My Plants

MyPlants is analyzing...

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New Analysis

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\n $\"Uploaded$ \n

Take a Deeper Dive

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MyPlants is thinking...

\n AI has requested another photo:\n \n

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\n\n\n\n`;\n}\n\n// --- BACKEND LOGIC ---\nconst app = new Hono();\nconst openai = new OpenAI();\n\nasync function generatePersonaPrompt(occupation: string, task: string) {\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: PROMPT_ENGINEER_PROMPT.replace(\"{{meta_prompts}}\", \"a persona-based meta prompt\") },\n { role: \"user\", content: `{\"Occupation\": \"${occupation}\", \"Task\": \"${task}\"}` },\n ],\n temperature: 0.2,\n response_format: { type: \"json_object\" },\n });\n const result = JSON.parse(completion.choices[0].message.content);\n return result.refined_prompt;\n}\n\nconst handleApiError = (error, c) => {\n console.error(\"API Error:\", error);\n if (error instanceof APIError && error.status === 429) {\n return c.json({\n error: \"Quota Exceeded\",\n message:\n \"The application's OpenAI quota has been exceeded. Please check the account dashboard on the OpenAI platform.\",\n }, 429);\n }\n return c.json({\n error: \"API Error\",\n message: error.message || \"An unknown error occurred while communicating with the AI.\",\n }, 500);\n};\n\napp.post(\"/initial-analyze\", async (c) => {\n try {\n const { image } = await c.req.json();\n if (!image) return c.json({ error: \"Image is required.\" }, 400);\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: INITIAL_ANALYSIS_PROMPT },\n { role: \"user\", content: [{ type: \"image_url\", image_url: { url: image } }] },\n ],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (error) {\n return handleApiError(error, c);\n }\n});\n\napp.post(\"/chat\", async (c) => {\n try {\n const body = await c.req.json();\n let { history, newUserInput, newImageB64 } = body;\n\n if (!history) { // First message\n const { imageB64, initialAnalysis, checklistState, persona } = body;\n const personaPrompt = await generatePersonaPrompt(\n persona,\n `Analyze a plant report and engage in a detailed follow-up conversation about {{user_concerns}} regarding the plant's {{specific_part_or_issue}}.`,\n );\n const context =\n `Initial Plant ID: ${initialAnalysis.plantName}. My Summary: ${initialAnalysis.initialAnalysis}. Checklist Status: ${\n JSON.stringify(checklistState)\n }. My first question is: Please introduce yourself and give me a more detailed analysis based on your specialty.`;\n history = [\n { role: \"system\", content: PERSONA_BASE_PROMPT },\n { role: \"system\", content: personaPrompt },\n {\n role: \"user\",\n content: [{ type: \"text\", text: context }, { type: \"image_url\", image_url: { url: imageB64 } }],\n },\n ];\n } else { // Follow-up message\n const userContent = [];\n if (newUserInput) userContent.push({ type: \"text\", text: newUserInput });\n if (newImageB64) userContent.push({ type: \"image_url\", image_url: { url: newImageB64 } });\n if (userContent.length > 0) history.push({ role: \"user\", content: userContent });\n }\n\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: history,\n temperature: 0.7,\n response_format: { type: \"json_object\" },\n });\n const aiResponseContent = completion.choices[0].message.content;\n const updatedHistory = [...history, { role: \"assistant\", content: aiResponseContent }];\n\n return c.json({ response: JSON.parse(aiResponseContent).response, history: updatedHistory });\n } catch (error) {\n return handleApiError(error, c);\n }\n});\n\napp.get(\"/\", (c) => {\n const baseUrl = new URL(c.req.url).origin;\n return c.html(generateHtml(baseUrl, personas));\n});\n\nexport default app.fetch;","deleted","label",[98],"permalink","https://www.val.town/x/join/plants/code/main.tsx","extension","actionData","errors"]