mirror of
https://github.com/microsoft/graphrag.git
synced 2026-01-14 09:07:20 +08:00
Deploying to gh-pages from @ microsoft/graphrag@469ee8568f 🚀
This commit is contained in:
AlonsoGuevara
parent
2e3e8921af
commit
ee719d160c
@ -2511,194 +2511,196 @@ search = DRIFTSearch(
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">AuthenticationError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[6]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> resp = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> search.search(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Who is agent Mercer?</span><span class="ansi-yellow-fg">"</span>)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/drift_search/search.py:213</span>, in <span class="ansi-cyan-fg">DRIFTSearch.search</span><span class="ansi-blue-fg">(self, query, conversation_history, reduce, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 210</span> <span style="color: rgb(95,135,135)"># Check if query state is empty</span>
|
||||
<span class="ansi-green-fg"> 211</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span style="color: rgb(0,135,0)">self</span>.query_state.graph:
|
||||
<span class="ansi-green-fg"> 212</span> <span style="color: rgb(95,135,135)"># Prime the search with the primer</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">213</span> primer_context, token_ct = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.context_builder.build_context(query)
|
||||
<span class="ansi-green-fg"> 214</span> llm_calls[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = token_ct[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">llm_calls</span><span class="ansi-yellow-fg">"</span>]
|
||||
<span class="ansi-green-fg"> 215</span> prompt_tokens[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = token_ct[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">prompt_tokens</span><span class="ansi-yellow-fg">"</span>]
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/drift_search/drift_context.py:199</span>, in <span class="ansi-cyan-fg">DRIFTSearchContextBuilder.build_context</span><span class="ansi-blue-fg">(self, query, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 190</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span class="ansi-bold" style="color: rgb(215,95,95)">ValueError</span>(missing_reports_error)
|
||||
<span class="ansi-green-fg"> 192</span> query_processor = PrimerQueryProcessor(
|
||||
<span class="ansi-green-fg"> 193</span> chat_model=<span style="color: rgb(0,135,0)">self</span>.model,
|
||||
<span class="ansi-green-fg"> 194</span> text_embedder=<span style="color: rgb(0,135,0)">self</span>.text_embedder,
|
||||
<span class="ansi-green-fg"> 195</span> token_encoder=<span style="color: rgb(0,135,0)">self</span>.token_encoder,
|
||||
<span class="ansi-green-fg"> 196</span> reports=<span style="color: rgb(0,135,0)">self</span>.reports,
|
||||
<span class="ansi-green-fg"> 197</span> )
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">199</span> query_embedding, token_ct = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> query_processor(query)
|
||||
<span class="ansi-green-fg"> 201</span> report_df = <span style="color: rgb(0,135,0)">self</span>.convert_reports_to_df(<span style="color: rgb(0,135,0)">self</span>.reports)
|
||||
<span class="ansi-green-fg"> 203</span> <span style="color: rgb(95,135,135)"># Check compatibility between query embedding and document embeddings</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/drift_search/primer.py:96</span>, in <span class="ansi-cyan-fg">PrimerQueryProcessor.__call__</span><span class="ansi-blue-fg">(self, query)</span>
|
||||
<span class="ansi-green-fg"> 85</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">__call__</span>(<span style="color: rgb(0,135,0)">self</span>, query: <span style="color: rgb(0,135,0)">str</span>) -> <span style="color: rgb(0,135,0)">tuple</span>[<span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">float</span>], <span style="color: rgb(0,135,0)">dict</span>[<span style="color: rgb(0,135,0)">str</span>, <span style="color: rgb(0,135,0)">int</span>]]:
|
||||
<span class="ansi-green-fg"> 86</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 87</span> <span class="ansi-yellow-fg"> Call method to process the query, expand it, and embed the result.</span>
|
||||
<span class="ansi-green-fg"> 88</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 94</span> <span class="ansi-yellow-fg"> tuple[list[float], int]: List of embeddings for the expanded query and the token count.</span>
|
||||
<span class="ansi-green-fg"> 95</span> <span class="ansi-yellow-fg"> """</span>
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">96</span> hyde_query, token_ct = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.expand_query(query)
|
||||
<span class="ansi-green-fg"> 97</span> logger.debug(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Expanded query: </span><span class="ansi-bold" style="color: rgb(175,95,135)">%s</span><span class="ansi-yellow-fg">"</span>, hyde_query)
|
||||
<span class="ansi-green-fg"> 98</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span style="color: rgb(0,135,0)">self</span>.text_embedder.embed(hyde_query), token_ct
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/drift_search/primer.py:70</span>, in <span class="ansi-cyan-fg">PrimerQueryProcessor.expand_query</span><span class="ansi-blue-fg">(self, query)</span>
|
||||
<span class="ansi-green-fg"> 63</span> template = secrets.choice(<span style="color: rgb(0,135,0)">self</span>.reports).full_content <span style="color: rgb(95,135,135)"># nosec S311</span>
|
||||
<span class="ansi-green-fg"> 65</span> prompt = <span class="ansi-yellow-fg">f</span><span class="ansi-yellow-fg">"""</span><span class="ansi-yellow-fg">Create a hypothetical answer to the following query: </span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>query<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span>
|
||||
<span class="ansi-green-fg"> 66</span> <span class="ansi-yellow-fg"> Format it to follow the structure of the template below:</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span>
|
||||
<span class="ansi-green-fg"> 67</span> <span class="ansi-yellow-fg"> </span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>template<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 68</span> <span class="ansi-yellow-fg"> Ensure that the hypothetical answer does not reference new named entities that are not present in the original query.</span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">70</span> model_response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.chat_model.achat(prompt)
|
||||
<span class="ansi-green-fg"> 71</span> text = model_response.output.content
|
||||
<span class="ansi-green-fg"> 73</span> prompt_tokens = num_tokens(prompt, <span style="color: rgb(0,135,0)">self</span>.token_encoder)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:82</span>, in <span class="ansi-cyan-fg">OpenAIChatFNLLM.achat</span><span class="ansi-blue-fg">(self, prompt, history, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 70</span> <span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 71</span> <span class="ansi-yellow-fg">Chat with the Model using the given prompt.</span>
|
||||
<span class="ansi-green-fg"> 72</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 79</span> <span class="ansi-yellow-fg"> The response from the Model.</span>
|
||||
<span class="ansi-green-fg"> 80</span> <span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 81</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> history <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>:
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">82</span> response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.model(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 83</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span>:
|
||||
<span class="ansi-green-fg"> 84</span> response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.model(prompt, history=history, **kwargs)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_chat_llm.py:94</span>, in <span class="ansi-cyan-fg">OpenAIChatLLMImpl.__call__</span><span class="ansi-blue-fg">(self, prompt, stream, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 91</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> stream:
|
||||
<span class="ansi-green-fg"> 92</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._streaming_chat_llm(prompt, **kwargs)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">94</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._text_chat_llm(prompt, **kwargs)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/services/openai_tools_parsing.py:130</span>, in <span class="ansi-cyan-fg">OpenAIParseToolsLLM.__call__</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 127</span> tools = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">tools</span><span class="ansi-yellow-fg">"</span>, [])
|
||||
<span class="ansi-green-fg"> 129</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> tools:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">130</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._delegate(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 132</span> completion_parameters = <span style="color: rgb(0,135,0)">self</span>._add_tools_to_parameters(kwargs, tools)
|
||||
<span class="ansi-green-fg"> 134</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._delegate(prompt, **completion_parameters)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:144</span>, in <span class="ansi-cyan-fg">BaseLLM.__call__</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg"> 143</span> prompt, kwargs = <span style="color: rgb(0,135,0)">self</span>._rewrite_input(prompt, kwargs)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">144</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._decorated_target(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-bold" style="color: rgb(0,135,0)">except</span> <span class="ansi-bold" style="color: rgb(215,95,95)">BaseException</span> <span class="ansi-bold" style="color: rgb(0,135,0)">as</span> e:
|
||||
<span class="ansi-green-fg"> 146</span> stack_trace = traceback.format_exc()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/json.py:78</span>, in <span class="ansi-cyan-fg">JsonReceiver.decorate.<locals>.invoke</span><span class="ansi-blue-fg">(prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">json_model</span><span class="ansi-yellow-fg">"</span>) <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> <span class="ansi-bold" style="color: rgb(175,0,255)">or</span> kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">json</span><span class="ansi-yellow-fg">"</span>):
|
||||
<span class="ansi-green-fg"> 77</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> this.invoke_json(delegate, prompt, kwargs)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">78</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **kwargs)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/rate_limiter.py:75</span>, in <span class="ansi-cyan-fg">RateLimiter.decorate.<locals>.invoke</span><span class="ansi-blue-fg">(prompt, **args)</span>
|
||||
<span class="ansi-green-fg"> 73</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">with</span> <span style="color: rgb(0,135,0)">self</span>._limiter.use(manifest):
|
||||
<span class="ansi-green-fg"> 74</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_acquired(manifest)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">75</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **args)
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 77</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_released(manifest)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:126</span>, in <span class="ansi-cyan-fg">BaseLLM._decorator_target</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> <span class="ansi-yellow-fg">"""Target for the decorator chain.</span>
|
||||
<span class="ansi-green-fg"> 122</span>
|
||||
<span class="ansi-green-fg"> 123</span> <span class="ansi-yellow-fg">Leave signature alone as prompt, kwargs.</span>
|
||||
<span class="ansi-green-fg"> 124</span> <span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 125</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_execute_llm()
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> output = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._execute_llm(prompt, kwargs)
|
||||
<span class="ansi-green-fg"> 127</span> result = LLMOutput(output=output)
|
||||
<span class="ansi-green-fg"> 128</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._inject_usage(result)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_text_chat_llm.py:173</span>, in <span class="ansi-cyan-fg">OpenAITextChatLLMImpl._execute_llm</span><span class="ansi-blue-fg">(self, prompt, kwargs)</span>
|
||||
<span class="ansi-green-fg"> 170</span> local_model_parameters = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model_parameters</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg"> 171</span> parameters = <span style="color: rgb(0,135,0)">self</span>._build_completion_parameters(local_model_parameters)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">173</span> raw_response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._client.chat.completions.with_raw_response.create(
|
||||
<span class="ansi-green-fg"> 174</span> messages=cast(Iterator[ChatCompletionMessageParam], messages),
|
||||
<span class="ansi-green-fg"> 175</span> **parameters,
|
||||
<span class="ansi-green-fg"> 176</span> )
|
||||
<span class="ansi-green-fg"> 177</span> completion = raw_response.parse()
|
||||
<span class="ansi-green-fg"> 178</span> headers = raw_response.headers
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_legacy_response.py:381</span>, in <span class="ansi-cyan-fg">async_to_raw_response_wrapper.<locals>.wrapped</span><span class="ansi-blue-fg">(*args, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 377</span> extra_headers[RAW_RESPONSE_HEADER] = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">true</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 379</span> kwargs[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">extra_headers</span><span class="ansi-yellow-fg">"</span>] = extra_headers
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">381</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> cast(LegacyAPIResponse[R], <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> func(*args, **kwargs))
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/resources/chat/completions/completions.py:2454</span>, in <span class="ansi-cyan-fg">AsyncCompletions.create</span><span class="ansi-blue-fg">(self, messages, model, audio, frequency_penalty, function_call, functions, logit_bias, logprobs, max_completion_tokens, max_tokens, metadata, modalities, n, parallel_tool_calls, prediction, presence_penalty, reasoning_effort, response_format, seed, service_tier, stop, store, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, web_search_options, extra_headers, extra_query, extra_body, timeout)</span>
|
||||
<span class="ansi-green-fg"> 2411</span> <span style="color: rgb(175,0,255)">@required_args</span>([<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">messages</span><span class="ansi-yellow-fg">"</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model</span><span class="ansi-yellow-fg">"</span>], [<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">messages</span><span class="ansi-yellow-fg">"</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model</span><span class="ansi-yellow-fg">"</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stream</span><span class="ansi-yellow-fg">"</span>])
|
||||
<span class="ansi-green-fg"> 2412</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">create</span>(
|
||||
<span class="ansi-green-fg"> 2413</span> <span style="color: rgb(0,135,0)">self</span>,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 2451</span> timeout: <span style="color: rgb(0,135,0)">float</span> | httpx.Timeout | <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> | NotGiven = NOT_GIVEN,
|
||||
<span class="ansi-green-fg"> 2452</span> ) -> ChatCompletion | AsyncStream[ChatCompletionChunk]:
|
||||
<span class="ansi-green-fg"> 2453</span> validate_response_format(response_format)
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">2454</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._post(
|
||||
<span class="ansi-green-fg"> 2455</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">/chat/completions</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg"> 2456</span> body=<span class="ansi-bold" style="color: rgb(0,135,0)">await</span> async_maybe_transform(
|
||||
<span class="ansi-green-fg"> 2457</span> {
|
||||
<span class="ansi-green-fg"> 2458</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">messages</span><span class="ansi-yellow-fg">"</span>: messages,
|
||||
<span class="ansi-green-fg"> 2459</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model</span><span class="ansi-yellow-fg">"</span>: model,
|
||||
<span class="ansi-green-fg"> 2460</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">audio</span><span class="ansi-yellow-fg">"</span>: audio,
|
||||
<span class="ansi-green-fg"> 2461</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">frequency_penalty</span><span class="ansi-yellow-fg">"</span>: frequency_penalty,
|
||||
<span class="ansi-green-fg"> 2462</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">function_call</span><span class="ansi-yellow-fg">"</span>: function_call,
|
||||
<span class="ansi-green-fg"> 2463</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">functions</span><span class="ansi-yellow-fg">"</span>: functions,
|
||||
<span class="ansi-green-fg"> 2464</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">logit_bias</span><span class="ansi-yellow-fg">"</span>: logit_bias,
|
||||
<span class="ansi-green-fg"> 2465</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">logprobs</span><span class="ansi-yellow-fg">"</span>: logprobs,
|
||||
<span class="ansi-green-fg"> 2466</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">max_completion_tokens</span><span class="ansi-yellow-fg">"</span>: max_completion_tokens,
|
||||
<span class="ansi-green-fg"> 2467</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">max_tokens</span><span class="ansi-yellow-fg">"</span>: max_tokens,
|
||||
<span class="ansi-green-fg"> 2468</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">metadata</span><span class="ansi-yellow-fg">"</span>: metadata,
|
||||
<span class="ansi-green-fg"> 2469</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">modalities</span><span class="ansi-yellow-fg">"</span>: modalities,
|
||||
<span class="ansi-green-fg"> 2470</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">n</span><span class="ansi-yellow-fg">"</span>: n,
|
||||
<span class="ansi-green-fg"> 2471</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">parallel_tool_calls</span><span class="ansi-yellow-fg">"</span>: parallel_tool_calls,
|
||||
<span class="ansi-green-fg"> 2472</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">prediction</span><span class="ansi-yellow-fg">"</span>: prediction,
|
||||
<span class="ansi-green-fg"> 2473</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">presence_penalty</span><span class="ansi-yellow-fg">"</span>: presence_penalty,
|
||||
<span class="ansi-green-fg"> 2474</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">reasoning_effort</span><span class="ansi-yellow-fg">"</span>: reasoning_effort,
