Bump version to 0.3.0: Merge pull request #5 from atomiechen/dev

Bump version to 0.3.0

.gitignore

@@ -6,3 +6,21 @@ dist
 *.env
 
 venv
+tmp*
+
+# image files
+*.png
+*.jpg
+*.jpeg
+*.gif
+*.svg
+*.ico
+*.pdf
+# audio files
+*.m4a
+*.mp3
+*.mp4
+*.wav
+*.flac
+*.aac
+

README.md

@@ -28,7 +28,9 @@ Example scripts are placed in [tests](./tests) folder.
 
 ## OpenAI API Request
 
-This toolkit uses HTTP API request instead of OpenAI's official python package to support client-side `timeout` control:
+### Timeout control
+
+This toolkit supports client-side `timeout` control, which OpenAI's official python package does not support yet:
 
 ```python
 from handyllm import OpenAIAPI
@@ -44,14 +46,20 @@ response = OpenAIAPI.chat(
 print(response['choices'][0]['message']['content'])
 ```
 
+### Authorization
+
 API key and organization will be loaded using the environment variable `OPENAI_API_KEY` and `OPENAI_ORGANIZATION`, or you can set manually:
 
 ```python
 OpenAIAPI.api_key = 'sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'
 OpenAIAPI.organization = '......'  # default: None
 ```
 
-Stream response of `chat`/`completions` can be achieved using `steam` parameter:
+Or, you can pass `api_key` and `organization` parameters in each API call.
+
+### Stream response
+
+Stream response of `chat`/`completions`/`finetunes_list_events` can be achieved using `steam` parameter:
 
 ```python
 response = OpenAIAPI.chat(
@@ -71,10 +79,40 @@ for text in OpenAIAPI.stream_chat(response):
 #         print(chunk['choices'][0]['delta']['content'], end='')
 ```
 
+### Supported APIs
+
+- chat
+- completions
+- edits
+- embeddings
+- models_list
+- models_retrieve
+- moderations
+- images_generations
+- images_edits
+- images_variations
+- audio_transcriptions
+- audtio_translations
+- files_list
+- files_upload
+- files_delete
+- files_retrieve
+- files_retrieve_content
+- finetunes_create
+- finetunes_list
+- finetunes_retrieve
+- finetunes_cancel
+- finetunes_list_events
+- finetunes_delete_model
+
+Please refer to [OpenAI official API reference](https://platform.openai.com/docs/api-reference) for details.
+
 
 
 ## Prompt
 
+### Prompt Conversion
+
 `PromptConverter` can convert this text file `prompt.txt` into a structured prompt for chat API calls:
 
 ```
@@ -109,7 +147,7 @@ chat = converter.rawfile2chat('prompt.txt')
 new_chat = converter.chat_replace_variables(chat, {r'%misc%': 'Note: do not use any bad word.'})
 ```
 
-
+### Substitute
 
 `PromptConverter` can also substitute placeholder variables like `%output_format%` stored in text files to make multiple prompts modular. A substitute map `substitute.txt` looks like this:
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "HandyLLM"
-version = "0.2.1"
+version = "0.3.0"
 authors = [
   { name="Atomie CHEN", email="atomic_cwh@163.com" },
 ]

src/handyllm/openai_api.py

@@ -33,7 +33,7 @@ def _get_organization_from_env():
         return os.environ.get('OPENAI_ORGANIZATION')
 
     @staticmethod
-    def _api_request(url, api_key, organization=None, timeout=None, **kwargs):
+    def _api_request(url, api_key, organization=None, method='post', timeout=None, **kwargs):
         if api_key is None:
             raise Exception("OpenAI API key is not set")
         if url is None:
@@ -50,20 +50,31 @@ def _api_request(url, api_key, organization=None, timeout=None, **kwargs):
         log_strs.append(f"timeout: {timeout}")
         module_logger.info('\n'.join(log_strs))
 
