Create app.py

app.py

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+import os
+import re
+import json
+import time
+import requests
+import anthropic
+import google.auth
+import gradio as gr
+from uuid import uuid4
+from dotenv import load_dotenv
+from google.auth.transport.requests import Request
+
+
+# Gemini
+def get_google_token():
+    credentials, project = google.auth.load_credentials_from_dict(
+        json.loads(os.environ.get('GCP_FINETUNE_KEY')),
+        scopes=[
+            "https://www.googleapis.com/auth/cloud-platform",
+            "https://www.googleapis.com/auth/generative-language.tuning",
+        ],
+    )
+    request = Request()
+    credentials.refresh(request)
+    access_token = credentials.token
+    return access_token
+
+
+def dubpro_english_to_hindi(text):
+    API_URL = os.environ.get("GEMINI_FINETUNED_ENG_HINDI_API")
+    BEARER_TOKEN = get_google_token()
+    headers = {
+        "Authorization": f"Bearer {BEARER_TOKEN}",
+        "Content-Type": "application/json",
+    }
+    payload = {
+        "contents": [
+            {
+                "parts": [{"text": f"text: {text}"}],
+                "role": "user",
+            }
+        ],
+        "generationConfig": {
+            "maxOutputTokens": 8192,
+            "temperature": 0.85,
+        },
+        "safetySettings": [
+            {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+            {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+            {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+            {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+        ],
+    }
+    result = requests.post(
+        url=API_URL,
+        headers=headers,
+        json=payload
+    )
+    response = result.json()
+    response_content = response['candidates'][0]['content']['parts'][0]['text'].replace("translated:", "").strip()
+    return response_content
+
+
+def gemini_english_to_hindi(text):
+    API_URL = os.environ.get("GEMINI_FINETUNED_ENG_HINDI_API")
+    BEARER_TOKEN = get_google_token()
+    headers = {
+        "Authorization": f"Bearer {BEARER_TOKEN}",
+        "Content-Type": "application/json",
+    }
+    payload = {
+        "contents": [
+            {
+                "parts": [{"text": f"Translate the following text to Hindi: `{text}` Output: "}],
+                "role": "user",
+            }
+        ],
+        "generationConfig": {
+            "maxOutputTokens": 8192,
+            "temperature": 0.85,
+        },
+        "safetySettings": [
+            {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+            {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+            {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+            {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+        ],
+    }
+    result = requests.post(
+        url=API_URL,
+        headers=headers,
+        json=payload
+    )
+    response = result.json()
+    response_content = response['candidates'][0]['content']['parts'][0]['text'].replace("translated:", "").replace("`", "").strip()
+    return response_content
+
+
+# GPT models
+def clean(result):
+    text = result["choices"][0]['message']["content"]
+    text = re.sub(r"\(.*?\)|\[.*?\]","", text)
+    text = text.strip("'").replace('"', "")
+    if "\n" in text.strip("\n"):
+        text = text.split("\n")[-1]
+    return text
+
+def openai_english_to_hindi(text, model):
+    prompt = f"Translate the following English text into Hindi such that the meaning in unchanged. Return only the translated text: `{text}`. Output: "
+
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {os.environ.get('OPENAI_API_KEY')}"
+    }
+    
+    messages = [
+        {"role": "system", "content": f"You are a language translation assistant."},
+        {"role": "user", "content": prompt}
+    ]
+    
+    resp = None
+    while resp is None:
+        resp = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json={
+            "model": model,
+            "messages": messages
+        })
+        if resp.status_code != 200:
+            print(resp.text)
+        time.sleep(0.5)
+    response_json = resp.json()
+
+    result_text = clean(response_json)
+    return result_text
+
+
+# Azure translate
+def azure_english_to_hindi(text):
+    headers = {
+        "Ocp-Apim-Subscription-Key": os.environ.get("AZURE_TRANSLATE_KEY"),
+        "Ocp-Apim-Subscription-Region": os.environ.get("AZURE_TRANSLATE_REGION"),
+        "Content-type": "application/json",
+        "X-ClientTraceId": str(uuid4()),
+    }
+    ENDPOINT = "https://api.cognitive.microsofttranslator.com/translate"
+    params = {
+        "api-version": "3.0",
+        "from": "en-US",
+        "to": "hi-IN",
+    }
+    texts = [{"text": text}]
+    request = requests.post(ENDPOINT, headers=headers, params=params, json=texts)
+    response = request.json()
+    return response[0]["translations"][0]["text"]
+
+
+# Anthopic Claude 3 Haiku
+def claude_english_to_hindi(text):
+    client = anthropic.Anthropic()
+    message = client.messages.create(
+        model="claude-3-haiku-20240307",
+        max_tokens=1000,
+        temperature=0.8,
+        system="You are an expert language translator.",
+        messages=[
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": "Translate the following English text into Hindi such that the meaning in unchanged. Return only the translated text: `The Electrons journey starts with Complex 1 or it can start with Complex 2 either of that.`. Output: "
+                    }
+                ]
+            }
+        ]
+    )
+    return message.content[0].text
+
+
+def render_translations(text):
+    dubpro = dubpro_english_to_hindi(text)
+    azure = azure_english_to_hindi(text)
+    gemini = gemini_english_to_hindi(text)
+    gpt_4 = openai_english_to_hindi(text, model="gpt-4")
+    claude_haiku = claude_english_to_hindi(text)
+    return gr.update(value=gpt_4), gr.update(value=dubpro), gr.update(value=gemini), gr.update(value=claude_haiku), gr.update(value=azure)
+
+
+with gr.Blocks(title="English to Hindi Translation Tools", theme="gradio/monochrome") as demo:
+    gr.Markdown("# English to Hindi Translation Tools")
+    input_textbox = gr.Textbox(label="Input Text", info="Text to translate", value="When you did it, you must have attended your classes well or you must have done your daily revision. Now you feel scared.")
+    submit = gr.Button(label="Submit")
+    with gr.Row():
+        gr.Label(value="Dubpro's Model", scale=1)
+        dubpro_model_textbox = gr.Textbox(label="Translated Text", scale=2, interactive=False)
+    with gr.Row():
+        gr.Label(value="GPT 4", scale=1)
+        gpt_4_textbox = gr.Textbox(label="Translated Text", scale=2, interactive=False)
+    with gr.Row():
+        gr.Label(value="Google Gemini", scale=1)
+        google_textbox = gr.Textbox(label="Translated Text", scale=2, interactive=False)
+    with gr.Row():
+        gr.Label(value="Anthropic Claude 3", scale=1)
+        claude_textbox = gr.Textbox(label="Translated Text", scale=2, interactive=False)
+    with gr.Row():
+        gr.Label(value="Azure Translate", scale=1)
+        azure_textbox = gr.Textbox(label="Translated Text", scale=2, interactive=False)
+
+    submit.click(render_translations, input_textbox, [gpt_4_textbox, dubpro_model_textbox, google_textbox, claude_textbox, azure_textbox])
+
+
+if __name__=="__main__":
+    demo.launch()