|
||||
<span class="ansi-green-fg"> 2475</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">response_format</span><span class="ansi-yellow-fg">"</span>: response_format,
|
||||
<span class="ansi-green-fg"> 2476</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">seed</span><span class="ansi-yellow-fg">"</span>: seed,
|
||||
<span class="ansi-green-fg"> 2477</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">service_tier</span><span class="ansi-yellow-fg">"</span>: service_tier,
|
||||
<span class="ansi-green-fg"> 2478</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stop</span><span class="ansi-yellow-fg">"</span>: stop,
|
||||
<span class="ansi-green-fg"> 2479</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">store</span><span class="ansi-yellow-fg">"</span>: store,
|
||||
<span class="ansi-green-fg"> 2480</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stream</span><span class="ansi-yellow-fg">"</span>: stream,
|
||||
<span class="ansi-green-fg"> 2481</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stream_options</span><span class="ansi-yellow-fg">"</span>: stream_options,
|
||||
<span class="ansi-green-fg"> 2482</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">temperature</span><span class="ansi-yellow-fg">"</span>: temperature,
|
||||
<span class="ansi-green-fg"> 2483</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">tool_choice</span><span class="ansi-yellow-fg">"</span>: tool_choice,
|
||||
<span class="ansi-green-fg"> 2484</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">tools</span><span class="ansi-yellow-fg">"</span>: tools,
|
||||
<span class="ansi-green-fg"> 2485</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">top_logprobs</span><span class="ansi-yellow-fg">"</span>: top_logprobs,
|
||||
<span class="ansi-green-fg"> 2486</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">top_p</span><span class="ansi-yellow-fg">"</span>: top_p,
|
||||
<span class="ansi-green-fg"> 2487</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">user</span><span class="ansi-yellow-fg">"</span>: user,
|
||||
<span class="ansi-green-fg"> 2488</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">web_search_options</span><span class="ansi-yellow-fg">"</span>: web_search_options,
|
||||
<span class="ansi-green-fg"> 2489</span> },
|
||||
<span class="ansi-green-fg"> 2490</span> completion_create_params.CompletionCreateParamsStreaming
|
||||
<span class="ansi-green-fg"> 2491</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> stream
|
||||
<span class="ansi-green-fg"> 2492</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span> completion_create_params.CompletionCreateParamsNonStreaming,
|
||||
<span class="ansi-green-fg"> 2493</span> ),
|
||||
<span class="ansi-green-fg"> 2494</span> options=make_request_options(
|
||||
<span class="ansi-green-fg"> 2495</span> extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
<span class="ansi-green-fg"> 2496</span> ),
|
||||
<span class="ansi-green-fg"> 2497</span> cast_to=ChatCompletion,
|
||||
<span class="ansi-green-fg"> 2498</span> stream=stream <span class="ansi-bold" style="color: rgb(175,0,255)">or</span> <span class="ansi-bold" style="color: rgb(0,135,0)">False</span>,
|
||||
<span class="ansi-green-fg"> 2499</span> stream_cls=AsyncStream[ChatCompletionChunk],
|
||||
<span class="ansi-green-fg"> 2500</span> )
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1791</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.post</span><span class="ansi-blue-fg">(self, path, cast_to, body, files, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1777</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">post</span>(
|
||||
<span class="ansi-green-fg"> 1778</span> <span style="color: rgb(0,135,0)">self</span>,
|
||||
<span class="ansi-green-fg"> 1779</span> path: <span style="color: rgb(0,135,0)">str</span>,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 1786</span> stream_cls: <span style="color: rgb(0,135,0)">type</span>[_AsyncStreamT] | <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>,
|
||||
<span class="ansi-green-fg"> 1787</span> ) -> ResponseT | _AsyncStreamT:
|
||||
<span class="ansi-green-fg"> 1788</span> opts = FinalRequestOptions.construct(
|
||||
<span class="ansi-green-fg"> 1789</span> method=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">post</span><span class="ansi-yellow-fg">"</span>, url=path, json_data=body, files=<span class="ansi-bold" style="color: rgb(0,135,0)">await</span> async_to_httpx_files(files), **options
|
||||
<span class="ansi-green-fg"> 1790</span> )
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1791</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1591</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.request</span><span class="ansi-blue-fg">(self, cast_to, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1588</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> err.response.aread()
|
||||
<span class="ansi-green-fg"> 1590</span> log.debug(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Re-raising status error</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1591</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._make_status_error_from_response(err.response) <span class="ansi-bold" style="color: rgb(0,135,0)">from</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
<span class="ansi-green-fg"> 1593</span> <span class="ansi-bold" style="color: rgb(0,135,0)">break</span>
|
||||
<span class="ansi-green-fg"> 1595</span> <span class="ansi-bold" style="color: rgb(0,135,0)">assert</span> response <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">could not resolve response (should never happen)</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-red-fg">AuthenticationError</span>: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************************************************************************************************************************zWYA. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}</pre>
|
||||
<pre>
0%| | 0/1 [00:00<?, ?it/s]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
100%|██████████| 1/1 [00:10<00:00, 10.35s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
0%| | 0/3 [00:00<?, ?it/s]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:22.0102 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:22.0671 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:23.0205 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
33%|███▎ | 1/3 [00:13<00:26, 13.08s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
67%|██████▋ | 2/3 [00:18<00:08, 8.57s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
100%|██████████| 3/3 [00:19<00:00, 5.16s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
0%| | 0/3 [00:00<?, ?it/s]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:42.0425 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:42.0705 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:42.0846 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
33%|███▎ | 1/3 [00:09<00:18, 9.31s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
67%|██████▋ | 2/3 [00:10<00:04, 4.46s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
100%|██████████| 3/3 [00:11<00:00, 2.94s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
0%| | 0/3 [00:00<?, ?it/s]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:53.0647 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:54.0403 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:37:55.0117 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
33%|███▎ | 1/3 [00:08<00:17, 8.91s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
67%|██████▋ | 2/3 [00:10<00:04, 4.42s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
100%|██████████| 3/3 [00:16<00:00, 5.33s/it]</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -2734,16 +2736,10 @@ search = DRIFTSearch(
|
||||
<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
|
||||
</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[7]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> <span class="ansi-yellow-bg">resp</span>.response
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'resp' is not defined</pre>
|
||||
<div class="jp-OutputArea-child jp-OutputArea-executeResult">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[7]:</div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>"Agent Alex Mercer is a pivotal figure within the Paranormal Military Squad, playing a central role in Operation: Dulce. This operation involves the exploration and investigation of the Dulce base, which is associated with advanced alien technology. Mercer's role is multifaceted, encompassing leadership, mentorship, and active participation in the mission [Data: Reports (0)].\n\n### Leadership Style\nMercer is characterized by a leadership style that emphasizes intuition, trust, and mentorship. He is known for nurturing talent and fostering a collaborative environment, as seen in his mentorship of Sam Rivera, a cybersecurity expert within the squad [Data: Reports (0); Sources (0, 1)].\n\n### Role in the Mission\nMercer's involvement in the exploration of the Dulce base is crucial. His leadership and decision-making skills are instrumental in navigating the complexities of the mission, which includes both the physical exploration of the base and the analysis of alien technology [Data: Reports (0)].\n\n### Team Dynamics\nMercer's leadership style contrasts with that of Agent Taylor Cruz, who is more authoritative and protocol-driven. Despite these differences, Mercer and Cruz maintain a professional relationship that underscores the collaborative nature of the mission [Data: Reports (0); Sources (0, 1)].\n\nIn summary, Agent Alex Mercer is a central figure in the Paranormal Military Squad, whose leadership and mentorship are vital to the success of Operation: Dulce. His role highlights the importance of teamwork and adaptability in achieving the mission's objectives [Data: Reports (0)]."</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -2781,14 +2777,108 @@ search = DRIFTSearch(
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[8]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> <span style="color: rgb(0,135,0)">print</span>(<span class="ansi-yellow-bg">resp</span>.context_data)
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>{"How does Agent Mercer's leadership style differ from Agent Cruz's?": {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'resp' is not defined</pre>
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
1 2 differently than praise from others. This was...
|
||||
2 3 contrast to the rigid silence enveloping the ...
|
||||
3 1 , the hollow echo of the bay a stark reminder ...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}, "How does Sam Rivera's cybersecurity expertise contribute to the mission?": {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
1 2 differently than praise from others. This was...
|
||||
2 1 , the hollow echo of the bay a stark reminder ...
|
||||
3 3 contrast to the rigid silence enveloping the ...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}, 'What are the key challenges faced by the Paranormal Military Squad in Operation: Dulce?': {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 2 differently than praise from others. This was...
|
||||
1 3 contrast to the rigid silence enveloping the ...
|
||||
2 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
3 4 a mask of duty.\n\nIn the midst of the descen...
|
||||
4 1 , the hollow echo of the bay a stark reminder ...}, "How does Sam Rivera's expertise compare to other team members' skills?": {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
1 2 differently than praise from others. This was...
|
||||
2 1 , the hollow echo of the bay a stark reminder ...
|
||||
3 3 contrast to the rigid silence enveloping the ...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}, "What are the potential consequences if Sam Rivera's cybersecurity efforts fail during the mission?": {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
1 2 differently than praise from others. This was...
|
||||
2 1 , the hollow echo of the bay a stark reminder ...
|
||||
3 3 contrast to the rigid silence enveloping the ...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}, 'What specific role does Alex Mercer play in overcoming these challenges?': {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 3 contrast to the rigid silence enveloping the ...
|
||||
1 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
2 1 , the hollow echo of the bay a stark reminder ...
|
||||
3 2 differently than praise from others. This was...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}, "How do other team members perceive Mercer's leadership compared to Cruz's?": {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
1 2 differently than praise from others. This was...
|
||||
2 3 contrast to the rigid silence enveloping the ...
|
||||
3 1 , the hollow echo of the bay a stark reminder ...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}, "How does Cruz's focus on protocol affect the team's adaptability during the mission?": {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
1 2 differently than praise from others. This was...
|
||||
2 3 contrast to the rigid silence enveloping the ...
|
||||
3 1 , the hollow echo of the bay a stark reminder ...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}, 'What specific cybersecurity measures is Sam Rivera implementing during the mission?': {'reports': id title \
|
||||
0 1 Paranormal Military Squad and Operation: Dulce
|
||||
|
||||
content
|
||||
0 # Paranormal Military Squad and Operation: Dul... , 'entities': Empty DataFrame
|
||||
Columns: [in_context]
|
||||
Index: [], 'sources': id text
|
||||
0 0 # Operation: Dulce\n\n## Chapter 1\n\nThe thru...
|
||||
1 2 differently than praise from others. This was...
|
||||
2 1 , the hollow echo of the bay a stark reminder ...
|
||||
3 3 contrast to the rigid silence enveloping the ...
|
||||
4 4 a mask of duty.\n\nIn the midst of the descen...}}
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -2706,67 +2706,23 @@ print(result.response)</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-14 14:08:01.0335 - ERROR - graphrag.query.structured_search.global_search.search - Exception in _map_response_single_batch
|
||||
Traceback (most recent call last):
|
||||
File "/home/runner/work/graphrag/graphrag/graphrag/query/structured_search/global_search/search.py", line 227, in _map_response_single_batch
|
||||
model_response = await self.model.achat(
|
||||
^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py", line 84, in achat
|
||||
response = await self.model(prompt, history=history, **kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_chat_llm.py", line 94, in __call__
|
||||
return await self._text_chat_llm(prompt, **kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/services/openai_tools_parsing.py", line 130, in __call__
|
||||
return await self._delegate(prompt, **kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py", line 144, in __call__
|
||||
return await self._decorated_target(prompt, **kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/json.py", line 77, in invoke
|
||||
return await this.invoke_json(delegate, prompt, kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/json.py", line 96, in invoke_json
|
||||
return await self.try_receive_json(delegate, prompt, kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/json.py", line 162, in try_receive_json
|
||||
result = await delegate(prompt, **kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/rate_limiter.py", line 75, in invoke
|
||||
result = await delegate(prompt, **args)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py", line 126, in _decorator_target
|
||||
output = await self._execute_llm(prompt, kwargs)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_text_chat_llm.py", line 173, in _execute_llm
|
||||
raw_response = await self._client.chat.completions.with_raw_response.create(
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_legacy_response.py", line 381, in wrapped
|
||||
return cast(LegacyAPIResponse[R], await func(*args, **kwargs))
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/resources/chat/completions/completions.py", line 2454, in create
|
||||
return await self._post(
|
||||
^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py", line 1791, in post
|
||||
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
File "/home/runner/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py", line 1591, in request
|
||||
raise self._make_status_error_from_response(err.response) from None
|
||||
openai.AuthenticationError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************************************************************************************************************************zWYA. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-14 14:08:01.0339 - WARNING - graphrag.query.structured_search.global_search.search - Warning: All map responses have score 0 (i.e., no relevant information found from the dataset), returning a canned 'I do not know' answer. You can try enabling `allow_general_knowledge` to encourage the LLM to incorporate relevant general knowledge, at the risk of increasing hallucinations.
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>I am sorry but I am unable to answer this question given the provided data.
|
||||
<pre>### Overview of Operation: Dulce
|
||||
|
||||
Operation: Dulce is a significant mission undertaken by the Paranormal Military Squad, an elite group tasked with investigating alien technology and its implications for humanity. The operation's primary focus is on the Dulce base, a central element of the mission, where agents explore its depths to uncover secrets and advanced alien technology [Data: Reports (0, 1)].
|
||||
|
||||
### Key Agents and Their Roles
|
||||
|
||||
The mission involves key agents, including Alex Mercer, Taylor Cruz, Jordan Hayes, and Sam Rivera, each playing significant roles in the execution of Operation: Dulce. These agents are part of the Paranormal Military Squad, which is responsible for navigating the complexities of the Dulce base and ensuring the mission's success [Data: Reports (1)].
|
||||
|
||||
### Mission Objectives and Importance
|
||||
|
||||
The operation's objectives revolve around exploring the Dulce base and understanding the advanced alien technology associated with it. This technology is crucial to the mission's goals and the overall success of Operation: Dulce. The mission's complexity and importance are underscored by the need to uncover the secrets of the Dulce base, which may have significant implications for humanity [Data: Reports (0, 1)].
|
||||
|
||||
### Motivation and Sense of Duty
|
||||
|
||||
A strong sense of duty drives the individuals involved in Operation: Dulce. This motivation is essential for the team members as they undertake the mission and navigate the complexities of the Dulce base. The sense of duty ensures that the agents remain committed to the mission's objectives and the broader implications of their work [Data: Reports (0)].
|
||||
|
||||
In summary, Operation: Dulce is a critical mission focused on exploring the Dulce base and its advanced alien technology, with a dedicated team of agents working to uncover its secrets for the benefit of humanity.
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
@ -2897,7 +2853,7 @@ print(
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>LLM calls: 1. Prompt tokens: 2401. Output tokens: 0.
|
||||
<pre>LLM calls: 2. Prompt tokens: 3418. Output tokens: 636.