-        request_data = kwargs
-        headers = {
-            'Authorization': 'Bearer ' + api_key,
-            'Content-Type': 'application/json'
-            }
+        files = kwargs.pop('files', None)
+        stream = kwargs.get('stream', False)
+        headers = { 'Authorization': 'Bearer ' + api_key }
+        json_data = None
+        data = None
+        params = None
         if organization is not None:
             headers['OpenAI-Organization'] = organization
-
-        stream = kwargs.get('stream', False)
-        response = requests.post(
-            url, 
-            headers=headers, 
-            # data=json.dumps(request_data),
-            json=request_data,
+        if method == 'post':
+            if files is None:
+                headers['Content-Type'] = 'application/json'
+                json_data = kwargs
+            else:  ## if files is not None, let requests handle the content type
+                data = kwargs
+        if method == 'get' and stream:
+            params = { "stream": "true" }
+
+        response = requests.request(
+            method,
+            url,
+            headers=headers,
+            data=data,
+            json=json_data,
+            files=files,
+            params=params,
             stream=stream,
             timeout=timeout,
             )
@@ -105,18 +116,30 @@ def stream_completions(response):
 
     @staticmethod
     def api_request_endpoint(request_url, endpoint_manager=None, **kwargs):
+        specified_api_key = kwargs.pop('api_key', None)
+        specified_organization = kwargs.pop('organization', None)
         if endpoint_manager != None:
             # 每次换服务器和key要同时换，保证服务器和key是对应的
             base_url, api_key, organization = endpoint_manager.get_endpoint()
         else:
             base_url = OpenAIAPI.base_url
-            api_key = OpenAIAPI.api_key if OpenAIAPI.api_key is not None else OpenAIAPI._get_key_from_env()
-            organization = OpenAIAPI.organization if OpenAIAPI.organization is not None else OpenAIAPI._get_organization_from_env()
+            if specified_api_key is not None:
+                api_key = specified_api_key
+            elif OpenAIAPI.api_key is not None:
+                api_key = OpenAIAPI.api_key
+            else:
+                api_key = OpenAIAPI._get_key_from_env()
+            if specified_organization is not None:
+                organization = specified_organization
+            elif OpenAIAPI.organization is not None:
+                organization = OpenAIAPI.organization 
+            else:
+                organization = OpenAIAPI._get_organization_from_env()
         url = base_url + request_url
         return OpenAIAPI._api_request(url, api_key, organization=organization, **kwargs)
 
     @staticmethod
-    def chat(timeout=None, endpoint_manager=None, logger=None, log_marks=[], **kwargs):
+    def chat(model, messages, timeout=None, endpoint_manager=None, logger=None, log_marks=[], **kwargs):
         request_url = '/chat/completions'
 
         if logger is not None and 'messages' in kwargs:
@@ -131,7 +154,7 @@ def chat(timeout=None, endpoint_manager=None, logger=None, log_marks=[], **kwarg
 
         start_time = time.time()
         try:
-            response = OpenAIAPI.api_request_endpoint(request_url, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+            response = OpenAIAPI.api_request_endpoint(request_url, model=model, messages=messages, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
 
             if logger is not None:
                 end_time = time.time()
@@ -170,7 +193,7 @@ def wrapper(response):
         return response
 
     @staticmethod
-    def completions(timeout=None, endpoint_manager=None, logger=None, log_marks=[], **kwargs):
+    def completions(model, prompt, timeout=None, endpoint_manager=None, logger=None, log_marks=[], **kwargs):
         request_url = '/completions'
 
         if logger is not None and 'prompt' in kwargs:
@@ -185,7 +208,7 @@ def completions(timeout=None, endpoint_manager=None, logger=None, log_marks=[],
 
         start_time = time.time()
         try:
-            response = OpenAIAPI.api_request_endpoint(request_url, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+            response = OpenAIAPI.api_request_endpoint(request_url, model=model, prompt=prompt, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
 
             if logger is not None:
                 end_time = time.time()
@@ -223,9 +246,116 @@ def wrapper(response):
         return response
 
