deploy: c71a6a8

_modules/autorag.html

@@ -425,10 +425,12 @@ <h1>Source code for autorag</h1><div class="highlight"><pre>
 <span class="kn">import</span> <span class="nn">os</span>
 <span class="kn">import</span> <span class="nn">sys</span>
 <span class="kn">from</span> <span class="nn">random</span> <span class="kn">import</span> <span class="n">random</span>
-<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Any</span>
 
 <span class="kn">from</span> <span class="nn">llama_index.core</span> <span class="kn">import</span> <span class="n">MockEmbedding</span>
+<span class="kn">from</span> <span class="nn">llama_index.core.base.llms.types</span> <span class="kn">import</span> <span class="n">CompletionResponse</span>
 <span class="kn">from</span> <span class="nn">llama_index.core.llms.mock</span> <span class="kn">import</span> <span class="n">MockLLM</span>
+<span class="kn">from</span> <span class="nn">llama_index.llms.bedrock</span> <span class="kn">import</span> <span class="n">Bedrock</span>
 <span class="kn">from</span> <span class="nn">llama_index.embeddings.openai</span> <span class="kn">import</span> <span class="n">OpenAIEmbedding</span>
 <span class="kn">from</span> <span class="nn">llama_index.embeddings.openai</span> <span class="kn">import</span> <span class="n">OpenAIEmbeddingModelType</span>
 
@@ -491,7 +493,6 @@ <h1>Source code for autorag</h1><div class="highlight"><pre>
 
 <span class="n">sys</span><span class="o">.</span><span class="n">excepthook</span> <span class="o">=</span> <span class="n">handle_exception</span>
 
-
 <span class="n">embedding_models</span> <span class="o">=</span> <span class="p">{</span>
 	<span class="c1"># llama index</span>
 	<span class="s2">&quot;openai&quot;</span><span class="p">:</span> <span class="n">LazyInit</span><span class="p">(</span>
@@ -532,25 +533,37 @@ <h1>Source code for autorag</h1><div class="highlight"><pre>
 		<span class="s2">&quot;To use local version, run pip install &#39;AutoRAG[gpu]&#39;&quot;</span>
 	<span class="p">)</span>
 
+
+<div class="viewcode-block" id="AutoRAGBedrock">
+<a class="viewcode-back" href="../api_spec/autorag.html#autorag.AutoRAGBedrock">[docs]</a>
+<span class="k">class</span> <span class="nc">AutoRAGBedrock</span><span class="p">(</span><span class="n">Bedrock</span><span class="p">):</span>
+<div class="viewcode-block" id="AutoRAGBedrock.acomplete">
+<a class="viewcode-back" href="../api_spec/autorag.html#autorag.AutoRAGBedrock.acomplete">[docs]</a>
+	<span class="k">async</span> <span class="k">def</span> <span class="nf">acomplete</span><span class="p">(</span>
+		<span class="bp">self</span><span class="p">,</span> <span class="n">prompt</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">formatted</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">Any</span>
+	<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">CompletionResponse</span><span class="p">:</span>
+		<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">complete</span><span class="p">(</span><span class="n">prompt</span><span class="p">,</span> <span class="n">formatted</span><span class="o">=</span><span class="n">formatted</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
+</div>
+
+
+
 <span class="n">generator_models</span> <span class="o">=</span> <span class="p">{</span>
 	<span class="s2">&quot;openai&quot;</span><span class="p">:</span> <span class="n">OpenAI</span><span class="p">,</span>
 	<span class="s2">&quot;openailike&quot;</span><span class="p">:</span> <span class="n">OpenAILike</span><span class="p">,</span>
 	<span class="s2">&quot;mock&quot;</span><span class="p">:</span> <span class="n">MockLLM</span><span class="p">,</span>
+	<span class="s2">&quot;bedrock&quot;</span><span class="p">:</span> <span class="n">AutoRAGBedrock</span><span class="p">,</span>
 <span class="p">}</span>
 
 <span class="k">try</span><span class="p">:</span>
 	<span class="kn">from</span> <span class="nn">llama_index.llms.huggingface</span> <span class="kn">import</span> <span class="n">HuggingFaceLLM</span>
 	<span class="kn">from</span> <span class="nn">llama_index.llms.ollama</span> <span class="kn">import</span> <span class="n">Ollama</span>
 
-	<span class="n">generator_models</span><span class="p">[</span><span class="s2">&quot;huggingfacellm&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">HuggingFaceLLM</span>
-	<span class="n">generator_models</span><span class="p">[</span><span class="s2">&quot;ollama&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">Ollama</span>
 <span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
 	<span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span>
 		<span class="s2">&quot;You are using API version of AutoRAG.&quot;</span>
 		<span class="s2">&quot;To use local version, run pip install &#39;AutoRAG[gpu]&#39;&quot;</span>
 	<span class="p">)</span>
 
-
 <span class="k">try</span><span class="p">:</span>
 	<span class="kn">import</span> <span class="nn">transformers</span>
 

_sources/local_model.md.txt

@@ -45,6 +45,7 @@ To change the LLM model type, you can change the `llm` parameter to the followin
 | HuggingFaceLLM | huggingfacellm |
 |   OpenAILike   |   openailike   |
 |     Ollama     |     ollama     |
+|    Bedrock     |    bedrock     |
 
 For example, if you want to use `OpenAILike` model, you can set `llm` parameter to `openailike`.