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -2623,225 +2623,23 @@ print(result.response)</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">AuthenticationError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[9]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> search_engine.search(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">What is operation dulce?</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg"> 3</span> <span style="color: rgb(0,135,0)">print</span>(result.response)
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>### Overview of Operation: Dulce
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/global_search/search.py:153</span>, in <span class="ansi-cyan-fg">GlobalSearch.search</span><span class="ansi-blue-fg">(self, query, conversation_history, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 150</span> llm_calls, prompt_tokens, output_tokens = {}, {}, {}
|
||||
<span class="ansi-green-fg"> 152</span> start_time = time.time()
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">153</span> context_result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.context_builder.build_context(
|
||||
<span class="ansi-green-fg"> 154</span> query=query,
|
||||
<span class="ansi-green-fg"> 155</span> conversation_history=conversation_history,
|
||||
<span class="ansi-green-fg"> 156</span> **<span style="color: rgb(0,135,0)">self</span>.context_builder_params,
|
||||
<span class="ansi-green-fg"> 157</span> )
|
||||
<span class="ansi-green-fg"> 158</span> llm_calls[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = context_result.llm_calls
|
||||
<span class="ansi-green-fg"> 159</span> prompt_tokens[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = context_result.prompt_tokens
|
||||
Operation: Dulce is a significant mission undertaken by the Paranormal Military Squad, focusing on the investigation of alien technology and its implications for humanity. The operation is centered around the exploration and uncovering of secrets within the Dulce base, which is known for its association with advanced alien technology [Data: Reports (0)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/global_search/community_context.py:98</span>, in <span class="ansi-cyan-fg">GlobalCommunityContext.build_context</span><span class="ansi-blue-fg">(self, query, conversation_history, use_community_summary, column_delimiter, shuffle_data, include_community_rank, min_community_rank, community_rank_name, include_community_weight, community_weight_name, normalize_community_weight, max_context_tokens, context_name, conversation_history_user_turns_only, conversation_history_max_turns, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 93</span> community_reports = <span style="color: rgb(0,135,0)">self</span>.community_reports
|
||||
<span class="ansi-green-fg"> 94</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span style="color: rgb(0,135,0)">self</span>.dynamic_community_selection <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>:
|
||||
<span class="ansi-green-fg"> 95</span> (
|
||||
<span class="ansi-green-fg"> 96</span> community_reports,
|
||||
<span class="ansi-green-fg"> 97</span> dynamic_info,
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">98</span> ) = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.dynamic_community_selection.select(query)
|
||||
<span class="ansi-green-fg"> 99</span> llm_calls += dynamic_info[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">llm_calls</span><span class="ansi-yellow-fg">"</span>]
|
||||
<span class="ansi-green-fg"> 100</span> prompt_tokens += dynamic_info[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">prompt_tokens</span><span class="ansi-yellow-fg">"</span>]
|
||||
### Key Participants
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/dynamic_community_selection.py:91</span>, in <span class="ansi-cyan-fg">DynamicCommunitySelection.select</span><span class="ansi-blue-fg">(self, query)</span>
|
||||
<span class="ansi-green-fg"> 88</span> relevant_communities = <span style="color: rgb(0,135,0)">set</span>()
|
||||
<span class="ansi-green-fg"> 90</span> <span class="ansi-bold" style="color: rgb(0,135,0)">while</span> queue:
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">91</span> gather_results = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> asyncio.gather(*[
|
||||
<span class="ansi-green-fg"> 92</span> rate_relevancy(
|
||||
<span class="ansi-green-fg"> 93</span> query=query,
|
||||
<span class="ansi-green-fg"> 94</span> description=(
|
||||
<span class="ansi-green-fg"> 95</span> <span style="color: rgb(0,135,0)">self</span>.reports[community].summary
|
||||
<span class="ansi-green-fg"> 96</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span style="color: rgb(0,135,0)">self</span>.use_summary
|
||||
<span class="ansi-green-fg"> 97</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span> <span style="color: rgb(0,135,0)">self</span>.reports[community].full_content
|
||||
<span class="ansi-green-fg"> 98</span> ),
|
||||
<span class="ansi-green-fg"> 99</span> model=<span style="color: rgb(0,135,0)">self</span>.model,
|
||||
<span class="ansi-green-fg"> 100</span> token_encoder=<span style="color: rgb(0,135,0)">self</span>.token_encoder,
|
||||
<span class="ansi-green-fg"> 101</span> rate_query=<span style="color: rgb(0,135,0)">self</span>.rate_query,
|
||||
<span class="ansi-green-fg"> 102</span> num_repeats=<span style="color: rgb(0,135,0)">self</span>.num_repeats,
|
||||
<span class="ansi-green-fg"> 103</span> semaphore=<span style="color: rgb(0,135,0)">self</span>.semaphore,
|
||||
<span class="ansi-green-fg"> 104</span> **<span style="color: rgb(0,135,0)">self</span>.model_params,
|
||||
<span class="ansi-green-fg"> 105</span> )
|
||||
<span class="ansi-green-fg"> 106</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> community <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> queue
|
||||
<span class="ansi-green-fg"> 107</span> ])
|
||||
<span class="ansi-green-fg"> 109</span> communities_to_rate = []
|
||||
<span class="ansi-green-fg"> 110</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> community, result <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> <span style="color: rgb(0,135,0)">zip</span>(queue, gather_results, strict=<span class="ansi-bold" style="color: rgb(0,135,0)">True</span>):
|
||||
The mission is executed by the Paranormal Military Squad, an elite group tasked with carrying out Operation: Dulce. Key agents involved in this operation include Alex Mercer, Taylor Cruz, Jordan Hayes, and Sam Rivera. Each of these agents plays a significant role in the mission, contributing to the exploration and understanding of the Dulce base [Data: Reports (1)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/rate_relevancy.py:53</span>, in <span class="ansi-cyan-fg">rate_relevancy</span><span class="ansi-blue-fg">(query, description, model, token_encoder, rate_query, num_repeats, semaphore, **model_params)</span>
|
||||
<span class="ansi-green-fg"> 51</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> _ <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> <span style="color: rgb(0,135,0)">range</span>(num_repeats):
|
||||
<span class="ansi-green-fg"> 52</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">with</span> semaphore <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> semaphore <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span> nullcontext():
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">53</span> model_response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> model.achat(
|
||||
<span class="ansi-green-fg"> 54</span> prompt=query, history=messages, model_parameters=model_params, json=<span class="ansi-bold" style="color: rgb(0,135,0)">True</span>
|
||||
<span class="ansi-green-fg"> 55</span> )
|
||||
<span class="ansi-green-fg"> 56</span> response = model_response.output.content
|
||||
<span class="ansi-green-fg"> 57</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
### The Dulce Base
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:84</span>, in <span class="ansi-cyan-fg">OpenAIChatFNLLM.achat</span><span class="ansi-blue-fg">(self, prompt, history, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 82</span> response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.model(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 83</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span>:
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">84</span> response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.model(prompt, history=history, **kwargs)
|
||||
<span class="ansi-green-fg"> 85</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> BaseModelResponse(
|
||||
<span class="ansi-green-fg"> 86</span> output=BaseModelOutput(
|
||||
<span class="ansi-green-fg"> 87</span> content=response.output.content,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 94</span> metrics=response.metrics,
|
||||
<span class="ansi-green-fg"> 95</span> )
|
||||
The Dulce base is a central element of the operation. It is a location deeply associated with advanced alien technology, which is a primary focus of the mission. Dr. Jordan Hayes, one of the agents, is particularly involved in working on this technology within the lab, highlighting the base's importance in the operation [Data: Reports (1)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_chat_llm.py:94</span>, in <span class="ansi-cyan-fg">OpenAIChatLLMImpl.__call__</span><span class="ansi-blue-fg">(self, prompt, stream, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 91</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> stream:
|
||||
<span class="ansi-green-fg"> 92</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._streaming_chat_llm(prompt, **kwargs)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">94</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._text_chat_llm(prompt, **kwargs)
|
||||
### Motivation and Execution
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/services/openai_tools_parsing.py:130</span>, in <span class="ansi-cyan-fg">OpenAIParseToolsLLM.__call__</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 127</span> tools = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">tools</span><span class="ansi-yellow-fg">"</span>, [])
|
||||
<span class="ansi-green-fg"> 129</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> tools:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">130</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._delegate(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 132</span> completion_parameters = <span style="color: rgb(0,135,0)">self</span>._add_tools_to_parameters(kwargs, tools)
|
||||
<span class="ansi-green-fg"> 134</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._delegate(prompt, **completion_parameters)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:144</span>, in <span class="ansi-cyan-fg">BaseLLM.__call__</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg"> 143</span> prompt, kwargs = <span style="color: rgb(0,135,0)">self</span>._rewrite_input(prompt, kwargs)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">144</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._decorated_target(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-bold" style="color: rgb(0,135,0)">except</span> <span class="ansi-bold" style="color: rgb(215,95,95)">BaseException</span> <span class="ansi-bold" style="color: rgb(0,135,0)">as</span> e:
|
||||
<span class="ansi-green-fg"> 146</span> stack_trace = traceback.format_exc()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/json.py:77</span>, in <span class="ansi-cyan-fg">JsonReceiver.decorate.<locals>.invoke</span><span class="ansi-blue-fg">(prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 72</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">invoke</span>(
|
||||
<span class="ansi-green-fg"> 73</span> prompt: TInput,
|
||||
<span class="ansi-green-fg"> 74</span> **kwargs: Unpack[LLMInput[TJsonModel, THistoryEntry, TModelParameters]],
|
||||
<span class="ansi-green-fg"> 75</span> ) -> LLMOutput[TOutput, TJsonModel, THistoryEntry]:
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">json_model</span><span class="ansi-yellow-fg">"</span>) <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> <span class="ansi-bold" style="color: rgb(175,0,255)">or</span> kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">json</span><span class="ansi-yellow-fg">"</span>):
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">77</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> this.invoke_json(delegate, prompt, kwargs)
|
||||
<span class="ansi-green-fg"> 78</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **kwargs)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/json.py:96</span>, in <span class="ansi-cyan-fg">JsonReceiver.invoke_json</span><span class="ansi-blue-fg">(self, delegate, prompt, kwargs)</span>
|
||||
<span class="ansi-green-fg"> 94</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> attempt > <span class="ansi-green-fg">0</span>:
|
||||
<span class="ansi-green-fg"> 95</span> kwargs[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">bust_cache</span><span class="ansi-yellow-fg">"</span>] = <span class="ansi-bold" style="color: rgb(0,135,0)">True</span>
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">96</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.try_receive_json(delegate, prompt, kwargs)
|
||||
<span class="ansi-green-fg"> 97</span> <span class="ansi-bold" style="color: rgb(0,135,0)">except</span> FailedToGenerateValidJsonError <span class="ansi-bold" style="color: rgb(0,135,0)">as</span> e:
|
||||
<span class="ansi-green-fg"> 98</span> error = e
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/json.py:162</span>, in <span class="ansi-cyan-fg">LooseModeJsonReceiver.try_receive_json</span><span class="ansi-blue-fg">(self, delegate, prompt, kwargs)</span>
|
||||
<span class="ansi-green-fg"> 159</span> <span class="ansi-yellow-fg">"""Invoke the JSON decorator."""</span>
|
||||
<span class="ansi-green-fg"> 160</span> json_model = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">json_model</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">162</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 163</span> json_string = <span style="color: rgb(0,135,0)">self</span>._marshaler.extract_json_string(result)
|
||||
<span class="ansi-green-fg"> 164</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/rate_limiter.py:75</span>, in <span class="ansi-cyan-fg">RateLimiter.decorate.<locals>.invoke</span><span class="ansi-blue-fg">(prompt, **args)</span>
|
||||
<span class="ansi-green-fg"> 73</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">with</span> <span style="color: rgb(0,135,0)">self</span>._limiter.use(manifest):
|
||||
<span class="ansi-green-fg"> 74</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_acquired(manifest)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">75</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **args)
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 77</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_released(manifest)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:126</span>, in <span class="ansi-cyan-fg">BaseLLM._decorator_target</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> <span class="ansi-yellow-fg">"""Target for the decorator chain.</span>
|
||||
<span class="ansi-green-fg"> 122</span>
|
||||
<span class="ansi-green-fg"> 123</span> <span class="ansi-yellow-fg">Leave signature alone as prompt, kwargs.</span>
|
||||
<span class="ansi-green-fg"> 124</span> <span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 125</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_execute_llm()
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> output = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._execute_llm(prompt, kwargs)
|
||||
<span class="ansi-green-fg"> 127</span> result = LLMOutput(output=output)
|
||||
<span class="ansi-green-fg"> 128</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._inject_usage(result)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_text_chat_llm.py:173</span>, in <span class="ansi-cyan-fg">OpenAITextChatLLMImpl._execute_llm</span><span class="ansi-blue-fg">(self, prompt, kwargs)</span>
|
||||
<span class="ansi-green-fg"> 170</span> local_model_parameters = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model_parameters</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg"> 171</span> parameters = <span style="color: rgb(0,135,0)">self</span>._build_completion_parameters(local_model_parameters)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">173</span> raw_response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._client.chat.completions.with_raw_response.create(
|
||||
<span class="ansi-green-fg"> 174</span> messages=cast(Iterator[ChatCompletionMessageParam], messages),
|
||||
<span class="ansi-green-fg"> 175</span> **parameters,
|
||||
<span class="ansi-green-fg"> 176</span> )
|
||||
<span class="ansi-green-fg"> 177</span> completion = raw_response.parse()
|
||||
<span class="ansi-green-fg"> 178</span> headers = raw_response.headers
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_legacy_response.py:381</span>, in <span class="ansi-cyan-fg">async_to_raw_response_wrapper.<locals>.wrapped</span><span class="ansi-blue-fg">(*args, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 377</span> extra_headers[RAW_RESPONSE_HEADER] = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">true</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 379</span> kwargs[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">extra_headers</span><span class="ansi-yellow-fg">"</span>] = extra_headers
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">381</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> cast(LegacyAPIResponse[R], <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> func(*args, **kwargs))
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/resources/chat/completions/completions.py:2454</span>, in <span class="ansi-cyan-fg">AsyncCompletions.create</span><span class="ansi-blue-fg">(self, messages, model, audio, frequency_penalty, function_call, functions, logit_bias, logprobs, max_completion_tokens, max_tokens, metadata, modalities, n, parallel_tool_calls, prediction, presence_penalty, reasoning_effort, response_format, seed, service_tier, stop, store, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, web_search_options, extra_headers, extra_query, extra_body, timeout)</span>
|
||||
<span class="ansi-green-fg"> 2411</span> <span style="color: rgb(175,0,255)">@required_args</span>([<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">messages</span><span class="ansi-yellow-fg">"</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model</span><span class="ansi-yellow-fg">"</span>], [<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">messages</span><span class="ansi-yellow-fg">"</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model</span><span class="ansi-yellow-fg">"</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stream</span><span class="ansi-yellow-fg">"</span>])
|
||||
<span class="ansi-green-fg"> 2412</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">create</span>(
|
||||
<span class="ansi-green-fg"> 2413</span> <span style="color: rgb(0,135,0)">self</span>,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 2451</span> timeout: <span style="color: rgb(0,135,0)">float</span> | httpx.Timeout | <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> | NotGiven = NOT_GIVEN,
|
||||
<span class="ansi-green-fg"> 2452</span> ) -> ChatCompletion | AsyncStream[ChatCompletionChunk]:
|
||||
