Merge branch 'main' into get-started

cohere-ai · Jan 8, 2025 · 8577933 · 8577933
2 parents 8c728c5 + 079c369
commit 8577933
Show file tree

Hide file tree

Showing 17 changed files with 143 additions and 63 deletions.
diff --git a/cohere-openapi.yaml b/cohere-openapi.yaml
@@ -17521,13 +17521,16 @@ paths:
                 	"context"
                 	"log"
 
+                	cohere "github.com/cohere-ai/cohere-go/v2"
                 	client "github.com/cohere-ai/cohere-go/v2/client"
                 )
 
                 func main() {
                 	co := client.NewClient()
 
-                	resp, err := co.Datasets.Get(context.TODO(), "dataset_id")
+                	resp, err := co.Datasets.List(
+                		context.TODO(),
+                		&cohere.DatasetsListRequest{})
 
                 	if err != nil {
                 		log.Fatal(err)
@@ -17542,8 +17545,8 @@ paths:
 
                 co = cohere.Client()
 
-                # get dataset
-                response = co.datasets.get(id="<<datasetId>>")
+                # get list of datasets
+                response = co.datasets.list()
 
                 print(response)
             - sdk: python
@@ -17556,7 +17559,7 @@ paths:
 
 
                 async def main():
-                    response = await co.datasets.get(id="<<datasetId>>")
+                    response = await co.datasets.list()
 
                     print(response)
 
@@ -17577,7 +17580,7 @@ paths:
                   public static void main(String[] args) {
                     Cohere cohere = Cohere.builder().clientName("snippet").build();
 
-                    DatasetsGetResponse response = cohere.datasets().get("dataset_id");
+                    DatasetsGetResponse response = cohere.datasets().list();
 
                     System.out.println(response);
                   }
@@ -17590,13 +17593,13 @@ paths:
                 const cohere = new CohereClient({});
 
                 (async () => {
-                  const datasets = await cohere.datasets.get('<<datasetId>>');
+                  const datasets = await cohere.datasets.list();
 
                   console.log(datasets);
                 })();
             - sdk: curl
               name: cURL
-              code: |-
+              code: |
                 curl --request GET \
                   --url https://api.cohere.com/v1/datasets \
                   --header 'accept: application/json' \
@@ -17891,9 +17894,9 @@ paths:
                 })();
             - sdk: curl
               name: cURL
-              code: |-
+              code: |
                 curl --request GET \
-                  --url https://api.cohere.com/v1/datasets \
+                  --url https://api.cohere.com/v1/datasets/id \
                   --header 'accept: application/json' \
                   --header "Authorization: bearer $CO_API_KEY"
       responses:
@@ -22948,8 +22951,11 @@ components:
             delta:
               type: object
               properties:
-                tool_plan:
-                  type: string
+                message:
+                  type: object
+                  properties:
+                    tool_plan:
+                      type: string
     ChatToolCallStartEvent:
       description: A streamed event delta which signifies a tool call has started streaming.
       allOf:
@@ -22961,22 +22967,11 @@ components:
             delta:
               type: object
               properties:
-                tool_call:
+                message:
                   type: object
                   properties:
-                    id:
-                      type: string
-                    type:
-                      type: string
-                      enum:
-                        - function
-                    function:
-                      type: object
-                      properties:
-                        name:
-                          type: string
-                        arguments:
-                          type: string
+                    tool_calls:
+                      $ref: "#/components/schemas/ToolCallV2"
     ChatToolCallDeltaEvent:
       description: A streamed event delta which signifies a delta in tool call arguments.
       allOf:
@@ -22988,14 +22983,17 @@ components:
             delta:
               type: object
               properties:
-                tool_call:
+                message:
                   type: object
                   properties:
-                    function:
+                    tool_calls:
                       type: object
                       properties:
-                        arguments:
-                          type: string
+                        function:
+                          type: object
+                          properties:
+                            arguments:
+                              type: string
     ChatToolCallEndEvent:
       description: A streamed event delta which signifies a tool call has finished
         streaming.

diff --git a/fern/pages/v2/fine-tuning/classify-fine-tuning/classify-starting-the-training.mdx b/fern/pages/v2/fine-tuning/classify-fine-tuning/classify-starting-the-training.mdx
@@ -94,20 +94,24 @@ Using `co.finetuning.create_finetuned_model()`, you can create a fine-tuned mode
 
 Here are some example code snippets for you to use.
 
