add italygpt.it

README.md

@@ -87,6 +87,7 @@ Just API's from some language model sites.
 | [bard.google.com](https://bard.google.com)       | custom / search                  |
 | [bing.com/chat](https://bing.com/chat)           | GPT-4/3.5                        |
 | [chat.forefront.ai/](https://chat.forefront.ai/) | GPT-4/3.5                        |
+| [italygpt.it](https://italygpt.it)               | GPT-3.5                          |
 
 ## Best sites <a name="best-sites"></a>
 

gpt4free/italygpt/README.md

@@ -0,0 +1,18 @@
+### Example: `italygpt`
+
+```python
+# create an instance
+from gpt4free import italygpt
+italygpt = italygpt.Completion()
+
+# initialize api
+italygpt.init()
+
+# get an answer
+italygpt.create(prompt="What is the meaning of life?")
+print(italygpt.answer) # html formatted
+
+# keep the old conversation
+italygpt.create(prompt="Are you a human?", messages=italygpt.messages)
+print(italygpt.answer)
+```

gpt4free/italygpt/__init__.py

@@ -0,0 +1,28 @@
+import requests, time, ast, json
+from bs4 import BeautifulSoup
+from hashlib import sha256
+
+class Completion:
+    # answer is returned with html formatting
+    next_id = None
+    messages = []
+    answer = None
+
+    def init(self):
+        r = requests.get("https://italygpt.it")
+        soup = BeautifulSoup(r.text, "html.parser")
+        self.next_id = soup.find("input", {"name": "next_id"})["value"]
+    
+    def create(self, prompt: str, messages: list = []):
+        try:
+            r = requests.get("https://italygpt.it/question", params={"hash": sha256(self.next_id.encode()).hexdigest(), "prompt": prompt, "raw_messages": json.dumps(messages)}).json()
+        except:
+            r = requests.get("https://italygpt.it/question", params={"hash": sha256(self.next_id.encode()).hexdigest(), "prompt": prompt, "raw_messages": json.dumps(messages)}).text
+            if "too many requests" in r.lower():
+                # rate limit is 17 requests per 1 minute
+                time.sleep(20)
+                return self.create(prompt, messages)
+        self.next_id = r["next_id"]
+        self.messages = ast.literal_eval(r["raw_messages"])
+        self.answer = r["response"]
+        return self