Merge pull request #46 from privacera/changelogs

Changelogs
privacera · Sep 6, 2024 · 365990c · 365990c
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -0,0 +1,32 @@
+# Changelog
+
+All changes to this repository can be referred from this file.
+
+
+### 📚 App-Specific Changelogs
+For detailed updates and changes specific to each application, refer to the following links:
+
+- [paig-common Changelog](./paig-common/CHANGELOG.md)
+- [paig-server Changelog](./paig-server/CHANGELOG.md)
+- [paig-client Changelog](./paig-client/CHANGELOG.md)
+
+
+
+## 2024-09-06
+
+### 🔧 CI/CD Integration
+Implemented GitHub Actions workflows to automate the development process:
+
+- **Continuous Integration (CI)**:
+  - Comprehensive testing pipeline for all applications to ensure code quality and functionality.
+
+- **Deployment Pipelines**:
+  - Automated deployment processes for  `paig-server`, `paig-client` and `paig-common`.
+
+
+### 📚 Documentation Updates
+- Updated documentation for installation and usage instructions.
+
+
+### 📓 Notebooks
+- Added jupyter and colab notebooks for quick start.
diff --git a/notebooks/paig-os/google-colab/PAIG_OpenAI.ipynb b/notebooks/paig-os/google-colab/PAIG_OpenAI.ipynb
@@ -238,7 +238,7 @@
         "\n",
         "This section demonstrates a simple Python application that uses OpenAI for inference. The PAIG Shield is integrated within the application. The PAIG Shield client is initialized using the `setup()` method and is then used to validate the prompts and replies. In this basic GenAI application, the PAIG Shield's `check_access()` method needs to be explicitly called for the prompt and reply. However, when using frameworks like LangChain, PAIG will automatically instrument the code and call the `check_access()` method for all interactions with LLMs and RAGs.\n",
         "\n",
-        "To enforce user or group-specific policies, the calling username should be set as the request context before processing the prompt. This can be done using the `with paig_client_client.create_shield_context(username=username):` syntax.\n",
+        "To enforce user or group-specific policies, the calling username should be set as the request context before processing the prompt. This can be done using the `with paig_shield_client.create_shield_context(username=username):` syntax.\n",
         "\n",
         "To stitch together related calls, an optional thread ID can be passed to the `check_access()` method to tie them together.\n",
         "\n",
@@ -260,7 +260,7 @@
       "outputs": [],
       "source": [
         "\n",
-        "from paig_client import client as paig_client_client\n",
+        "from paig_client import client as paig_shield_client\n",
         "from paig_client.model import ConversationType\n",
         "import paig_client.exception\n",
         "from openai import OpenAI\n",
@@ -272,19 +272,19 @@
         ")\n",
         "\n",
         "# PAIG supports frameworks like LangChain and VectorDBs like Milvus, OpenSearch. The integration to be considered should be passed as the frameworks parameter.\n",
-        "paig_client_client.setup(frameworks=[])\n",
+        "paig_shield_client.setup(frameworks=[])\n",
         "\n",
         "# Create a function which can be called for the prompts\n",
         "def query_as_user(username, prompt_text):\n",
         "    # Generate a random UUID which will be used to bind a prompt with a reply\n",
         "    privacera_thread_id = str(uuid.uuid4())\n",
         "\n",
         "    try:\n",
-        "        with paig_client_client.create_shield_context(username=username):\n",
+        "        with paig_shield_client.create_shield_context(username=username):\n",
         "            print(f\"PROMPT BY USER: {prompt_text}\")\n",
         "\n",
         "            # Validate prompt with Privacera Shield\n",
-        "            updated_prompt_text = paig_client_client.check_access(\n",
+        "            updated_prompt_text = paig_shield_client.check_access(\n",
         "                text=prompt_text,\n",
         "                conversation_type=ConversationType.PROMPT,\n",
         "                thread_id=privacera_thread_id\n",
@@ -309,7 +309,7 @@
         "            print(f\"LLM Response: {llm_response}\")\n",
         "\n",
         "            # Validate LLM response with Privacera Shield\n",
-        "            updated_reply_text = paig_client_client.check_access(\n",
+        "            updated_reply_text = paig_shield_client.check_access(\n",
         "                text=llm_response,\n",
         "                conversation_type=ConversationType.REPLY,\n",
         "                thread_id=privacera_thread_id\n",

diff --git a/notebooks/paig-os/google-colab/PAIG_colab.ipynb b/notebooks/paig-os/google-colab/PAIG_colab.ipynb
@@ -189,13 +189,13 @@
       },
       "outputs": [],
       "source": [
-        "from paig_client import client as paig_client_client\n",
+        "from paig_client import client as paig_shield_client\n",
         "from openai import OpenAI\n",
         "\n",
         "# Set the OPENAI_API_KEY environment variable or set it here\n",
         "openai_client = OpenAI()\n",
         "\n",
-        "paig_client_client.setup(frameworks=[])\n"
+        "paig_shield_client.setup(frameworks=[])\n"
       ]
     },
     {
@@ -224,7 +224,7 @@
       },
       "outputs": [],
       "source": [
-        "from paig_client import client as paig_client_client\n",
+        "from paig_client import client as paig_shield_client\n",
         "from paig_client.model import ConversationType\n",
         "import paig_client.exception\n",
         "import uuid\n",
@@ -236,11 +236,11 @@
         "privacera_thread_id = str(uuid.uuid4())\n",
         "\n",
         "try:\n",
-        "   with paig_client_client.create_shield_context(username=user):\n",
+        "   with paig_shield_client.create_shield_context(username=user):\n",
         "      prompt_text = \"Who was the first President of USA and where did they live?\"\n",
         "      print(f\"User Prompt: {prompt_text}\")\n",
         "      # Validate prompt with Privacera Shield\n",
-        "      updated_prompt_text = paig_client_client.check_access(\n",
+        "      updated_prompt_text = paig_shield_client.check_access(\n",
         "         text=prompt_text,\n",
         "         conversation_type=ConversationType.PROMPT,\n",
         "         thread_id=privacera_thread_id\n",
@@ -261,7 +261,7 @@
         "      llm_response = response.choices[0].message.content\n",
         "      print(f\"LLM Response: {llm_response}\")\n",
         "      # Validate LLM response with Privacera Shield\n",
-        "      updated_reply_text = paig_client_client.check_access(\n",
+        "      updated_reply_text = paig_shield_client.check_access(\n",
         "         text=llm_response,\n",
         "         conversation_type=ConversationType.REPLY,\n",
         "         thread_id=privacera_thread_id\n",

diff --git a/notebooks/paig-os/jupyter-notebook/PAIG_OpenAI_jupyter.ipynb b/notebooks/paig-os/jupyter-notebook/PAIG_OpenAI_jupyter.ipynb
@@ -272,7 +272,7 @@
     "\n",
     "This section demonstrates a simple Python application that uses OpenAI for inference. The PAIG Shield is integrated within the application. The PAIG Shield client is initialized using the `setup()` method and is then used to validate the prompts and replies. In this basic GenAI application, the PAIG Shield's `check_access()` method needs to be explicitly called for the prompt and reply. However, when using frameworks like LangChain, PAIG will automatically instrument the code and call the `check_access()` method for all interactions with LLMs and RAGs.\n",
     "\n",
-    "To enforce user or group-specific policies, the calling username should be set as the request context before processing the prompt. This can be done using the `with paig_client_client.create_shield_context(username=username):` syntax.\n",
+    "To enforce user or group-specific policies, the calling username should be set as the request context before processing the prompt. This can be done using the `with paig_shield_client.create_shield_context(username=username):` syntax.\n",
     "\n",
     "To stitch together related calls, an optional thread ID can be passed to the `check_access()` method to tie them together.\n",
     "\n",
@@ -292,7 +292,7 @@
    },
    "outputs": [],
    "source": [
-    "from paig_client import client as paig_client_client\n",
+    "from paig_client import client as paig_shield_client\n",
     "from paig_client.model import ConversationType\n",
     "import paig_client.exception\n",
     "from openai import OpenAI\n",
@@ -304,19 +304,19 @@
     ")\n",
     "\n",
     "# PAIG supports frameworks like LangChain and VectorDBs like Milvus, OpenSearch. The integration to be considered should be passed as the frameworks parameter.\n",
-    "paig_client_client.setup(frameworks=[])\n",
+    "paig_shield_client.setup(frameworks=[])\n",
     "\n",
     "# Create a function which can be called for the prompts\n",
     "def query_as_user(username, prompt_text):\n",
     "    # Generate a random UUID which will be used to bind a prompt with a reply\n",
     "    privacera_thread_id = str(uuid.uuid4())\n",
     "\n",
     "    try:\n",
-    "        with paig_client_client.create_shield_context(username=username):\n",
+    "        with paig_shield_client.create_shield_context(username=username):\n",
     "            print(f\"PROMPT BY USER: {prompt_text}\")\n",
     "\n",
     "            # Validate prompt with Privacera Shield\n",
-    "            updated_prompt_text = paig_client_client.check_access(\n",
+    "            updated_prompt_text = paig_shield_client.check_access(\n",
     "                text=prompt_text,\n",
     "                conversation_type=ConversationType.PROMPT,\n",
     "                thread_id=privacera_thread_id\n",
@@ -341,7 +341,7 @@
     "            print(f\"LLM Response: {llm_response}\")\n",
     "\n",
     "            # Validate LLM response with Privacera Shield\n",
-    "            updated_reply_text = paig_client_client.check_access(\n",
+    "            updated_reply_text = paig_shield_client.check_access(\n",
     "                text=llm_response,\n",
     "                conversation_type=ConversationType.REPLY,\n",
     "                thread_id=privacera_thread_id\n",