-### Starting a Single-label Fine-tune
+### Starting a single-label fine-tuning job
 
 ```python PYTHON
 # create dataset
-single_label_dataset = co.datasets.create(name="single-label-dataset",
-                                          data=open("path/to/train.csv, "rb"),
-                                          type="single-label-finetune-input",
-                                          parse_info=ParseInfo(delimiter=",")) # parse_info is optional
-print(single_label_dataset.await_validation())
+single_label_dataset = co.datasets.create(
+    name="single-label-dataset",
+    data=open("single_label_dataset.jsonl", "rb"),
+    type="single-label-classification-finetune-input",
+)
+
+print(co.wait(single_label_dataset).dataset.validation_status)
 
 # start the fine-tune job using this dataset
-finetune = co.finetuning.create_finetuned_model(
+from cohere.finetuning.finetuning import BaseModel, FinetunedModel, Settings
+
+single_label_finetune = co.finetuning.create_finetuned_model(
   request=FinetunedModel(
-    name="single-label-ft",
+    name="single-label-finetune",
     settings=Settings(
       base_model=BaseModel(
         base_type="BASE_TYPE_CLASSIFICATION",
@@ -117,50 +121,54 @@ finetune = co.finetuning.create_finetuned_model(
   ),
 )
 
-print(f"fine-tune ID: {finetune.id}, fine-tune status: {finetune.status}")
+print(f"fine-tune ID: {single_label_finetune.finetuned_model.id}, fine-tune status: {single_label_finetune.finetuned_model.status}")
 ```
 
-### Starting a Multi-label Fine-tune
+### Starting a multi-label fine-tuning job
 
 ```python PYTHON
 # create dataset
-multi_label_dataset = co.create_dataset(name="multi-label-dataset",
-                                        data=open("path/to/train.jsonl", "rb"),
-                                        dataset_type="multi-label-finetune-input")
-
-print(multi_label_dataset.await_validation())
+multi_label_dataset = co.datasets.create(
+    name="multi-label-dataset",
+    data=open("multi_label_dataset.jsonl", "rb"),
+    type="multi-label-classification-finetune-input",
+)
+
+print(co.wait(multi_label_dataset).dataset.validation_status)
 
 # start the fine-tune job using this dataset
-finetune = co.finetuning.create_finetuned_model(
+from cohere.finetuning.finetuning import BaseModel, FinetunedModel, Settings
+
+multi_label_finetune = co.finetuning.create_finetuned_model(
   request=FinetunedModel(
-    name="single-label-ft",
+    name="multi-label-finetune",
     settings=Settings(
       base_model=BaseModel(
         base_type="BASE_TYPE_CLASSIFICATION",
       ),
-      dataset_id=single_label_dataset.id,
+      dataset_id=multi_label_dataset.id,
     ),
   ),
 )
 
-print(f"fine-tune ID: {finetune.id}, fine-tune status: {finetune.status}")
+print(f"fine-tune ID: {multi_label_finetune.finetuned_model.id}, fine-tune status: {multi_label_finetune.finetuned_model.status}")
 ```
 
-### Calling a fine-tune
+### Calling a fine-tuned model
 
 ```python PYTHON
 import cohere
 
 co = cohere.ClientV2('Your API key')
-# get the custom model object
-ft = co.finetuning.get_finetuned_model(finetune.finetuned_model.id)
+# get the custom model object (replace with your finetune name e.g. multi_label_finetune)
+model_id = single_label_finetune.finetuned_model.id
+
 
 response = co.classify(
     inputs=["classify this!"],
-    model=ft.id+"-ft",
+    model=model_id+"-ft"
 )
 
-# Printing the model's response.
 print(response)
 ```
 

diff --git a/fern/pages/v2/text-generation/structured-outputs.mdx b/fern/pages/v2/text-generation/structured-outputs.mdx
@@ -4,7 +4,7 @@ slug: "v2/docs/structured-outputs"
 
 hidden: false
 
-description: "This page describes how to get Cohere models to create outputs in a certain format, such as JSON."
+description: "This page describes how to get Cohere models to create outputs in a certain format, such as JSON, TOOLS."
 image: "../../../assets/images/f1cc130-cohere_meta_image.jpg"  
 keywords: "Cohere, language models, structured outputs"
 

diff --git a/.../pages/v2/tutorials/build-things-with-cohere/building-a-chatbot-with-cohere.mdx b/.../pages/v2/tutorials/build-things-with-cohere/building-a-chatbot-with-cohere.mdx
@@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg"
 keywords: "Cohere, chatbot"
 ---
 
-<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt3.ipynb">Open in Colab</a>
+<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt3_v2.ipynb">Open in Colab</a>
 
 As its name implies, the Chat endpoint enables developers to build chatbots that can handle conversations. At the core of a conversation is a multi-turn dialog between the user and the chatbot. This requires the chatbot to have the state (or “memory”) of all the previous turns to maintain the state of the conversation.
 

diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/building-an-agent-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/building-an-agent-with-cohere.mdx
@@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg"
 keywords: "Cohere, agents"
 ---
 
-<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt7.ipynb">Open in Colab</a>
+<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt7_v2.ipynb">Open in Colab</a>
 
 Tool use extends the ideas from [RAG](/v2/docs/rag-with-cohere), where external systems are used to guide the response of an LLM, but by leveraging a much bigger set of tools than what’s possible with RAG. The concept of tool use leverages LLMs' useful feature of being able to act as a reasoning and decision-making engine.
 

diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/rag-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/rag-with-cohere.mdx
@@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg"
 keywords: "Cohere, retrieval-augmented generation, RAG"
 ---
 