     @staticmethod
-    def embeddings(timeout=None, endpoint_manager=None, **kwargs):
+    def edits(model, instruction, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/edits'
+        return OpenAIAPI.api_request_endpoint(request_url, model=model, instruction=instruction, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def embeddings(model, input, timeout=None, endpoint_manager=None, **kwargs):
         request_url = '/embeddings'
-        return OpenAIAPI.api_request_endpoint(request_url, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+        return OpenAIAPI.api_request_endpoint(request_url, model=model, input=input, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def models_list(timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/models'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def models_retrieve(model, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/models/{model}'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def moderations(input, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/moderations'
+        return OpenAIAPI.api_request_endpoint(request_url, input=input, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def images_generations(prompt, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/images/generations'
+        return OpenAIAPI.api_request_endpoint(request_url, prompt=prompt, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def images_edits(image, prompt, mask=None, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/images/edits'
+        files = { 'image': image }
+        if mask:
+            files['mask'] = mask
+        return OpenAIAPI.api_request_endpoint(request_url, prompt=prompt, method='post', files=files, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def images_variations(image, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/images/variations'
+        files = { 'image': image }
+        return OpenAIAPI.api_request_endpoint(request_url, method='post', files=files, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def audio_transcriptions(file, model, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/audio/transcriptions'
+        files = { 'file': file }
+        return OpenAIAPI.api_request_endpoint(request_url, model=model, method='post', files=files, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def audio_translations(file, model, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/audio/translations'
+        files = { 'file': file }
+        return OpenAIAPI.api_request_endpoint(request_url, model=model, method='post', files=files, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def files_list(timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/files'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def files_upload(file, purpose, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/files'
+        files = { 'file': file }
+        return OpenAIAPI.api_request_endpoint(request_url, purpose=purpose, method='post', files=files, timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def files_delete(file_id, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/files/{file_id}'
+        return OpenAIAPI.api_request_endpoint(request_url, method='delete', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def files_retrieve(file_id, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/files/{file_id}'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def files_retrieve_content(file_id, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/files/{file_id}/content'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def finetunes_create(training_file, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/fine-tunes'
+        return OpenAIAPI.api_request_endpoint(request_url, training_file=training_file, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def finetunes_list(timeout=None, endpoint_manager=None, **kwargs):
+        request_url = '/fine-tunes'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def finetunes_retrieve(fine_tune_id, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/fine-tunes/{fine_tune_id}'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def finetunes_cancel(fine_tune_id, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/fine-tunes/{fine_tune_id}/cancel'
+        return OpenAIAPI.api_request_endpoint(request_url, method='post', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def finetunes_list_events(fine_tune_id, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/fine-tunes/{fine_tune_id}/events'
+        return OpenAIAPI.api_request_endpoint(request_url, method='get', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
+
+    @staticmethod
+    def finetunes_delete_model(model, timeout=None, endpoint_manager=None, **kwargs):
+        request_url = f'/models/{model}'
+        return OpenAIAPI.api_request_endpoint(request_url, method='delete', timeout=timeout, endpoint_manager=endpoint_manager, **kwargs)
 
 
 if __name__ == '__main__':

src/handyllm/utils.py

@@ -0,0 +1,25 @@
+import requests
+from urllib.parse import urlparse
+import os
+import time
+
+
+def get_filename_from_url(download_url):
+    # Parse the URL.
+    parsed_url = urlparse(download_url)
+    # The last part of the path is usually the filename.
+    filename = os.path.basename(parsed_url.path)
+    return filename
+
+def download_binary(download_url, file_path=None, dir='.'):
+    response = requests.get(download_url, allow_redirects=True)
+    if file_path == None:
+        filename = get_filename_from_url(download_url)
+        if filename == '' or filename == None:
+            filename = 'download_' + time.strftime("%Y%m%d_%H%M%S")
+        file_path = os.path.abspath(os.path.join(dir, filename))
+    # Open the file in binary mode and write to it.
+    with open(file_path, "wb") as file:
+        file.write(response.content)
+    return file_path
+

tests/test_audio.py

@@ -0,0 +1,17 @@
+from handyllm import OpenAIAPI
+
+from dotenv import load_dotenv, find_dotenv
+# load env parameters from file named .env
+# API key is read from environment variable OPENAI_API_KEY
+# organization is read from environment variable OPENAI_ORGANIZATION
+load_dotenv(find_dotenv())
+
+file_path = 'hello.m4a'
+
+with open(file_path, "rb") as file_bin:
+    response = OpenAIAPI.audio_transcriptions(
+        file=file_bin,
+        model='whisper-1',
+        # timeout=10,
+    )
+print(response['text'])