<span class="ansi-green-fg"> 2453</span> validate_response_format(response_format)
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">2454</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._post(
|
||||
<span class="ansi-green-fg"> 2455</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">/chat/completions</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg"> 2456</span> body=<span class="ansi-bold" style="color: rgb(0,135,0)">await</span> async_maybe_transform(
|
||||
<span class="ansi-green-fg"> 2457</span> {
|
||||
<span class="ansi-green-fg"> 2458</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">messages</span><span class="ansi-yellow-fg">"</span>: messages,
|
||||
<span class="ansi-green-fg"> 2459</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model</span><span class="ansi-yellow-fg">"</span>: model,
|
||||
<span class="ansi-green-fg"> 2460</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">audio</span><span class="ansi-yellow-fg">"</span>: audio,
|
||||
<span class="ansi-green-fg"> 2461</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">frequency_penalty</span><span class="ansi-yellow-fg">"</span>: frequency_penalty,
|
||||
<span class="ansi-green-fg"> 2462</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">function_call</span><span class="ansi-yellow-fg">"</span>: function_call,
|
||||
<span class="ansi-green-fg"> 2463</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">functions</span><span class="ansi-yellow-fg">"</span>: functions,
|
||||
<span class="ansi-green-fg"> 2464</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">logit_bias</span><span class="ansi-yellow-fg">"</span>: logit_bias,
|
||||
<span class="ansi-green-fg"> 2465</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">logprobs</span><span class="ansi-yellow-fg">"</span>: logprobs,
|
||||
<span class="ansi-green-fg"> 2466</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">max_completion_tokens</span><span class="ansi-yellow-fg">"</span>: max_completion_tokens,
|
||||
<span class="ansi-green-fg"> 2467</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">max_tokens</span><span class="ansi-yellow-fg">"</span>: max_tokens,
|
||||
<span class="ansi-green-fg"> 2468</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">metadata</span><span class="ansi-yellow-fg">"</span>: metadata,
|
||||
<span class="ansi-green-fg"> 2469</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">modalities</span><span class="ansi-yellow-fg">"</span>: modalities,
|
||||
<span class="ansi-green-fg"> 2470</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">n</span><span class="ansi-yellow-fg">"</span>: n,
|
||||
<span class="ansi-green-fg"> 2471</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">parallel_tool_calls</span><span class="ansi-yellow-fg">"</span>: parallel_tool_calls,
|
||||
<span class="ansi-green-fg"> 2472</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">prediction</span><span class="ansi-yellow-fg">"</span>: prediction,
|
||||
<span class="ansi-green-fg"> 2473</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">presence_penalty</span><span class="ansi-yellow-fg">"</span>: presence_penalty,
|
||||
<span class="ansi-green-fg"> 2474</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">reasoning_effort</span><span class="ansi-yellow-fg">"</span>: reasoning_effort,
|
||||
<span class="ansi-green-fg"> 2475</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">response_format</span><span class="ansi-yellow-fg">"</span>: response_format,
|
||||
<span class="ansi-green-fg"> 2476</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">seed</span><span class="ansi-yellow-fg">"</span>: seed,
|
||||
<span class="ansi-green-fg"> 2477</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">service_tier</span><span class="ansi-yellow-fg">"</span>: service_tier,
|
||||
<span class="ansi-green-fg"> 2478</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stop</span><span class="ansi-yellow-fg">"</span>: stop,
|
||||
<span class="ansi-green-fg"> 2479</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">store</span><span class="ansi-yellow-fg">"</span>: store,
|
||||
<span class="ansi-green-fg"> 2480</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stream</span><span class="ansi-yellow-fg">"</span>: stream,
|
||||
<span class="ansi-green-fg"> 2481</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">stream_options</span><span class="ansi-yellow-fg">"</span>: stream_options,
|
||||
<span class="ansi-green-fg"> 2482</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">temperature</span><span class="ansi-yellow-fg">"</span>: temperature,
|
||||
<span class="ansi-green-fg"> 2483</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">tool_choice</span><span class="ansi-yellow-fg">"</span>: tool_choice,
|
||||
<span class="ansi-green-fg"> 2484</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">tools</span><span class="ansi-yellow-fg">"</span>: tools,
|
||||
<span class="ansi-green-fg"> 2485</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">top_logprobs</span><span class="ansi-yellow-fg">"</span>: top_logprobs,
|
||||
<span class="ansi-green-fg"> 2486</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">top_p</span><span class="ansi-yellow-fg">"</span>: top_p,
|
||||
<span class="ansi-green-fg"> 2487</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">user</span><span class="ansi-yellow-fg">"</span>: user,
|
||||
<span class="ansi-green-fg"> 2488</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">web_search_options</span><span class="ansi-yellow-fg">"</span>: web_search_options,
|
||||
<span class="ansi-green-fg"> 2489</span> },
|
||||
<span class="ansi-green-fg"> 2490</span> completion_create_params.CompletionCreateParamsStreaming
|
||||
<span class="ansi-green-fg"> 2491</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> stream
|
||||
<span class="ansi-green-fg"> 2492</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span> completion_create_params.CompletionCreateParamsNonStreaming,
|
||||
<span class="ansi-green-fg"> 2493</span> ),
|
||||
<span class="ansi-green-fg"> 2494</span> options=make_request_options(
|
||||
<span class="ansi-green-fg"> 2495</span> extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
|
||||
<span class="ansi-green-fg"> 2496</span> ),
|
||||
<span class="ansi-green-fg"> 2497</span> cast_to=ChatCompletion,
|
||||
<span class="ansi-green-fg"> 2498</span> stream=stream <span class="ansi-bold" style="color: rgb(175,0,255)">or</span> <span class="ansi-bold" style="color: rgb(0,135,0)">False</span>,
|
||||
<span class="ansi-green-fg"> 2499</span> stream_cls=AsyncStream[ChatCompletionChunk],
|
||||
<span class="ansi-green-fg"> 2500</span> )
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1791</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.post</span><span class="ansi-blue-fg">(self, path, cast_to, body, files, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1777</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">post</span>(
|
||||
<span class="ansi-green-fg"> 1778</span> <span style="color: rgb(0,135,0)">self</span>,
|
||||
<span class="ansi-green-fg"> 1779</span> path: <span style="color: rgb(0,135,0)">str</span>,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 1786</span> stream_cls: <span style="color: rgb(0,135,0)">type</span>[_AsyncStreamT] | <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>,
|
||||
<span class="ansi-green-fg"> 1787</span> ) -> ResponseT | _AsyncStreamT:
|
||||
<span class="ansi-green-fg"> 1788</span> opts = FinalRequestOptions.construct(
|
||||
<span class="ansi-green-fg"> 1789</span> method=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">post</span><span class="ansi-yellow-fg">"</span>, url=path, json_data=body, files=<span class="ansi-bold" style="color: rgb(0,135,0)">await</span> async_to_httpx_files(files), **options
|
||||
<span class="ansi-green-fg"> 1790</span> )
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1791</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1591</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.request</span><span class="ansi-blue-fg">(self, cast_to, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1588</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> err.response.aread()
|
||||
<span class="ansi-green-fg"> 1590</span> log.debug(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Re-raising status error</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1591</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._make_status_error_from_response(err.response) <span class="ansi-bold" style="color: rgb(0,135,0)">from</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
<span class="ansi-green-fg"> 1593</span> <span class="ansi-bold" style="color: rgb(0,135,0)">break</span>
|
||||
<span class="ansi-green-fg"> 1595</span> <span class="ansi-bold" style="color: rgb(0,135,0)">assert</span> response <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">could not resolve response (should never happen)</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-red-fg">AuthenticationError</span>: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************************************************************************************************************************zWYA. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}</pre>
|
||||
A strong sense of duty drives the individuals involved in Operation: Dulce. This sense of responsibility motivates the team members to undertake the mission and navigate the complexities of the Dulce base. The Paranormal Military Squad's involvement is critical to the mission's success, with meticulous planning and coordination being essential components of their strategy. The agents convene in a sterile briefing room to discuss and execute their missions, ensuring that every aspect of the operation is carefully considered [Data: Reports (0, 1)].
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -2879,17 +2677,54 @@ result.context_data["reports"]</div>
|
||||
<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
|
||||
</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[10]</span><span class="ansi-green-fg">, line 2</span>
|
||||
<span class="ansi-green-fg"> 1</span> <span style="color: rgb(95,135,135)"># inspect the data used to build the context for the LLM responses</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">2</span> <span class="ansi-yellow-bg">result</span>.context_data[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">reports</span><span class="ansi-yellow-fg">"</span>]
|
||||
<div class="jp-OutputArea-child jp-OutputArea-executeResult">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[10]:</div>
|
||||
<div class="jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/html" tabindex="0">
|
||||
<div>
|
||||
<style scoped="">
|
||||
.dataframe tbody tr th:only-of-type {
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'result' is not defined</pre>
|
||||
.dataframe tbody tr th {
|
||||
vertical-align: top;
|
||||
}
|
||||
|
||||
.dataframe thead th {
|
||||
text-align: right;
|
||||
}
|
||||
</style>
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>id</th>
|
||||
<th>title</th>
|
||||
<th>occurrence weight</th>
|
||||
<th>content</th>
|
||||
<th>rank</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>0</th>
|
||||
<td>0</td>
|
||||
<td>Operation: Dulce and Dulce Base Exploration</td>
|
||||
<td>1.0</td>
|
||||
<td># Operation: Dulce and Dulce Base Exploration\...</td>
|
||||
<td>8.5</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>1</th>
|
||||
<td>1</td>
|
||||
<td>Paranormal Military Squad and Operation: Dulce</td>
|
||||
<td>1.0</td>
|
||||
<td># Paranormal Military Squad and Operation: Dul...</td>
|
||||
<td>8.5</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -2961,17 +2796,12 @@ print(
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[11]</span><span class="ansi-green-fg">, line 2</span>
|
||||
<span class="ansi-green-fg"> 1</span> <span style="color: rgb(95,135,135)"># inspect number of LLM calls and tokens in dynamic community selection</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">2</span> llm_calls = <span class="ansi-yellow-bg">result</span>.llm_calls_categories[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>]
|
||||
<span class="ansi-green-fg"> 3</span> prompt_tokens = result.prompt_tokens_categories[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>]
|
||||
<span class="ansi-green-fg"> 4</span> output_tokens = result.output_tokens_categories[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>]
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'result' is not defined</pre>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>Build context (gpt-4o)
|
||||
LLM calls: 2. Prompt tokens: 1761. Output tokens: 254.
|
||||
Map-reduce (gpt-4o)
|
||||
LLM calls: 2. Prompt tokens: 3510. Output tokens: 704.
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -3449,202 +3449,32 @@ print(result.response)</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">AuthenticationError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[13]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> search_engine.search(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Tell me about Agent Mercer</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg"> 2</span> <span style="color: rgb(0,135,0)">print</span>(result.response)
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:39:14.0304 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>### Overview of Agent Alex Mercer
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/local_search/search.py:63</span>, in <span class="ansi-cyan-fg">LocalSearch.search</span><span class="ansi-blue-fg">(self, query, conversation_history, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 61</span> search_prompt = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 62</span> llm_calls, prompt_tokens, output_tokens = {}, {}, {}
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">63</span> context_result = <span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">context_builder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">build_context</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 65</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">conversation_history</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">conversation_history</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 66</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">kwargs</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 67</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">context_builder_params</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 68</span> <span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 69</span> llm_calls[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = context_result.llm_calls
|
||||
<span class="ansi-green-fg"> 70</span> prompt_tokens[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = context_result.prompt_tokens
|
||||
Agent Alex Mercer is a prominent member of the Paranormal Military Squad, an elite group tasked with executing Operation: Dulce. He plays a crucial role in the mission, providing guidance and emphasizing the importance of intuition and trust among his team members [Data: Reports (1); Entities (0, 4)]. Mercer's leadership and mentorship are particularly significant, as he serves as a mentor to Sam Rivera, offering valuable support and leadership [Data: Reports (1); Entities (0, 3)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/local_search/mixed_context.py:139</span>, in <span class="ansi-cyan-fg">LocalSearchMixedContext.build_context</span><span class="ansi-blue-fg">(self, query, conversation_history, include_entity_names, exclude_entity_names, conversation_history_max_turns, conversation_history_user_turns_only, max_context_tokens, text_unit_prop, community_prop, top_k_mapped_entities, top_k_relationships, include_community_rank, include_entity_rank, rank_description, include_relationship_weight, relationship_ranking_attribute, return_candidate_context, use_community_summary, min_community_rank, community_context_name, column_delimiter, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 134</span> pre_user_questions = <span class="ansi-yellow-fg">"</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-yellow-fg">"</span>.join(
|
||||
<span class="ansi-green-fg"> 135</span> conversation_history.get_user_turns(conversation_history_max_turns)
|
||||
<span class="ansi-green-fg"> 136</span> )
|
||||
<span class="ansi-green-fg"> 137</span> query = <span class="ansi-yellow-fg">f</span><span class="ansi-yellow-fg">"</span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>query<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>pre_user_questions<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">139</span> selected_entities = <span class="ansi-yellow-bg">map_query_to_entities</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 140</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 141</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedding_vectorstore</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">entity_text_embeddings</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 143</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">all_entities_dict</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">entities</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 144</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">embedding_vectorstore_key</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embedding_vectorstore_key</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">include_entity_names</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">include_entity_names</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 146</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">exclude_entity_names</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">exclude_entity_names</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 147</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">top_k_mapped_entities</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 148</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">oversample_scaler</span><span class="ansi-yellow-bg">=</span><span class="ansi-green-fg ansi-yellow-bg">2</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 149</span> <span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 151</span> <span style="color: rgb(95,135,135)"># build context</span>
|
||||
<span class="ansi-green-fg"> 152</span> final_context = <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">str</span>]()
|
||||
### Role in Operation: Dulce
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/entity_extraction.py:58</span>, in <span class="ansi-cyan-fg">map_query_to_entities</span><span class="ansi-blue-fg">(query, text_embedding_vectorstore, text_embedder, all_entities_dict, embedding_vectorstore_key, include_entity_names, exclude_entity_names, k, oversample_scaler)</span>
|
||||
<span class="ansi-green-fg"> 54</span> matched_entities = []
|
||||
<span class="ansi-green-fg"> 55</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query != <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>:
|
||||
<span class="ansi-green-fg"> 56</span> <span style="color: rgb(95,135,135)"># get entities with highest semantic similarity to query</span>
|
||||
<span class="ansi-green-fg"> 57</span> <span style="color: rgb(95,135,135)"># oversample to account for excluded entities</span>
