")
let string = JSON.stringify(json, null, 2)
fs.writeFileSync('metaforecasts.json', string);
}
main()

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/* Imports */ /* Imports */
import fs from "fs" import fs from "fs"
import { mongoReadWithReadCredentials } from "../mongo-wrapper.js"
/* Definitions */ /* Definitions */
let locationData = "./data/" let locationData = "./data/"
/* Body */ /* Body */
let rawdata = fs.readFileSync("./data/merged-questions.json") // run from topmost folder, not from src // let rawdata = fs.readFileSync("./data/merged-questions.json") // run from topmost folder, not from src
let data = JSON.parse(rawdata) async function main(){
let data = await mongoReadWithReadCredentials("metaforecasts") //JSON.parse(rawdata)
let processDescription = (description) => { let processDescription = (description) => {
if(description == null || description == undefined || description == ""){ if(description == null || description == undefined || description == ""){
return "" return ""
@ -29,20 +30,21 @@ let processDescription = (description) => {
let results = [] let results = []
for(let datum of data){ for(let datum of data){
// do something // do something
let description = processDescription(datum["Description"]) let description = processDescription(datum["description"])
let forecasts = datum["# Forecasts"] || "unknown" let forecasts = datum["qualityindicators"] ? datum["qualityindicators"].numforecasts : "unknown"
results.push("Title: "+datum["Title"]) let stars = datum["qualityindicators"] ? datum["qualityindicators"].stars : 2
results.push("URL: "+datum["URL"]) results.push("Title: "+datum["title"])
results.push("Platform: "+datum["Platform"]) results.push("URL: "+datum["url"])
results.push("Binary question?: "+datum["Binary question?"]) results.push("Platform: "+datum["platform"])
results.push("Percentage: "+datum["Percentage"])
results.push("Description: "+description) results.push("Description: "+description)
results.push("# Forecasts: "+ forecasts) results.push("Number of forecasts: "+ forecasts)
results.push("Stars: "+datum["Stars"]) results.push("Stars: "+forecasts)
results.push("\n") results.push("\n")
} }
let string = results.join("\n") let string = results.join("\n")
string = string.replaceAll("\n\n", "\n") string = string.replaceAll("\n\n", "\n")
fs.writeFileSync("./data/elicit-output.txt", string) fs.writeFileSync("elicit-output.txt", string)
}
main()