diff --git a/notebooks/paig-os/jupyter-notebook/PAIG_jupyter.ipynb b/notebooks/paig-os/jupyter-notebook/PAIG_jupyter.ipynb
@@ -226,13 +226,13 @@
    },
    "outputs": [],
    "source": [
-    "from paig_client import client as paig_client_client\n",
+    "from paig_client import client as paig_shield_client\n",
     "from openai import OpenAI\n",
     "\n",
     "# Set the OPENAI_API_KEY environment variable or set it here\n",
     "openai_client = OpenAI()\n",
     "\n",
-    "paig_client_client.setup(frameworks=[])\n"
+    "paig_shield_client.setup(frameworks=[])\n"
    ]
   },
   {
@@ -261,7 +261,7 @@
    },
    "outputs": [],
    "source": [
-    "from paig_client import client as paig_client_client\n",
+    "from paig_client import client as paig_shield_client\n",
     "from paig_client.model import ConversationType\n",
     "import paig_client.exception\n",
     "import uuid\n",
@@ -273,11 +273,11 @@
     "privacera_thread_id = str(uuid.uuid4())\n",
     "\n",
     "try:\n",
-    "   with paig_client_client.create_shield_context(username=user):\n",
+    "   with paig_shield_client.create_shield_context(username=user):\n",
     "      prompt_text = \"Who was the first President of USA and where did they live?\"\n",
     "      print(f\"User Prompt: {prompt_text}\")\n",
     "      # Validate prompt with Privacera Shield\n",
-    "      updated_prompt_text = paig_client_client.check_access(\n",
+    "      updated_prompt_text = paig_shield_client.check_access(\n",
     "         text=prompt_text,\n",
     "         conversation_type=ConversationType.PROMPT,\n",
     "         thread_id=privacera_thread_id\n",
@@ -298,7 +298,7 @@
     "      llm_response = response.choices[0].message.content\n",
     "      print(f\"LLM Response: {llm_response}\")\n",
     "      # Validate LLM response with Privacera Shield\n",
-    "      updated_reply_text = paig_client_client.check_access(\n",
+    "      updated_reply_text = paig_shield_client.check_access(\n",
     "         text=llm_response,\n",
     "         conversation_type=ConversationType.REPLY,\n",
     "         thread_id=privacera_thread_id\n",

diff --git a/paig-client/CHANGELOG.md b/paig-client/CHANGELOG.md
@@ -0,0 +1,6 @@
+# paig-client Changelog
+All notable changes to paig-client will be documented in this file.
+
+## [v0.0.1] - 2024-09-06
+### Added
+- Initial release of the `paig-client`.
diff --git a/paig-common/CHANGELOG.md b/paig-common/CHANGELOG.md
@@ -0,0 +1,9 @@
+# paig-common Changelog
+All changes to paig-common will be documented in this file.
+
+## [v0.0.1] - 2024-09-06
+### Added
+- Initial release of the `paig-common` shared library.
+- Added utility functions for API handling, error management, and data processing.
+- Added encryption and decryption functions for data security.
+- Added base classes for Async API clients, RBACs.
diff --git a/paig-server/CHANGELOG.md b/paig-server/CHANGELOG.md
@@ -0,0 +1,17 @@
+# paig-server Changelog
+All changes to paig-server will be documented in this file.
+
+## [v0.0.2] - 2024-09-06
+### Added
+- For audit storage Opensearch support added
+
+### Changed
+- Improved server startup experience
+- Fixed warnings
+- Updated dependencies
+- Scanner loading time improved
+
+
+## [v0.0.1] - 2024-08-14
+### Added
+- Initial release of the `paig-server`.
diff --git a/t b/t