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">58</span> search_results = <span class="ansi-yellow-bg">text_embedding_vectorstore</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">similarity_search_by_text</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 59</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 60</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg ansi-bold" style="color: rgb(0,135,0)">lambda</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">:</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">)</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 61</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">oversample_scaler</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 62</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 63</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> result <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> search_results:
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> embedding_vectorstore_key == EntityVectorStoreKey.ID <span class="ansi-bold" style="color: rgb(175,0,255)">and</span> <span style="color: rgb(0,135,0)">isinstance</span>(
|
||||
<span class="ansi-green-fg"> 65</span> result.document.id, <span style="color: rgb(0,135,0)">str</span>
|
||||
<span class="ansi-green-fg"> 66</span> ):
|
||||
In the context of Operation: Dulce, Alex Mercer is one of the agents exploring the Dulce base, a mysterious and secretive location associated with advanced alien technology [Data: Reports (1); Entities (0, 8); Relationships (23, 24, 37)]. His involvement in the mission is marked by a balance between compliance with protocols and a natural inclination to question and explore all details, which sometimes leads to internal conflict [Data: Claims (3, 5)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/vector_stores/lancedb.py:134</span>, in <span class="ansi-cyan-fg">LanceDBVectorStore.similarity_search_by_text</span><span class="ansi-blue-fg">(self, text, text_embedder, k, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 130</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">similarity_search_by_text</span>(
|
||||
<span class="ansi-green-fg"> 131</span> <span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, text_embedder: TextEmbedder, k: <span style="color: rgb(0,135,0)">int</span> = <span class="ansi-green-fg">10</span>, **kwargs: Any
|
||||
<span class="ansi-green-fg"> 132</span> ) -> <span style="color: rgb(0,135,0)">list</span>[VectorStoreSearchResult]:
|
||||
<span class="ansi-green-fg"> 133</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""Perform a similarity search using a given input text."""</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">134</span> query_embedding = <span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 135</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query_embedding:
|
||||
<span class="ansi-green-fg"> 136</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span style="color: rgb(0,135,0)">self</span>.similarity_search_by_vector(query_embedding, k)
|
||||
### Relationships and Interactions
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/entity_extraction.py:60</span>, in <span class="ansi-cyan-fg">map_query_to_entities.<locals>.<lambda></span><span class="ansi-blue-fg">(t)</span>
|
||||
<span class="ansi-green-fg"> 54</span> matched_entities = []
|
||||
<span class="ansi-green-fg"> 55</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query != <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>:
|
||||
<span class="ansi-green-fg"> 56</span> <span style="color: rgb(95,135,135)"># get entities with highest semantic similarity to query</span>
|
||||
<span class="ansi-green-fg"> 57</span> <span style="color: rgb(95,135,135)"># oversample to account for excluded entities</span>
|
||||
<span class="ansi-green-fg"> 58</span> search_results = text_embedding_vectorstore.similarity_search_by_text(
|
||||
<span class="ansi-green-fg"> 59</span> text=query,
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">60</span> text_embedder=<span class="ansi-bold" style="color: rgb(0,135,0)">lambda</span> t: <span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">)</span>,
|
||||
<span class="ansi-green-fg"> 61</span> k=k * oversample_scaler,
|
||||
<span class="ansi-green-fg"> 62</span> )
|
||||
<span class="ansi-green-fg"> 63</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> result <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> search_results:
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> embedding_vectorstore_key == EntityVectorStoreKey.ID <span class="ansi-bold" style="color: rgb(175,0,255)">and</span> <span style="color: rgb(0,135,0)">isinstance</span>(
|
||||
<span class="ansi-green-fg"> 65</span> result.document.id, <span style="color: rgb(0,135,0)">str</span>
|
||||
<span class="ansi-green-fg"> 66</span> ):
|
||||
Mercer shares a professional relationship with other key members of the Paranormal Military Squad, including Taylor Cruz, Jordan Hayes, and Sam Rivera. His relationship with Taylor Cruz is primarily professional, with a competitive undercurrent due to Cruz's authoritative nature [Data: Relationships (0, 2)]. With Jordan Hayes, Mercer shares mutual respect and understanding, particularly admiring each other's expertise and analytical abilities [Data: Relationships (1)]. His mentorship of Sam Rivera highlights his role in guiding and supporting his colleagues [Data: Relationships (2, 15)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:240</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingFNLLM.embed</span><span class="ansi-blue-fg">(self, text, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 228</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">embed</span>(<span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, **kwargs) -> <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">float</span>]:
|
||||
<span class="ansi-green-fg"> 229</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 230</span> <span class="ansi-yellow-fg"> Embed the given text using the Model.</span>
|
||||
<span class="ansi-green-fg"> 231</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 238</span> <span class="ansi-yellow-fg"> The embeddings of the text.</span>
|
||||
<span class="ansi-green-fg"> 239</span> <span class="ansi-yellow-fg"> """</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">240</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">run_coroutine_sync</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">aembed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">kwargs</span><span class="ansi-yellow-bg">)</span><span class="ansi-yellow-bg">)</span>
|
||||
### Leadership and Challenges
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/utils.py:132</span>, in <span class="ansi-cyan-fg">run_coroutine_sync</span><span class="ansi-blue-fg">(coroutine)</span>
|
||||
<span class="ansi-green-fg"> 130</span> _thr.start()
|
||||
<span class="ansi-green-fg"> 131</span> future = asyncio.run_coroutine_threadsafe(coroutine, _loop)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">132</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">future</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">result</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
|
||||
As a leader, Alex Mercer is depicted as experiencing internal conflict between adhering to protocols and his natural curiosity to explore and question details. This conflict is highlighted through his interactions with Taylor Cruz and his own reflections [Data: Claims (3)]. Despite these challenges, Mercer's leadership is crucial to the success of Operation: Dulce, as he is involved in leading the mission into the Dulce base [Data: Claims (5)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.13/x64/lib/python3.11/concurrent/futures/_base.py:456</span>, in <span class="ansi-cyan-fg">Future.result</span><span class="ansi-blue-fg">(self, timeout)</span>
|
||||
<span class="ansi-green-fg"> 454</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> CancelledError()
|
||||
<span class="ansi-green-fg"> 455</span> <span class="ansi-bold" style="color: rgb(0,135,0)">elif</span> <span style="color: rgb(0,135,0)">self</span>._state == FINISHED:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">456</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">__get_result</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 457</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span>:
|
||||
<span class="ansi-green-fg"> 458</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span class="ansi-bold" style="color: rgb(215,95,95)">TimeoutError</span>()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.13/x64/lib/python3.11/concurrent/futures/_base.py:401</span>, in <span class="ansi-cyan-fg">Future.__get_result</span><span class="ansi-blue-fg">(self)</span>
|
||||
<span class="ansi-green-fg"> 399</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span style="color: rgb(0,135,0)">self</span>._exception:
|
||||
<span class="ansi-green-fg"> 400</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">401</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._exception
|
||||
<span class="ansi-green-fg"> 402</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 403</span> <span style="color: rgb(95,135,135)"># Break a reference cycle with the exception in self._exception</span>
|
||||
<span class="ansi-green-fg"> 404</span> <span style="color: rgb(0,135,0)">self</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:207</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingFNLLM.aembed</span><span class="ansi-blue-fg">(self, text, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 195</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">aembed</span>(<span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, **kwargs) -> <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">float</span>]:
|
||||
<span class="ansi-green-fg"> 196</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 197</span> <span class="ansi-yellow-fg"> Embed the given text using the Model.</span>
|
||||
<span class="ansi-green-fg"> 198</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 205</span> <span class="ansi-yellow-fg"> The embeddings of the text.</span>
|
||||
<span class="ansi-green-fg"> 206</span> <span class="ansi-yellow-fg"> """</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">207</span> response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.model([text], **kwargs)
|
||||
<span class="ansi-green-fg"> 208</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> response.output.embeddings <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>:
|
||||
<span class="ansi-green-fg"> 209</span> msg = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">No embeddings found in response</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:144</span>, in <span class="ansi-cyan-fg">BaseLLM.__call__</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg"> 143</span> prompt, kwargs = <span style="color: rgb(0,135,0)">self</span>._rewrite_input(prompt, kwargs)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">144</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._decorated_target(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-bold" style="color: rgb(0,135,0)">except</span> <span class="ansi-bold" style="color: rgb(215,95,95)">BaseException</span> <span class="ansi-bold" style="color: rgb(0,135,0)">as</span> e:
|
||||
<span class="ansi-green-fg"> 146</span> stack_trace = traceback.format_exc()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/rate_limiter.py:75</span>, in <span class="ansi-cyan-fg">RateLimiter.decorate.<locals>.invoke</span><span class="ansi-blue-fg">(prompt, **args)</span>
|
||||
<span class="ansi-green-fg"> 73</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">with</span> <span style="color: rgb(0,135,0)">self</span>._limiter.use(manifest):
|
||||
<span class="ansi-green-fg"> 74</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_acquired(manifest)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">75</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **args)
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 77</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_released(manifest)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:126</span>, in <span class="ansi-cyan-fg">BaseLLM._decorator_target</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> <span class="ansi-yellow-fg">"""Target for the decorator chain.</span>
|
||||
<span class="ansi-green-fg"> 122</span>
|
||||
<span class="ansi-green-fg"> 123</span> <span class="ansi-yellow-fg">Leave signature alone as prompt, kwargs.</span>
|
||||
<span class="ansi-green-fg"> 124</span> <span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 125</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_execute_llm()
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> output = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._execute_llm(prompt, kwargs)
|
||||
<span class="ansi-green-fg"> 127</span> result = LLMOutput(output=output)
|
||||
<span class="ansi-green-fg"> 128</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._inject_usage(result)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_embeddings_llm.py:126</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingsLLMImpl._execute_llm</span><span class="ansi-blue-fg">(self, prompt, kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> local_model_parameters = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model_parameters</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg"> 122</span> embeddings_parameters = <span style="color: rgb(0,135,0)">self</span>._build_embeddings_parameters(
|
||||
<span class="ansi-green-fg"> 123</span> local_model_parameters
|
||||
<span class="ansi-green-fg"> 124</span> )
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> result_raw = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._client.embeddings.with_raw_response.create(
|
||||
<span class="ansi-green-fg"> 127</span> <span style="color: rgb(0,135,0)">input</span>=prompt,
|
||||
<span class="ansi-green-fg"> 128</span> **embeddings_parameters,
|
||||
<span class="ansi-green-fg"> 129</span> )
|
||||
<span class="ansi-green-fg"> 130</span> result = result_raw.parse()
|
||||
<span class="ansi-green-fg"> 131</span> headers = result_raw.headers
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_legacy_response.py:381</span>, in <span class="ansi-cyan-fg">async_to_raw_response_wrapper.<locals>.wrapped</span><span class="ansi-blue-fg">(*args, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 377</span> extra_headers[RAW_RESPONSE_HEADER] = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">true</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 379</span> kwargs[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">extra_headers</span><span class="ansi-yellow-fg">"</span>] = extra_headers
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">381</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> cast(LegacyAPIResponse[R], <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> func(*args, **kwargs))
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/resources/embeddings.py:251</span>, in <span class="ansi-cyan-fg">AsyncEmbeddings.create</span><span class="ansi-blue-fg">(self, input, model, dimensions, encoding_format, user, extra_headers, extra_query, extra_body, timeout)</span>
|
||||
<span class="ansi-green-fg"> 245</span> embedding.embedding = np.frombuffer( <span style="color: rgb(95,135,135)"># type: ignore[no-untyped-call]</span>
|
||||
<span class="ansi-green-fg"> 246</span> base64.b64decode(data), dtype=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">float32</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 247</span> ).tolist()
|
||||
<span class="ansi-green-fg"> 249</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> obj
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">251</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._post(
|
||||
<span class="ansi-green-fg"> 252</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">/embeddings</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg"> 253</span> body=maybe_transform(params, embedding_create_params.EmbeddingCreateParams),
|
||||
<span class="ansi-green-fg"> 254</span> options=make_request_options(
|
||||
<span class="ansi-green-fg"> 255</span> extra_headers=extra_headers,
|
||||
<span class="ansi-green-fg"> 256</span> extra_query=extra_query,
|
||||
<span class="ansi-green-fg"> 257</span> extra_body=extra_body,
|
||||
<span class="ansi-green-fg"> 258</span> timeout=timeout,
|
||||
<span class="ansi-green-fg"> 259</span> post_parser=parser,
|
||||
<span class="ansi-green-fg"> 260</span> ),
|
||||
<span class="ansi-green-fg"> 261</span> cast_to=CreateEmbeddingResponse,
|
||||
<span class="ansi-green-fg"> 262</span> )
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1791</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.post</span><span class="ansi-blue-fg">(self, path, cast_to, body, files, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1777</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">post</span>(
|
||||
<span class="ansi-green-fg"> 1778</span> <span style="color: rgb(0,135,0)">self</span>,
|
||||
<span class="ansi-green-fg"> 1779</span> path: <span style="color: rgb(0,135,0)">str</span>,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 1786</span> stream_cls: <span style="color: rgb(0,135,0)">type</span>[_AsyncStreamT] | <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>,
|
||||
<span class="ansi-green-fg"> 1787</span> ) -> ResponseT | _AsyncStreamT:
|
||||
<span class="ansi-green-fg"> 1788</span> opts = FinalRequestOptions.construct(
|
||||
<span class="ansi-green-fg"> 1789</span> method=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">post</span><span class="ansi-yellow-fg">"</span>, url=path, json_data=body, files=<span class="ansi-bold" style="color: rgb(0,135,0)">await</span> async_to_httpx_files(files), **options
|
||||
<span class="ansi-green-fg"> 1790</span> )
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1791</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1591</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.request</span><span class="ansi-blue-fg">(self, cast_to, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1588</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> err.response.aread()
|
||||
<span class="ansi-green-fg"> 1590</span> log.debug(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Re-raising status error</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1591</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._make_status_error_from_response(err.response) <span class="ansi-bold" style="color: rgb(0,135,0)">from</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
<span class="ansi-green-fg"> 1593</span> <span class="ansi-bold" style="color: rgb(0,135,0)">break</span>
|
||||
<span class="ansi-green-fg"> 1595</span> <span class="ansi-bold" style="color: rgb(0,135,0)">assert</span> response <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">could not resolve response (should never happen)</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-red-fg">AuthenticationError</span>: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************************************************************************************************************************zWYA. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}</pre>
|
||||
In summary, Agent Alex Mercer is a key figure in the Paranormal Military Squad, known for his leadership, mentorship, and critical role in Operation: Dulce. His relationships with other team members and his internal conflicts add depth to his character, making him an integral part of the mission's dynamics [Data: Reports (1); Entities (0, 4); Relationships (0, 1, 2, 23, 24, 37); Claims (3, 5)].
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -3686,203 +3516,32 @@ print(result.response)</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">AuthenticationError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[14]</span><span class="ansi-green-fg">, line 2</span>
|
||||
<span class="ansi-green-fg"> 1</span> question = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Tell me about Dr. Jordan Hayes</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">2</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> search_engine.search(question)
|
||||
<span class="ansi-green-fg"> 3</span> <span style="color: rgb(0,135,0)">print</span>(result.response)
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:39:36.0519 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>## Overview of Dr. Jordan Hayes
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/local_search/search.py:63</span>, in <span class="ansi-cyan-fg">LocalSearch.search</span><span class="ansi-blue-fg">(self, query, conversation_history, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 61</span> search_prompt = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 62</span> llm_calls, prompt_tokens, output_tokens = {}, {}, {}
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">63</span> context_result = <span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">context_builder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">build_context</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 65</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">conversation_history</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">conversation_history</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 66</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">kwargs</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 67</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">context_builder_params</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 68</span> <span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 69</span> llm_calls[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = context_result.llm_calls
|
||||
<span class="ansi-green-fg"> 70</span> prompt_tokens[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">build_context</span><span class="ansi-yellow-fg">"</span>] = context_result.prompt_tokens
|
||||
Dr. Jordan Hayes is a prominent scientist and a key member of the Paranormal Military Squad, known for their expertise in physics and composed demeanor. They play a significant role in Operation: Dulce, particularly in working with alien technology. Dr. Hayes is recognized for their analytical mind and reflective nature, often contemplating the complexities of their missions and the layers of data they encounter [Data: Entities (2); Reports (1)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/local_search/mixed_context.py:139</span>, in <span class="ansi-cyan-fg">LocalSearchMixedContext.build_context</span><span class="ansi-blue-fg">(self, query, conversation_history, include_entity_names, exclude_entity_names, conversation_history_max_turns, conversation_history_user_turns_only, max_context_tokens, text_unit_prop, community_prop, top_k_mapped_entities, top_k_relationships, include_community_rank, include_entity_rank, rank_description, include_relationship_weight, relationship_ranking_attribute, return_candidate_context, use_community_summary, min_community_rank, community_context_name, column_delimiter, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 134</span> pre_user_questions = <span class="ansi-yellow-fg">"</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-yellow-fg">"</span>.join(
|
||||
<span class="ansi-green-fg"> 135</span> conversation_history.get_user_turns(conversation_history_max_turns)
|
||||
<span class="ansi-green-fg"> 136</span> )
|
||||
<span class="ansi-green-fg"> 137</span> query = <span class="ansi-yellow-fg">f</span><span class="ansi-yellow-fg">"</span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>query<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>pre_user_questions<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">139</span> selected_entities = <span class="ansi-yellow-bg">map_query_to_entities</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 140</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 141</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedding_vectorstore</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">entity_text_embeddings</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 143</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">all_entities_dict</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">entities</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 144</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">embedding_vectorstore_key</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embedding_vectorstore_key</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">include_entity_names</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">include_entity_names</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 146</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">exclude_entity_names</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">exclude_entity_names</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 147</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">top_k_mapped_entities</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 148</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">oversample_scaler</span><span class="ansi-yellow-bg">=</span><span class="ansi-green-fg ansi-yellow-bg">2</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 149</span> <span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 151</span> <span style="color: rgb(95,135,135)"># build context</span>
|
||||
<span class="ansi-green-fg"> 152</span> final_context = <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">str</span>]()
|
||||
## Role in Operation: Dulce
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/entity_extraction.py:58</span>, in <span class="ansi-cyan-fg">map_query_to_entities</span><span class="ansi-blue-fg">(query, text_embedding_vectorstore, text_embedder, all_entities_dict, embedding_vectorstore_key, include_entity_names, exclude_entity_names, k, oversample_scaler)</span>
|
||||
<span class="ansi-green-fg"> 54</span> matched_entities = []
|
||||
<span class="ansi-green-fg"> 55</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query != <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>:
|
||||
<span class="ansi-green-fg"> 56</span> <span style="color: rgb(95,135,135)"># get entities with highest semantic similarity to query</span>
|
||||
<span class="ansi-green-fg"> 57</span> <span style="color: rgb(95,135,135)"># oversample to account for excluded entities</span>
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">58</span> search_results = <span class="ansi-yellow-bg">text_embedding_vectorstore</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">similarity_search_by_text</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 59</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 60</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg ansi-bold" style="color: rgb(0,135,0)">lambda</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">:</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">)</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 61</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">oversample_scaler</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 62</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 63</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> result <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> search_results:
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> embedding_vectorstore_key == EntityVectorStoreKey.ID <span class="ansi-bold" style="color: rgb(175,0,255)">and</span> <span style="color: rgb(0,135,0)">isinstance</span>(
|
||||
<span class="ansi-green-fg"> 65</span> result.document.id, <span style="color: rgb(0,135,0)">str</span>
|
||||
<span class="ansi-green-fg"> 66</span> ):
|
||||
In the context of Operation: Dulce, Dr. Hayes is deeply involved in exploring the Dulce base and working on alien technology. Their role is crucial as they provide analytical insights and express concerns about the mission, indicating a strong involvement in the analytical assessment of the operation. Dr. Hayes is also noted for identifying a suspicious panel within the base, suggesting a hidden element that could be critical to the mission's success [Data: Reports (1); Claims (6, 10)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/vector_stores/lancedb.py:134</span>, in <span class="ansi-cyan-fg">LanceDBVectorStore.similarity_search_by_text</span><span class="ansi-blue-fg">(self, text, text_embedder, k, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 130</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">similarity_search_by_text</span>(
|
||||
<span class="ansi-green-fg"> 131</span> <span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, text_embedder: TextEmbedder, k: <span style="color: rgb(0,135,0)">int</span> = <span class="ansi-green-fg">10</span>, **kwargs: Any
|
||||
<span class="ansi-green-fg"> 132</span> ) -> <span style="color: rgb(0,135,0)">list</span>[VectorStoreSearchResult]:
|
||||
<span class="ansi-green-fg"> 133</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""Perform a similarity search using a given input text."""</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">134</span> query_embedding = <span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 135</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query_embedding:
|
||||
<span class="ansi-green-fg"> 136</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span style="color: rgb(0,135,0)">self</span>.similarity_search_by_vector(query_embedding, k)
|
||||
## Professional Relationships
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/entity_extraction.py:60</span>, in <span class="ansi-cyan-fg">map_query_to_entities.<locals>.<lambda></span><span class="ansi-blue-fg">(t)</span>
|
||||
<span class="ansi-green-fg"> 54</span> matched_entities = []
|
||||
<span class="ansi-green-fg"> 55</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query != <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>:
|
||||
<span class="ansi-green-fg"> 56</span> <span style="color: rgb(95,135,135)"># get entities with highest semantic similarity to query</span>
|
||||
<span class="ansi-green-fg"> 57</span> <span style="color: rgb(95,135,135)"># oversample to account for excluded entities</span>
|
||||
<span class="ansi-green-fg"> 58</span> search_results = text_embedding_vectorstore.similarity_search_by_text(
|
||||
<span class="ansi-green-fg"> 59</span> text=query,
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">60</span> text_embedder=<span class="ansi-bold" style="color: rgb(0,135,0)">lambda</span> t: <span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">)</span>,
|
||||
<span class="ansi-green-fg"> 61</span> k=k * oversample_scaler,
|
||||
<span class="ansi-green-fg"> 62</span> )
|
||||
<span class="ansi-green-fg"> 63</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> result <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> search_results:
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> embedding_vectorstore_key == EntityVectorStoreKey.ID <span class="ansi-bold" style="color: rgb(175,0,255)">and</span> <span style="color: rgb(0,135,0)">isinstance</span>(
|
||||
<span class="ansi-green-fg"> 65</span> result.document.id, <span style="color: rgb(0,135,0)">str</span>
|
||||
<span class="ansi-green-fg"> 66</span> ):
|
||||
Dr. Hayes maintains professional relationships with other key members of the Paranormal Military Squad, including Taylor Cruz and Sam Rivera. Their relationship with Taylor Cruz is marked by differing views on protocol and adaptability, with Dr. Hayes advocating for adaptability in the face of unknown variables. This skepticism towards strict adherence to protocols is evident in their interactions during mission briefings. Additionally, Dr. Hayes shares a common belief in the importance of adaptability with Sam Rivera, further emphasizing their role in promoting flexibility within the team [Data: Reports (1); Relationships (5, 9, 25); Claims (2)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:240</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingFNLLM.embed</span><span class="ansi-blue-fg">(self, text, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 228</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">embed</span>(<span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, **kwargs) -> <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">float</span>]:
|
||||
<span class="ansi-green-fg"> 229</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 230</span> <span class="ansi-yellow-fg"> Embed the given text using the Model.</span>
|
||||
<span class="ansi-green-fg"> 231</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 238</span> <span class="ansi-yellow-fg"> The embeddings of the text.</span>
|
||||
<span class="ansi-green-fg"> 239</span> <span class="ansi-yellow-fg"> """</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">240</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">run_coroutine_sync</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">aembed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">kwargs</span><span class="ansi-yellow-bg">)</span><span class="ansi-yellow-bg">)</span>
|
||||
## Contributions and Expertise
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/utils.py:132</span>, in <span class="ansi-cyan-fg">run_coroutine_sync</span><span class="ansi-blue-fg">(coroutine)</span>
|
||||
<span class="ansi-green-fg"> 130</span> _thr.start()
|
||||
<span class="ansi-green-fg"> 131</span> future = asyncio.run_coroutine_threadsafe(coroutine, _loop)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">132</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">future</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">result</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
|
||||
Dr. Hayes' expertise in physics and alien technology is a cornerstone of their contributions to the Paranormal Military Squad. They work in a lab dedicated to alien technology, where their analytical skills are put to use in understanding and potentially leveraging this technology for the mission's objectives. Their composed and reflective nature allows them to approach challenges with a calculated skepticism, ensuring that the team remains adaptable and prepared for the unpredictable elements of their mission [Data: Entities (2, 13); Relationships (51); Reports (1)].
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.13/x64/lib/python3.11/concurrent/futures/_base.py:456</span>, in <span class="ansi-cyan-fg">Future.result</span><span class="ansi-blue-fg">(self, timeout)</span>
|
||||
<span class="ansi-green-fg"> 454</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> CancelledError()
|
||||
<span class="ansi-green-fg"> 455</span> <span class="ansi-bold" style="color: rgb(0,135,0)">elif</span> <span style="color: rgb(0,135,0)">self</span>._state == FINISHED:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">456</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">__get_result</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 457</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span>:
|
||||
<span class="ansi-green-fg"> 458</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span class="ansi-bold" style="color: rgb(215,95,95)">TimeoutError</span>()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.13/x64/lib/python3.11/concurrent/futures/_base.py:401</span>, in <span class="ansi-cyan-fg">Future.__get_result</span><span class="ansi-blue-fg">(self)</span>
|
||||
<span class="ansi-green-fg"> 399</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span style="color: rgb(0,135,0)">self</span>._exception:
|
||||
<span class="ansi-green-fg"> 400</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">401</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._exception
|
||||
<span class="ansi-green-fg"> 402</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 403</span> <span style="color: rgb(95,135,135)"># Break a reference cycle with the exception in self._exception</span>
|
||||
<span class="ansi-green-fg"> 404</span> <span style="color: rgb(0,135,0)">self</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:207</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingFNLLM.aembed</span><span class="ansi-blue-fg">(self, text, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 195</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">aembed</span>(<span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, **kwargs) -> <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">float</span>]:
|
||||
<span class="ansi-green-fg"> 196</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 197</span> <span class="ansi-yellow-fg"> Embed the given text using the Model.</span>
|
||||
<span class="ansi-green-fg"> 198</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 205</span> <span class="ansi-yellow-fg"> The embeddings of the text.</span>
|
||||
<span class="ansi-green-fg"> 206</span> <span class="ansi-yellow-fg"> """</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">207</span> response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.model([text], **kwargs)
|
||||
<span class="ansi-green-fg"> 208</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> response.output.embeddings <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>:
|
||||
<span class="ansi-green-fg"> 209</span> msg = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">No embeddings found in response</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:144</span>, in <span class="ansi-cyan-fg">BaseLLM.__call__</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg"> 143</span> prompt, kwargs = <span style="color: rgb(0,135,0)">self</span>._rewrite_input(prompt, kwargs)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">144</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._decorated_target(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-bold" style="color: rgb(0,135,0)">except</span> <span class="ansi-bold" style="color: rgb(215,95,95)">BaseException</span> <span class="ansi-bold" style="color: rgb(0,135,0)">as</span> e:
|
||||
<span class="ansi-green-fg"> 146</span> stack_trace = traceback.format_exc()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/rate_limiter.py:75</span>, in <span class="ansi-cyan-fg">RateLimiter.decorate.<locals>.invoke</span><span class="ansi-blue-fg">(prompt, **args)</span>
|
||||
<span class="ansi-green-fg"> 73</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">with</span> <span style="color: rgb(0,135,0)">self</span>._limiter.use(manifest):
|
||||
<span class="ansi-green-fg"> 74</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_acquired(manifest)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">75</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **args)
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 77</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_released(manifest)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:126</span>, in <span class="ansi-cyan-fg">BaseLLM._decorator_target</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> <span class="ansi-yellow-fg">"""Target for the decorator chain.</span>
|
||||
<span class="ansi-green-fg"> 122</span>
|
||||
<span class="ansi-green-fg"> 123</span> <span class="ansi-yellow-fg">Leave signature alone as prompt, kwargs.</span>
|
||||
<span class="ansi-green-fg"> 124</span> <span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 125</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_execute_llm()
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> output = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._execute_llm(prompt, kwargs)
|
||||
<span class="ansi-green-fg"> 127</span> result = LLMOutput(output=output)
|
||||
<span class="ansi-green-fg"> 128</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._inject_usage(result)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_embeddings_llm.py:126</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingsLLMImpl._execute_llm</span><span class="ansi-blue-fg">(self, prompt, kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> local_model_parameters = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model_parameters</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg"> 122</span> embeddings_parameters = <span style="color: rgb(0,135,0)">self</span>._build_embeddings_parameters(
|
||||
<span class="ansi-green-fg"> 123</span> local_model_parameters
|
||||
<span class="ansi-green-fg"> 124</span> )
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> result_raw = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._client.embeddings.with_raw_response.create(
|
||||
<span class="ansi-green-fg"> 127</span> <span style="color: rgb(0,135,0)">input</span>=prompt,
|
||||
<span class="ansi-green-fg"> 128</span> **embeddings_parameters,
|
||||
<span class="ansi-green-fg"> 129</span> )
|
||||
<span class="ansi-green-fg"> 130</span> result = result_raw.parse()
|
||||
<span class="ansi-green-fg"> 131</span> headers = result_raw.headers
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_legacy_response.py:381</span>, in <span class="ansi-cyan-fg">async_to_raw_response_wrapper.<locals>.wrapped</span><span class="ansi-blue-fg">(*args, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 377</span> extra_headers[RAW_RESPONSE_HEADER] = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">true</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 379</span> kwargs[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">extra_headers</span><span class="ansi-yellow-fg">"</span>] = extra_headers
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">381</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> cast(LegacyAPIResponse[R], <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> func(*args, **kwargs))
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/resources/embeddings.py:251</span>, in <span class="ansi-cyan-fg">AsyncEmbeddings.create</span><span class="ansi-blue-fg">(self, input, model, dimensions, encoding_format, user, extra_headers, extra_query, extra_body, timeout)</span>
|
||||
<span class="ansi-green-fg"> 245</span> embedding.embedding = np.frombuffer( <span style="color: rgb(95,135,135)"># type: ignore[no-untyped-call]</span>
|
||||
<span class="ansi-green-fg"> 246</span> base64.b64decode(data), dtype=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">float32</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 247</span> ).tolist()
|
||||
<span class="ansi-green-fg"> 249</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> obj
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">251</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._post(
|
||||
<span class="ansi-green-fg"> 252</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">/embeddings</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg"> 253</span> body=maybe_transform(params, embedding_create_params.EmbeddingCreateParams),
|
||||
<span class="ansi-green-fg"> 254</span> options=make_request_options(
|
||||
<span class="ansi-green-fg"> 255</span> extra_headers=extra_headers,
|
||||
<span class="ansi-green-fg"> 256</span> extra_query=extra_query,
|
||||
<span class="ansi-green-fg"> 257</span> extra_body=extra_body,
|
||||
<span class="ansi-green-fg"> 258</span> timeout=timeout,
|
||||
<span class="ansi-green-fg"> 259</span> post_parser=parser,
|
||||
<span class="ansi-green-fg"> 260</span> ),
|
||||
<span class="ansi-green-fg"> 261</span> cast_to=CreateEmbeddingResponse,
|
||||
<span class="ansi-green-fg"> 262</span> )
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1791</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.post</span><span class="ansi-blue-fg">(self, path, cast_to, body, files, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1777</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">post</span>(
|
||||
<span class="ansi-green-fg"> 1778</span> <span style="color: rgb(0,135,0)">self</span>,
|
||||
<span class="ansi-green-fg"> 1779</span> path: <span style="color: rgb(0,135,0)">str</span>,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 1786</span> stream_cls: <span style="color: rgb(0,135,0)">type</span>[_AsyncStreamT] | <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>,
|
||||
<span class="ansi-green-fg"> 1787</span> ) -> ResponseT | _AsyncStreamT:
|
||||
<span class="ansi-green-fg"> 1788</span> opts = FinalRequestOptions.construct(
|
||||
<span class="ansi-green-fg"> 1789</span> method=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">post</span><span class="ansi-yellow-fg">"</span>, url=path, json_data=body, files=<span class="ansi-bold" style="color: rgb(0,135,0)">await</span> async_to_httpx_files(files), **options
|
||||
<span class="ansi-green-fg"> 1790</span> )
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1791</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1591</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.request</span><span class="ansi-blue-fg">(self, cast_to, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1588</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> err.response.aread()
|
||||
<span class="ansi-green-fg"> 1590</span> log.debug(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Re-raising status error</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1591</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._make_status_error_from_response(err.response) <span class="ansi-bold" style="color: rgb(0,135,0)">from</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
<span class="ansi-green-fg"> 1593</span> <span class="ansi-bold" style="color: rgb(0,135,0)">break</span>
|
||||
<span class="ansi-green-fg"> 1595</span> <span class="ansi-bold" style="color: rgb(0,135,0)">assert</span> response <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">could not resolve response (should never happen)</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-red-fg">AuthenticationError</span>: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************************************************************************************************************************zWYA. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}</pre>
|
||||
In summary, Dr. Jordan Hayes is a vital member of the Paranormal Military Squad, bringing a unique blend of scientific expertise and analytical insight to Operation: Dulce. Their role in exploring the Dulce base and working with alien technology, coupled with their advocacy for adaptability, makes them an indispensable asset to the team.
