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| Author | SHA1 | Date | |
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| 3286df6450 |
@@ -7,11 +7,11 @@ export const triggerEventSetup: GraphNode<typeof MessagesState> = async (state)
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let nc = state?.messages?.at(-1)?.content ?? "" //keep a copy of normalized trigger event. Again two things, womp womp
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//Now give in-context examples. hopwfully we can self-teach?
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let similarityResults = await rankExampleTriggerEvents(state.disinformationTitle)
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// let similarityResults = await rankExampleTriggerEvents(state.disinformationTitle)
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let messages : BaseMessage[] = similarityResults.map((item) => {
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return new AIMessage(`- Event: ${item.rawtext} \n\n - Claims and given scores: ${item.cleantext}`)
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})
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// let messages : BaseMessage[] = similarityResults.map((item) => {
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// return new AIMessage(`- Event: ${item.rawtext} \n\n - Claims and given scores: ${item.cleantext}`)
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// })
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return { messages: messages, disinformationTitle: state.disinformationTitle, normalizedClaim: nc };
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return { disinformationTitle: state.disinformationTitle, normalizedClaim: nc };
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};
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@@ -3,9 +3,10 @@ Once the information has been created as below, a dataset can be created to feed
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There is a false disinformation claim circulating:
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###NTITLE###
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Produce up-to 5 specific events that happened that have led to the spread of this disinformation.
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Produce up-to 5 specific "trigger events" that happened that could have led to the spread of this disinformation.
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Remember the time frame of the disinformation campaign: ###CDATE###
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Include no information or events that would not have been available at the time.
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Produce no more text other than the json.
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@@ -16,5 +17,11 @@ Include a url to a source for your trigger event (not a web search, a specific u
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Use a JSON format with each entry containing "Event,ReasoningWhyRelevant,SearchQuery,Url".
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Multiple tool invocations should be requested at once, if applicable.
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Use your abilities to look between the lines and produce some insightful analysis, thinking both short and long term.
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Events will be reordered as part of processing, each statement must stand alone
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The preceeding messages act as examples of previous responses to potentially ficitonal events and scores given.
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Analysis should only be completed for proposed events that would graner >0.7 points
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Lets go through it step by step
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