Add sequence2txt model.py (#1633)

### What problem does this PR solve?

#1514 

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

rag/llm/__init__.py

@@ -17,7 +17,7 @@
 from .chat_model import *
 from .cv_model import *
 from .rerank_model import *
-
+from .sequence2txt_model import *
 
 EmbeddingModel = {
     "Ollama": OllamaEmbed,
@@ -81,3 +81,12 @@
     "Youdao": YoudaoRerank,
     "Xinference": XInferenceRerank
 }
+
+
+Seq2txtModel = {
+    "OpenAI": GPTSeq2txt,
+    "Tongyi-Qianwen": QWenSeq2txt,
+    "Ollama": OllamaSeq2txt,
+    "Azure-OpenAI": AzureSeq2txt,
+    "Xinference": XinferenceSeq2txt
+}

rag/llm/sequence2txt_model.py

@@ -0,0 +1,89 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from openai.lib.azure import AzureOpenAI
+from zhipuai import ZhipuAI
+import io
+from abc import ABC
+from ollama import Client
+from openai import OpenAI
+import os
+import json
+from rag.utils import num_tokens_from_string
+
+
+class Base(ABC):
+    def __init__(self, key, model_name):
+        pass
+
+    def transcription(self, audio, **kwargs):
+        transcription = self.client.audio.transcriptions.create(
+            model=self.model_name,
+            file=audio,
+            response_format="text"
+        )
+        return transcription.text.strip(), num_tokens_from_string(transcription.text.strip())
+
+
+class GPTSeq2txt(Base):
+    def __init__(self, key, model_name="whisper-1", base_url="https://api.openai.com/v1"):
+        if not base_url: base_url = "https://api.openai.com/v1"
+        self.client = OpenAI(api_key=key, base_url=base_url)
+        self.model_name = model_name
+
+
+class QWenSeq2txt(Base):
+    def __init__(self, key, model_name="paraformer-realtime-8k-v1", **kwargs):
+        import dashscope
+        dashscope.api_key = key
+        self.model_name = model_name
+
+    def transcription(self, audio, format):
+        from http import HTTPStatus
+        from dashscope.audio.asr import Recognition
+
+        recognition = Recognition(model=self.model_name,
+                                  format=format,
+                                  sample_rate=16000,
+                                  callback=None)
+        result = recognition.call(audio)
+
+        ans = ""
+        if result.status_code == HTTPStatus.OK:
+            for sentence in result.get_sentence():
+                ans += str(sentence + '\n')
+            return ans, num_tokens_from_string(ans)
+
+        return "**ERROR**: " + result.message, 0
+
+
+class OllamaSeq2txt(Base):
+    def __init__(self, key, model_name, lang="Chinese", **kwargs):
+        self.client = Client(host=kwargs["base_url"])
+        self.model_name = model_name
+        self.lang = lang
+
+
+class AzureSeq2txt(Base):
+    def __init__(self, key, model_name, lang="Chinese", **kwargs):
+        self.client = AzureOpenAI(api_key=key, azure_endpoint=kwargs["base_url"], api_version="2024-02-01")
+        self.model_name = model_name
+        self.lang = lang
+
+
+class XinferenceSeq2txt(Base):
+    def __init__(self, key, model_name="", base_url=""):
+        self.client = OpenAI(api_key="xxx", base_url=base_url)
+        self.model_name = model_name