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f275565 9274cc0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 | from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import httpx
import json
import uvicorn
import os
app = FastAPI()
OLLAMA_URL = "http://localhost:11434/api/chat"
# تعريف شكل البيانات المستلمة
class AnalysisRequest(BaseModel):
user_text: str # النص المجمع من حوار المستخدم فقط
@app.get("/")
async def check():
return {
"status": "success",
"state":"ok"
}
@app.post("/analyze/personality")
async def analyze_personality(data: AnalysisRequest):
# الـ Prompt باللغة الإنجليزية فقط
# analysis_prompt = f"""
# Analyze the user text and return a JSON object with exactly these keys:
# 'decision_making', 'energy', 'focus', 'lifestyle', 'compatible_type' 'personality_type' ,.
# Each key (except compatible_type and personality_type) must be an object with a 'summary' field in ENGLISH.
# The 'summary' should be a concise psychological insight (1-2 sentences).
# 'compatible_type' should be a 4-letter MBTI code (e.g., 'INTJ') just it not a code inside it.
# 'personality_type' should be a 4-letter MBTI code (e.g., 'INTJ') just it not a code inside it.
# User Text: "{data.user_text}"
# """
analysis_prompt = f"""
Act as an MBTI classifier. Analyze the following text and identify the user's personality type.
Constraints:
1. Output MUST be ONLY a valid JSON.
2. Provide ONLY the 4-letter MBTI code.
User Text:
{data.user_text}
"""
analysis_prompt += """
Response Format:
{
"mbti": "MUST be a 4-letter MBTI code (e.g., 'INTJ') just it not a code inside it."
}
"""
# analysis_prompt = f"""
# Analyze the user text based on MBTI personality theory.
# Return a JSON object with EXACTLY these keys:
# 'decision_making', 'energy', 'focus', 'lifestyle', 'compatible_type'.
# Requirements:
# 1. 'personality_type': MUST be the 4-letter MBTI code that is the user's identified type.
# 2. There is a 'summary' field inside 'decision_making', 'energy', 'focus', and 'lifestyle'
# 2. For each 'summary' field (except compatible_type), write a 1-2 sentence psychological insight in ENGLISH.
# 3. 'compatible_type' MUST be the 4-letter MBTI code that is most compatible with the user's identified type.
# User Text: "{data.user_text}"
# """
# analysis_prompt = f"""
# Analyze the following user text based on MBTI personality theory.
# Return a JSON object with EXACTLY these keys:
# 'personality_type', 'decision_making', 'energy', 'focus', 'lifestyle', 'compatible_type'.
# Requirements:
# 1. 'personality_type': MUST be the 4-letter MBTI code that is the user's identified type.
# 2. The 'summary' field inside 'decision_making', 'energy', 'focus', and 'lifestyle' must be written in English.
# 3. The 'summary' should be a concise psychological insight (1-2 sentences) in English.
# 4. 'compatible_type': The 4-letter MBTI code in ENGLISH that best matches the user.
# User Text:
# \"\"\"{data.user_text}\"\"\"
# Respond ONLY in valid JSON.
# """
payload = {
"model": "llama3.2:1b",
"messages": [
{"role": "system", "content": "You are a professional MBTI profiler. Respond ONLY in valid JSON. All text must be in English."},
{"role": "user", "content": analysis_prompt}
],
"stream": False,
"format": "json"
}
async with httpx.AsyncClient(timeout=60.0) as client:
try:
url = os.environ.get("OLLAMA_URL", OLLAMA_URL)
response = await client.post(url, json=payload)
response.raise_for_status()
result = response.json()
analysis_content = result.get("message", {}).get("content", "")
return json.loads(analysis_content)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
uvicorn.run(app, host="0.0.0.0", port=os.environ.get("PORT",7860)) # منفذ مختلف عن سيرفر الدردشة |