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Dockerfile

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+# Use a Python base image
+FROM python:3.10-slim
+
+# Set the working directory
+WORKDIR /app
+
+# Copy the requirements file and install dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# --- IMPORTANT: Configure Caching to /tmp ---
+# Spaces only allow writing to /tmp, which is critical for many ML libraries.
+# Although not strictly required for google-genai, it is a best practice.
+ENV XDG_CACHE_HOME=/tmp/hf_cache
+ENV HF_HOME=/tmp/hf_cache
+
+# Copy your application code
+# This copies main.py, snake_rec.py, and your .env (if you want to use it
+# but using HF Secrets is much better, see Step 3)
+COPY . .
+
+# Expose the required port (7860 is the default for HF Spaces)
+EXPOSE 7860
+
+# The command to run your FastAPI application using uvicorn
+# 'main:app' refers to the 'app' object in 'main.py'
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

main.py

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+from fastapi import FastAPI
+from snake_rec import snake_app as snake
+from fastapi.middleware.cors import CORSMiddleware
+
+app=FastAPI()
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+@app.get("/")
+
+def home():
+    return {"message":"SISISIS"}
+
+
+app.include_router(snake)

requirements.txt

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+fastapi
+uvicorn[standard]
+python-dotenv
+google-genai
+python-multipart
+Pillow
+requests
+supabase-py

snake_rec.py

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+from fastapi import APIRouter, UploadFile, File, Form
+from google.genai.types import GenerateContentConfig
+from google import genai
+from typing import Optional
+from dotenv import load_dotenv
+import os
+from uuid import uuid4
+import requests
+import io
+from PIL import Image
+from supabase import create_client
+
+# Load environment variables
+load_dotenv()
+url = os.getenv('url')
+key = os.getenv('key')
+GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
+
+# Initialize clients
+client = genai.Client(api_key=GOOGLE_API_KEY)
+supabase = create_client(url, key)
+
+# Memory for chat history
+user = []
+chatbot = []
+
+snake_app = APIRouter()
+
+# Prompt for image analysis
+prompt_text = (
+    "You will get a snake image. You have to tell what kind of snake it is "
+    "and if it's venomous or non-venomous. If image is not a snake then just say "
+    "'There is no snake in image!'."
+)
+
+@snake_app.post("/snake")
+async def snakeeee(f1: Optional[UploadFile] = File(None), text: Optional[str] = Form(None)):
+    memory = {
+        'User': user,
+        'Chatbot_response': chatbot
+    }
+
+    # Case 1: File only or file + text
+    if f1:
+        # Save file locally
+        file_extension = f1.filename.split(".")[-1]
+        file_name = f"{uuid4()}.{file_extension}"
+        file_data = await f1.read()
+        with open(file_name, "wb") as f:
+            f.write(file_data)
+
+        # Upload to Supabase
+        supabase.storage.from_("user_files").upload(
+            f"images/{file_name}",
+            file_data,
+            {"content-type": f"image/{file_extension}"}
+        )
+        public_url = supabase.storage.from_("user_files").get_public_url(f"images/{file_name}")
+        response = requests.get(public_url)
+
+        if response.status_code == 200:
+            image_response = io.BytesIO(response.content)
+            image_content = Image.open(image_response)
+
+            # Prepare contents for Gemini
+            contents = [image_content, prompt_text]
+
+            # Generate response
+            response_gemini = client.models.generate_content(
+                model="gemini-2.5-flash",
+                contents=contents
+            )
+            chatbot.append(response_gemini.text)
+
+            # If text is also provided, append to chat history and process
+            if text:
+                user.append(text)
+                prompt_chat = (
+                    f"You are a Snake Chatbot. User queries about snakes. Make Sure your response should not be so long which make user difficult to understand. "
+                    f"Chat history: {memory}"
+                )
+                response_text = client.models.generate_content(
+                    model="gemini-2.5-flash",
+                    config=GenerateContentConfig(
+                        system_instruction=prompt_chat,
+                        temperature=0.1
+                    ),
+                    contents=text
+                )
+                chatbot.append(response_text.text)
+                return {
+
+                    'Chatbot': response_text.text
+                }
+
+            return {'Chatbot': response_gemini.text}
+
+    # Case 2: Text only
+    if text:
+        user.append(text)
+        prompt_chat = (
+            f"You are a Snake Chatbot know . User queries about snakes. Make sure your response should not be so long which make user difficult to understand. "
+            f"Chat history: {memory}"
+        )
+        response_text = client.models.generate_content(
+            model="gemini-2.5-flash",
+            config=GenerateContentConfig(
+                system_instruction=prompt_chat,
+                temperature=0.1
+            ),
+            contents=text
+        )
+        chatbot.append(response_text.text)
+        return {'Chatbot': response_text.text}
+
+    # Case 3: Neither file nor text
+    return {'error': 'No file or text provided'}