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -3929,16 +3588,78 @@ print(result.response)</div>
|
||||
<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
|
||||
</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[15]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> <span class="ansi-yellow-bg">result</span>.context_data[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">entities</span><span class="ansi-yellow-fg">"</span>].head()
|
||||
<div class="jp-OutputArea-child jp-OutputArea-executeResult">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[15]:</div>
|
||||
<div class="jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/html" tabindex="0">
|
||||
<div>
|
||||
<style scoped="">
|
||||
.dataframe tbody tr th:only-of-type {
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'result' is not defined</pre>
|
||||
.dataframe tbody tr th {
|
||||
vertical-align: top;
|
||||
}
|
||||
|
||||
.dataframe thead th {
|
||||
text-align: right;
|
||||
}
|
||||
</style>
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>id</th>
|
||||
<th>entity</th>
|
||||
<th>description</th>
|
||||
<th>number of relationships</th>
|
||||
<th>in_context</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>0</th>
|
||||
<td>2</td>
|
||||
<td>JORDAN HAYES</td>
|
||||
<td>Dr. Jordan Hayes is a scientist and a member o...</td>
|
||||
<td>9</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>1</th>
|
||||
<td>13</td>
|
||||
<td>LAB</td>
|
||||
<td>A lab where Dr. Jordan Hayes works on alien te...</td>
|
||||
<td>1</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>2</th>
|
||||
<td>10</td>
|
||||
<td>AGENT HAYES</td>
|
||||
<td>Agent Hayes is a member of the team exploring ...</td>
|
||||
<td>5</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>3</th>
|
||||
<td>12</td>
|
||||
<td>AGENT CRUZ</td>
|
||||
<td></td>
|
||||
<td>5</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>4</th>
|
||||
<td>15</td>
|
||||
<td>BRIEFING ROOM</td>
|
||||
<td></td>
|
||||
<td>2</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -3974,23 +3695,97 @@ print(result.response)</div>
|
||||
<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
|
||||
</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[16]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> <span class="ansi-yellow-bg">result</span>.context_data[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">relationships</span><span class="ansi-yellow-fg">"</span>].head()
|
||||
<div class="jp-OutputArea-child jp-OutputArea-executeResult">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[16]:</div>
|
||||
<div class="jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/html" tabindex="0">
|
||||
<div>
|
||||
<style scoped="">
|
||||
.dataframe tbody tr th:only-of-type {
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'result' is not defined</pre>
|
||||
.dataframe tbody tr th {
|
||||
vertical-align: top;
|
||||
}
|
||||
|
||||
.dataframe thead th {
|
||||
text-align: right;
|
||||
}
|
||||
</style>
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>id</th>
|
||||
<th>source</th>
|
||||
<th>target</th>
|
||||
<th>description</th>
|
||||
<th>weight</th>
|
||||
<th>links</th>
|
||||
<th>in_context</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>0</th>
|
||||
<td>5</td>
|
||||
<td>TAYLOR CRUZ</td>
|
||||
<td>JORDAN HAYES</td>
|
||||
<td>Taylor Cruz and Jordan Hayes have a profession...</td>
|
||||
<td>7.0</td>
|
||||
<td>1</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>1</th>
|
||||
<td>9</td>
|
||||
<td>JORDAN HAYES</td>
|
||||
<td>SAM RIVERA</td>
|
||||
<td>Jordan Hayes and Sam Rivera are both agents wo...</td>
|
||||
<td>14.0</td>
|
||||
<td>4</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>2</th>
|
||||
<td>25</td>
|
||||
<td>JORDAN HAYES</td>
|
||||
<td>TAYLOR CRUZ</td>
|
||||
<td>Jordan Hayes and Taylor Cruz are both agents w...</td>
|
||||
<td>18.0</td>
|
||||
<td>1</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>3</th>
|
||||
<td>6</td>
|
||||
<td>TAYLOR CRUZ</td>
|
||||
<td>SAM RIVERA</td>
|
||||
<td>Taylor Cruz and Sam Rivera are both agents wor...</td>
|
||||
<td>20.0</td>
|
||||
<td>4</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>4</th>
|
||||
<td>10</td>
|
||||
<td>JORDAN HAYES</td>
|
||||
<td>PARANORMAL MILITARY SQUAD</td>
|
||||
<td>Jordan Hayes is a member of the Paranormal Mil...</td>
|
||||
<td>9.0</td>
|
||||
<td>3</td>
|
||||
<td>True</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
|
||||
<div class="jp-Cell jp-CodeCell jp-Notebook-cell">
|
||||
</div>
|
||||
</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs">
|
||||
<div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs">
|
||||
<div class="jp-Cell-inputWrapper" tabindex="0">
|
||||
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
|
||||
</div>
|
||||
@ -4017,25 +3812,6 @@ print(result.response)</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-Cell-outputWrapper">
|
||||
<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
|
||||
</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[17]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">reports</span><span class="ansi-yellow-fg">"</span> <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> <span class="ansi-yellow-bg">result</span>.context_data:
|
||||
<span class="ansi-green-fg"> 2</span> result.context_data[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">reports</span><span class="ansi-yellow-fg">"</span>].head()
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'result' is not defined</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div><div class="jp-Cell jp-CodeCell jp-Notebook-cell">
|
||||
<div class="jp-Cell jp-CodeCell jp-Notebook-cell">
|
||||
@ -4067,16 +3843,50 @@ print(result.response)</div>
|
||||
<div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser">
|
||||
</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[18]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> <span class="ansi-yellow-bg">result</span>.context_data[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">sources</span><span class="ansi-yellow-fg">"</span>].head()
|
||||
<div class="jp-OutputArea-child jp-OutputArea-executeResult">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[18]:</div>
|
||||
<div class="jp-RenderedHTMLCommon jp-RenderedHTML jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/html" tabindex="0">
|
||||
<div>
|
||||
<style scoped="">
|
||||
.dataframe tbody tr th:only-of-type {
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'result' is not defined</pre>
|
||||
.dataframe tbody tr th {
|
||||
vertical-align: top;
|
||||
}
|
||||
|
||||
.dataframe thead th {
|
||||
text-align: right;
|
||||
}
|
||||
</style>
|
||||
<table border="1" class="dataframe">
|
||||
<thead>
|
||||
<tr style="text-align: right;">
|
||||
<th></th>
|
||||
<th>id</th>
|
||||
<th>text</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<th>0</th>
|
||||
<td>0</td>
|
||||
<td># Operation: Dulce\n\n## Chapter 1\n\nThe thru...</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>1</th>
|
||||
<td>2</td>
|
||||
<td>differently than praise from others. This was...</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>2</th>
|
||||
<td>3</td>
|
||||
<td>contrast to the rigid silence enveloping the ...</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -4116,15 +3926,21 @@ print(result.response)</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">NameError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[19]</span><span class="ansi-green-fg">, line 1</span>
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">1</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">claims</span><span class="ansi-yellow-fg">"</span> <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> <span class="ansi-yellow-bg">result</span>.context_data:
|
||||
<span class="ansi-green-fg"> 2</span> <span style="color: rgb(0,135,0)">print</span>(result.context_data[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">claims</span><span class="ansi-yellow-fg">"</span>].head())
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre> id entity object_id status start_date end_date \
|
||||
0 2 JORDAN HAYES NONE SUSPECTED NONE NONE
|
||||
1 6 JORDAN HAYES NONE SUSPECTED NONE NONE
|
||||
2 10 JORDAN HAYES NONE TRUE NONE NONE
|
||||
3 1 TAYLOR CRUZ NONE SUSPECTED NONE NONE
|
||||
4 7 TAYLOR CRUZ NONE SUSPECTED NONE NONE
|
||||
|
||||
<span class="ansi-red-fg">NameError</span>: name 'result' is not defined</pre>
|
||||
description in_context
|
||||
0 Jordan Hayes is portrayed as skeptical of Tayl... True
|
||||
1 Jordan Hayes is providing analytical insights ... True
|
||||
2 Jordan Hayes identified a suspicious panel tha... True
|
||||
3 Taylor Cruz's leadership style is described as... True
|
||||
4 Taylor Cruz is asserting command over the miss... True
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -4237,212 +4053,16 @@ print(candidate_questions.response)</div>
|
||||
<div class="jp-OutputArea jp-Cell-outputArea">
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0">
|
||||
<pre>
|
||||
<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
|
||||
<span class="ansi-red-fg">AuthenticationError</span> Traceback (most recent call last)
|
||||
<span class="ansi-cyan-fg">Cell</span><span class="ansi-cyan-fg"> </span><span class="ansi-green-fg">In[21]</span><span class="ansi-green-fg">, line 5</span>
|
||||
<span class="ansi-green-fg"> 1</span> question_history = [
|
||||
<span class="ansi-green-fg"> 2</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Tell me about Agent Mercer</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg"> 3</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">What happens in Dulce military base?</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg"> 4</span> ]
|
||||
<span class="ansi-green-fg">----> </span><span class="ansi-green-fg">5</span> candidate_questions = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> question_generator.agenerate(
|
||||
<span class="ansi-green-fg"> 6</span> question_history=question_history, context_data=<span class="ansi-bold" style="color: rgb(0,135,0)">None</span>, question_count=<span class="ansi-green-fg">5</span>
|
||||
<span class="ansi-green-fg"> 7</span> )
|
||||
<span class="ansi-green-fg"> 8</span> <span style="color: rgb(0,135,0)">print</span>(candidate_questions.response)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/question_gen/local_gen.py:80</span>, in <span class="ansi-cyan-fg">LocalQuestionGen.agenerate</span><span class="ansi-blue-fg">(self, question_history, context_data, question_count, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 74</span> conversation_history = ConversationHistory.from_list(history)
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> context_data <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>:
|
||||
<span class="ansi-green-fg"> 77</span> <span style="color: rgb(95,135,135)"># generate context data based on the question history</span>
|
||||
<span class="ansi-green-fg"> 78</span> result = cast(
|
||||
<span class="ansi-green-fg"> 79</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">ContextBuilderResult</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">80</span> <span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">context_builder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">build_context</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 81</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">question_text</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 82</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">conversation_history</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">conversation_history</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 83</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">kwargs</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 84</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">context_builder_params</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 85</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">)</span>,
|
||||
<span class="ansi-green-fg"> 86</span> )
|
||||
<span class="ansi-green-fg"> 87</span> context_data = cast(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">str</span><span class="ansi-yellow-fg">"</span>, result.context_chunks)
|
||||
<span class="ansi-green-fg"> 88</span> context_records = result.context_records
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/structured_search/local_search/mixed_context.py:139</span>, in <span class="ansi-cyan-fg">LocalSearchMixedContext.build_context</span><span class="ansi-blue-fg">(self, query, conversation_history, include_entity_names, exclude_entity_names, conversation_history_max_turns, conversation_history_user_turns_only, max_context_tokens, text_unit_prop, community_prop, top_k_mapped_entities, top_k_relationships, include_community_rank, include_entity_rank, rank_description, include_relationship_weight, relationship_ranking_attribute, return_candidate_context, use_community_summary, min_community_rank, community_context_name, column_delimiter, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 134</span> pre_user_questions = <span class="ansi-yellow-fg">"</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-yellow-fg">"</span>.join(
|
||||
<span class="ansi-green-fg"> 135</span> conversation_history.get_user_turns(conversation_history_max_turns)
|
||||
<span class="ansi-green-fg"> 136</span> )
|
||||
<span class="ansi-green-fg"> 137</span> query = <span class="ansi-yellow-fg">f</span><span class="ansi-yellow-fg">"</span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>query<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-bold" style="color: rgb(175,95,0)">\n</span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>pre_user_questions<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">139</span> selected_entities = <span class="ansi-yellow-bg">map_query_to_entities</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 140</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 141</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedding_vectorstore</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">entity_text_embeddings</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 143</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">all_entities_dict</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">entities</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 144</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">embedding_vectorstore_key</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embedding_vectorstore_key</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">include_entity_names</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">include_entity_names</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 146</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">exclude_entity_names</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">exclude_entity_names</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 147</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">top_k_mapped_entities</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 148</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">oversample_scaler</span><span class="ansi-yellow-bg">=</span><span class="ansi-green-fg ansi-yellow-bg">2</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 149</span> <span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 151</span> <span style="color: rgb(95,135,135)"># build context</span>
|
||||
<span class="ansi-green-fg"> 152</span> final_context = <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">str</span>]()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/entity_extraction.py:58</span>, in <span class="ansi-cyan-fg">map_query_to_entities</span><span class="ansi-blue-fg">(query, text_embedding_vectorstore, text_embedder, all_entities_dict, embedding_vectorstore_key, include_entity_names, exclude_entity_names, k, oversample_scaler)</span>
|
||||
<span class="ansi-green-fg"> 54</span> matched_entities = []
|
||||
<span class="ansi-green-fg"> 55</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query != <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>:
|
||||
<span class="ansi-green-fg"> 56</span> <span style="color: rgb(95,135,135)"># get entities with highest semantic similarity to query</span>
|
||||
<span class="ansi-green-fg"> 57</span> <span style="color: rgb(95,135,135)"># oversample to account for excluded entities</span>
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">58</span> search_results = <span class="ansi-yellow-bg">text_embedding_vectorstore</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">similarity_search_by_text</span><span class="ansi-yellow-bg">(</span>
|
||||
<span class="ansi-green-fg"> 59</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">query</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 60</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg ansi-bold" style="color: rgb(0,135,0)">lambda</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">:</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">)</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 61</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg">=</span><span class="ansi-yellow-bg">k</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">oversample_scaler</span><span class="ansi-yellow-bg">,</span>
|
||||
<span class="ansi-green-fg"> 62</span> <span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 63</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> result <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> search_results:
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> embedding_vectorstore_key == EntityVectorStoreKey.ID <span class="ansi-bold" style="color: rgb(175,0,255)">and</span> <span style="color: rgb(0,135,0)">isinstance</span>(
|
||||
<span class="ansi-green-fg"> 65</span> result.document.id, <span style="color: rgb(0,135,0)">str</span>
|
||||
<span class="ansi-green-fg"> 66</span> ):
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/vector_stores/lancedb.py:134</span>, in <span class="ansi-cyan-fg">LanceDBVectorStore.similarity_search_by_text</span><span class="ansi-blue-fg">(self, text, text_embedder, k, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 130</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">similarity_search_by_text</span>(
|
||||
<span class="ansi-green-fg"> 131</span> <span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, text_embedder: TextEmbedder, k: <span style="color: rgb(0,135,0)">int</span> = <span class="ansi-green-fg">10</span>, **kwargs: Any
|
||||
<span class="ansi-green-fg"> 132</span> ) -> <span style="color: rgb(0,135,0)">list</span>[VectorStoreSearchResult]:
|
||||
<span class="ansi-green-fg"> 133</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""Perform a similarity search using a given input text."""</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">134</span> query_embedding = <span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 135</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query_embedding:
|
||||
<span class="ansi-green-fg"> 136</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span style="color: rgb(0,135,0)">self</span>.similarity_search_by_vector(query_embedding, k)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/query/context_builder/entity_extraction.py:60</span>, in <span class="ansi-cyan-fg">map_query_to_entities.<locals>.<lambda></span><span class="ansi-blue-fg">(t)</span>
|
||||
<span class="ansi-green-fg"> 54</span> matched_entities = []
|
||||
<span class="ansi-green-fg"> 55</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> query != <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">"</span>:
|
||||
<span class="ansi-green-fg"> 56</span> <span style="color: rgb(95,135,135)"># get entities with highest semantic similarity to query</span>
|
||||
<span class="ansi-green-fg"> 57</span> <span style="color: rgb(95,135,135)"># oversample to account for excluded entities</span>
|
||||
<span class="ansi-green-fg"> 58</span> search_results = text_embedding_vectorstore.similarity_search_by_text(
|
||||
<span class="ansi-green-fg"> 59</span> text=query,
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">60</span> text_embedder=<span class="ansi-bold" style="color: rgb(0,135,0)">lambda</span> t: <span class="ansi-yellow-bg">text_embedder</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">embed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">t</span><span class="ansi-yellow-bg">)</span>,
|
||||
<span class="ansi-green-fg"> 61</span> k=k * oversample_scaler,
|
||||
<span class="ansi-green-fg"> 62</span> )
|
||||
<span class="ansi-green-fg"> 63</span> <span class="ansi-bold" style="color: rgb(0,135,0)">for</span> result <span class="ansi-bold" style="color: rgb(175,0,255)">in</span> search_results:
|
||||
<span class="ansi-green-fg"> 64</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> embedding_vectorstore_key == EntityVectorStoreKey.ID <span class="ansi-bold" style="color: rgb(175,0,255)">and</span> <span style="color: rgb(0,135,0)">isinstance</span>(
|
||||
<span class="ansi-green-fg"> 65</span> result.document.id, <span style="color: rgb(0,135,0)">str</span>
|
||||
<span class="ansi-green-fg"> 66</span> ):
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:240</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingFNLLM.embed</span><span class="ansi-blue-fg">(self, text, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 228</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">embed</span>(<span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, **kwargs) -> <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">float</span>]:
|
||||
<span class="ansi-green-fg"> 229</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 230</span> <span class="ansi-yellow-fg"> Embed the given text using the Model.</span>
|
||||
<span class="ansi-green-fg"> 231</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 238</span> <span class="ansi-yellow-fg"> The embeddings of the text.</span>
|
||||
<span class="ansi-green-fg"> 239</span> <span class="ansi-yellow-fg"> """</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">240</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">run_coroutine_sync</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">aembed</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">text</span><span class="ansi-yellow-bg">,</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">*</span><span class="ansi-yellow-bg">kwargs</span><span class="ansi-yellow-bg">)</span><span class="ansi-yellow-bg">)</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/utils.py:132</span>, in <span class="ansi-cyan-fg">run_coroutine_sync</span><span class="ansi-blue-fg">(coroutine)</span>
|
||||
<span class="ansi-green-fg"> 130</span> _thr.start()
|
||||
<span class="ansi-green-fg"> 131</span> future = asyncio.run_coroutine_threadsafe(coroutine, _loop)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">132</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg">future</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">result</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.13/x64/lib/python3.11/concurrent/futures/_base.py:456</span>, in <span class="ansi-cyan-fg">Future.result</span><span class="ansi-blue-fg">(self, timeout)</span>
|
||||
<span class="ansi-green-fg"> 454</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> CancelledError()
|
||||
<span class="ansi-green-fg"> 455</span> <span class="ansi-bold" style="color: rgb(0,135,0)">elif</span> <span style="color: rgb(0,135,0)">self</span>._state == FINISHED:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">456</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-yellow-bg" style="color: rgb(0,135,0)">self</span><span class="ansi-yellow-bg">.</span><span class="ansi-yellow-bg">__get_result</span><span class="ansi-yellow-bg">(</span><span class="ansi-yellow-bg">)</span>
|
||||
<span class="ansi-green-fg"> 457</span> <span class="ansi-bold" style="color: rgb(0,135,0)">else</span>:
|
||||
<span class="ansi-green-fg"> 458</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span class="ansi-bold" style="color: rgb(215,95,95)">TimeoutError</span>()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.11.13/x64/lib/python3.11/concurrent/futures/_base.py:401</span>, in <span class="ansi-cyan-fg">Future.__get_result</span><span class="ansi-blue-fg">(self)</span>
|
||||
<span class="ansi-green-fg"> 399</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span style="color: rgb(0,135,0)">self</span>._exception:
|
||||
<span class="ansi-green-fg"> 400</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">401</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._exception
|
||||
<span class="ansi-green-fg"> 402</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 403</span> <span style="color: rgb(95,135,135)"># Break a reference cycle with the exception in self._exception</span>
|
||||
<span class="ansi-green-fg"> 404</span> <span style="color: rgb(0,135,0)">self</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/graphrag/language_model/providers/fnllm/models.py:207</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingFNLLM.aembed</span><span class="ansi-blue-fg">(self, text, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 195</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">aembed</span>(<span style="color: rgb(0,135,0)">self</span>, text: <span style="color: rgb(0,135,0)">str</span>, **kwargs) -> <span style="color: rgb(0,135,0)">list</span>[<span style="color: rgb(0,135,0)">float</span>]:
|
||||
<span class="ansi-green-fg"> 196</span> <span style="color: rgb(188,188,188)"> </span><span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 197</span> <span class="ansi-yellow-fg"> Embed the given text using the Model.</span>
|
||||
<span class="ansi-green-fg"> 198</span>
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 205</span> <span class="ansi-yellow-fg"> The embeddings of the text.</span>
|
||||
<span class="ansi-green-fg"> 206</span> <span class="ansi-yellow-fg"> """</span>
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">207</span> response = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.model([text], **kwargs)
|
||||
<span class="ansi-green-fg"> 208</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> response.output.embeddings <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>:
|
||||
<span class="ansi-green-fg"> 209</span> msg = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">No embeddings found in response</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:144</span>, in <span class="ansi-cyan-fg">BaseLLM.__call__</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 142</span> <span class="ansi-bold" style="color: rgb(0,135,0)">try</span>:
|
||||
<span class="ansi-green-fg"> 143</span> prompt, kwargs = <span style="color: rgb(0,135,0)">self</span>._rewrite_input(prompt, kwargs)
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">144</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._decorated_target(prompt, **kwargs)
|
||||
<span class="ansi-green-fg"> 145</span> <span class="ansi-bold" style="color: rgb(0,135,0)">except</span> <span class="ansi-bold" style="color: rgb(215,95,95)">BaseException</span> <span class="ansi-bold" style="color: rgb(0,135,0)">as</span> e:
|
||||
<span class="ansi-green-fg"> 146</span> stack_trace = traceback.format_exc()
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/services/rate_limiter.py:75</span>, in <span class="ansi-cyan-fg">RateLimiter.decorate.<locals>.invoke</span><span class="ansi-blue-fg">(prompt, **args)</span>
|
||||
<span class="ansi-green-fg"> 73</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">with</span> <span style="color: rgb(0,135,0)">self</span>._limiter.use(manifest):
|
||||
<span class="ansi-green-fg"> 74</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_acquired(manifest)
|
||||
<span class="ansi-green-fg">---> </span><span class="ansi-green-fg">75</span> result = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> delegate(prompt, **args)
|
||||
<span class="ansi-green-fg"> 76</span> <span class="ansi-bold" style="color: rgb(0,135,0)">finally</span>:
|
||||
<span class="ansi-green-fg"> 77</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_limit_released(manifest)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/base/base_llm.py:126</span>, in <span class="ansi-cyan-fg">BaseLLM._decorator_target</span><span class="ansi-blue-fg">(self, prompt, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> <span class="ansi-yellow-fg">"""Target for the decorator chain.</span>
|
||||
<span class="ansi-green-fg"> 122</span>
|
||||
<span class="ansi-green-fg"> 123</span> <span class="ansi-yellow-fg">Leave signature alone as prompt, kwargs.</span>
|
||||
<span class="ansi-green-fg"> 124</span> <span class="ansi-yellow-fg">"""</span>
|
||||
<span class="ansi-green-fg"> 125</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._events.on_execute_llm()
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> output = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._execute_llm(prompt, kwargs)
|
||||
<span class="ansi-green-fg"> 127</span> result = LLMOutput(output=output)
|
||||
<span class="ansi-green-fg"> 128</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._inject_usage(result)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/fnllm/openai/llm/openai_embeddings_llm.py:126</span>, in <span class="ansi-cyan-fg">OpenAIEmbeddingsLLMImpl._execute_llm</span><span class="ansi-blue-fg">(self, prompt, kwargs)</span>
|
||||
<span class="ansi-green-fg"> 121</span> local_model_parameters = kwargs.get(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">model_parameters</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg"> 122</span> embeddings_parameters = <span style="color: rgb(0,135,0)">self</span>._build_embeddings_parameters(
|
||||
<span class="ansi-green-fg"> 123</span> local_model_parameters
|
||||
<span class="ansi-green-fg"> 124</span> )
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">126</span> result_raw = <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._client.embeddings.with_raw_response.create(
|
||||
<span class="ansi-green-fg"> 127</span> <span style="color: rgb(0,135,0)">input</span>=prompt,
|
||||
<span class="ansi-green-fg"> 128</span> **embeddings_parameters,
|
||||
<span class="ansi-green-fg"> 129</span> )
|
||||
<span class="ansi-green-fg"> 130</span> result = result_raw.parse()
|
||||
<span class="ansi-green-fg"> 131</span> headers = result_raw.headers
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_legacy_response.py:381</span>, in <span class="ansi-cyan-fg">async_to_raw_response_wrapper.<locals>.wrapped</span><span class="ansi-blue-fg">(*args, **kwargs)</span>
|
||||
<span class="ansi-green-fg"> 377</span> extra_headers[RAW_RESPONSE_HEADER] = <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">true</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 379</span> kwargs[<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">extra_headers</span><span class="ansi-yellow-fg">"</span>] = extra_headers
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">381</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> cast(LegacyAPIResponse[R], <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> func(*args, **kwargs))
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/resources/embeddings.py:251</span>, in <span class="ansi-cyan-fg">AsyncEmbeddings.create</span><span class="ansi-blue-fg">(self, input, model, dimensions, encoding_format, user, extra_headers, extra_query, extra_body, timeout)</span>
|
||||
<span class="ansi-green-fg"> 245</span> embedding.embedding = np.frombuffer( <span style="color: rgb(95,135,135)"># type: ignore[no-untyped-call]</span>
|
||||
<span class="ansi-green-fg"> 246</span> base64.b64decode(data), dtype=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">float32</span><span class="ansi-yellow-fg">"</span>
|
||||
<span class="ansi-green-fg"> 247</span> ).tolist()
|
||||
<span class="ansi-green-fg"> 249</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> obj
|
||||
<span class="ansi-green-fg">--> </span><span class="ansi-green-fg">251</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>._post(
|
||||
<span class="ansi-green-fg"> 252</span> <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">/embeddings</span><span class="ansi-yellow-fg">"</span>,
|
||||
<span class="ansi-green-fg"> 253</span> body=maybe_transform(params, embedding_create_params.EmbeddingCreateParams),
|
||||
<span class="ansi-green-fg"> 254</span> options=make_request_options(
|
||||
<span class="ansi-green-fg"> 255</span> extra_headers=extra_headers,
|
||||
<span class="ansi-green-fg"> 256</span> extra_query=extra_query,
|
||||
<span class="ansi-green-fg"> 257</span> extra_body=extra_body,
|
||||
<span class="ansi-green-fg"> 258</span> timeout=timeout,
|
||||
<span class="ansi-green-fg"> 259</span> post_parser=parser,
|
||||
<span class="ansi-green-fg"> 260</span> ),
|
||||
<span class="ansi-green-fg"> 261</span> cast_to=CreateEmbeddingResponse,
|
||||
<span class="ansi-green-fg"> 262</span> )
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1791</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.post</span><span class="ansi-blue-fg">(self, path, cast_to, body, files, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1777</span> <span class="ansi-bold" style="color: rgb(0,135,0)">async</span> <span class="ansi-bold" style="color: rgb(0,135,0)">def</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-blue-fg">post</span>(
|
||||
<span class="ansi-green-fg"> 1778</span> <span style="color: rgb(0,135,0)">self</span>,
|
||||
<span class="ansi-green-fg"> 1779</span> path: <span style="color: rgb(0,135,0)">str</span>,
|
||||
<span class="ansi-green-fg"> (...)</span><span class="ansi-green-fg"> 1786</span> stream_cls: <span style="color: rgb(0,135,0)">type</span>[_AsyncStreamT] | <span class="ansi-bold" style="color: rgb(0,135,0)">None</span> = <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>,
|
||||
<span class="ansi-green-fg"> 1787</span> ) -> ResponseT | _AsyncStreamT:
|
||||
<span class="ansi-green-fg"> 1788</span> opts = FinalRequestOptions.construct(
|
||||
<span class="ansi-green-fg"> 1789</span> method=<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">post</span><span class="ansi-yellow-fg">"</span>, url=path, json_data=body, files=<span class="ansi-bold" style="color: rgb(0,135,0)">await</span> async_to_httpx_files(files), **options
|
||||
<span class="ansi-green-fg"> 1790</span> )
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1791</span> <span class="ansi-bold" style="color: rgb(0,135,0)">return</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> <span style="color: rgb(0,135,0)">self</span>.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
|
||||
|
||||
<span class="ansi-cyan-fg">File </span><span class="ansi-green-fg">~/work/graphrag/graphrag/.venv/lib/python3.11/site-packages/openai/_base_client.py:1591</span>, in <span class="ansi-cyan-fg">AsyncAPIClient.request</span><span class="ansi-blue-fg">(self, cast_to, options, stream, stream_cls)</span>
|
||||
<span class="ansi-green-fg"> 1588</span> <span class="ansi-bold" style="color: rgb(0,135,0)">await</span> err.response.aread()
|
||||
<span class="ansi-green-fg"> 1590</span> log.debug(<span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">Re-raising status error</span><span class="ansi-yellow-fg">"</span>)
|
||||
<span class="ansi-green-fg">-> </span><span class="ansi-green-fg">1591</span> <span class="ansi-bold" style="color: rgb(0,135,0)">raise</span> <span style="color: rgb(0,135,0)">self</span>._make_status_error_from_response(err.response) <span class="ansi-bold" style="color: rgb(0,135,0)">from</span><span style="color: rgb(188,188,188)"> </span><span class="ansi-bold" style="color: rgb(0,135,0)">None</span>
|
||||
<span class="ansi-green-fg"> 1593</span> <span class="ansi-bold" style="color: rgb(0,135,0)">break</span>
|
||||
<span class="ansi-green-fg"> 1595</span> <span class="ansi-bold" style="color: rgb(0,135,0)">assert</span> response <span class="ansi-bold" style="color: rgb(175,0,255)">is</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> <span class="ansi-bold" style="color: rgb(0,135,0)">None</span>, <span class="ansi-yellow-fg">"</span><span class="ansi-yellow-fg">could not resolve response (should never happen)</span><span class="ansi-yellow-fg">"</span>
|
||||
|
||||
<span class="ansi-red-fg">AuthenticationError</span>: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-proj-********************************************************************************************************************************************************zWYA. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}</pre>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>2025-08-15 23:40:34.0597 - WARNING - graphrag.query.structured_search.local_search.mixed_context - Reached token limit - reverting to previous context state
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
<div class="jp-OutputArea-child">
|
||||
<div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
|
||||
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0">
|
||||
<pre>['- What is the role of Agent Alex Mercer in the exploration of the Dulce base?', '- How does Agent Mercer interact with other members of the Paranormal Military Squad during Operation: Dulce?', '- What are the key responsibilities of Agent Mercer in Operation: Dulce?', "- How does Agent Mercer's leadership style impact the success of the mission at the Dulce base?", '- What challenges does Agent Mercer face while exploring the Dulce base?']
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
BIN
sitemap.xml.gz
BIN
sitemap.xml.gz
Binary file not shown.
Loading…
Reference in New Issue
Block a user