PEP 621

autogen/oai/client.py

@@ -287,22 +287,42 @@ def yes_or_no_filter(context, response):
 
     def _completions_create(self, client, params):
         completions = client.chat.completions if "messages" in params else client.completions
-        # If streaming is enabled, has messages, and does not have functions, then
-        # iterate over the chunks of the response
-        if params.get("stream", False) and "messages" in params and "functions" not in params:
+        # If streaming is enabled and has messages, then iterate over the chunks of the response.
+        if params.get("stream", False) and "messages" in params:
             response_contents = [""] * params.get("n", 1)
             finish_reasons = [""] * params.get("n", 1)
             completion_tokens = 0
 
             # Set the terminal text color to green
             print("\033[32m", end="")
 
+            # Prepare for potential function call
+            full_function_call = None
             # Send the chat completion request to OpenAI's API and process the response in chunks
             for chunk in completions.create(**params):
                 if chunk.choices:
                     for choice in chunk.choices:
                         content = choice.delta.content
+                        function_call_chunk = choice.delta.function_call
                         finish_reasons[choice.index] = choice.finish_reason
+
+                        # Handle function call
+                        if function_call_chunk:
+                            if hasattr(function_call_chunk, "name") and function_call_chunk.name:
+                                if full_function_call is None:
+                                    full_function_call = {"name": "", "arguments": ""}
+                                full_function_call["name"] += function_call_chunk.name
+                                completion_tokens += 1
+                            if hasattr(function_call_chunk, "arguments") and function_call_chunk.arguments:
+                                full_function_call["arguments"] += function_call_chunk.arguments
+                                completion_tokens += 1
+                        if choice.finish_reason == "function_call":
+                            # Need something here? I don't think so.
+                            pass
+                        if not content:
+                            continue
+                        # End handle function call
+
                         # If content is present, print it to the terminal and update response variables
                         if content is not None:
                             print(content, end="", flush=True)
@@ -336,7 +356,7 @@ def _completions_create(self, client, params):
                         index=i,
                         finish_reason=finish_reasons[i],
                         message=ChatCompletionMessage(
-                            role="assistant", content=response_contents[i], function_call=None
+                            role="assistant", content=response_contents[i], function_call=full_function_call
                         ),
                         logprobs=None,
                     )
@@ -346,16 +366,14 @@ def _completions_create(self, client, params):
                         index=i,
                         finish_reason=finish_reasons[i],
                         message=ChatCompletionMessage(
-                            role="assistant", content=response_contents[i], function_call=None
+                            role="assistant", content=response_contents[i], function_call=full_function_call
                         ),
                     )
 
                 response.choices.append(choice)
         else:
-            # If streaming is not enabled or using functions, send a regular chat completion request
-            # Functions are not supported, so ensure streaming is disabled
+            # If streaming is not enabled, send a regular chat completion request
             params = params.copy()
-            params["stream"] = False
             response = completions.create(**params)
         return response
 

pyproject.toml

@@ -49,3 +49,71 @@ unfixable = ["F401"]
 [tool.ruff.mccabe]
 # Unlike Flake8, default to a complexity level of 10.
 max-complexity = 10
+
+[project]
+name = "pyautogen"
+version = "0.2.2"
+description = "Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework"
+readme = "README.md"
+authors = [
+    {name = "AutoGen", email = "[email protected]"},
+]
+classifiers = [
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent",
+    "Programming Language :: Python :: 3",
+]
+requires-python = ">=3.9, <3.12"
+dependencies = [
+    "diskcache",
+    "flaml",
+    "openai~=1.3",
+    "python-dotenv",
+    "termcolor",
+    "tiktoken",
+    "openai>=1.3",
+    "pydantic>=1.10,<3",
+]
+
+[project.urls]
+Homepage = "https://github.com/microsoft/autogen"
+
+[project.optional-dependencies]
+test = [
+    "coverage>=5.3",
+    "ipykernel",
+    "nbconvert",
+    "nbformat",
+    "pre-commit",
+    "pytest-asyncio",
+    "pytest>=6.1.1",
+]
+blendsearch = [
+    "flaml[blendsearch]",
+]
+mathchat = [
+    "pydantic==1.10.9",
+    "sympy",
+    "wolframalpha",
+]
+retrievechat = [
+    "chromadb",
+    "ipython",
+    "pypdf",
+    "sentence_transformers",
+]
+teachable = [
+    "chromadb",
+]
+lmm = [
+    "pillow",
+    "replicate",
+]
+graphs = [
+    "matplotlib~=3.8.1",
+    "networkx~=3.2.1",
+]
+
+[build-system]
+requires = ["pdm-backend"]
+build-backend = "pdm.backend"

website/docs/Installation.md

@@ -31,19 +31,19 @@ The following command will deactivate the current `conda` environment:
 conda deactivate
 ```
 
-### Option 3: poetry
+### Option 3: pdm
 
-Another option is with `poetry`, which is a dependency manager for Python.
+Another option is with `pdm`, which is a dependency manager for Python.
 
-[Poetry](https://python-poetry.org/docs/) is a tool for dependency management and packaging in Python. It allows you to declare the libraries your project depends on and it will manage (install/update) them for you. Poetry offers a lockfile to ensure repeatable installs, and can build your project for distribution.
+[PDM](https://python-poetry.org/docs/) is a tool for dependency management and packaging in Python. It allows you to declare the libraries your project depends on and it will manage (install/update) them for you. PDM offers a lockfile to ensure repeatable installs, and can build your project for distribution.
 
-You can install it by following [this doc](https://python-poetry.org/docs/#installation),
+You can install it by following [this doc](https://pdm-project.org/latest/#installation),
 and then create a virtual environment as below:
 ```bash
-poetry init
-poetry shell
+pdm init
+pdm venv activate
 
-poetry add pyautogen
+pdm add pyautogen
 ```
 
 The following command will deactivate the current `poetry` environment: