Add spec changes

Co-authored-by: billytrend-cohere <[email protected]>

snippets/snippets/node/chat-v2-post/default.ts

@@ -0,0 +1,19 @@
+const { CohereClientV2 } = require('cohere-ai');
+
+const cohere = new CohereClientV2({
+  token: '<<apiKey>>',
+});
+
+(async () => {
+  const response = await cohere.chat({
+    model: 'command-r-plus',
+    messages: [
+      {
+        role: 'user',
+        content: 'hello world!',
+      },
+    ],
+  });
+
+  console.log(response);
+})();

snippets/snippets/node/chat-v2-post/documents.ts

@@ -0,0 +1,22 @@
+const { CohereClientV2 } = require('cohere-ai');
+
+const cohere = new CohereClientV2({
+  token: '<<apiKey>>',
+});
+
+(async () => {
+  const response = await cohere.chat({
+    model: 'command-r-plus',
+    messages: [
+      {
+        role: 'user',
+        content: [
+          { type: 'document', id: '1', document: { text: 'Cohere is the best!' } },
+          { type: 'text', text: "Who's the best?" },
+        ],
+      },
+    ],
+  });
+
+  console.log(response);
+})();

snippets/snippets/node/chat-v2-post/stream.ts

@@ -0,0 +1,23 @@
+const { CohereClientV2 } = require('cohere-ai');
+
+const cohere = new CohereClientV2({
+  token: '<<apiKey>>',
+});
+
+(async () => {
+  const stream = await cohere.chatStream({
+    model: 'command-r-plus',
+    messages: [
+      {
+        role: 'user',
+        content: 'hello world!',
+      },
+    ],
+  });
+
+  for await (const chatEvent of stream) {
+    if (chatEvent.type === 'content-delta') {
+      console.log(chatEvent.delta?.message);
+    }
+  }
+})();

snippets/snippets/node/chat-v2-post/tools.ts

@@ -0,0 +1,52 @@
+const { CohereClientV2 } = require('cohere-ai');
+
+const cohere = new CohereClientV2({
+  token: '<<apiKey>>',
+});
+
+(async () => {
+  const response = await cohere.chat({
+    model: 'command-r-plus',
+    tools: [
+      {
+        type: 'function',
+        function: {
+          name: 'query_daily_sales_report',
+          description:
+            'Connects to a database to retrieve overall sales volumes and sales information for a given day.',
+          parameters: {
+            day: {
+              description: 'Retrieves sales data for this day, formatted as YYYY-MM-DD.',
+              type: 'str',
+              required: true,
+            },
+          },
+        },
+      },
+      {
+        type: 'function',
+        function: {
+          name: 'query_product_catalog',
+          description:
+            'Connects to a a product catalog with information about all the products being sold, including categories, prices, and stock levels.',
+          parameters: {
+            category: {
+              description: 'Retrieves product information data for all products in this category.',
+              type: 'str',
+              required: true,
+            },
+          },
+        },
+      },
+    ],
+    messages: [
+      {
+        role: 'user',
+        content:
+          "Can you provide a sales summary for 29th September 2023, and also give me some details about the products in the 'Electronics' category, for example their prices and stock levels?",
+      },
+    ],
+  });
+
+  console.log(response);
+})();

snippets/snippets/python-async/chat-v2-post.py

@@ -0,0 +1,19 @@
+import cohere
+import asyncio
+
+co = cohere.AsyncClientV2("<<apiKey>>")
+
+
+async def main():
+    response = await co.chat(
+        model="command-r-plus",
+        messages=[
+            cohere.v2.ChatMessage2_User(
+                content="hello world!"
+            )
+        ]
+    )
+
+    print(response)
+
+asyncio.run(main())

snippets/snippets/python-async/embed-jobs-post.py

@@ -6,8 +6,8 @@
 
 async def main():
     # start an embed job
-    response = await co.embed_jobs.create(
-        dataset_id=ds.id, input_type="search_document", model="embed-english-v3.0"
+    job = await co.embed_jobs.create(
+        dataset_id="my-dataset-id", input_type="search_document", model="embed-english-v3.0"
     )
 
     # poll the server until the job is complete

snippets/snippets/python-async/finetuning/create-finetuned-model.py

@@ -16,7 +16,7 @@ async def main():
             name="test-finetuned-model",
             settings=Settings(
                 base_model=BaseModel(
-                    base_type=BaseType.BASE_TYPE_GENERATIVE,
+                    base_type=BaseType.BASE_TYPE_CHAT,
                 ),
                 dataset_id="my-dataset-id",
             ),

snippets/snippets/python/chat-v2-post/default.py

@@ -0,0 +1,14 @@
+import cohere
+
+co = cohere.ClientV2("<<apiKey>>")
+
+response = co.chat(
+    model="command-r-plus",
+    messages=[
+        cohere.v2.ChatMessage2_User(
+            content="hello world!"
+        )
+    ]
+)
+
+print(response)

snippets/snippets/python/chat-v2-post/documents.py

@@ -0,0 +1,21 @@
+import cohere
+
+co = cohere.ClientV2("<<apiKey>>")
+
+response = co.chat(
+    model="command-r-plus",
+    messages=[
+        cohere.v2.ChatMessage2_User(
+            content=[
+                cohere.v2.DocumentContent(
+                    id=1,
+                    document={'title': 'The best',
+                              'text': 'Cohere is the best!'}
+                ),
+                cohere.v2.TextContent(text="Who's the best?"),
+            ]
+        )
+    ]
+)
+
+print(response)

snippets/snippets/python/chat-v2-post/stream.py

@@ -0,0 +1,16 @@
+import cohere
+
+co = cohere.ClientV2("<<apiKey>>")
+
+response = co.chat_stream(
+    model="command-r-plus",
+    messages=[
+        cohere.v2.ChatMessage2_User(
+            content="hello world!"
+        )
+    ]
+)
+
+for event in response:
+    if event.event_type == "text-generation":
+        print(event.text, end='')

snippets/snippets/python/chat-v2-post/tools.py

@@ -0,0 +1,38 @@
+import cohere
+
+co = cohere.Client("<<apiKey>>")
+
+response = co.chat(
+    model="command-r-plus",
+    tools=[
+        cohere.v2.Tool2(type='function', function={
+            "name": 'query_daily_sales_report',
+                    "description": 'Connects to a database to retrieve overall sales volumes and sales information for a given day.',
+                    "parameters": {
+                        "day": {
+                            "description": 'Retrieves sales data for this day, formatted as YYYY-MM-DD.',
+                            "type": 'str',
+                            "required": True,
+                        },
+                    }
+        }),
+        cohere.v2.Tool2(type='function', function={
+            "name": 'query_product_catalog',
+                    "description": 'Connects to a a product catalog with information about all the products being sold, including categories, prices, and stock levels.',
+                    "parameters": {
+                        "category": {
+                            "description": 'Retrieves product information data for all products in this category.',
+                            "type": 'str',
+                            "required": True,
+                        },
+                    }
+        })
+    ],
+    messages=[
+        cohere.v2.ChatMessage2_User(
+            content="Can you provide a sales summary for 29th September 2023, and also give me some details about the products in the 'Electronics' category, for example their prices and stock levels?"
+        )
+    ]
+)
+
+print(response)

snippets/snippets/python/dataset-post.py

@@ -3,7 +3,7 @@
 co = cohere.Client("<<apiKey>>")
 
 # upload a dataset
-response = co.datasets.create(
+my_dataset = co.datasets.create(
     name="prompt-completion-dataset",
     data=open("./prompt-completion.jsonl", "rb"),
     type="prompt-completion-finetune-input",

snippets/snippets/python/embed-jobs-post.py

@@ -3,8 +3,8 @@
 co = cohere.Client("<<apiKey>>")
 
 # start an embed job
-response = co.embed_jobs.create(
-    dataset_id=ds.id, input_type="search_document", model="embed-english-v3.0"
+job = co.embed_jobs.create(
+    dataset_id="my-dataset-id", input_type="search_document", model="embed-english-v3.0"
 )
 
 # poll the server until the job is complete

snippets/snippets/python/finetuning/create-finetuned-model.py

@@ -3,6 +3,7 @@
     FinetunedModel,
     Hyperparameters,
     Settings,
+    WandbConfig
 )
 import cohere
 
@@ -14,6 +15,11 @@
     train_epoch=1,
     learning_rate=0.01,
 )
+wnb_config = WandbConfig(
+    project="test-project",
+    api_key="<<wandbApiKey>>",
+    entity="test-entity",
+)
 finetuned_model = co.finetuning.create_finetuned_model(
     request=FinetunedModel(
         name="test-finetuned-model",
@@ -23,7 +29,8 @@
             ),
             dataset_id="my-dataset-id",
             hyperparameters=hp,
+            wandb=wnb_config,
         ),
     )
 )
-print(response)
+print(finetuned_model)

snippets/snippets/python/finetuning/update-finetuned-model.py

@@ -1,3 +1,7 @@
+from cohere.finetuning import (
+    BaseModel,
+    Settings,
+)
 import cohere
 
 co = cohere.Client("<<apiKey>>")