Merge pull request #303 from SylphAI-Inc/revert_or_296

add change log

adalflow/CHANGELOG.md

@@ -1,4 +1,10 @@
-
+## [0.2.7] - TO Be Released
+### Added
+- `Memory` is completed with `call` and `add_dialog_turn` methods.
+- Integrated `LanceDB` in the `Retriever`
+### Improved
+- `BedrockAPIClient` added more details on setup, yet it is still in experimental stage.
+- `AzureAPIClient` added more details on setup, yet it is still in experimental stage.
 ## [0.2.6] - 2024-11-25
 ### Improved
 - Add default `max_tokens=512` to the `AnthropicAPIClient` to avoid the error when the user does not provide the `max_tokens` in the prompt.

adalflow/adalflow/components/model_client/bedrock_client.py

@@ -39,6 +39,10 @@ def get_first_message_content(completion: Dict) -> str:
 class BedrockAPIClient(ModelClient):
     __doc__ = r"""A component wrapper for the Bedrock API client.
 
+    Note:
+
+    This api is in experimental and is not fully tested and validated yet.
+
     Support:
     1. AWS Titan
     2. Claude

notebooks/adalflow_colab_template.ipynb

@@ -87,8 +87,8 @@
     "\n",
     "\n",
     "# Set environment variables\n",
-    "os.environ['OPENAI_API_KEY'] = openai_api_key\n",
-    "os.environ['GROQ_API_KEY'] = groq_api_key\n",
+    "os.environ[\"OPENAI_API_KEY\"] = openai_api_key\n",
+    "os.environ[\"GROQ_API_KEY\"] = groq_api_key\n",
     "\n",
     "print(\"API keys have been set.\")"
    ]

notebooks/evaluation/adalflow_llm_eval.ipynb

@@ -95,7 +95,7 @@
     "\n",
     "\n",
     "# Set environment variables\n",
-    "os.environ['OPENAI_API_KEY'] = openai_api_key\n",
+    "os.environ[\"OPENAI_API_KEY\"] = openai_api_key\n",
     "\n",
     "print(\"API keys have been set.\")"
    ]
@@ -301,11 +301,11 @@
    "source": [
     "# without questions, and with customized judgement query\n",
     "\n",
+    "\n",
     "def compute_llm_as_judge_wo_questions():\n",
     "    from adalflow.eval.llm_as_judge import LLMasJudge, DefaultLLMJudge\n",
     "    from adalflow.components.model_client import OpenAIClient\n",
     "\n",
-    "\n",
     "    llm_judge = DefaultLLMJudge(\n",
     "        model_client=OpenAIClient(),\n",
     "        model_kwargs={\n",
@@ -413,7 +413,7 @@
     "    eval_rslt = llm_evaluator.compute(\n",
     "        questions=questions, gt_answers=gt_answers, pred_answers=pred_answers\n",
     "    )\n",
-    "    print(eval_rslt)\n"
+    "    print(eval_rslt)"
    ]
   },
   {
@@ -569,8 +569,12 @@
     }
    ],
    "source": [
-    "source=\"Paul Merson has restarted his row with Andros Townsend after the Tottenham midfielder was brought on with only seven minutes remaining in his team 's 0-0 draw with Burnley on Sunday . 'Just been watching the game , did you miss the coach ? # RubberDub # 7minutes , ' Merson put on Twitter . Merson initially angered Townsend for writing in his Sky Sports column that 'if Andros Townsend can get in ( the England team ) then it opens it up to anybody . ' Paul Merson had another dig at Andros Townsend after his appearance for Tottenham against Burnley Townsend was brought on in the 83rd minute for Tottenham as they drew 0-0 against Burnley Andros Townsend scores England 's equaliser in their 1-1 friendly draw with Italy in Turin on Tuesday night The former Arsenal man was proven wrong when Townsend hit a stunning equaliser for England against Italy and he duly admitted his mistake . 'It 's not as though I was watching hoping he would n't score for England , I 'm genuinely pleased for him and fair play to him \\u00e2\\u20ac\\u201c it was a great goal , ' Merson said . 