cleint and server code integrated

.gitattributes

@@ -1 +1,3 @@
 *.png filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text

.github/workflows/main.yml

@@ -16,4 +16,4 @@ jobs:
       - name: Push to hub
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
-        run: git push --force https://sssingh:$HF_TOKEN@huggingface.co/spaces/sssingh/pic-to-story main
+        run: git push --force https://sssingh:$HF_TOKEN@huggingface.co/spaces/sssingh/guruzee main

Dockerfile

@@ -0,0 +1,12 @@
+FROM python:3.10
+
+WORKDIR app
+
+COPY server_requirements.txt .
+RUN pip install -r server_requirements.txt
+
+COPY src/server_config.py .
+COPY src/server.py .
+COPY .env .
+
+CMD ["uvicorn", "server:guruzee", "--host=0.0.0.0", "--port=8000"]

README.md

@@ -1,5 +1,18 @@
-# GuruZee 
-> Where Math Meets Marvel with AI Wizardry for Primary School Prowess! 🧙♂📚✨
+
+title: Guruzee
+emoji: 📚
+colorFrom: blue
+colorTo: red
+sdk: gradio
+sdk_version: 4.4.1
+app_file: src/client.py
+pinned: false
+license: mit
+
+# GuruZee
+***Where Math Meets Marvel with AI Wizardry for Primary School Prowess! 🧙♂📚✨***
+
+<img src="https://github.com/sssingh/guruzee/blob/main/assets/title.png?raw=true" width="1000" height="400"/><br><br>  
 
 ## Introduction
 GuruZee, your go-to guru for primary school math (for now).   
@@ -20,7 +33,7 @@ Solve a problem
 just select one of the pre-configured `Example` image from Example section at the 
 bottom. The answer and explanation will appear on the right.
 
-<img src="https://github.com/sssingh/guruzee/blob/main/assets/aap=eample.png?raw=true" width="1000" height="450"/><br><br> 
+<img src="https://github.com/sssingh/guruzee/blob/main/assets/app-example.png?raw=true" width="1000" height="450"/><br><br>  
 
 Prepare questions and answers
 -----------------------------
@@ -30,5 +43,5 @@ just select one the pre-configured `Example` image from Example section in the b
 The answer and explanation will appear on the right.
 
 ## App Architecture
-[TODO]
+<img src="https://github.com/sssingh/guruzee/blob/main/assets/wip.jpg?raw=true" width="1000" height="400"/><br><br>  
 

requirements.txt

@@ -1,5 +1,3 @@
-fastapi
-uvicorn
 requests
 pymongo[tls, srv]==4.4.*
 gradio==3.45.*

server_requirements.txt

@@ -0,0 +1,4 @@
+fastapi
+uvicorn
+requests
+python-dotenv

src/app_config.py

@@ -8,28 +8,13 @@ load_dotenv()
 
 @dataclass
 class __AppConfig:
-    solver_persona = """You an expert primary school maths teacher. Given an 
-            image of a primary school maths problem you can analyze the problem and 
-            produce a detailed solution with explanation."""
-    teacher_persona = (
-        solver_persona
-        + """ \nIn addition to this, given a
-            collection images from primary school maths text book you can generate
-            questions and there answers based on the topic shown in text book images,
-            you will provide the detailed answers with explanation"""
-    )
-    solver_instruction = """Analyze the primary school math problem in the the image. 
-            Strictly first provide the answer to the problem and then only the solution 
-            explanation. Put a newline after each 80 chars"""
     openai_max_access_count = 200
     openai_curr_access_count = None
     mongo_client = None
     db = "mydb"
     collection = "guruzee-openai-access-counter"
     key = "current_count"
-    OPENAI_API_ENDPOINT = os.getenv("OPENAI_API_ENDPOINT")
     GURUZEE_API_ENDPOINT = os.getenv("GURUZEE_API_ENDPOINT")
-    OPENAI_KEY = os.getenv("OPENAI_KEY")
     HF_TOKEN = os.getenv("HF_TOKEN")
     MONGO_CONN_STR = os.getenv("MONGO_CONN_STR")
     title = "GuruZee, your go-to guru for primary school math"

