fix : adding writer support article, fixed the announcement article and deleted failing multitask.py task

Author: ivanleomk

docs/blog/.authors.yml

@@ -27,4 +27,8 @@ authors:
     name: Thierry Jean
     description: Contributor
     avatar: https://avatars.githubusercontent.com/u/68975210?v=4
-    url: https://www.linkedin.com/in/thierry-jean/
+    url: https://www.linkedin.com/in/thierry-jean/
+  yanomaly:
+    name: Yan
+    description: Contributor
+    avatar: https://avatars.githubusercontent.com/u/87994542?v=4

docs/blog/posts/writer-support.md

@@ -21,7 +21,9 @@ We're excited to announce that `instructor` now supports [Writer](https://writer
 
 ## Getting Started
 
-First, install `instructor` with Writer support by running `pip install instructor[writer]` in your terminal. Then, head over to [Writer](https://writer.com) to sign up for Writer access and get an API key. You can paste API key as environment variable _WRITER_API_KEY_, or set attribute for Writer constructor.
+First, make sure that you've signed up for an account on [Writer](https://writer.com) and obtained an API key. Once you've done so, install `instructor` with Writer support by running `pip install instructor[writer]` in your terminal.
+
+Make sure to set the `WRITER_API_KEY` environment variable with your Writer API key or pass it as an argument to the `Writer` constructor.
 
 <!-- more -->
 
@@ -118,7 +120,7 @@ for obj in extraction_stream:
     #> date='March 15th, 2024' location='Grand Tech Arena, 4521 Innovation Drive' budget=50000 eadline='February 20th'
 ```
 
-As well, if you don't sure that your request will be successfully performed from the first attempt, don't excite we also support retries mechanism! It's quite easy in use:
+As with all our integrations, `instructor` ships with the ability to automatically retry requests that happen due to schema validation without you having to do anything.
 
 ```python
 import instructor
@@ -142,7 +144,7 @@ class User(BaseModel):
         ..., description="The name of the user"
     )
     age: int
-    
+
 
 user = client.chat.completions.create(
     model="palmyra-x-004",
@@ -155,4 +157,6 @@ print(user)
 #> name='JASON' age=12
 ```
 
-And that’s it! We showed only small part of things you can do featuring Writer provider: different types of classification, sentimental analysis and other cool stuff are ready to be used out of the box. We're excited to see what you build with Instructor and Writer! If you have any questions about Writer, do check out the [Writer documentation](https://dev.writer.com/home/introduction).
+This was a sneak peek into the things that you can do with Writer and `instructor` - from classification of text to sentimen analysis and more.
+
+We're excited to see what you build with `instructor` and Writer. If you have any other questions about writer, do check out the [Writer Documentation](https://dev.writer.com/introduction) for the API sdk.

docs/integrations/index.md

@@ -22,11 +22,12 @@ Instructor supports a wide range of AI model providers, each with their own capa
 - [Anthropic](./anthropic.md) - Claude and Claude 2 models
 - [Google](./google.md) - PaLM and Gemini models
 - [Vertex AI](./vertex.md) - Google Cloud's AI platform
-- [Cohere](./cohere.md) - Command and other Cohere models
+- [Cohere](./cohere.md) - Command-R and other Cohere models
 - [Groq](./groq.md) - High-performance inference platform
 - [Mistral](./mistral.md) - Mistral's hosted models
 - [Fireworks](./fireworks.md) - High-performance model inference
-- [Cerebras](./cerebras.md) - AI accelerator platform
+- [Cerebras](./cerebras.md) - Llama-3-70B and other Open Source Models at blazing fast inference speeds
+- [Writer](./writer.md) - Palmyra-X-004 and other Writer models
 
 ### Model Management
 

docs/integrations/writer.md

@@ -0,0 +1,181 @@
+---
+title: Structured Outputs with Writer
+description: Learn how to use Writer for structured outputs using their latest Palmyra-X-004 model for more reliable system outputs
+---
+
+# Structured Outputs with Writer
+
+This guide demonstrates how to use Writer for structured outputs using their latest Palmyra-X-004 model for more reliable system outputs.
+
+You'll need to sign up for an account and get an API key. You can do that [here](https://writer.com).
+
+```bash
+export WRITER_API_KEY=<your-api-key-here>
+pip install "instructor[writer]"
+```
+
+## Palmyra-X-004
+
+Writer supports structured outputs with their latest Palmyra-X-004 model that introduces tool calling functionality
+
+### Sync Example
+
+```python
+import instructor
+from writerai import Writer
+from pydantic import BaseModel
+
+# Initialize Writer client
+client = instructor.from_writer(Writer(api_key="your API key"))
+
+
+class User(BaseModel):
+    name: str
+    age: int
+
+
+# Extract structured data
+user = client.chat.completions.create(
+    model="palmyra-x-004",
+    messages=[{"role": "user", "content": "Extract: John is 30 years old"}],
+    response_model=User,
+)
+
+print(user)
+#> name='John' age=30
+```
+
+### Async Example
+
+```python
+import instructor
+from writerai import AsyncWriter
+from pydantic import BaseModel
+
+# Initialize Writer client
+client = instructor.from_writer(AsyncWriter())
+
+
+class User(BaseModel):
+    name: str
+    age: int
+
+
+async def extract_user():
+    # Extract structured data
+    user = await client.chat.completions.create(
+        model="palmyra-x-004",
+        messages=[{"role": "user", "content": "Extract: John is 30 years old"}],
+        response_model=User,
+    )
+
+    print(user)
+    # > name='John' age=30
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    asyncio.run(extract_user())
+```
+
+## Nested Objects
+
+Writer also supports nested objects, which is useful for extracting data from more complex responses.
+
+```python
+import instructor
+from writerai import Writer
+from pydantic import BaseModel
+
+# Initialize Writer client
+client = instructor.from_writer(Writer())
+
+
+class Address(BaseModel):
+    street: str
+    city: str
+    country: str
+
+
+class User(BaseModel):
+    name: str
+    age: int
+    addresses: list[Address]
+
+
+# Create structured output with nested objects
+user = client.chat.completions.create(
+    model="palmyra-x-004",
+    messages=[
+        {
+            "role": "user",
+            "content": """
+            Extract: Jason is 25 years old.
+            He lives at 123 Main St, New York, USA
+            and has a summer house at 456 Beach Rd, Miami, USA
+        """,
+        },
+    ],
+    response_model=User,
+)
+print(user)
+#> {
+#>     'name': 'Jason',
+#>     'age': 25,
+#>     'addresses': [
+#>         {
+#>             'street': '123 Main St',
+#>             'city': 'New York',
+#>             'country': 'USA'
+#>         },
+#>         {
+#>             'street': '456 Beach Rd',
+#>             'city': 'Miami',
+#>             'country': 'USA'
+#>         }
+#>     ]
+#> }
+```
+
+## Streaming Support
+
+Instructor has two main ways that you can use to stream responses out
+
+1. **Iterables**: These are useful when you'd like to stream a list of objects of the same type (Eg. use structured outputs to extract multiple users)
+2. **Partial Streaming**: This is useful when you'd like to stream a single object and you'd like to immediately start processing the response as it comes in.
+
+We currently support streaming for Writer with native tool for both methods listed above.
+
+### Partial Streaming
+
+```python
+import instructor
+from writerai import Writer
+from pydantic import BaseModel
+
+client = instructor.from_writer(Writer())
+
+
+class Person(BaseModel):
+    name: str
+    age: int
+
+
+resp = client.chat.completions.create_partial(
+    model="palmyra-x-004",
+    messages=[
+        {
+            "role": "user",
+            "content": "Ivan is 27 and lives in Singapore",
+        }
+    ],
+    response_model=Person,
+)
+
+for person in resp:
+    print(person)
+    # > name=None age=None
+    # > name='Ivan' age=None
+    # > name='Ivan' age=27
+```

mkdocs.yml

@@ -223,6 +223,7 @@ nav:
     - OpenAI: 'integrations/openai.md'
     - Together: 'integrations/together.md'
     - Vertex AI: 'integrations/vertex.md'
+    - Writer: 'integrations/writer.md'
   - CLI Reference:
       - "CLI Reference": "cli/index.md"
       - "Finetuning GPT-3.5": "cli/finetune.md"