'It 's just a matter of opinion , and my opinion was that he got pulled off after half an hour at Manchester United in front of Roy Hodgson , so he should n't have been in the squad . 'When I 'm wrong , I hold my hands up . I do n't have a problem with doing that - I 'll always be the first to admit when I 'm wrong . ' Townsend hit back at Merson on Twitter after scoring for England against Italy Sky Sports pundit Merson ( centre ) criticised Townsend 's call-up to the England squad last week Townsend hit back at Merson after netting for England in Turin on Wednesday , saying 'Not bad for a player that should be 'nowhere near the squad ' ay @ PaulMerse ? ' Any bad feeling between the pair seemed to have passed but Merson was unable to resist having another dig at Townsend after Tottenham drew at Turf Moor .\",\n",
-    "summary=\"Paul merson was brought on with only seven minutes remaining in his team 's 0-0 draw with burnley . Andros townsend scored the tottenham midfielder in the 89th minute . Paul merson had another dig at andros townsend after his appearance . The midfielder had been brought on to the england squad last week . Click here for all the latest arsenal news news .\",\n",
+    "source = (\n",
+    "    \"Paul Merson has restarted his row with Andros Townsend after the Tottenham midfielder was brought on with only seven minutes remaining in his team 's 0-0 draw with Burnley on Sunday . 'Just been watching the game , did you miss the coach ? # RubberDub # 7minutes , ' Merson put on Twitter . Merson initially angered Townsend for writing in his Sky Sports column that 'if Andros Townsend can get in ( the England team ) then it opens it up to anybody . ' Paul Merson had another dig at Andros Townsend after his appearance for Tottenham against Burnley Townsend was brought on in the 83rd minute for Tottenham as they drew 0-0 against Burnley Andros Townsend scores England 's equaliser in their 1-1 friendly draw with Italy in Turin on Tuesday night The former Arsenal man was proven wrong when Townsend hit a stunning equaliser for England against Italy and he duly admitted his mistake . 'It 's not as though I was watching hoping he would n't score for England , I 'm genuinely pleased for him and fair play to him \\u00e2\\u20ac\\u201c it was a great goal , ' Merson said . 'It 's just a matter of opinion , and my opinion was that he got pulled off after half an hour at Manchester United in front of Roy Hodgson , so he should n't have been in the squad . 'When I 'm wrong , I hold my hands up . I do n't have a problem with doing that - I 'll always be the first to admit when I 'm wrong . ' Townsend hit back at Merson on Twitter after scoring for England against Italy Sky Sports pundit Merson ( centre ) criticised Townsend 's call-up to the England squad last week Townsend hit back at Merson after netting for England in Turin on Wednesday , saying 'Not bad for a player that should be 'nowhere near the squad ' ay @ PaulMerse ? ' Any bad feeling between the pair seemed to have passed but Merson was unable to resist having another dig at Townsend after Tottenham drew at Turf Moor .\",\n",
+    ")\n",
+    "summary = (\n",
+    "    \"Paul merson was brought on with only seven minutes remaining in his team 's 0-0 draw with burnley . Andros townsend scored the tottenham midfielder in the 89th minute . Paul merson had another dig at andros townsend after his appearance . The midfielder had been brought on to the england squad last week . Click here for all the latest arsenal news news .\",\n",
+    ")\n",
     "\n",
     "compute_g_eval_summarization(source=source, summary=summary)"
    ]

