Fixing issue with format code snippets pipeline (#412)

* testing workflow trigger * testing workflow trigger * testing workflow trigger * testing workflow trigger * testing workflow trigger * testing workflow trigger * reformat python code examples --------- Co-authored-by: Max Shkutnyk <[email protected]>
cohere-ai · Feb 18, 2025 · 05b391d · 05b391d
1 parent 8374c65
commit 05b391d
Show file tree

Hide file tree

Showing 14 changed files with 304 additions and 370 deletions.
diff --git a/.github/workflows/check-python-code-snippets.yml b/.github/workflows/check-python-code-snippets.yml
@@ -43,11 +43,8 @@ jobs:
         run: |
           git diff --exit-code || echo "::set-output name=changes::true"
 
-      - name: Commit and Push Changes
+      - name: Fail if changes are detected
         if: steps.diff.outputs.changes == 'true'
         run: |
-          git config --local user.email "[email protected]"
-          git config --local user.name "GitHub Action"
-          git add -u
-          git commit -m "Format Python snippets in MDX files"
-          git push
+          echo "Changes in python code snippets are detected. Please run check-python-code-snippets locally and commit the changes."
+          exit 1
diff --git a/fern/pages/deployment-options/private-deployment/private-deployment-usage.mdx b/fern/pages/deployment-options/private-deployment/private-deployment-usage.mdx
@@ -66,8 +66,7 @@ The only difference between using Cohere's models on private deployments and the
 import cohere
 
 co = cohere.Client(
-    api_key="", # Leave this blank
-    base_url="<YOUR_DEPLOYMENT_URL>"
+    api_key="", base_url="<YOUR_DEPLOYMENT_URL>"  # Leave this blank
 )
 ```
 

diff --git a/fern/pages/get-started/quickstart/rag-quickstart.mdx b/fern/pages/get-started/quickstart/rag-quickstart.mdx
@@ -29,7 +29,9 @@ Next, import the library and create a client.
 ```python PYTHON
 import cohere
 
-co = cohere.Client("COHERE_API_KEY") # Get your free API key here: https://dashboard.cohere.com/api-keys
+co = cohere.Client(
+    "COHERE_API_KEY"
+)  # Get your free API key here: https://dashboard.cohere.com/api-keys
 ```
 
 </Tab>
@@ -39,8 +41,7 @@ co = cohere.Client("COHERE_API_KEY") # Get your free API key here: https://dashb
 import cohere
 
 co = cohere.Client(
-    api_key="", # Leave this blank
-    base_url="<YOUR_DEPLOYMENT_URL>"
+    api_key="", base_url="<YOUR_DEPLOYMENT_URL>"  # Leave this blank
 )
 ```
 
@@ -118,7 +119,7 @@ message = "Are there fitness-related benefits?"
 response = co.chat(
     model="command-r-plus-08-2024",
     message=message,
-    documents=documents
+    documents=documents,
 )
 
 print(response.text)
@@ -132,7 +133,7 @@ message = "Are there fitness-related benefits?"
 response = co.chat(
     model="command-r-plus-08-2024",
     message=message,
-    documents=documents
+    documents=documents,
 )
 
 print(response.text)
@@ -144,9 +145,7 @@ print(response.text)
 message = "Are there fitness-related benefits?"
 
 response = co.chat(
-    model="YOUR_MODEL_NAME",
-    message=message,
-    documents=documents
+    model="YOUR_MODEL_NAME", message=message, documents=documents
 )
 
 print(response.text)
@@ -158,9 +157,7 @@ print(response.text)
 message = "Are there fitness-related benefits?"
 
 response = co.chat(
-    model="YOUR_ENDPOINT_NAME",
-    message=message,
-    documents=documents
+    model="YOUR_ENDPOINT_NAME", message=message, documents=documents
 )
 
 print(response.text)
@@ -171,10 +168,7 @@ print(response.text)
 ```python PYTHON
 message = "Are there fitness-related benefits?"
 
-response = co.chat(
-    message=message,
-    documents=documents
-)
+response = co.chat(message=message, documents=documents)
 
 print(response.text)
 ```

diff --git a/fern/pages/get-started/quickstart/reranking-quickstart.mdx b/fern/pages/get-started/quickstart/reranking-quickstart.mdx
@@ -26,7 +26,9 @@ Next, import the library and create a client.
 ```python PYTHON
 import cohere
 
-co = cohere.Client("COHERE_API_KEY") # Get your free API key here: https://dashboard.cohere.com/api-keys
+co = cohere.Client(
+    "COHERE_API_KEY"
+)  # Get your free API key here: https://dashboard.cohere.com/api-keys
 ```
 
 </Tab>
@@ -36,8 +38,7 @@ co = cohere.Client("COHERE_API_KEY") # Get your free API key here: https://dashb
 import cohere
 
 co = cohere.Client(
-    api_key="", # Leave this blank
-    base_url="<YOUR_DEPLOYMENT_URL>"
+    api_key="", base_url="<YOUR_DEPLOYMENT_URL>"  # Leave this blank
 )
 ```
 
@@ -62,10 +63,7 @@ co = cohere.SagemakerClient(
 ```python PYTHON
 import cohere
 
-co = cohere.Client(
-    api_key="AZURE_API_KEY",
-    base_url="AZURE_ENDPOINT"
-)
+co = cohere.Client(api_key="AZURE_API_KEY", base_url="AZURE_ENDPOINT")
 ```
 </Tab>
 
@@ -96,10 +94,7 @@ query = "Are there fitness-related perks?"
 
 # Rerank the documents
 results = co.rerank(
-    model="rerank-v3.5",
-    query=query,
-    documents=documents,
-    top_n=2
+    model="rerank-v3.5", query=query, documents=documents, top_n=2
 )
 
 for result in results.results:
@@ -114,10 +109,7 @@ query = "Are there fitness-related perks?"
 
 # Rerank the documents
 results = co.rerank(
-    model="rerank-v3.5",
-    query=query,
-    documents=documents,
-    top_n=2
+    model="rerank-v3.5", query=query, documents=documents, top_n=2
 )
 
 for result in results.results:
@@ -135,7 +127,7 @@ results = co.rerank(
     model="YOUR_ENDPOINT_NAME",
     query=query,
     documents=documents,
-    top_n=2
+    top_n=2,
 )
 
 for result in results.results:
@@ -149,11 +141,7 @@ for result in results.results:
 query = "Are there fitness-related perks?"
 
 # Rerank the documents
-results = co.rerank(
-    query=query,
-    documents=documents,
-    top_n=2
-)
+results = co.rerank(query=query, documents=documents, top_n=2)
 
 for result in results.results:
     print(result)

diff --git a/fern/pages/get-started/quickstart/sem-search-quickstart.mdx b/fern/pages/get-started/quickstart/sem-search-quickstart.mdx
@@ -28,7 +28,9 @@ Next, import the library and create a client.
 ```python PYTHON
 import cohere
 
-co = cohere.Client("COHERE_API_KEY") # Get your free API key here: https://dashboard.cohere.com/api-keys
+co = cohere.Client(
+    "COHERE_API_KEY"
+)  # Get your free API key here: https://dashboard.cohere.com/api-keys
 ```
 
 </Tab>
@@ -38,8 +40,7 @@ co = cohere.Client("COHERE_API_KEY") # Get your free API key here: https://dashb
 import cohere
 
 co = cohere.Client(
-    api_key="", # Leave this blank
-    base_url="<YOUR_DEPLOYMENT_URL>"
+    api_key="", base_url="<YOUR_DEPLOYMENT_URL>"  # Leave this blank
 )
 ```
 
@@ -81,8 +82,7 @@ co = cohere.SagemakerClient(
 import cohere
 
 co = cohere.Client(
-    api_key="AZURE_API_KEY_COMMAND",
-    base_url="AZURE_ENDPOINT_COMMAND"
+    api_key="AZURE_API_KEY_COMMAND", base_url="AZURE_ENDPOINT_COMMAND"
 )
 ```
 </Tab>
@@ -107,7 +107,7 @@ doc_emb = co.embed(
     model="embed-english-v3.0",
     input_type="search_document",
     texts=documents,
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -126,7 +126,7 @@ doc_emb = co.embed(
     model="embed-english-v3.0",
     input_type="search_document",
     texts=documents,
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -145,7 +145,7 @@ doc_emb = co.embed(
     model="YOUR_MODEL_NAME",
     input_type="search_document",
     texts=documents,
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -164,7 +164,7 @@ doc_emb = co.embed(
     model="YOUR_ENDPOINT_NAME",
     input_type="search_document",
     texts=documents,
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -182,7 +182,7 @@ documents = [
 doc_emb = co.embed(
     input_type="search_document",
     texts=documents,
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -202,7 +202,7 @@ query_emb = co.embed(
     model="embed-english-v3.0",
     input_type="search_query",
     texts=[query],
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -217,7 +217,7 @@ query_emb = co.embed(
     model="embed-english-v3.0",
     input_type="search_query",
     texts=[query],
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -232,7 +232,7 @@ query_emb = co.embed(
     model="YOUR_MODEL_NAME",
     input_type="search_query",
     texts=[query],
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -247,7 +247,7 @@ query_emb = co.embed(
     model="YOUR_ENDPOINT_NAME",
     input_type="search_query",
     texts=[query],
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -261,7 +261,7 @@ query = "Ways to connect with my teammates"
 query_emb = co.embed(
     input_type="search_query",
     texts=[query],
-    embedding_types=["float"]
+    embedding_types=["float"],
 ).embeddings.float
 ```
 </Tab>
@@ -274,17 +274,19 @@ Then, perform semantic search by computing the similarity between the query embe
 ```python PYTHON
 import numpy as np
 
+
 # Compute dot product similarity and display results
 def return_results(query_emb, doc_emb, documents):
-    n = 2 # customize your top N results
+    n = 2  # customize your top N results
     scores = np.dot(query_emb, np.transpose(doc_emb))[0]
     max_idx = np.argsort(-scores)[:n]
-        
+
     for rank, idx in enumerate(max_idx):
         print(f"Rank: {rank+1}")
         print(f"Score: {scores[idx]}")
         print(f"Document: {documents[idx]}\n")
-
+
+
 return_results(query_emb, doc_emb, documents)
 ```
 ```mdx wordWrap