first round of content classifier

src/app/api/ai/classify/route.ts

@@ -0,0 +1,52 @@
+import { classification } from "@/app/schemas/content-classification"
+import OpenAI from "openai"
+import { OAIStream, withResponseModel } from "zod-stream"
+
+import { RateLimiter } from "@/lib/rate-limiter"
+
+const oai = new OpenAI({
+  apiKey: process.env["OPENAI_API_KEY"] ?? undefined,
+  organization: process.env["OPENAI_ORG_ID"] ?? undefined
+})
+
+export const runtime = "edge"
+
+interface IRequest {
+  // response_model: { schema: typeof dashboardSchema; name: string }
+  messages: OpenAI.ChatCompletionMessageParam[]
+}
+
+export async function POST(request: Request) {
+  const rateLimit = await RateLimiter(request)
+
+  if (!rateLimit || rateLimit?.isLimited) {
+    return new Response("Daily limit exceeded", {
+      status: 429
+    })
+  }
+  const { messages } = (await request.json()) as IRequest
+
+  const params = withResponseModel({
+    response_model: {
+      schema: classification,
+      name: "classification of content"
+    },
+    params: {
+      temperature: 0.2,
+      seed: 1,
+      messages,
+
+      model: "gpt-4-1106-preview",
+      stream: true
+    },
+    mode: "TOOLS"
+  })
+
+  const extractionStream = await oai.chat.completions.create(params)
+
+  return new Response(
+    OAIStream({
+      res: extractionStream
+    })
+  )
+}

src/app/content-analysis.tsx

@@ -0,0 +1,150 @@
+import { useState } from "react"
+import { useJsonStream } from "stream-hooks"
+
+import { Overview } from "@/components/overview"
+import { Button } from "@/components/ui/button"
+import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card"
+import { Textarea } from "@/components/ui/textarea"
+
+import { classification } from "./schemas/content-classification"
+import { treasury } from "./text"
+
+export const ContentAnalysis = () => {
+  const [submitted, setSubmitted] = useState(false)
+  const [content, _setContent] = useState(treasury)
+  const [prompt, _setPrompt] = useState(
+    "I care mostly about the ideas in this report that can help me improve my business "
+  )
+
+  const { data, loading, startStream } = useJsonStream({
+    schema: classification
+  })
+
+  const submitMessage = async () => {
+    try {
+      setSubmitted(true)
+      await startStream({
+        url: "/api/ai/classify",
+        method: "POST",
+        body: {
+          messages: [
+            {
+              content: `You are tasks with classifying the following content.
+
+                Think about what this content could be. 
+
+                Then piece together the information you have to classify it.
+
+                Here is some additional context from the user of the tool: ${prompt}
+                  `,
+
+              role: "system"
+            },
+
+            {
+              content: content,
+              role: "user"
+            }
+          ]
+        }
+      })
+    } catch (e) {
+      console.error(e)
+    }
+  }
+
+  return !submitted ? (
+    <>
+      <div>
+        <div>
+          <p>Status: {loading ? "fetching" : submitted ? "submitted" : "idle"}</p>
+        </div>
+        <p>
+          This example parses any kind of content and classifies and pulls out some vital
+          information from it. You can copy and paste email threads, newsletters or any other kind
+          of content. It will then classify the content and pull out the important information.
+        </p>
+        <br />
+        <p>This prompt will be sent as context before the content</p>
+        <Textarea
+          className="mb-12 w-full"
+          defaultValue={prompt}
+          onChange={e => _setPrompt(e.target.value)}
+        />
+        <p>Content to classify</p>
+        <Textarea
+          className="mb-12 min-h-[50vh] w-full"
+          defaultValue={content}
+          onChange={e => _setContent(e.target.value)}
+        />
+        <Button onClick={submitMessage}>Generate report</Button>
+      </div>
+    </>
+  ) : (
+    <div className="">
+      <div>
+        <p>Status: {loading ? "fetching" : submitted ? "submitted" : "idle"}</p>
+      </div>
+      <Card>
+        <CardHeader>
+          <CardTitle>Tasks</CardTitle>
+        </CardHeader>
+        <CardContent>
+          <pre>{JSON.stringify(data.tasks, null, 2)}</pre>
+        </CardContent>
+      </Card>
+      <Card>
+        <CardHeader>
+          <CardTitle>Calendar</CardTitle>
+        </CardHeader>
+        <CardContent>
+          <pre>{JSON.stringify(data.calendar, null, 2)}</pre>
+        </CardContent>
+      </Card>
+      <Card>
+        <CardHeader>
+          <CardTitle>Ideas</CardTitle>
+        </CardHeader>
+        <CardContent>
+          {data.insights ? (
+            data.insights.map((idea, i) => (
+              <div key={i} className="py-2">
+                <h2 className="text-lg pb-2">{idea.topic}</h2>
+                <p className="pl-2">{idea.detailed_description}</p>
+              </div>
+            ))
+          ) : (
+            <p>No ideas yet!</p>
+          )}
+        </CardContent>
+      </Card>
+      <Card>
+        <CardHeader>
+          <CardTitle>People</CardTitle>
+        </CardHeader>
+        <CardContent>
+          {data.people ? (
+            data.people.map((person, i) => (
+              <div key={i} className="py-2">
+                <h2 className="text-lg">
+                  {person.name} - {person.role}
+                </h2>
+                <p className="pl-2">{person.context}</p>
+              </div>
+            ))
+          ) : (
+            <p>No people yet!</p>
+          )}
+        </CardContent>
+      </Card>
+      <Card>
+        <CardHeader>
+          <CardTitle>Follow Ups</CardTitle>
+        </CardHeader>
+        <CardContent>
+          <pre>{JSON.stringify(data.follow_ups, null, 2)}</pre>
+        </CardContent>
+      </Card>
+    </div>
+  )
+}