notebooks/qas/adalflow_object_count_auto_optimization.ipynb

@@ -137,12 +137,14 @@
     "\n",
     "# Prompt user to enter their API keys securely\n",
     "openai_api_key = getpass(\"Please enter your OpenAI API key: \")\n",
-    "groq_api_key = getpass(\"Please enter your GROQ API key, simplly press Enter if you don't have one: \")\n",
+    "groq_api_key = getpass(\n",
+    "    \"Please enter your GROQ API key, simplly press Enter if you don't have one: \"\n",
+    ")\n",
     "\n",
     "\n",
     "# Set environment variables\n",
-    "os.environ['OPENAI_API_KEY'] = openai_api_key\n",
-    "os.environ['GROQ_API_KEY'] = groq_api_key\n",
+    "os.environ[\"OPENAI_API_KEY\"] = openai_api_key\n",
+    "os.environ[\"GROQ_API_KEY\"] = groq_api_key\n",
     "\n",
     "print(\"API keys have been set.\")"
    ]
@@ -209,6 +211,7 @@
     "<END_OF_USER>\n",
     "\"\"\"\n",
     "\n",
+    "\n",
     "class ObjectCountTaskPipeline(adal.Component):\n",
     "    def __init__(self, model_client: adal.ModelClient, model_kwargs: Dict):\n",
     "        super().__init__()\n",
@@ -242,9 +245,7 @@
     "        self, question: str, id: str = None\n",
     "    ) -> Union[adal.GeneratorOutput, adal.Parameter]:\n",
     "        output = self.llm_counter(prompt_kwargs={\"input_str\": question}, id=id)\n",
-    "        return output\n",
-    "\n",
-    "\n"
+    "        return output"
    ]
   },
   {
@@ -329,44 +330,42 @@
     "from adalflow.components.model_client.groq_client import GroqAPIClient\n",
     "\n",
     "\n",
-    "if len(os.environ['OPENAI_API_KEY']) > 1:\n",
-    "  gpt_3_model = {\n",
-    "      \"model_client\": OpenAIClient(),\n",
-    "      \"model_kwargs\": {\n",
-    "          \"model\": \"gpt-3.5-turbo\",\n",
-    "          \"max_tokens\": 2000,\n",
-    "          \"temperature\": 0.0,\n",
-    "          \"top_p\": 0.99,\n",
-    "          \"frequency_penalty\": 0,\n",
-    "          \"presence_penalty\": 0,\n",
-    "          \"stop\": None,\n",
-    "      },\n",
-    "  }\n",
-    "  gpt_4o_model = {\n",
-    "      \"model_client\": OpenAIClient(),\n",
-    "      \"model_kwargs\": {\n",
-    "          \"model\": \"gpt-4o\",\n",
-    "          \"max_tokens\": 4000,\n",
-    "          \"temperature\": 0.0,\n",
-    "          \"top_p\": 0.99,\n",
-    "          \"frequency_penalty\": 0,\n",
-    "          \"presence_penalty\": 0,\n",
-    "          \"stop\": None,\n",
-    "      },\n",
-    "  }\n",
+    "if len(os.environ[\"OPENAI_API_KEY\"]) > 1:\n",
+    "    gpt_3_model = {\n",
+    "        \"model_client\": OpenAIClient(),\n",
+    "        \"model_kwargs\": {\n",
+    "            \"model\": \"gpt-3.5-turbo\",\n",
+    "            \"max_tokens\": 2000,\n",
+    "            \"temperature\": 0.0,\n",
+    "            \"top_p\": 0.99,\n",
+    "            \"frequency_penalty\": 0,\n",
+    "            \"presence_penalty\": 0,\n",
+    "            \"stop\": None,\n",
+    "        },\n",
+    "    }\n",
+    "    gpt_4o_model = {\n",
+    "        \"model_client\": OpenAIClient(),\n",
+    "        \"model_kwargs\": {\n",
+    "            \"model\": \"gpt-4o\",\n",
+    "            \"max_tokens\": 4000,\n",
+    "            \"temperature\": 0.0,\n",
+    "            \"top_p\": 0.99,\n",
+    "            \"frequency_penalty\": 0,\n",
+    "            \"presence_penalty\": 0,\n",
+    "            \"stop\": None,\n",
+    "        },\n",
+    "    }\n",
     "\n",
-    "if len(os.environ['GROQ_API_KEY']) > 1:\n",
-    "  llama_3_1_model ={\n",
-    "      \"model_client\": GroqAPIClient(),\n",
-    "      \"model_kwargs\": {\n",
-    "          \"model\": \"llama-3.1-8b-instant\"\n",
-    "      }\n",
-    "  }\n",
+    "if len(os.environ[\"GROQ_API_KEY\"]) > 1:\n",
+    "    llama_3_1_model = {\n",
+    "        \"model_client\": GroqAPIClient(),\n",
+    "        \"model_kwargs\": {\"model\": \"llama-3.1-8b-instant\"},\n",
+    "    }\n",
     "\n",
     "\n",
     "question = \"I have a flute, a piano, a trombone, four stoves, a violin, an accordion, a clarinet, a drum, two lamps, and a trumpet. How many musical instruments do I have?\"\n",
     "task_pipeline = ObjectCountTaskPipeline(**gpt_3_model)\n",
-    "print(task_pipeline)\n"
+    "print(task_pipeline)"
    ]
   },
   {
@@ -467,6 +466,7 @@
     "from adalflow.datasets.big_bench_hard import BigBenchHard\n",
     "from adalflow.utils.data import subset_dataset\n",
     "\n",
+    "\n",
     "def load_datasets(max_samples: int = None):\n",
     "    \"\"\"Load the dataset\"\"\"\n",
     "    train_data = BigBenchHard(split=\"train\")\n",
@@ -479,7 +479,7 @@
     "        val_data = subset_dataset(val_data, max_samples)\n",
