basic openai support

chat_service.py

@@ -1,35 +1,49 @@
 import os
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
+import openai
 
 # from huggingface_hub.inference_api import InferenceApi
 
 class ChatService:
-    def __init__(self, api="huggingface", repo_id = "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5"):
+    def __init__(self, api="openai", model_id = "gpt-3.5-turbo"):
+    # def __init__(self, api="huggingface", model_id = "OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5"):
         self._api = api
         self._device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
-        if self._api=="huggingface":
-            self._tokenizer = AutoTokenizer.from_pretrained(repo_id)
-            self._model = AutoModelForCausalLM.from_pretrained(repo_id,torch_dtype=torch.float16)
-            # self._model = AutoModelForCausalLM.from_pretrained(repo_id).half()
+        if self._api=="openai":
+            openai.api_key = os.getenv("OPENAI_API_KEY")
+            self._model_id = model_id
+        elif self._api=="huggingface":
+            self._system_prompt = "Below are a series of dialogues between various people and an AI assistant. The AI tries to be helpful, polite, honest, sophisticated, emotionally aware, and humble-but-knowledgeable. The assistant is happy to help with almost anything, and will do its best to understand exactly what is needed. It also tries to avoid giving false or misleading information, and it caveats when it isn't entirely sure about the right answer. That said, the assistant is practical and really does its best, and doesn't let caution get too much in the way of being useful.\n-----\n"
+            self._user_name = "<|prompter|>"
+            self._agent_name = "<|assistant|>"
+            self._tokenizer = AutoTokenizer.from_pretrained(model_id)
+            self._model = AutoModelForCausalLM.from_pretrained(model_id,torch_dtype=torch.float16)
+            # self._model = AutoModelForCausalLM.from_pretrained(model_id).half()
             self._model.eval().to(self._device)
         else:
             raise Exception(f"Unknown API: {self._api}")
 
-        self._system_prompt = "Below are a series of dialogues between various people and an AI assistant. The AI tries to be helpful, polite, honest, sophisticated, emotionally aware, and humble-but-knowledgeable. The assistant is happy to help with almost anything, and will do its best to understand exactly what is needed. It also tries to avoid giving false or misleading information, and it caveats when it isn't entirely sure about the right answer. That said, the assistant is practical and really does its best, and doesn't let caution get too much in the way of being useful.\n-----\n"
-        self._user_name = "<|prompter|>"
-        self._agent_name = "<|assistant|>"
         self.reset()
 
     def reset(self):
         self._user_history = []
         self._agent_history = []
-        self._full_history = self._user_history if self._user_history else ""
+        self._full_history = self._system_prompt if self._system_prompt else ""
+        self._messages = []
+        if self._system_prompt:
+            self._messages.append({"role": "system", "content": self._system_prompt})
 
 
     def _chat(self, prompt):
-        if self._api=="huggingface":
+        if self._api=="openai":
+            response = openai.ChatCompletion.create(
+                model=self._model_id,
+                messages=self._messages,
+                )
+            agent_response = response['choices'][0]['message']['content']
+        elif self._api=="huggingface":
             tokens = self._tokenizer.encode(prompt, return_tensors="pt", padding=True)
             tokens = tokens.to(self._device)
             outputs = self._model.generate(
@@ -42,7 +56,6 @@ class ChatService:
                 pad_token_id=self._tokenizer.eos_token_id,
             )
             agent_response = self._tokenizer.decode(outputs[0], truncate_before_pattern=[r"\n\n^#", "^'''", "\n\n\n"])
-
         else:
             raise Exception(f"API not implemented: {self._api}")
         return agent_response
@@ -52,8 +65,10 @@ class ChatService:
             self._full_history += f"{self._user_name}: {prompt}\n"
         else:
             self._full_history += f"{prompt}\n"
+        self._messages.append({"role": "user", "content": prompt})
         self._user_history.append(prompt)
         agent_response = self._chat(self._full_history)
+        self._messages.append({"role": "assistant", "content": agent_response})
         if self._agent_name:
             self._full_history += f"{self._agent_name}: {agent_response}\n"
         else:

environment.yml

@@ -19,3 +19,4 @@ dependencies:
     - open_clip_torch
     - vosk
     - transformers
+    - openai

requirements.txt

@@ -14,4 +14,5 @@ pydub
 torch
 numpy
 open_clip_torch
-transformers
+transformers
+openai