Add new provider - blackboxai

Author: Simatwa

docs/README.md

@@ -69,6 +69,8 @@ These are simply the hosts of the LLMs, which include:
 6. [WebChatGPT](https://github.com/Simatwa/WebChatGPT) - **OpenAI** *(Session ID required)*
 7. [Bard](https://github.com/acheong08/bard) - **Google** *(Session ID required)*
 8. [Phind](https://www.phind.com) - *default*
+9. [Llama2](https://www.llama2.ai)
+10. [Blackboxai](https://www.blackbox.ai)
 
 <details>
 

src/pytgpt/__init__.py

@@ -14,6 +14,7 @@
     "bard",
     "phind",
     "llama2",
+    "blackboxai",
 ]
 
 gpt4free_providers = [

src/pytgpt/blackboxai/__init__.py

@@ -0,0 +1,6 @@
+from .main import BLACKBOXAI
+from .main import session
+
+__info__ = "Interact with Blackboxai models"
+
+__all__ = ["BLACKBOXAI", "session"]

src/pytgpt/blackboxai/main.py

@@ -0,0 +1,216 @@
+import re
+import json
+import yaml
+import requests
+from pytgpt.utils import Optimizers
+from pytgpt.utils import Conversation
+from pytgpt.utils import AwesomePrompts
+
+session = requests.Session()
+
+default_model = None
+
+
+class BLACKBOXAI:
+    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,
+        model: str = default_model,
+    ):
+        """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.
+            model (str, optional): Model name. Defaults to "Phind Model".
+        """
+        self.max_tokens_to_sample = max_tokens
+        self.is_conversation = is_conversation
+        self.chat_endpoint = "https://www.blackbox.ai/api/chat"
+        self.stream_chunk_size = 64
+        self.timeout = timeout
+        self.last_response = {}
+        self.model = model
+        self.previewToken: str = None
+        self.userId: str = ""
+        self.codeModelMode: bool = True
+        self.id: str = ""
+        self.agentMode: dict = {}
+        self.trendingAgentMode: dict = {}
+        self.isMicMode: bool = False
+
+        self.headers = {
+            "Content-Type": "application/json",
+            "User-Agent": "",
+            "Accept": "*/*",
+            "Accept-Encoding": "Identity",
+        }
+
+        self.__available_optimizers = (
+            method
+            for method in dir(Optimizers)
+            if callable(getattr(Optimizers, method)) and not method.startswith("__")
+        )
+        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
+        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
+        {
+           "text" : "print('How may I help you today?')"
+        }
+        ```
+        """
+        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}"
+                )
+
+        session.headers.update(self.headers)
+        payload = {
+            "messages": [
+                # json.loads(prev_messages),
+                {"content": conversation_prompt, "role": "user"}
+            ],
+            "id": self.id,
+            "previewToken": self.previewToken,
+            "userId": self.userId,
+            "codeModelMode": self.codeModelMode,
+            "agentMode": self.agentMode,
+            "trendingAgentMode": self.trendingAgentMode,
+            "isMicMode": self.isMicMode,
+        }
+
+        def for_stream():
+            response = session.post(
+                self.chat_endpoint, json=payload, stream=True, timeout=self.timeout
+            )
+            if (
+                not response.ok
+                or not response.headers.get("Content-Type")
+                == "text/plain; charset=utf-8"
+            ):
+                raise Exception(
+                    f"Failed to generate response - ({response.status_code}, {response.reason}) - {response.text}"
+                )
+            streaming_text = ""
+            for value in response.iter_lines(
+                decode_unicode=True,
+                chunk_size=self.stream_chunk_size,
+                delimiter="\n",
+            ):
+                try:
+                    if bool(value):
+                        streaming_text += value + ("\n" if stream else "")
+
+                        resp = dict(text=streaming_text)
+                        self.last_response.update(resp)
+                        yield value if raw else resp
+                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["text"]

src/pytgpt/console.py

@@ -485,6 +485,22 @@ def __init__(
                     act=awesome_prompt,
                 )
 
+            elif provider == "blackboxai":
+
+                from pytgpt.blackboxai import BLACKBOXAI
+
+                self.bot = BLACKBOXAI(
+                    is_conversation=disable_conversation,
+                    max_tokens=max_tokens,
+                    timeout=timeout,
+                    intro=intro,
+                    filepath=filepath,
+                    update_file=update_file,
+                    proxies=proxies,
+                    history_offset=history_offset,
+                    act=awesome_prompt,
+                )
+
             elif provider in pytgpt.gpt4free_providers:
                 from pytgpt.gpt4free import GPT4FREE
 

src/pytgpt/llama2/main.py

@@ -146,12 +146,12 @@ def for_stream():
             message_load: str = ""
             for value in response.iter_lines(
                 decode_unicode=True,
-                delimiter="" if raw else "\n",
+                delimiter="\n",
                 chunk_size=self.stream_chunk_size,
             ):
                 try:
                     if bool(value.strip()):
-                        message_load += value
+                        message_load += value + ("\n" if stream else "")
                         resp: dict = dict(text=message_load)
                         yield value if raw else resp
                         self.last_response.update(resp)

tests/test_blackboxai.py

@@ -0,0 +1,13 @@
+import unittest
+import tests.base as base
+from pytgpt.blackboxai import BLACKBOXAI
+
+
+class TestBlackboxai(base.llmBase):
+    def setUp(self):
+        self.bot = BLACKBOXAI()
+        self.prompt = base.prompt
+
+
+if __name__ == "__main__":
+    unittest.main()