fix: omit max_tokens from OpenAI requests when None (Azure compatibility)

.github/workflows/build-wheel.yml

@@ -0,0 +1,41 @@
+# Builds the memu-py wheel for linux-x86_64 on every push to main.
+# The uploaded artifact ("memu-wheel") can be consumed cross-repo via
+# actions/download-artifact@v7 with `repository` + `github-token` params,
+# or via the GitHub REST API: GET /repos/{owner}/{repo}/actions/artifacts?name=memu-wheel
+
+name: build-wheel
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build-wheel:
+    name: build linux-x86_64 wheel
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
+        with:
+          python-version: "3.13"
+
+      - name: Setup Rust
+        uses: dtolnay/rust-toolchain@stable
+
+      - name: Install maturin
+        run: uv tool install maturin
+
+      - name: Build wheel
+        run: uvx maturin build --release --out dist --compatibility manylinux_2_39
+
+      - name: Upload wheel artifact
+        uses: actions/upload-artifact@v7
+        with:
+          name: memu-wheel
+          path: dist/*.whl
+          retention-days: 7
+          if-no-files-found: error

src/memu/llm/backends/openai.py

@@ -15,15 +15,17 @@ def build_summary_payload(
         self, *, text: str, system_prompt: str | None, chat_model: str, max_tokens: int | None
     ) -> dict[str, Any]:
         prompt = system_prompt or "Summarize the text in one short paragraph."
-        return {
+        payload: dict[str, Any] = {
             "model": chat_model,
             "messages": [
                 {"role": "system", "content": prompt},
                 {"role": "user", "content": text},
             ],
             "temperature": 0.2,
-            "max_tokens": max_tokens,
         }
+        if max_tokens is not None:
+            payload["max_tokens"] = max_tokens
+        return payload
 
     def parse_summary_response(self, data: dict[str, Any]) -> str:
         return cast(str, data["choices"][0]["message"]["content"])
@@ -56,9 +58,11 @@ def build_vision_payload(
             ],
         })
 
-        return {
+        payload: dict[str, Any] = {
             "model": chat_model,
             "messages": messages,
             "temperature": 0.2,
-            "max_tokens": max_tokens,
         }
+        if max_tokens is not None:
+            payload["max_tokens"] = max_tokens
+        return payload

src/memu/llm/openai_sdk.py

@@ -53,12 +53,15 @@ async def chat(
         user_message: ChatCompletionUserMessageParam = {"role": "user", "content": prompt}
         messages.append(user_message)
 
-        response = await self.client.chat.completions.create(
-            model=self.chat_model,
-            messages=messages,
-            temperature=temperature,
-            max_tokens=max_tokens,
-        )
+        kwargs: dict[str, Any] = {
+            "model": self.chat_model,
+            "messages": messages,
+            "temperature": temperature,
+        }
+        if max_tokens is not None:
+            kwargs["max_tokens"] = max_tokens
+
+        response = await self.client.chat.completions.create(**kwargs)
         content = response.choices[0].message.content
         logger.debug("OpenAI chat response: %s", response)
         return content or "", response
@@ -76,12 +79,15 @@ async def summarize(
         user_message: ChatCompletionUserMessageParam = {"role": "user", "content": text}
         messages: list[ChatCompletionMessageParam] = [system_message, user_message]
 
-        response = await self.client.chat.completions.create(
-            model=self.chat_model,
-            messages=messages,
-            temperature=1,
-            max_tokens=max_tokens,
-        )
+        kwargs: dict[str, Any] = {
+            "model": self.chat_model,
+            "messages": messages,
+            "temperature": 1,
+        }
+        if max_tokens is not None:
+            kwargs["max_tokens"] = max_tokens
+
+        response = await self.client.chat.completions.create(**kwargs)
         content = response.choices[0].message.content
         logger.debug("OpenAI summarize response: %s", response)
         return content or "", response
@@ -142,12 +148,15 @@ async def vision(
         }
         messages.append(user_message)
 
-        response = await self.client.chat.completions.create(
-            model=self.chat_model,
-            messages=messages,
-            temperature=1,
-            max_tokens=max_tokens,
-        )
+        kwargs: dict[str, Any] = {
+            "model": self.chat_model,
+            "messages": messages,
+            "temperature": 1,
+        }
+        if max_tokens is not None:
+            kwargs["max_tokens"] = max_tokens
+
+        response = await self.client.chat.completions.create(**kwargs)
         content = response.choices[0].message.content
         logger.debug("OpenAI vision response: %s", response)
         return content or "", response