src/app/page.tsx

@@ -3,6 +3,7 @@
 import { ScrollArea } from "@/components/ui/scroll-area"
 import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs"
 
+import { ContentAnalysis } from "./content-analysis"
 import { Dashboard } from "./dashboard"
 
 export default function page() {
@@ -12,13 +13,14 @@ export default function page() {
         <Tabs defaultValue="overview" className="space-y-4">
           <TabsList>
             <TabsTrigger value="overview">Overview</TabsTrigger>
-            <TabsTrigger value="analytics" disabled>
-              Analytics
-            </TabsTrigger>
+            <TabsTrigger value="parser">Content Parser</TabsTrigger>
           </TabsList>
           <TabsContent value="overview" className="space-y-4">
             <Dashboard />
           </TabsContent>
+          <TabsContent value="parser" className="space-y-4">
+            <ContentAnalysis />
+          </TabsContent>
         </Tabs>
       </div>
     </ScrollArea>

src/app/schemas/content-classification.tsx

@@ -0,0 +1,80 @@
+import { z } from "zod"
+
+export const classification = z.object({
+  people: z
+    .object({
+      name: z.string(),
+      role: z.string().nullable(),
+      email: z.string().nullable(),
+      phone: z.string().nullable(),
+      location: z.string().nullable(),
+      department: z.string().nullable(),
+      company: z.string().nullable(),
+      context: z.string({
+        description: "What is the context of this person in the content?"
+      })
+    })
+    .array(),
+  calendar: z
+    .object(
+      {
+        event_name: z.string(),
+        start_time: z.date().nullable(),
+        end_time: z.date().nullable(),
+        location: z.string().nullable(),
+        invitees: z
+          .string({ description: "Invitees should be a comma separated list of emails" })
+          .nullable()
+      },
+      {
+        description:
+          "Is there a calendar event in this piece of content that we should be aware of?"
+      }
+    )
+    .array(),
+  tasks: z
+    .object(
+      {
+        task_name: z.string(),
+        due_date: z.date().nullable(),
+        start_date: z.date().nullable(),
+        priority: z.string().nullable(),
+        description: z.string().nullable()
+      },
+      {
+        description: "Is there a task in this piece of content that we should be aware of?"
+      }
+    )
+    .array(),
+  insights: z
+    .object(
+      {
+        topic: z.string({ description: "What is the insight about?" }),
+        detailed_description: z.string({
+          description: "What is the insight about in more thorough detail?"
+        }),
+        date: z.string({ description: "When was this thought had?" }) // zodDate not supported error?
+        // related: z.string({ description: "What other thoughts are related to this one?" }).nullable() THIS SHOULD CALL ANOTHER FUNCTION TO FIND RELATED NOTES!
+      },
+      {
+        description: `Is there a insight in this piece of content that the reader should be aware of?
+
+          Each insight should be a separate and distinct thought or idea.`
+      }
+    )
+    .array(),
+
+  follow_ups: z
+    .object(
+      {
+        follow_up: z.string({ description: "What is the follow up about?" }),
+        due_date: z.date({ description: "When is the follow up due?" }),
+        completed: z.boolean({ description: "Is the follow up completed?" })
+      },
+      {
+        description:
+          "Knowing the context of the content when would and what would be a good time to follow up?"
+      }
+    )
+    .array()
+})