     "        test_data = subset_dataset(test_data, max_samples)\n",
     "\n",
-    "    return train_data, val_data, test_data\n"
+    "    return train_data, val_data, test_data"
    ]
   },
   {
@@ -583,11 +583,11 @@
     "    def prepare_task(self, sample: Example):\n",
     "        return self.task.call, {\"question\": sample.question, \"id\": sample.id}\n",
     "\n",
-    "    def prepare_eval(\n",
-    "        self, sample: Example, y_pred: adal.GeneratorOutput\n",
-    "    ) -> float:\n",
+    "    def prepare_eval(self, sample: Example, y_pred: adal.GeneratorOutput) -> float:\n",
     "        y_label = -1\n",
-    "        if (y_pred is not None and y_pred.data is not None):  # if y_pred and y_pred.data: might introduce bug when the data is 0\n",
+    "        if (\n",
+    "            y_pred is not None and y_pred.data is not None\n",
+    "        ):  # if y_pred and y_pred.data: might introduce bug when the data is 0\n",
     "            y_label = y_pred.data\n",
     "        return self.eval_fn, {\"y\": y_label, \"y_gt\": sample.answer}"
    ]
@@ -820,7 +820,7 @@
     "from adalflow.datasets.types import Example\n",
     "\n",
     "\n",
-    "class ObjectCountAdalComponent(adal.AdalComponent):# noqa: F811\n",
+    "class ObjectCountAdalComponent(adal.AdalComponent):  # noqa: F811\n",
     "    def __init__(\n",
     "        self,\n",
     "        model_client: adal.ModelClient,\n",
@@ -844,12 +844,11 @@
     "    def prepare_task(self, sample: Example):\n",
     "        return self.task.call, {\"question\": sample.question, \"id\": sample.id}\n",
     "\n",
-    "\n",
-    "    def prepare_eval(\n",
-    "        self, sample: Example, y_pred: adal.GeneratorOutput\n",
-    "    ) -> float:\n",
+    "    def prepare_eval(self, sample: Example, y_pred: adal.GeneratorOutput) -> float:\n",
     "        y_label = -1\n",
-    "        if (y_pred is not None and y_pred.data is not None):  # if y_pred and y_pred.data: might introduce bug when the data is 0\n",
+    "        if (\n",
+    "            y_pred is not None and y_pred.data is not None\n",
+    "        ):  # if y_pred and y_pred.data: might introduce bug when the data is 0\n",
     "            y_label = y_pred.data\n",
     "        return self.eval_fn, {\"y\": y_label, \"y_gt\": sample.answer}\n",
     "\n",
@@ -891,7 +890,7 @@
     "        **gpt_3_model,\n",
     "        teacher_model_config=gpt_4o_model,\n",
     "        text_optimizer_model_config=gpt_4o_model,\n",
-    "        backward_engine_model_config=gpt_4o_model\n",
+    "        backward_engine_model_config=gpt_4o_model,\n",
     "    )\n",
     "    print(adal_component)\n",
     "    trainer = adal.Trainer(\n",
@@ -916,7 +915,7 @@
     "        test_dataset=test_dataset,\n",
     "        debug=debug,\n",
     "        resume_from_ckpt=resume_from_ckpt,\n",
-    "    )\n"
+    "    )"
    ]
   },
   {
@@ -3255,10 +3254,14 @@
     }
    ],
    "source": [
-    "train(debug=False, max_steps=12, strategy=\"constrained\",\n",
-    "      raw_shots=0, bootstrap_shots=1,\n",
-    "      exclude_input_fields_from_bootstrap_demos=True\n",
-    "      )"
+    "train(\n",
+    "    debug=False,\n",
+    "    max_steps=12,\n",
+    "    strategy=\"constrained\",\n",
+    "    raw_shots=0,\n",
+    "    bootstrap_shots=1,\n",
+    "    exclude_input_fields_from_bootstrap_demos=True,\n",
+    ")"
    ]
   },
   {
@@ -6015,13 +6018,17 @@
     }
    ],
    "source": [
-    "\n",
     "ckpt_path = \"/content/adalflow/ckpt/ObjectCountAdalComponent/constrained_max_steps_12_4e8a1_run_1.json\"\n",
     "\n",
-    "train(debug=False, max_steps=12, strategy=\"constrained\",\n",
-    "                raw_shots=0, bootstrap_shots=1,\n",
-    "                resume_from_ckpt=ckpt_path,\n",
-    "                exclude_input_fields_from_bootstrap_demos=True)"
+    "train(\n",
+    "    debug=False,\n",
+    "    max_steps=12,\n",
+    "    strategy=\"constrained\",\n",
+    "    raw_shots=0,\n",
+    "    bootstrap_shots=1,\n",
+    "    resume_from_ckpt=ckpt_path,\n",
+    "    exclude_input_fields_from_bootstrap_demos=True,\n",
+    ")"
    ]
   },
   {
@@ -8038,11 +8045,15 @@
     }
    ],
    "source": [
-    "\n",
-    "train(debug=False, max_steps=12, strategy=\"random\",\n",
-    "                raw_shots=0, bootstrap_shots=1,\n",
-    "                resume_from_ckpt=ckpt_path,\n",
-    "                exclude_input_fields_from_bootstrap_demos=False)"
+    "train(\n",
+    "    debug=False,\n",
+    "    max_steps=12,\n",
+    "    strategy=\"random\",\n",
+    "    raw_shots=0,\n",
+    "    bootstrap_shots=1,\n",
+    "    resume_from_ckpt=ckpt_path,\n",
+    "    exclude_input_fields_from_bootstrap_demos=False,\n",
+    ")"
    ]
   },
   {