-<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt6.ipynb">Open in Colab</a>
+<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt6_v2.ipynb">Open in Colab</a>
 
 The Chat endpoint provides comprehensive support for various text generation use cases, including retrieval-augmented generation (RAG). 
 

diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/reranking-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/reranking-with-cohere.mdx
@@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg"
 keywords: "Cohere, language models, ReRank models"
 ---
 
-<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt5.ipynb">Open in Colab</a>
+<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt5_v2.ipynb">Open in Colab</a>
 
 Reranking is a technique that leverages [embeddings](/v2/docs/embeddings) as the last stage of a retrieval process, and is especially useful in [RAG systems](/v2/docs/retrieval-augmented-generation-rag).
 

diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/semantic-search-with-cohere.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/semantic-search-with-cohere.mdx
@@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg"
 keywords: "Cohere, language models, "
 ---
 
-<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt4.ipynb">Open in Colab</a>
+<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt4_v2.ipynb">Open in Colab</a>
 
 [Text embeddings](/v2/docs/embeddings) are lists of numbers that represent the context or meaning inside a piece of text. This is particularly useful in search or information retrieval applications. With text embeddings, this is called semantic search.
 

diff --git a/fern/pages/v2/tutorials/build-things-with-cohere/text-generation-tutorial.mdx b/fern/pages/v2/tutorials/build-things-with-cohere/text-generation-tutorial.mdx
@@ -7,7 +7,7 @@ image: "../../../../assets/images/f1cc130-cohere_meta_image.jpg"
 keywords: "Cohere, how do LLMs generate text"
 ---
 
-<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt2.ipynb">Open in Colab</a>
+<a target="_blank" href="https://colab.research.google.com/github/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/getting-started/v2/tutorial_pt2_v2.ipynb">Open in Colab</a>
 
 Command is Cohere’s flagship LLM. It generates a response based on a user message or prompt. It is trained to follow user commands and to be instantly useful in practical business applications, like summarization, copywriting, extraction, and question-answering.
 

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,9 +1,13 @@
+[project]
+name = "cohere-developer-experience"
+
 [tool.poetry]
-name = "py-snips"
+name = "cohere-developer-experience"
 version = "0.1.0"
 description = ""
 authors = ["Your Name <[email protected]>"]
 readme = "README.md"
+package-mode = false
 
 [tool.poetry.dependencies]
 python = "^3.11"

diff --git a/snippets/snippets/curl/dataset-get.sh b/snippets/snippets/curl/dataset-get.sh
@@ -1,4 +1,4 @@
 curl --request GET \
-  --url https://api.cohere.com/v1/datasets \
+  --url https://api.cohere.com/v1/datasets/id \
   --header 'accept: application/json' \
-  --header "Authorization: bearer $CO_API_KEY"
+  --header "Authorization: bearer $CO_API_KEY"
diff --git a/snippets/snippets/curl/dataset-list.sh b/snippets/snippets/curl/dataset-list.sh
@@ -0,0 +1,4 @@
+curl --request GET \
+  --url https://api.cohere.com/v1/datasets \
+  --header 'accept: application/json' \
+  --header "Authorization: bearer $CO_API_KEY"
diff --git a/snippets/snippets/go/dataset-list/main.go b/snippets/snippets/go/dataset-list/main.go
@@ -0,0 +1,23 @@
+package main
+
+import (
+	"context"
+	"log"
+
+	cohere "github.com/cohere-ai/cohere-go/v2"
+	client "github.com/cohere-ai/cohere-go/v2/client"
+)
+
+func main() {
+	co := client.NewClient()
+
+	resp, err := co.Datasets.List(
+		context.TODO(),
+		&cohere.DatasetsListRequest{})
+
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	log.Printf("%+v", resp)
+}
diff --git a/snippets/snippets/java/app/src/main/java/DatasetList.java b/snippets/snippets/java/app/src/main/java/DatasetList.java
@@ -0,0 +1,13 @@
+/* (C)2024 */
+import com.cohere.api.Cohere;
+import com.cohere.api.resources.datasets.types.DatasetsGetResponse;
+
+public class DatasetGet {
+  public static void main(String[] args) {
+    Cohere cohere = Cohere.builder().clientName("snippet").build();
+
+    DatasetsGetResponse response = cohere.datasets().list();
+
+    System.out.println(response);
+  }
+}
diff --git a/snippets/snippets/node/dataset-list.ts b/snippets/snippets/node/dataset-list.ts
@@ -0,0 +1,9 @@
+const { CohereClient } = require('cohere-ai');
+
+const cohere = new CohereClient({});
+
+(async () => {
+  const datasets = await cohere.datasets.list();
+
+  console.log(datasets);
+})();
diff --git a/snippets/snippets/python-async/dataset-list.py b/snippets/snippets/python-async/dataset-list.py
@@ -0,0 +1,13 @@
+import cohere
+import asyncio
+
+co = cohere.AsyncClient()
+
+
+async def main():
+    response = await co.datasets.list()
+
+    print(response)
+
+
+asyncio.run(main())