src/client.py

@@ -25,12 +25,17 @@ def solve(image_path: str):
     Invokes the GuruZee API passing the raw image bytes and returns the response
     to client
     """
-    print(image_path)
     image_data = __encode_image(image_path=image_path)
     headers = {"Content-Type": "application/json"}
     payload = {"data": image_data}
-    response = requests.post(config.GURUZEE_API_ENDPOINT, headers=headers, json=payload)
-    return response.json()
+    end_point = config.GURUZEE_API_ENDPOINT + "/solve"
+    response = requests.post(end_point, headers=headers, json=payload)
+    # increment the openai access counter and compute count stats
+    mongo.increment_curr_access_count()
+    max_count = config.openai_max_access_count
+    curr_count = config.openai_curr_access_count
+    available_count = max_count - curr_count
+    return response.json(), max_count, curr_count, available_count
 
 
 def create_interface():
@@ -72,8 +77,8 @@ def create_interface():
                     <br>
                     Select/upload an `Image` containing the problem Then hit 
                     `GO!` button.
-                    Alternatively, just select one the pre-configured `Example` image 
-                    from Example section in the bottom**  
+                    Alternatively, just select one of the pre-configured `Example` image 
+                    from the Example section at the bottom**  
                     <br>
                     Visit the [project's repo](https://github.com/sssingh/GuruZee)  
                     <br>
@@ -147,13 +152,13 @@ def create_interface():
                     ],
                     fn=solve,
                     inputs=[image],
-                    outputs=[answer],
+                    outputs=[answer, max_count, curr_count, available_count],
                     run_on_click=True,
                 )
         submit_button.click(
             fn=solve,
             inputs=[image],
-            outputs=[answer],
+            outputs=[answer, max_count, curr_count, available_count],
         )
         clear_button.click(fn=clear, inputs=[], outputs=[image, answer])
         image.clear(fn=clear, inputs=[], outputs=[image, answer])

src/server.py

@@ -1,5 +1,5 @@
 import requests
-from app_config import config
+from server_config import server_config
 from fastapi import FastAPI
 from pydantic import BaseModel
 
@@ -18,17 +18,17 @@ def __analyze_single_image(image_data: str):
     image_data = {"url": f"data:image/jpeg;base64,{image_data}"}
     headers = {
         "Content-Type": "application/json",
-        "Authorization": f"Bearer {config.OPENAI_KEY}",
+        "Authorization": f"Bearer {server_config.OPENAI_KEY}",
     }
     payload = {
         "model": "gpt-4-vision-preview",
         "temperature": 0.2,  # low temperature because we want deterministic responses
         "messages": [
-            {"role": "system", "content": config.solver_persona},
+            {"role": "system", "content": server_config.solver_persona},
             {
                 "role": "user",
                 "content": [
-                    {"type": "text", "text": config.solver_instruction},
+                    {"type": "text", "text": server_config.solver_instruction},
                     {
                         "type": "image_url",
                         "image_url": image_data,
@@ -39,7 +39,9 @@ def __analyze_single_image(image_data: str):
         "max_tokens": 600,
     }
 
-    response = requests.post(config.OPENAI_API_ENDPOINT, headers=headers, json=payload)
+    response = requests.post(
+        server_config.OPENAI_API_ENDPOINT, headers=headers, json=payload
+    )
     return response.json()
 
 
@@ -51,3 +53,8 @@ async def solve(image: SingleImageData):
     """
     output = __analyze_single_image(image.data)
     return output["choices"][0]["message"]["content"]
+
+
+@guruzee.get("/health")
+async def health():
+    return {"Message": "Healthy and kicking!"}

src/server_config.py

@@ -0,0 +1,29 @@
+import os
+from dotenv import load_dotenv
+from dataclasses import dataclass
+
+# load environment variables from .env (only available in dev environment)
+load_dotenv()
+
+
+@dataclass
+class __ServerConfig:
+    solver_persona = """You an expert primary school maths teacher. Given an 
+            image of a primary school maths problem you can analyze the problem and 
+            produce a detailed solution with explanation."""
+    teacher_persona = (
+        solver_persona
+        + """ \nIn addition to this, given a
+            collection images from primary school maths text book you can generate
+            questions and there answers based on the topic shown in text book images,
+            you will provide the detailed answers with explanation"""
+    )
+    solver_instruction = """Analyze the primary school math problem in the the image. 
+            Strictly first provide the answer to the problem and then only the solution 
+            explanation. Put a newline after each 80 chars"""
+    teacher_instruction = """"""
+    OPENAI_API_ENDPOINT = os.getenv("OPENAI_API_ENDPOINT")
+    OPENAI_KEY = os.getenv("OPENAI_KEY")
+
+
+server_config = __ServerConfig()