Create AI.py

AI.py

@@ -0,0 +1,240 @@
+import requests
+from requests import get
+from uuid import uuid4
+from re import findal
+
+import io
+import re
+import json
+from webscout.AIutel import Optimizers
+from webscout.AIutel import Conversation
+from typing import Any
+import logging
+class OPENGPT:
+    def __init__(
+        self,
+        is_conversation: bool = True,
+        max_tokens: int = 600,
+        timeout: int = 30,
+        intro: str = None,
+        filepath: str = None,
+        update_file: bool = True,
+        proxies: dict = {},
+        history_offset: int = 10250,
+        act: str = None,
+    ):
+        """Instantiates OPENGPT
+
+        Args:
+            is_conversation (bool, optional): Flag for chatting conversationally. Defaults to True
+            max_tokens (int, optional): Maximum number of tokens to be generated upon completion. Defaults to 600.
+            timeout (int, optional): Http request timeout. Defaults to 30.
+            intro (str, optional): Conversation introductory prompt. Defaults to None.
+            filepath (str, optional): Path to file containing conversation history. Defaults to None.
+            update_file (bool, optional): Add new prompts and responses to the file. Defaults to True.
+            proxies (dict, optional): Http request proxies. Defaults to {}.
+            history_offset (int, optional): Limit conversation history to this number of last texts. Defaults to 10250.
+            act (str|int, optional): Awesome prompt key or index. (Used as intro). Defaults to None.
+        """
+        self.session = requests.Session()
+        self.max_tokens_to_sample = max_tokens
+        self.is_conversation = is_conversation
+        self.chat_endpoint = (
+            "https://opengpts-example-vz4y4ooboq-uc.a.run.app/runs/stream"
+        )
+        self.stream_chunk_size = 64
+        self.timeout = timeout
+        self.last_response = {}
+        self.assistant_id = "bca37014-6f97-4f2b-8928-81ea8d478d88"
+        self.authority = "opengpts-example-vz4y4ooboq-uc.a.run.app"
+
+        self.headers = {
+            "authority": self.authority,
+            "accept": "text/event-stream",
+            "accept-language": "en-US,en;q=0.7",
+            "cache-control": "no-cache",
+            "content-type": "application/json",
+            "origin": "https://opengpts-example-vz4y4ooboq-uc.a.run.app",
+            "pragma": "no-cache",
+            "referer": "https://opengpts-example-vz4y4ooboq-uc.a.run.app/",
+            "sec-fetch-site": "same-origin",
+            "sec-gpc": "1",
+            "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
+        }
+
+        self.__available_optimizers = (
+            method
+            for method in dir(Optimizers)
+            if callable(getattr(Optimizers, method)) and not method.startswith("__")
+        )
+        self.session.headers.update(self.headers)
+        Conversation.intro = (
+            AwesomePrompts().get_act(
+                act, raise_not_found=True, default=None, case_insensitive=True
+            )
+            if act
+            else intro or Conversation.intro
+        )
+        self.conversation = Conversation(
+            is_conversation, self.max_tokens_to_sample, filepath, update_file
+        )
+        self.conversation.history_offset = history_offset
+        self.session.proxies = proxies
+
+    def ask(
+        self,
+        prompt: str,
+        stream: bool = False,
+        raw: bool = False,
+        optimizer: str = None,
+        conversationally: bool = False,
+    ) -> dict:
+        """Chat with AI
+
+        Args:
+            prompt (str): Prompt to be send.
+            stream (bool, optional): Flag for streaming response. Defaults to False.
+            raw (bool, optional): Stream back raw response as received. Defaults to False.
+            optimizer (str, optional): Prompt optimizer name - `[code, shell_command]`. Defaults to None.
+            conversationally (bool, optional): Chat conversationally when using optimizer. Defaults to False.
+        Returns:
+           dict : {}
+        ```json
+        {
+            "messages": [
+                {
+                    "content": "Hello there",
+                    "additional_kwargs": {},
+                    "type": "human",
+                    "example": false
+                },
+                {
+                    "content": "Hello! How can I assist you today?",
+                    "additional_kwargs": {
+                    "agent": {
+                        "return_values": {
+                            "output": "Hello! How can I assist you today?"
+                            },
+                        "log": "Hello! How can I assist you today?",
+                        "type": "AgentFinish"
+                    }
+                },
+                "type": "ai",
+                "example": false
+                }]
+        }
+        ```
+        """
+        conversation_prompt = self.conversation.gen_complete_prompt(prompt)
+        if optimizer:
+            if optimizer in self.__available_optimizers:
+                conversation_prompt = getattr(Optimizers, optimizer)(
+                    conversation_prompt if conversationally else prompt
+                )
+            else:
+                raise Exception(
+                    f"Optimizer is not one of {self.__available_optimizers}"
+                )
+
+        self.session.headers.update(self.headers)
+        self.session.headers.update(
+            dict(
+                cookie=f"opengpts_user_id={uuid4().__str__()}",
+            )
+        )
+        payload = {
+            "input": [
+                {
+                    "content": conversation_prompt,
+                    "additional_kwargs": {},
+                    "type": "human",
+                    "example": False,
+                },
+            ],
+            "assistant_id": self.assistant_id,
+            "thread_id": "",
+        }
+
+        def for_stream():
+            response = self.session.post(
+                self.chat_endpoint, json=payload, stream=True, timeout=self.timeout
+            )
+            if (
+                not response.ok
+                or not response.headers.get("Content-Type")
+                == "text/event-stream; charset=utf-8"
+            ):
+                raise Exception(
+                    f"Failed to generate response - ({response.status_code}, {response.reason}) - {response.text}"
+                )
+
+            for value in response.iter_lines(
+                decode_unicode=True,
+                chunk_size=self.stream_chunk_size,
+            ):
+                try:
+                    modified_value = re.sub("data:", "", value)
+                    resp = json.loads(modified_value)
+                    if len(resp) == 1:
+                        continue
+                    self.last_response.update(resp[1])
+                    yield value if raw else resp[1]
+                except json.decoder.JSONDecodeError:
+                    pass
+            self.conversation.update_chat_history(
+                prompt, self.get_message(self.last_response)
+            )
+
+        def for_non_stream():
+            for _ in for_stream():
+                pass
+            return self.last_response
+
+        return for_stream() if stream else for_non_stream()
+
+    def chat(
+        self,
+        prompt: str,
+        stream: bool = False,
+        optimizer: str = None,
+        conversationally: bool = False,
+    ) -> str:
+        """Generate response `str`
+        Args:
+            prompt (str): Prompt to be send.
+            stream (bool, optional): Flag for streaming response. Defaults to False.
+            optimizer (str, optional): Prompt optimizer name - `[code, shell_command]`. Defaults to None.
+            conversationally (bool, optional): Chat conversationally when using optimizer. Defaults to False.
+        Returns:
+            str: Response generated
+        """
+
+        def for_stream():
+            for response in self.ask(
+                prompt, True, optimizer=optimizer, conversationally=conversationally
+            ):
+                yield self.get_message(response)
+
+        def for_non_stream():
+            return self.get_message(
+                self.ask(
+                    prompt,
+                    False,
+                    optimizer=optimizer,
+                    conversationally=conversationally,
+                )
+            )
+
+        return for_stream() if stream else for_non_stream()
+
+    def get_message(self, response: dict) -> str:
+        """Retrieves message only from response
+
+        Args:
+            response (dict): Response generated by `self.ask`
+
+        Returns:
+            str: Message extracted
+        """
+        assert isinstance(response, dict), "Response should be of dict data-type only"
+        return response["content"]